AN ANALYSIS OF THE IMPACT OF LOADSHEDDING

ON THE WESTERN CAPE AGRICULTURAL SECTOR

Report for the Western Cape Department of Agriculture

Bureau for Food & Agricultural Policy (BFAP)

29 May 2023
This publication is a technical report by the Bureau for Food and Agricultural Policy (BFAP)
commissioned by Western Cape Department of Agriculture (WC DoA). The research team would
like to thank all agricultural stakeholders who participated by supporting this project with information
and insights.

Report Authors:
Kandas Cloete [kandas@bfap.co.za]
Louw Pienaar [louw@bfap.co.za]
Tracy Davids [tracy@bfap.co.za]
Marion Delport [marion@bfap.co.za]
Ferdi Meyer [ferdi@bfap.co.za]
Gerhard van der Burgh [gerhard@bfap.co.za]
Wiltrud Durand [wiltrud@bfap.co.za]
Karen Truter [karen@bfap.co.za]
Marnus Gouse [marnus@bfap.co.za]

Suggested Citation:
Cloete, K., Pienaar, L., Davids, T., Delport, M., Meyer, F. Van der Burgh, G., Durand, W., Truter, K. &
Gouse, M., 2023. An analysis of the impact of loadshedding on the Western Cape agricultural sector.
Report Commissioned by WC DoA. Elsenburg: Bureau for Food and Agricultural Policy (BFAP).
 MAIN MESSAGES
Electricity dependency overview of the Western Cape agricultural sector
• Western Cape primary production and agro-processing
Temporal distribution of electricity demand for irrigation

electricity use was estimated at ±2 TWh in 2022.

• Intensive livestock operations are primarily situated in
Swartland, Hessequa, Drakenstein, City of Cape Town
(CoCT), Swellendam and George municipalities.
• Biggest electricity demand for irrigation purposes is in the
Annual electricity use:
Witzenberg, Langeberg, Breede Valley, Oudtshoorn,
• Western Cape 16 TWh
Theewaterskloof and Cederberg municipalities, where
• CoCT 70% of province total
80% of demand for electricity is from October-March.
• Primary agriculture 1.2 TWh
(of which about 90% is for • >90% of producers are dependent on Eskom as their
irrigation) primary, or only, source of electricity, but some businesses
• Agro-processing 0.8 TWh have already started investing in alternatives.

Impact of loadshedding on the Western Cape agricultural sector

• The causality analysis showed that the biggest drivers of
impact in the system are operational capacity and
scheduling, together with input supply.
• Four case studies were conducted to analyse the short- and
longer-term impact of loadshedding, indicating that the risk
posed by interruptions in electricity supply in the livestock
industry is very high, but the impact on volume, area, jobs
and GPV is even greater in the horticulture industry.
• Small and informal businesses are more vulnerable.
• Running primary production and agro-processing facilities in
the Western Cape uninterrupted for a full year at stage 6
loadshedding will demand spending of R3.95 to R4.08 bn per
annum, with savings on Eskom expenditure (R1.42 bn).

Potential interventions to consider for the Western Cape agricultural sector

• The responsibility of generating electricity can be forced
upon businesses, but with such a responsibility businesses still
depend on government to create an enabling environment.
• Industry organisations can ensure the effective
communication of the strategic actions taken at various
levels of government with agribusinesses.
• If any level of government implements alternative energy
solutions to reduce/remove loadshedding, these
implementations could ease the responsibility on businesses
to invest in their own electricity generation, avoiding
additional constraints on individual agribusinesses.
• Risk mitigation priorities should include water supply, an
enabling regulatory environment and curtailment rather
than loadshedding for agro-processing facilities.

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EXECUTIVE SUMMARY
The objective of this study is to provide a description of the energy dependency of the Western
Cape agricultural sector on the national grid, within the context of the loadshedding situation, and
to describe the on- and off-farm implications and quantify its socio-economic impacts. To reduce
and/or mitigate the impact, the study provides recommendations on potential interventions that
can be implemented by value chain role-players, industry, and the various spheres of government.
To provide the context of the industry assessed with respect to energy dependency and the
impact of loadshedding, an overview of the value of the agricultural value chain in the Western
Cape, with focus on GDP and employment is presented. The report also presents findings from
existing literature on the impact of loadshedding on the South African economy and the agricultural
sector, and a brief look at the cost of alternatives and the policies regulating the implementation
thereof.
A matrix was built of the structure of the agricultural value chain in the Western Cape. This
included linking the flow of products from farm to consumer, calculating the number of jobs, income
and electricity spend per value chain actor. To provide an overview of the energy dependency of
the Western Cape agricultural sector by industry, consideration was given to the type of energy
being used and the suppliers of energy, and the spatial and temporal distribution of energy use.
The Western Cape’s total energy demand in 2021 equated to 16 067 GWh (16 TWh). The City of
Cape Town metropolitan were responsible for 70% of the total demand and the other 24
municipalities combinedly responsible for 30%. Within these municipal electricity use, the use by
primary agriculture and agro-processing are included. The distribution of commercial agricultural
expenditure by municipality provides an indication of the relative intensity of agriculture’s electricity
usage. While the Western Cape is responsible for 8% of South African electricity demand, its share
of national agricultural electricity expenditure in 2017 equated to 22.4%, indicating that the primary
agricultural sector in the Western Cape is more energy intensive than agriculture in other provinces.
Intensive livestock operations are primarily situated in Swartland, Hessequa, Drakenstein, City of
Cape Town, Swellendam and George municipalities. Biggest electricity demand for irrigation
purposes is recorded for the Witzenberg, Langeberg, Breede Valley, Oudtshoorn, Theewaterskloof
and Cederberg municipalities, where 80% of demand for electricity is from October-March.
An estimate of economic activities of the primary agricultural sector, which includes gross farm
income, total costs and the share of electricity and fuel costs to total costs, formed the basis of the
analyses in this report. Producers in the Western Cape spend around R75.3 billion to generate
around R79 billion worth of outputs. The R2.6 billion spent to buy electricity were 3.43% of total costs.
When spending on fuel was added, the combined total reached 7.4%. Given these estimates, an
official Eskom tariff of R2.15/kWh was used to calculate total electricity use of around 1 200 GWh in
2022. In a similar calculation, agro-processors in the Western Cape spend around R89.8 billion to
generate around R105.6 billion worth of outputs. The total estimated spend on electricity of R1.27
billion implies that, at an Eskom tariff for industrial firms of R1.50/kWh for 2022, these agro-processing
industries used a combined 844 GWh. In relative terms, , processors spend around 1.4% (of total
costs) on electricity and another 1.7% for fuel, with a combined spend of 3.1%.
A systematic approach was used to address the quantification of the impact of loadshedding
at various stages. Firstly, the relationships between causes and effects in the Western Cape
agricultural sector were analysed and described. Thereafter, impact was evaluated based on
operations, volume and price, and ultimately profitability. These analysis steps and findings provide

ii
the necessary platform to unpack loadshedding’s socio-economic impact and the impact on
government objectives.
One of the golden threads throughout the study has been the interconnectedness of value
chains – not only within a single commodity, but across commodities. The second thread widely
observed is that loadshedding sets off a series of events, many of them having a knock-on effect
on other matters. Interactive Qualitative Analysis (IQA) was employed to establish causality and
identify potential feedback loops. Highlights from the causality analysis include that the chain of
events as a result of loadshedding starts with ‘Operational capacity & scheduling’ (biggest delta –
net relationship direction – between causes and effects, thus ranked first), followed by ‘Input supply
& availability’. The biggest outcomes – elements subjected to change in the system – are the ones
with the biggest negative delta, namely ‘Socio-economics’ and ‘Product selling prices’. Four
feedback loops exist in the system, which strengthen the argument of complexity and
interconnectedness in agricultural value chains. The recursive nature of causality also exposes the
risk continued loadshedding poses.
Given the outcomes of the causality analysis, a matrix approach was followed to indicate the
impact of different stages of loadshedding on operations. The objective was to highlight the biggest
risks for businesses, as derived from surveys and interviews, by making use of a Likert scale schematic.
The highest risk for value chain disruptions and output reduction are related to water (supply and
irrigation), intensive livestock production, and the processing and cooling of produce. From the
interviews with stakeholders, it became clear that smaller role-players are more vulnerable. This holds
true throughout the different value chains, but especially in the case of emerging producers,
informal processors, and smaller commercial producers. One could, to a large extent, assume that
impact of loadshedding on these role-players are typically one level higher than what has been
indicated on average, and the operational activities of these producers and agro-processors would
be disrupted at one stage of loadshedding earlier than for the average. At the same time, large
scale producers and agro-processors, who have already invested extensively in alternatives, can at
an additional cost temporarily absorb more of the impact of various stages of loadshedding.
Three case studies – one per sub-sector – were conducted to simulate the impact of
loadshedding stage 6 against a business-as-usual baseline. Assuming that the case studies are
indicative of the impact on volume and price by sub-sector, the impact can be summarised as
follows. For livestock (poultry), 20% of the cost incurred due to loadshedding is passed on to the
consumer, with 80% absorbed in the value chain. Although production volume is marginally
affected in the short run, and increased imports are triggered, it mostly reverts to baseline conditions
in the long run, assuming that the energy situation normalises due to current investments in private
generation capacity. Thus, while adding to food price inflation, availability should not be affected,
as imports can replace the production contraction.
For field crops (canola), it was assumed that one third of the additional cost incurred due to
loadshedding can be passed onto consumers, with one third pushed to producers and one third
absorbed by the agro-processors. Contraction of area and volume of 2-3% in the short run could be
expected, which also curtails exports, where applicable, somewhat. Similar to livestock, a recovery
to baseline levels over the latter part of the outlook is expected. Prices are well integrated in global
markets and while the need to import may increase, food availability should not be affected. Since
wheat is already mostly priced at import parity, price impacts will be limited, but imports will rise to
ensure availability.
The horticultural sub-sector could be split into two: produce predominantly cultivated for exports,
e.g., fruit, and produce cultivated primarily for local consumption, e.g., vegetables. Regarding the

iii
former (apples was used as case study), a negative impact of up to 10% GPV is projected under a
“conservative” scenario modelled for loadshedding stage 6. Negative quality and volume impacts
– up to a 12-15% decrease in exports – in the short run could have long run structural implications for
the industry, as water limitations emanating from increased loadshedding could reduce the area
under cultivation. Although not modelled, the vegetable industry would emulate grains to the
extent where the cost of loadshedding is partially passed on to the consumer as volume reductions
will increase the prices of fresh produce for consumers. A product like wine, which has a large
domestic and international footprint is likely to experience a combination of both the fruit and
vegetable impacts. The most critical component to surviving this crisis was identified as sustained
supply from water schemes and irrigation at farm-level.
The impact of loadshedding inevitably affects the socio-economic aspects of agricultural value
chains and the provincial government objectives. This report reiterates that job opportunities in the
horticultural sector, which is the biggest employer of on-farm and off-farm agri workers in the
Western Cape, are most vulnerable, putting those jobs at risk. The WC DoA aims to create an
enabling environment for producers and processors to grow Value Added and grow employment
opportunities. It is clear that the ongoing energy supply shortage are set to influence some of the
major outcome indicators that the Department has set out to achieve towards 2024. In this regard,
growing exports, value added and ensuring continued success on land reform projects will be
difficult to maintain. A high-level overview of the policy environment applicable to the study
highlighted the slowly changing regulatory environment that still constraints the implementation of
alternatives, especially with respect to the implementation of green energy options.
Considering the direct and indirect cost, operational impact and risk to individual role-players in
the agricultural value chains, a set of potential interventions were developed. The matrix outlining
this non-exhaustive list of interventions considers both the mandates and competencies of
businesses, industry, and government to implement interventions during the season on hand, the
rest of 2023 and over a 10-year period. Given the complexity and magnitude of interventions
required, a collective effort from all stakeholders is necessary to mitigate this electricity crisis in the
Western Cape. To illustrate, running primary production and agro-processing facilities in the Western
Cape uninterrupted for a full year at stage 6 loadshedding will demand spending of around R4
billion per annum on alternative energy sources, with savings on Eskom expenditure of R1.42 billion.
While the responsibility of generating electricity can be forced upon businesses, with such a
responsibility businesses still depend on government to create an enabling environment. Industry
organisations can ensure the effective communication of the strategic actions taken at various
levels of government with agribusinesses. If any level of government implements alternative energy
solutions to reduce/remove loadshedding, these implementations could ease the responsibility on
businesses to invest in their own electricity generation, avoiding additional constraints on individual
agribusinesses.
Given the findings regarding the impact of loadshedding in the Western Cape agricultural
sector, it is recommended that risk mitigation priorities should include water supply, an enabling
regulatory environment and, in particular in the livestock sub-sector, curtailment rather than
loadshedding for agro-processing facilities.
In conclusion, every attempt has been made to reflect the true state of energy dependency,
the impact of loadshedding and the potential implementable interventions to mitigate the impact
on the Western Cape agricultural sector within the timeframes provides. However, ample scope
exists to refine, enrich and expand the research in collaboration with businesses, industry and
government.

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TABLE OF CONTENTS
MAIN MESSAGES............................................................................................................................................. i
EXECUTIVE SUMMARY .................................................................................................................................... i
TABLE OF BOXES ............................................................................................................................................. v
TABLE OF TABLES ........................................................................................................................................... vi
TABLE OF FIGURES ......................................................................................................................................... vi
1. INTRODUCTION ..................................................................................................................................... 1
2. OVERVIEW OF THE AGRICULTURAL VALUE CHAIN IN THE WC ........................................................ 2
3. LITERATURE ............................................................................................................................................. 4
3.1. Overview of electricity use ........................................................................................................ 4
3.2. Overview of the economic impact of loadshedding ........................................................... 7
3.3. High-level policy overview ....................................................................................................... 10
3.4. Overview of agricultural surveys ............................................................................................. 11
4. ENERGY DEPENDENCY OVERVIEW ................................................................................................... 13
4.1. Overview of energy sources and electricity use .................................................................. 13
4.2. Spatial and temporal distribution of electricity use ............................................................. 15
5. IMPACT OF LOADSHEDDING............................................................................................................. 18
5.1. Causality argument .................................................................................................................. 18
5.2. Impact on operations .............................................................................................................. 22
5.3. Impact on volume and price .................................................................................................. 25
5.4. Impact on profitability .............................................................................................................. 28
5.5. Socio-economic impact .......................................................................................................... 32
5.6. Impact on government objectives ........................................................................................ 34
6. POTENTIAL INTERVENTIONS ................................................................................................................ 36
7. CONCLUSION ..................................................................................................................................... 39
8. REFERENCES ........................................................................................................................................ 41

TABLE OF BOXES
Box 1: Dependency on Eskom for extraction of scheme water – Berg river case study ..................... 17
Box 2: Impact of loadshedding on the livestock industry – Broiler chicken case study....................... 23
Box 3: Impact of loadshedding on the field crop industry – Canola case study ................................. 27
Box 4: Impact of loadshedding on the horticulture industry – Apple case study ................................. 30

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TABLE OF TABLES
Table 1: Western Cape energy demand and consumption: 2021 ........................................................... 5
Table 2: Estimated Western Cape Primary agricultural energy usage: 2022 .......................................... 5
Table 3: Estimated Western Cape agro-processing energy usage: 2022 ................................................ 6
Table 4: High-level overview of policy applicable to the loadshedding impact study ...................... 10
Table 5: Overview of participants by value chain node and operational size .................................... 12
Table 6: Overview of primary and secondary energy dependency ..................................................... 12
Table 7: Predominant energy sources by industry .................................................................................... 13
Table 8: Electricity demand estimates by major industry, node and action ........................................ 14
Table 9: Location of commercial agro-processing and value-adding facilities: 2017 ........................ 14
Table 10: Temporal distribution of electricity demand for irrigation purposes in GWh: 2017 .............. 16
Table 11: Tabular inter-relationship diagram.............................................................................................. 19
Table 12: Description of elements and relationships................................................................................. 21
Table 13: Matrix indicating the impact of different levels of loadshedding on operations ................ 23
Table 14: Annual cost of alternative energy supply per stage of loadshedding: 2022 equivalent ... 26
Table 15: WC DoA impact of loadshedding on key outcome indicators ............................................. 35
Table 16: Potential interventions to mitigate the impact of loadshedding ........................................... 37
Table 17: Matrix output on supply impact and implementation of energy solutions .......................... 38

TABLE OF FIGURES
Figure 1: Agriculture and agro-processing contribution in the Western Cape in 2022 .......................... 2
Figure 2: Western Cape agricultural value chain linkages 2022 values ................................................... 3
Figure 3: Estimated impact of loadshedding on quarterly growth in real GDP ...................................... 7
Figure 4: Planned and unplanned outages (breakdowns) trend: 2018-2022 ......................................... 8
Figure 5: Upper limit of cumulative loadshedding annually: 2014-2022................................................... 9
Figure 6: Hourly distribution of loadshedding: 2022 ..................................................................................... 9
Figure 7: Investment cost and LCOS comparison of backup technologies .......................................... 10
Figure 8: Primary agriculture: (A) Livestock, (B) Horticulture, (C) Winter & (D) Summer crops ............ 15
Figure 9: Berg river water management area ........................................................................................... 17
Figure 10: Cluttered systems influence diagram ....................................................................................... 19
Figure 11: Uncluttered systems influence diagram ................................................................................... 20
Figure 12: Final systems influence diagram ................................................................................................ 20
Figure 13: Impact of loadshedding related costs on chicken prices in South Africa – Baseline vs.
Stage 6 loadshedding scenario................................................................................................. 24
Figure 14: Absolute change in production, consumption and import volumes as a result of stage
6 loadshedding, expressed relative to the baseline projection from 2023 – 2030 ............. 24
Figure 15: Absolute change in crush volume, cake and oil production as a result of stage 6
loadshedding, expressed relative to the baseline projection from 2023 – 2026 ................ 28
Figure 16: Gross value of canola production: baseline vs scenario: 2023-2026 .................................... 28
Figure 17: Impact of described scenario on GPV from 2020 – 2032 ....................................................... 31
Figure 18: Impact of described scenario on Witzenberg prototype farm from 2022 – 2032 ............... 32
Figure 19: Western Cape food Inflation and contribution per food group ........................................... 33
Figure 20: Western Cape agri worker household provision of services .................................................. 34

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1. INTRODUCTION
South Africa is currently experiencing a major energy crisis, brought about by several
longstanding challenges in the energy sector. Although large parts of the population and business
community has been dealing with intermittent interruptions in the electricity supply for most of the
past decade, the situation has deteriorated substantially over the last year and the scale and
magnitude of current supply shortages will have significant bearing on the agricultural sector and
larger economy. To date, there has been no research undertaken to assess the on and off-farm
implications of loadshedding as it relates to production, processing and marketing of agriculture
and food products.
The aim of this report is to provide a description of the energy dependence of the Western Cape
agricultural sector and to contextualise and assess how loadshedding impacts the various
economic activities related to agricultural production located in the province. It provides a best
possible estimate of the extent to which food production and processing is dependent on Eskom
Holdings (SOC) Entity Ltd (Eskom - South Africa’s state-owned energy company), municipalities
and/or other sources of energy and evaluates the exposure of the various segments of the Western
Cape agricultural value chain related to its dependence on Eskom for its energy supply.
Loadshedding is a method through which Eskom deliberately shuts down electricity supply in
parts of the power distribution system in an attempt to avoid failure in the larger part of the system
at times when the demand exceeds supply. The power utility’s inability to generate sufficient energy
to power the country’s economy is well cited in various reports and in the media and will not be
covered in this report. Instead, BFAP’s integrated value chain approach is used, informed by
multiple stakeholder engagements, to describe and assess the complexity and potential impact of
loadshedding as locally produced agricultural products move from the farm, through the value
chain and ultimately reach consumers, either locally or internationally.
We estimate the impact of loadshedding at different loadshedding stages - a set number of
hours during which value chain actors such as producers, processing firms, service providers, traders
and input suppliers are left without electricity to run operations. Despite some advancement in
energy regulation to allow additional energy supplies into the national grid and significant
investments in the past two years in renewable energy, there is consensus that South Africans will
continue to suffer from recurring loadshedding at least until the end of 2024 (BER, 2023). The impact
on individual businesses is significant, and the aggregated and spill-over impacts on the entire food
system has bearing on macroeconomic outcomes such as food security, food production and
processing capacity, unemployment and social unrest to name just a few. The current energy crisis
in South Africa, , comes at a time of international economic downturn and a local economy battling
to bring stubbornly high food inflation under control. Furthermore, the agricultural sector in South
Africa, but in particular the Western Cape, has had a difficult 2022 season compared to 2020 and
2021 with factors such as farm input cost inflation growing faster than farm incomes, price pressure
on exported fruit products and a stagnating SA economy dragging demand for locally consumed
food products lower.
Given this context, our research on the impact of loadshedding on the Western Cape
agricultural sector is aimed at ultimately drafting a set of potential interventions that would minimise
the main negative impacts whilst recognising the limited mandate of the Department to directly
fund energy investments. We also discuss the mechanisms through which loadshedding is expected
to impact the value chains by identifying causal relationships linking energy shortages to business
operations, impacts on volumes and prices in the market, profitability considerations and some
socio-economic impacts on consumers and farm workers in the Western Cape. Loadshedding will

1
also undoubtedly impact several government objectives since already scarce resources will need
to be re-allocated to continue providing services at a higher cost, but also the broad impact of
loadshedding is set to negatively impact on key strategic outcomes. More specifically,
loadshedding will impact the WC DoAs ability to shape and direct increased agricultural production
in a sustainable manner, improve food security and safety and enhance inclusivity and (WC DoA,
2020). This document concludes with some recommendations and potential interventions for the
Department, producers and value chain actors.

2. OVERVIEW OF THE AGRICULTURAL VALUE CHAIN IN THE WC

From the outset it is important to define what is meant by the agricultural sector under review in
this report. Traditionally and at the macroeconomic level, the extent of the agricultural sector is
often depicted in terms of its contribution to the Gross Domestic Product (GDP) and formal
employment, which is presented in Figure 1. Considering just the primary level of agricultural
production, the value-added contribution of farms producing agricultural outputs were estimated
at 3% of the total Western Cape economy in 2022, whilst agro-processing added another 4%. This
combined 7% contribution to GDP is significant in itself but if one also takes into consideration the
14% contribution that these two sectors make in terms of employment, the importance of the
broader agricultural value chain is clear. While significant, this description of the agricultural sector
does not yet include all the different linkages that agriculture has to other parts of the economy,
both in terms of utilising inputs and services from other industries, as well as producing products used
in downstream segments of the economy. Structurally, agriculture and agro-processing can also
not exist independently of one another, unless all processed products are imported, and/or all fresh
produce exported. Rather, the interconnectedness of farms and processors is what makes the entire
supply chain able to competitively produce products. Thus, external risks that impact any
component or linkage of the agricultural value chain, impacts the whole as well.

FIGURE 1: A GRICULTURE AND AGRO - PROCESSING CONTRIBUTION IN THE W ESTERN CAPE IN 2022
SOURCE: QUANTEC, 2023

The Western Cape agricultural sector is internationally competitive, and a large proportion of
South Africa’s fruit and wine exports are from the province. At the time of the last completed farm
census there were around 6 500 commercial producers in the province and another 3 800 emerging
growers (StatsSA, 2020; DALRRD, 2021). No official data provides a breakdown of the number of
agro-processing firms located in the Western Cape, but published information from 2014 suggests

2
that food and beverage manufacturers made up 25% of both national sales income and the
number of employed (StatsSA, 2014). We estimate that the number of agro-processors in the
Western Cape is between 1 000 - 2 000 firms, which produce a variety of value-added products.
Before embarking on the main objective of this report which is to describe, assess and analyse the
impact of loadshedding on the agricultural sector, this next section provides a brief explanation of
the integrated nature of the food value chain and provides the base from which we’ll assess the
economic impact of loadshedding. This will also be used as the base through which we identify
causal relationships within the value chain as it relates to energy dependence and the impact of
loadshedding.
Figure 2 presents a schematic diagram of the agricultural value chain in the Western Cape,
specifically linking different agriculture and agro-processing industries with industries that supply
goods and services as products move through the various stages towards final consumer markets.
The values shown in the figure represents gross output (for farming), gross income (for inputs and
services), or gross value of production (for agro-processing. Thus, inputs and services are reported
as costs to the industry, incorporated into the value of produce reported at farm and/or agro-
processing level. Values reported for farming are incorporated into the total value of production
reported at agro-processing level where value is added or products are processed.

FIGURE 2: W ESTERN CAPE AGRICULTURAL VALUE CHAIN LINKAGES : 2022

SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023

This compilation was compiled using various sources that detail the structure of the economy. In
the absence of recently updated statistics, we estimate the total value of agricultural output in the
Western Cape at R81.3 billion in 2022. Of this, 50% came from horticulture gross farm income and
33% and 16% from field crops and livestock farming respectively. In order to generate this farming
income, Western Cape farms were reliant on several input industries with the most notable for our
research focus being feed, packaging, fertiliser and electricity. In total, farming costs (excluding
labour) were approximately R61 billion in 2022, which resulted in Value Added of around R20.7
billion. Two important direct costs related to the focus of this study is the spending of farms on
electricity and fuel, which had a combined value of sales to the agricultural industries of R4.8 billion.
Moving beyond the farm-gate, agro-processors realised an estimated combined gross income
of around R106 billion, which is disaggregated into the main industries in Figure 2. Other food
products, which includes potato chips, nutritional and dietary supplements, herbs and spices and

3
infant food to name a few, are the biggest categories. Other substantive industries in the Western
Cape include cellars and distilleries (beverages), fruit processing, dairy processors and animal feed.
Quantification of loadshedding’s impact must be assessed on each of these processing segments
of the Western Cape economy largely due to significant differences in the nature of processing and
the related electricity intensity between them. These firms are mostly directly integrated to farms
located in the province, such that fruits are canned or juiced, wine grapes pressed, grains milled
and so forth. Often the single biggest expenditure item for agro-processing firm is the purchasing of
raw materials coming from farms, usually in the order of 70% of total costs at the secondary level.
This again highlights a fundamental principle when thinking about the functioning of agricultural
supply chains. In order for processors to be competitive, farm products need to be procured at low
prices (compared to imported raw material), on a consistent basis to ensure ample throughput.
Whereas farms mostly operate on a seasonal basis that depends on the nature of production,
processors operate at a much larger scale due to agglomeration effects and large capital
equipment and other assets means that plants often need to have high (>70%) utilisation rates to
remain competitive. If this cannot be maintained over long periods of time, the relatively large, fixed
costs cannot be sustainably recovered.
But, agro-processors are not only dependent on raw material from farms, they often also depend
on one another for raw material and services. Consider the feed industry as an example - feed
manufacturers buy grains from producers as the main ingredient to manufacture compound feeds,
but also buy raw materials from other agro-processors such as oilcake (oil crushers). This dynamic
also has bearing when anticipating the impacts of loadshedding on agro-processing firms, since
primary agriculture then also depends on feed mills to supply feed competitively. Thus, an escalation
of prices in the chain, even relatively small margins, can easily scale and create multipliers working
against producers in the economy.
Now that we have detailed the size and linkages of the agricultural economy with its related
products and services, we briefly review some of the available literature on the impact of
loadshedding in South Africa.

3. LITERATURE
The significant increase in loadshedding hours in 2022 has brought about a greater emphasis on
the policies restricting or enabling alternative solutions, the direct and indirect implications of
loadshedding and the potential alternative solutions to mitigate loadshedding. The dependency of
the agricultural sector on the national electricity grid is undeniable. The focal point for this literature
overview is to summarise existing literature with respect to policy, impact reports compiled by
recognised research institutes and agriculturally focused surveys.

3.1. Overview of electricity use

The Western Cape’s total energy demand in 2021 equated to 16 067 GWh (16 TWh). The City of
Cape Town metropolitan were responsible for 70% of the total demand and the other 24
municipalities combinedly responsible for 30% (Table 1). Of the municipal electricity use shown, the
use by primary agriculture (Table 2) and agro-processing (Table 3) are included. The distribution of
commercial agricultural expenditure by municipality provides an indication of the relative intensity
of agriculture’s electricity usage. While the Western Cape is responsible for 8% of South African
electricity demand, its share of national agricultural electricity expenditure in 2017 equated to 22.4%
(Enerdata, 2023; GreenCape, 2022a; StatsSA, 2020a; StatsSA, 2020b), indicating that primary
agricultural sector in the Western Cape is more energy intensive than agriculture in other provinces.

4
T ABLE 1: W ESTERN CAPE ENERGY DEMAND AND CONSUMPTION : 2021
# Municipality Total annual Total Western Cumulative Commercial agriculture
demand (GWh) Cape % % electricity expenditure (2017)
1 Drakenstein 794 4.9% 4.9% 7.8%
2 George 494 3.1% 8.0% 3.5%
3 Stellenbosch 429 2.7% 10.7% 6.5%
4 Breede Valley 354 2.2% 12.9% 10.7%
5 Langeberg 319 2.0% 14.9% 6.0%
6 Mossel Bay 318 2.0% 16.9% 1.3%
7 Saldanha Bay 267 1.7% 18.5% 0.5%
8 Overstrand 252 1.6% 20.1% 0.8%
9 Witzenberg 212 1.3% 21.4% 14.8%
10 Knysna 202 1.3% 22.7% 0.8%
11 Swartland 202 1.3% 23.9% 5.2%
12 Oudtshoorn 176 1.1% 25.0% 4.8%
13 Bitou 116 0.7% 25.7% 0.3%
14 Hessequa 94 0.6% 26.3% 2.4%
15 Matzikama 88 0.5% 26.9% 3.2%
16 Berg River 83 0.5% 27.4% 3.5%
17 Cape Agulhas 78 0.5% 27.9% 1.6%
18 Cederberg 70 0.4% 28.3% 7.1%
19 Theewaterskloof 64 0.4% 28.7% 7.8%
20 Beaufort West 63 0.4% 29.1% 0.4%*
21 Swellendam 56 0.3% 29.5% 2.2%
22 Kannaland 34 0.2% 29.7% 0.9%
23 Prince Albert 10 0.1% 29.7% 0.4%*
24 Laingsburg 8 0.1% 29.8% 0.4%*
25 City of Cape Town 11 282 70.2% 100% 7.1%
Total 16 067 100% 100% 100%
SOURCE: GREENCAPE, 2022A & STATSSA, 2020A
NOTE: * REPORTED COMBINEDLY AS CENTRAL KAROO

In estimating the energy usage of the agricultural value chain in the Western Cape, one
requires a sense of the type of economic output generated by the various industries located in the
province. Limitations on data availability and access (Eskom could not provide data on electricity
use per province) required that we compile a set of analyses from various sources to gage the
energy use of agriculture and agro-processing in the Western Cape. It should be noted that much
of the data that is available is outdated. Consequently, the compilation in Table 2 and Table 3
required a series of adjustments and collations from various sources (Hortgro, CGA, BerriesZA, SATI,
SAWIS, Vinpro, WC DoA, SAGIS, FPMs, MilkSA, RPO, SAPA, SAPPA, and others).

T ABLE 2: ESTIMATED W ESTERN CAPE P RIMARY AGRICULTURAL ENERGY USAGE : 2022

Electricity Fuel
Total
Total costs Share of Share of Combined
Primary Agriculture income Spend Spend
R' million total total share (%)
R' million R' million R' million
costs (%) costs (%)
Livestock 26 559
Horticulture 36 927
75 333 2 585 3.43 2 965 3.94 7.37
Vegetables 4 101
Field Crops 11 819
Total 79 405
Estimated Electricity Use 1 200 GWh @ R2.15 per kWh
SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023

5
 Table 2 presents a brief synthesis of economic activities of the primary agricultural sector, which
includes estimations on gross farm income, total costs and the share of electricity and fuel costs to
total costs. Producers in the Western Cape spend around R75.3 billion to generate around R79 billion
worth of outputs. In total, the R2.6 billion spend to buy electricity contributed 3.43% to total costs,
whilst if we add the spending on fuel the combined total energy spend reaches 7.4%. Given these
estimates, we use the official Eskom tariff of R2.15/kWh as per their annual report to calculate total
electricity use of around 1 200 GWh in 2022.
A similar calculation for the agro-processing sector in the Western Cape is even more
challenged by data limitations. However, in broad industry terms, we calculate much of the same
indicators for the Western Cape presented in Table 2 but utilise national statistics to estimate current
levels of economic output and energy expenditure. The last time that StatsSA published information
about the provincial share of manufacturing output was in 2014. The data revealed that in South
Africa’s total sale of goods and services from the food and beverages sub-sector, the Western Cape
contributed a share of 24.7%. Similar shares were reported for the total value of wages (25.4%) and
number of employees (25.8%) (StatsSA, Manufacturing Industry: Financial, 2014). In the process of
updating agro-processing indicators, we assume that the Western Cape retained 25% share of total
income and estimate a relative share between different agro-processing industries. Our base data
originated from the Supply and Use Tables published by StatsSA (2021) with a base year of 2019. We
adjust the levels of these indicators using a combination of Producer Price Indices (PPI) to update
costs of manufacturing and total income from StatsSAs (2023) Manufacturing Production and Sales
publication to calculate best estimates of 2022 income and costs per industry, as well as the
estimated spend on electricity and fuel. Table 3 provides the estimated energy use in agro-
processing in the Western Cape. The total estimated spend on electricity of R1.27 billion implies that,
at the standard Eskom tariff for industrial firms of R1.50/kWh for 2022, these agro-processing industries
use a combined 844 GWh. In terms of shares to total costs, processors spend around 1.4% on
electricity and another 1.7% added for fuel spending to get to a combined 3.1%.

T ABLE 3: ESTIMATED W ESTERN CAPE AGRO- PROCESSING ENERGY USAGE : 2022

Electricity Fuel
Total
Total costs Share of Share of Combined
Industry income Spend Spend
R' million total costs total costs Share (%)
R' million R' million R' million
(%) (%)
Meat, fish, fruit, veg, oils 28 950 25 750 300 1.16 256 1.00 2.16
Dairy 14 500 12 718 160 1.25 174 1.36 2.62
Grain and animal feeds 10 600 9 824 128 1.30 89 0.91 2.21
Other food products 29 300 24 803 345 1.39 673 2.71 4.11
Beverages (excl. beer) 22 235 17 089 334 1.95 304 1.78 3.73
Total 105 585 89 826 1 266 1.41 1 496 1.67 3.08
Estimated Electricity Use 844 GWh @ R1.50 per kWh
SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023

The breakdown presented in Table 2 and Table 3 shows that primary agriculture and agro-
processing utilise roughly the same amount of GWh, but the spending share in primary agriculture is
more than double that of processors (3.4% vs 1.41%). This is partly due to the price difference of
electricity, but also because agricultural production is more energy intensive per unit of output. It is
also worth noting that fuel expenditure at farm level is double the expenditure at agro-processing
level.

6
 3.2. Overview of the economic impact of loadshedding
Despite the relatively low demand for electricity from agriculture, agriculture is the economic
sector most affected by loadshedding. The South African Reserve Bank [SARB] (2019) evaluated the
impact of loadshedding on the agriculture, forestry and fisheries sector’s real output growth and
found that these are negatively correlated. An increase in the intensity of loadshedding (more MW
not supplied) decreased the South African agricultural sector’s real GDP growth by 0.27%. In a
follow-up study, SARB (2022) estimated the impact of loadshedding on real GDP (quarter-to-quarter
seasonally adjusted not-annualised) growth per 1 GWh of loadshedding (Figure 3). The outcome of
the analysis shows that under the four different measures (previous estimate, unadjusted, adjusted
for weekends and public holidays, and adjusted for weekends and public holidays and outside
conventional working hours), agriculture consistently is the economic sector most affected by
loadshedding. When adjusted for weekends, public holidays and non-conventional working hours,
one additional GWh of loadshedding was estimated to lower agriculture’s quarterly growth in real
GDP by -0.0134 percentage points, on average (that is ten times the percentage point impact per
1GWh electricity supply reduction on total GDP).
For the third quarter of 2022, the loadshedding intensity was measured at 1 692.5 GWh1 when
adjusting for weekends, public holidays and non-conventional working hours. This implies that
loadshedding lowered agriculture’s quarterly real GDP growth for 2022 Q3 by an estimated -22.7%
(1 692.5GWh x -0.0134% (Real GDP growth reduction per 1GWh loadshedding)), compared to the
2.3% total GDP growth reduction for the same time period. It appears that this could be an
overstated/exaggeration of the impact on agriculture’s GDP, but it is the official figure supplied by
SARB. It could also be an indication of agriculture’s resilience to be able to mitigate the immediate
impact, where possible, and at additional cost. Thus, if industry did not take action, this impact on
agriculture could have realised unless role-players started implementing mitigation strategies.

FIGURE 3: E STIMATED IMPACT OF LOADSHEDDING ON QUARTERLY GROWTH IN REAL GDP

SOURCE: SARB, 2022

1GWh is a unit measure of energy used per hour and quantifies the intensity of loadshedding for a particular timeframe.
Here, it captures the total Gigawatt hours of loadshedding that occurred during Q3 2022.

7
 While the economic impact of electricity outages is undeniable, quantifying the impact requires
a distinction based on the nature of the outage. The cost of unserved energy (CoUE) is an
international measure used to quantify infrequent, unplanned and sudden occurrences of
electricity outages that typically have a duration of less than 3 hours. For the South African
agricultural sector, the CoUE per unit of energy not supplied is quantified at R67/kWh (for the period
2018-2019 in 2020 value). Loadshedding is argued to fall into a different category, defined as
“electricity not delivered due to frequent, recurring, and planned outages”. Consequently, the
estimation of the cost of loadshedding (CoLS) “accounts for the inherent resilience and adaptive
response of end-users” and considers the immediate direct and indirect damages and cost but
does not account for the longer-term indirect cost (Nova Economics, 2023).
Nova Economics (2023) conducted their study to estimate CoLS at a macro level, not at an
individual industry level. Thus, on a national level, the impact of loadshedding on the economy is
estimated at R9.53/kWh, with agriculture bearing 10.4% (or R0.99/kWh) of the total cost. However,
when considering the contribution to GDP, the normalised CoLS for agriculture is estimated at
R4.01/kWh, which shows that it is the sector most adversely affected by loadshedding.
While perhaps important to distinguish between the cost associated with the different natures of
outages – unplanned/sudden vs planned/recurring occurrences – the probability and magnitude
of Eskom’s unplanned outages (breakdowns) are increasing. Figure 4 highlights the relative shift from
2018 to 2022 with respect to the loss factors of planned maintenance and unplanned outages (CSIR,
2023). One of the consequences of these unplanned outages are loadshedding schedule changes
at (very) short notice, which severely limits end-users’ ability to respond.

FIGURE 4: P LANNED AND UNPLANNED OUTAGES (BREAKDOWNS) TREND : 2018-2022

SOURCE: CSIR, 2023
NOTE: DATA PRESENTED IS HOURLY TEMPORAL RESOLUTION

Given the trend described above, it is not surprising that 2022 has been the most intensive
loadshedding year. South Africans experienced more loadshedding in quarter 3 of 2022 than in any
other preceding year. This gruelling loadshedding schedule was trumped in December 2022, where
more loadshedding was experienced in a single month than in any year before 2022. Figure 5
highlights the extent of loadshedding in 2022 compared to previous years (CSIR, 2023).

8
FIGURE 5: UPPER LIMIT OF CUMULATIVE LOADSHEDDING ANNUALLY : 2014-2022
SOURCE: CSIR, 2023

Figure 6 breaks down the hourly distribution of loadshedding, highlighting the contrast between
the first and second half of the year as well as the extent of switches between stages. The figure also
provides context on the most occurring stage (stage 4) compared to the previous norm (stage 2).
Lastly, this figure is paramount to quantify the short- and medium-term impact of loadshedding on
the upstream, on-farm and downstream operations of the Western Cape agricultural sector.

FIGURE 6: H OURLY DISTRIBUTION OF LOADSHEDDING : 2022

SOURCE: CSIR, 2023

Although loadshedding is considered planned outage, the rapid escalation in the extent thereof
highlighted in Figure 5 and Figure 6, left many role-players in agricultural value chains vulnerable
and underprepared to mitigate its impact. The life-time cost comparison of batteries, diesel
generators and solar in Figure 7 provides a high-level overview of both the initial capital investment
required for the different options, as well as a levelised cost of storage (LCOS) and procurement of
electricity from a solar power provider (GreenCape, 2023a). LCOS accounts for all costs incurred,

9
including the cost of replacement in the case of batteries, and energy produced throughout the
lifetime of the device. Except for solar, which is the most expensive option from an investment cost
perspective, the cost of operating on any other alternative source starts at R4/kWh, which is 2-3
times more expensive than electricity sources from Eskom.
8 16
LCOS or PPA (R/kWh)

Investment cost (R'000/kW capacity)

6 12

4 8

2 4

0 0

Lead acid Advanced Lead Lithium-ion Diesel Generator Rooftop solar PV

( 2) Acid ( 4)
Levelised cost of storage (LCOS) Power purchase agreement (PPA) Investment cost
FIGURE 7: INVESTMENT COST AND LCOS COMPARISON OF BACKUP TECHNOLOGIES
SOURCE: GREENCAPE, 2023A

3.3. High-level policy overview

There are critical policy components applicable to the analysis of the impact of loadshedding on
the Western Cape Agricultural sector. Table 4 below highlights these.

T ABLE 4: HIGH - LEVEL OVERVIEW OF POLICY APPLICABLE TO THE LOADSHEDDING IMPACT STUDY
Exclusion of critical infrastructure Tax rates and rebates
Regulation NRS048-9, the national standard for To uphold the commitment made at the 2021 United
loadshedding, regulates the implementation of Nations Climate Change Conference (COP26),
loadshedding with consideration for: South Africa’s carbon tax rate will increase annually
to reach R450/tonne by 2030. The current effective
• the safety of people and the environment
rate is R159/tonne (GreenCape, 2023a).
• the potential damage associated with plants of
a critical nature, e.g., waterworks According to the most recent budget speech
• constraints of a technical nature in the (National Treasury, 2023), a rebate of 25%, up to a
execution of loadshedding (Department of maximum of R15 000, can be claimed for rooftop
Economic Development and Tourism [DEDAT], solar panels installations from 1 March 2023.
2019) Businesses can also take advantage, using the
Section 12B capital allowance, to depreciate 100%
Critical infrastructure, and properties sharing of the initial cost in year 1, effectively increasing the
dedicated electricity supply lines with such tax rebate to 12%. According to PwC (2023),
infrastructure, is therefore excluded. This includes, businesses will be able to claim a deduction of 125%
but is not limited to hospitals, ports, railways, water in the first year on all new renewable energy
treatment plants, food production and storage projects. This allowance is valid until February 2025
facilities (where technically feasible), critical on wind, solar, hydropower and biomass, but
electronic communication and broadcasting excludes batteries and inverters.
infrastructure, and other essential infrastructure.
Manufacturers of foodstuffs can claim a refund on
If loadshedding were to be implemented at the the Road Accident Fund levy for diesel to reduce the
Cape Town port terminal, Transnet requires two- impact of loadshedding on food prices. This applies
weeks’ notice, after which negotiations between to the fuel used to run infrastructure used in the
Eskom and the port authorities will start to determine manufacturing process, e.g., generators (National
the extent of loadshedding the port will experience. Treasury, 2023).

10
 Curtailment Energy supply regulation
Curtailment – the action of power usage reduction Continuous approval of energy trading licences by
– can either be voluntary or required on a specific the National Energy Regulator of South Africa
energy supply zone. The goal of curtailment is to (NERSA) allows developers to contractually supply
reduce dependency on electricity supply to avoid energy to the energy trader via power purchase
or reduce loadshedding. Large customers with the agreements (PPA). A diversified customer pool is
own electricity supply from a main station can provided by the trader, together with flexible and
implement curtailment to avoid loadshedding. affordable energy contracts for the South African
Where more than one customer is supplied from a market. The action reduces developers’ overall off-
main station, curtailment relies on collaboration by take risk (GreenCape, 2023a).
the customers in the zone. Curtailment
Proposed amendments to Schedule 2 of the
arrangements – the extent of power usage
Electricity Regulation Act, 2006 (ERA) were published
reduction – is specified by zone and level of
by the Minister of Mineral Resources and Energy for
loadshedding (DEDAT, 2019). In February 2023,
public comment. The proposed changes include:
around 20 farms on the Broodkraal feeder line in the
Berg River Valley avoided loadshedding by • Removal of the current 100 MW threshold
reducing their electricity usage when requested by • Clarification on the activities that can occur
Eskom to do so (Scholtz, 2023). without requiring a generation license, but
would still require registration with NERSA
(GreenCape, 2023a).

3.4. Overview of agricultural surveys

Three voluntary, online surveys by industry bodies were executed over the last 18 months to
extract essential details with respect to the impact of loadshedding on operations in the agricultural
sector. While some were completed at a national level, the application and relevance within the
context of the Western Cape agricultural sector holds.
A total of 360 respondents participated in the Agri Western Cape survey in November 2021. A
large proportion of the respondents are involved in primary agriculture (92%), with 49% of
respondent only involved in primary agriculture, compared to the 43% of respondents that are
vertically integrated primary producers, and 8% are value chain role players outside of primary
production. Most respondents (93%) are fully dependant on Eskom, either directly or via their
municipality, and do not have any permanent alternative sources, with less than 1% completely
independent from Eskom. Of the complement (6%), half is still 70% or more dependent on Eskom,
with the other relying on Eskom for less than 70% of their total energy needs. Given the limited
alternative energy sources recorded and the vast majority of respondents involved in primary
production, it is not surprising that the biggest demand of energy occurs during daytime (06:00-
17:00). Of the 360 respondents, 196 require electricity supply for 12 hours or less a day, whereas 106
require supply for more than 18 hours a day. The complement (58 of the 360) typically require supply
between 12 and 18 hours a day. Although not explicitly stated, a logical explanation for the timing
of electricity demand is related to the typical work hours – single shift on farms, double shifts in
packhouses and processing facilities, with cold storage facilities requiring continuous (24/7) supply
(Agri Wes-Kaap [AWK], 2021).
In a voluntary national survey by AgBiz, 489 operators in agricultural value chains provided input
into the impact of loadshedding on their businesses (Table 5). The table indicates the spread by
node and size of participants. From the survey results, it was found that the biggest impact of
loadshedding include losses incurred in terms of irrigation water and time, operational hours and
cooling abilities, product quality and/or volume are the biggest risks. In addition, greater operational
and capital expenditure, together with equipment damage are affecting businesses in the
agricultural value chains. Additional operational expenditure ranges from R2 000 per month to R10

11
million per month, with reported indirect cost of up to R20 million per month, whilst capital
expenditure of up to R220 million to mitigate loadshedding was recorded. The bulk (90%+) of
participants indicated that they cannot or can only partially pass this additional cost on into the
value chain. Given the cost that has to be absorbed in the chain together with the losses incurred,
70% of the respondents indicated that they expected shortages of agricultural products and food
to occur. To mitigate the impact of loadshedding and invest in alternative energy sources, the
majority of respondents indicated that financial assistance such as a subsidised loan (57%) would
persuade them to invest in self-sufficient electricity supply solutions, followed by the ability to sell
excess electricity freely (16%) and the removal of barriers to grid access (8%). One tenth of
respondents indicated the nature of their energy consumption is such that no alternative sources
can feasibly meet the demand.

T ABLE 5: OVERVIEW OF PARTICIPANTS BY VALUE CHAIN NODE AND OPERATIONAL SIZE

Small (<R10m Medium (R10m-R50m Large (>R50m Total %
turnover per annum) turnover per annum) turnover per annum)
Upstream 28 13 36 77 16%
Production 143 132 82 357 73%
Downstream 13 13 29 55 11%
Total 184 158 147 489 100%
% 38% 32% 30% 100%
SOURCE: AGBIZ, 2023

Fruit SA surveyed more than 200 role-players in the fruit industry across the country. In the survey,
95% of the participants are more than 50% dependent on Eskom, with only 7% of those participants
indicating a reliance of 50-80%. While these results do indicate that there has been investment in
alternative energy infrastructure to supplement operational energy demand, the vast majority of
participants are dependent on Eskom electricity supply to run operations. Considering the energy
demand to run operations optimally, 52% of participants indicated that their operations require
uninterrupted 24-hour energy supply. It is believed that these participants are most likely running
technologically advanced irrigation/fertigation systems at farm level and/or packhouses and cold
storage facilities. Other participants typically require between 8 and 12 hours of electricity per day
to run their operations optimally. It appears that there is a strong correlation between participants
with back-up power in case of loadshedding and the participants with high reliance on electricity
supply, as 56% of participants indicated that they have back-ups, with the bulk thereof being diesel
generators (73%), followed by solar (15%) and other solutions (12%). Table 6 highlights the average
irrigation hours per commodity, on average, for the participants of the survey, as well as the average
operating hours per day, in agro-processing.

T ABLE 6: OVERVIEW OF PRIMARY AND SECONDARY ENERGY DEPENDENCY

Primary Secondary
Western Cape Off-peak season Peak season In-season
survey data Responses Avg. irrigation Responses Avg. irrigation Responses Avg. usage
hours/day hours/day hours/day
Berries 23 12.6 22 13.5 16 18.3
Table grapes 71 16.7 71 17.7 68 13.8
Citrus 21 16.1 22 13.8 15 16.4
Avocados 6 11.5 5 15.7 4 13.0
SOURCE: FRUITSA, 2023

12
4. ENERGY DEPENDENCY OVERVIEW
At a provincial level, the width and depth of the agricultural sector in the Western Cape is likely
unmatched elsewhere in the country. Primary production operations span approximately 13 million
hectares, of which 2 million hectares are cultivated and 320 000 hectares are under irrigation (WC
DoA, 2022). Multiple livestock, field crops and horticulture commodities are produced in the Western
Cape, complemented by an expansive agro-processing and value adding industry. Consequently,
the energy demand and dependency in the province could differ considerably between regions,
commodities, facilities and the risk associated with the demand and dependency. In order to
provide an overview of the energy dependency of the Western Cape agricultural sector by
subsector / industry, consideration will be given to the type of energy being used and the suppliers
of energy (Eskom direct, municipality or own generation), and the spatial and temporal distribution
(within a day and between seasons) of energy use.

4.1. Overview of energy sources and electricity use

Energy is a key input in the production, storage, and processing of agricultural products. While
some processes are typically driven by energy sources that are not electricity, e.g., coal, the bulk of
processes are primarily dependent on electricity supply. Table 7 provides a high-level overview of
the conventional and alternative energy sources by industry. The semi-structured interviews
conducted with key stakeholders confirmed dependency on Eskom as the primary source, as has
been identified in the AWK survey, although investment in alternatives have increased to reduce
the impact. In an industry such as intensive livestock production, e.g. broilers, installation of
alternative energy supply is part and parcel in the development, as the consequences of supply
interruption is too great a risk to bear. Thus, while the industry may be better prepared to deal with
loadshedding as it is prepared for unplanned and sudden occurrences of electricity outages, the
installed infrastructure was not meant to deal with the extensive (more than 11 529 hours)
loadshedding in 2022. It also implies that for the periods where producers rely on prolonged use of
backup power, they are at risk of power failure if that backup fails, with no alternative. For instance,
if a backup generator fails while running during a prolonged outage, broiler producers that rely on
controlled environment housing can suffer significant damages. At higher levels of loadshedding,
this risk is greater. The electricity demand for major actions in different industries at various nodes in
the value chain are shown in Table 8.

T ABLE 7: P REDOMINANT ENERGY SOURCES BY INDUSTRY

Industry Conventional Alternative
Heating Cooling Processing/ Heating Cooling Processing/
value-add value-add
Livestock
Coal Electricity Electricity n/a Diesel generator/ Diesel generator
Solar PV(& BESS)
Irrigation Cooling Processing/ Irrigation Cooling Processing/
value-add value-add
Horticulture
Electricity Electricity Electricity Diesel generator/ Diesel generator/ Diesel generator/
Solar PV (& BESS) Solar PV (& BESS) Solar PV (& BESS)
Irrigation Dryland Processing/ Irrigation Dryland Processing/
value-add value-add
Field crops
Electricity n/a Electricity Diesel generator/ n/a Diesel generator
Solar PV (& BESS)
SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023

13
T ABLE 8: ELECTRICITY DEMAND ESTIMATES BY MAJOR INDUSTRY , NODE AND ACTION
Industry Node Action Unit of measure kWh per unit
Livestock Primary Broiler Per tonne 150-300
Piggery Per tonne 100-200
Feedlot Per tonne 30-50
Dairy Per 1 000 litres 30-50
Agro-processing / value-adding Meat processing Per tonne processed 200-400
Dairy processing Per 1 000 litres 250-300
Horticulture Inputs Packaging material Per packed tonne 15-20
Primary Irrigation Per hectare 2 400-5 000
Agro-processing / value-adding Packhouse Per packed tonne 30-40
Juicing Tonne 100-200
Canning Tonne 100-200
Cellar Tonne 90-110
Distribution & marketing Cooling Tonne 80-180
Field crops Primary Irrigation Per hectare 1 800-6 000
Agro-processing / value-adding Crushing Per tonne 40-60
Milling Per tonne 90-110
SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023

While it is assumed that the vast majority of commercial primary production would occur in rural
areas, there is a small component (3%) of livestock production (e.g., feedlots, piggeries, dairies,
chicken batteries) that is typically situated within town boundaries. An overlay of built-up/town
areas2 with the infrastructure recorded in the 2017 fly-over also provided the necessary base to
develop Table 9. The table provides a breakdown of the number of facilities by type and location,
concluding that 15% of commercial agro-processing and value-adding facilities are located in
urban areas. These indicators provided the upper limits with respect to the supplier of electricity to
agro-processing facilities, with 85% facilities likely to depend on Eskom directly.

T ABLE 9: LOCATION OF COMMERCIAL AGRO - PROCESSING AND VALUE - ADDING FACILITIES : 2017
Facilities # Urban facilities # Rural facilities Total Urban share Rural share
Horticulture
Fruit drying 1 3 4 25% 75%
Citrus processing 1 1 2 50% 50%
Canned fruit 1 0 1 100% 0%
Berry processing 0 3 3 0% 100%
Berry 0 1 1 0% 100%
Other 140 161 301 47% 53%
Bottling and juice 0 1 1 0% 100%
Fruit packers and cold chain 24 129 153 16% 84%
Cool chain facilities 36 28 64 56% 44%
Wine cellar 73 504 577 13% 87%
Olive and wine cellar 2 32 34 6% 94%
Distillery 6 8 14 43% 57%
Agri packhouse 20 962 982 2% 98%
Fruit packers 14 74 88 16% 84%
Olive cellar 3 49 52 6% 94%
Nursery 33 191 224 15% 85%
Horticulture sub-total 354 2147 2501 14% 86%

2These are approximate and quite outdated town boundaries, therefore leading to a likely underestimation of proportion
of infrastructure situated within town or municipal boundaries today (2023).

14
 Field crops
Millers 22 22 44 50% 50%
Grain storage 41 310 351 12% 88%
Brewery 34 29 63 54% 46%
Tea processing 1 74 75 1% 99%
Field crop sub-total 98 435 533 18% 82%
Livestock
Meat processing 32 59 91 35% 65%
Livestock sub-total 32 59 91 35% 65%
Total 484 2641 3125 15% 85%
SOURCE: WC DOA, 2018

4.2. Spatial and temporal distribution of electricity use

While the total electricity demand of the value chains for livestock, horticulture and field crop
industries in the Western Cape are estimated in Table 2 and Table 3 there is also a spatial distribution
of electricity use that is linked to the density of production. In Figure 8, the four maps provide a
spatial overview of the density of intensive livestock production, the density of drip and micro
irrigation (a proxy for horticultural production), and summer and winter pivot irrigation (a proxy for
irrigated field crops and pastures).

FIGURE 8: P RIMARY AGRICULTURE : (A) LIVESTOCK, (B) HORTICULTURE , (C) W INTER & (D) SUMMER CROPS
SOURCE: COMPILED BY BFAP FROM WC DOA, 2018, AND ESKOM. 2022

The most prominent intensive livestock operations in the Western Cape are dairies, chicken
batteries, piggeries and feedlots. While dairies are spread across the Overberg, Southern Cape and

15
West Coast regions, chicken batteries are predominantly found in the rural areas in close proximity
to the more densely populated southwestern parts of the province. Piggery locations follow a similar
pattern to chicken batteries but does branch out further north in the province. Feedlots, although
in number the smallest of the intensive livestock production group, appear to be rather scattered
across the province. These operations function continuously, with a fairly even electricity demand
distribution throughout the year. Higher demand for meat products during November and
December results in an uptick over this period.
Considering both the density of irrigation area by municipality and the unitary electricity
demand from Table 8, together with the seasonality of irrigation which is affected by rainfall, a
temporal distribution of electricity demand for irrigation purposes per municipality can be created
(Table 10). The table, sorted according to the total annual electricity demand in GWh for irrigation
purposes indicates that the Witzenberg municipality has the highest demand at 91 GWh per annum.

T ABLE 10: T EMPORAL DISTRIBUTION OF ELECTRICITY DEMAND FOR IRRIGATION PURPOSES IN GW H : 2017
Municipality Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total
Witzenberg 18.36 13.98 10.99 3.78 1.07 0.57 0.80 1.19 3.36 7.59 12.59 16.45 91
Langeberg 16.22 12.15 9.06 4.27 1.89 1.14 1.38 1.83 4.02 7.74 12.41 15.29 87
Breede Valley 15.87 13.97 10.68 4.09 1.47 0.82 1.00 1.33 3.10 6.83 11.82 15.06 86
Oudtshoorn 13.10 10.13 8.56 5.07 3.58 2.75 3.00 3.66 5.29 7.79 10.23 12.74 86
Theewaterskloof 14.39 11.29 9.21 3.20 1.06 0.72 1.05 1.47 3.42 6.63 10.12 13.13 76
Cederberg 10.75 8.68 8.39 4.92 2.81 2.06 2.21 2.77 5.09 7.07 8.86 10.57 74
George 9.92 7.50 6.24 3.34 2.15 1.65 1.86 2.32 3.62 5.72 7.80 9.68 62
Drakenstein 10.82 9.19 6.76 2.83 1.00 0.52 0.70 0.96 2.35 4.81 8.16 10.16 58
Kannaland 8.89 6.83 5.60 3.14 2.07 1.55 1.71 2.10 3.17 4.89 6.70 8.46 55
Hessequa 7.62 5.83 4.90 2.87 1.98 1.52 1.68 2.06 3.06 4.60 6.07 7.52 50
Swartland 8.16 6.79 4.94 2.19 0.89 0.70 1.13 1.49 2.99 4.63 6.67 8.03 49
Swellendam 7.05 5.28 4.46 2.45 1.53 1.19 1.43 1.82 3.00 4.36 5.58 6.89 45
Berg River 6.37 5.34 4.60 2.32 1.32 1.16 1.44 1.77 2.96 4.10 5.17 6.34 43
Stellenbosch 7.55 6.16 4.23 1.96 0.77 0.39 0.53 0.71 1.69 3.43 5.97 7.11 40
Matzikama 6.49 5.48 3.98 1.80 0.81 0.50 0.61 0.77 1.56 3.09 5.20 6.28 37
Mossel Bay 5.44 4.19 3.50 2.06 1.43 1.11 1.24 1.53 2.24 3.27 4.27 5.32 36
Beaufort West 3.70 2.88 2.43 1.44 1.02 0.78 0.85 1.04 1.49 2.18 2.87 3.58 24
City of Cape Town 3.65 3.00 2.14 0.99 0.42 0.24 0.31 0.40 0.88 1.75 2.92 3.51 20
Prince Albert 2.22 1.75 1.45 0.82 0.54 0.40 0.44 0.54 0.81 1.24 1.68 2.12 14
Knysna 2.04 1.55 1.31 0.79 0.56 0.43 0.47 0.58 0.84 1.26 1.65 2.03 14
Overstrand 1.39 1.11 0.86 0.43 0.23 0.16 0.18 0.23 0.41 0.73 1.10 1.34 8
Laingsburg 1.02 0.77 0.63 0.33 0.20 0.15 0.16 0.20 0.33 0.54 0.76 0.96 6
Bitou 0.67 0.52 0.43 0.25 0.18 0.13 0.15 0.18 0.26 0.39 0.51 0.64 4
Cape Agulhas 0.45 0.33 0.25 0.13 0.07 0.06 0.08 0.10 0.18 0.31 0.43 0.50 3
Saldanha Bay 0.18 0.13 0.10 0.06 0.04 0.06 0.12 0.16 0.27 0.25 0.17 0.20 2
Total 182 145 116 56 29 21 25 31 56 95 140 174 1 069
SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023

Total irrigation electricity demand is calculated to be slightly more than 1 TWh per annum, using
the 2017 fly-over data as a basis. Table 10 also highlights the impact of winter rainfall and growing
seasons on electricity demand, with demand peaking in the hottest and most important growing
months – October to March. 80% of the total electricity demand occurs within these six months, with
only 20% demanded over the winter period of April to September. Considering the substantial
loadshedding during the second half of 2022 (Figure 5 and Figure 6), both short- and longer-term
negative impacts on production could be expected.

16
 Table 10 covers the aggregate of horticultural production, winter and summer crop production
under irrigation – both spatially and temporally. In addition to electricity demand for irrigation
purposes, electricity is also critical input into other nodes and value chains. Intensive livestock
operations function on fairly even levels throughout the year, resulting in the consequent demand
of electricity downstream to also be fairly consistent, with the exception of the uptick over the latter
part of the year. In terms of field crops and horticulture, the demand of off-farm services typically
increases for a period of around six months of the year, during and post-harvest, after which facilities
run at much lower electricity demand levels as most energy-intensive processes are completed for
the season.

B OX 1: DEPENDENCY ON ESKOM FOR EXTRACTION OF SCHEME WATER – B ERG RIVER CASE STUDY
Water is the most critical natural resource in the agricultural sector, not only for irrigation purposes but
also for animal husbandry and human consumption. The Berg river region is home to more than 650 000
hectares of cultivated agricultural land, of which around 80 000 are irrigated fields (WC DoA, 2018). To
maintain crop yields, quality of produce, ensure sustainable farming and support animal and human
consumption, good quality and consistent quantities of water is of utmost importance.

FIGURE 9: B ERG RIVER WATER MANAGEMENT AREA

SOURCE: DEPARTMENT OF ENVIRONMENTAL AFFAIRS AND DEVELOPMENT
PLANNING [DEADP], 2011

Irrigated crops differ in the amount of water

necessary for optimal growth and production.
Within the Western Cape, the irrigation requirement
is generally lower during the winter months due to
lower transpiration rates and higher rainfall.
However, in the summer months timely irrigation is
essential to limit stress on crops, increasing the
dependency on electricity in the supply of water
within the Berg River Water Management Area.
Sensitive crops like berries and vegetables would be
impacted severely even with only little restrictions in
water supply, while table grapes, fruit orchards and
wine grapes could be impacted to a lesser extent,
although the consequences could still be
detrimental to production. Animal husbandry would also be affected since water is necessary all year
round.
Within water schemes, producers are entitled to a given amount of water per annum, whereafter
various limitations are set per day, week and/or month. Any external influence that inhibits users to pump
the necessary daily usage, or to fill buffer dams with surplus water, results in user allocated water being lost
to sea. Therefore, not being able to pump water directly from the Berg river or sub-station, due to
loadshedding, will not only result in less available water for on-farm usage but also wastage of water.
Water released from the Berg River dam takes approximately four days to reach the last water-user
within the scheme (whereas water released for the Zonderend Water Use Association takes ±20 days to
reach the last producer). Constantly changing between stages of loadshedding causes a ripple effect and
makes planning within the scheme extremely difficult. To quantify, approximately 33 million m3 of water on
average per season are released into the Atlantic Ocean in normal years (little to no loadshedding), while
around 48 million m3 of water has flowed through the estuary in the 2022/23 season due to the indirect
influence of loadshedding, difficulty of planning and mismanagement. Compared to the previous summer
season (1 November – 20 April), 6% less water was released from the dam in 2022/23 while water extraction
from the scheme decreased by 18%. Water released for agricultural use but not extracted increases risks at
farm level and is likely to result in a decrease in the economic output of the area.

17
 One example of a direct impact of loadshedding can be seen in the Perdeberg area. This region
consists mainly of vineyards and is dependent on a single large pump to extract water directly from the
Berg river for irrigation purposes and human and animal consumption. Large pumps like this need
approximately three hours to reach full capacity to feed the line from which individual producers extract
water to their production units. Consequently, the impact on producers is already extreme during
loadshedding stage 5 – not only because of the “off” hours, but because the “on” hours are in some
instances limited to four consecutive hours, which effectively reduce extraction at capacity to 1 hour in 10
hours. In such a case, the pumping of water during loadshedding becomes unviable. The scheduled water
available, released from the dam in the river for extraction by users in the Perdeberg area, is lost to sea and
is putting production and the economic viability of farms at risk.
SOURCE: BERG RIVER MAIN IRRIGATION BOARD, 2023

5. IMPACT OF LOADSHEDDING
A systematic approach was used to address the problem of quantifying loadshedding impacts
at various stages. Firstly, the relationship(s) between causes and effects in the Western Cape
agricultural sector are analysed and described. Thereafter, impact is evaluated based on
operations, volume and price, and ultimately profitability. These analyses provide the necessary
platform to unpack loadshedding’s socio-economic impact and impact on government
objectives.

5.1. Causality argument

One of the golden threads throughout the study has been the interconnectedness of value
chains – not only within a single commodity, but across commodities. The second thread widely
observed is that loadshedding sets off a series of events, many of them having a knock-on effect
on other matters. To analyse the relationship(s) between causes and effects in the Western Cape
agricultural sector, Interactive Qualitative Analysis (IQA), developed by Northcutt and McCoy
(2004), is employed to establish causality and identify potential feedback loops. A feedback loop
is present if there is a recirculation of an influence pattern within a group of three or more system
elements. The effect of the feedback is strengthened and accelerated by means of its recirculation
through the various elements in the system. IQA is a research design that establishes an in-depth
understanding of phenomenon by axial coding of data in a systematic process. By grouping core
phrases together and assigning an appropriate name to each collection, it is possible to move away
from an assortment of core phrases to a unit of meaning. The differences with respect to the extent
of meaning between grouped and named phrases are first determined and then graphically
depicted to show all possible relationships. The outcome of the application of this research design
is a systems influence diagram (SID), which links construct relationships and clearly illustrates
associations between the major influences (Northcutt & McCoy, 2004).
The data collected during the semi-structured interviews were coded, grouped and analysed
to construct the causality arguments. Eight themes emerged when the coded data was grouped,
which became the system elements, as outlined in Table 11. Determining all the “out” and “in”
relationships for each element enables determining which elements are the driving forces behind
most change within the system, and which elements mostly become the subject of change in the
system. The inter-relationship diagram shows that the impact of loadshedding is setting of a chain
of events starting with ‘Operational capacity & scheduling’ (biggest delta, thus ranked first). The
second biggest driver is ‘Input supply & availability’, referring to typical inputs, as described in Figure
2. The biggest outcomes – elements subjected to change in the system, are the ones with the
biggest negative delta, namely socio-economics and product selling prices.

18
T ABLE 11: T ABULAR INTER - RELATIONSHIP DIAGRAM
1 2 3 4 5 6 7 8 Out In  Rank
1 Opex & Capex /// ^ * < ^ < * * 2 2 0 4
Financial implications
2 < /// < ^ < < ^ ^ 3 4 -1 5
(cash flow & profitability)
3 Output quality & volume * ^ /// < ^ < * 3 ^ 2 1 3
4 Input supply & availability ^ < ^ /// * ^ ^ 4 * 1 3 2
5 Product selling price < ^ < * /// < * 1 < 4 -3 8
6 Operational capacity & scheduling ^ ^ ^ < ^ /// ^ 6 ^ 1 5 1
7 Biological, current & fixed assets * < * < * < /// 1 ^ 3 -2 6
8 Socio-economics * < < * ^ < < 1 ///4 -3 7
21 21 0
/// Same element in column & row < Relationship exists where column element influences row element
* No direct relationship exists ^ Relationship exists where row element influences column element
SOURCE: COMPILED BY BFAP, 2023

The saturated SID indicates all directions of influence between the respective elements and is
therefore extremely complete and rich in data, but also difficult to understand and interpret. Figure
10 graphically depicts the data from Table 11, clearly showing that there are definite drivers and
outcomes in the system due to loadshedding. The relationships on the left side of the figure have
more outgoing arrows than inwards, while the opposite holds true to those elements on the right
side.

Financial
Output quality
implications (cash
& volume
flow & profitability)

Operational
capacity & Biological, current
scheduling & fixed assets

Input supply & Socio-

availability economics

Product selling
Opex & Capex
price

FIGURE 10: CLUTTERED SYSTEMS INFLUENCE DIAGRAM

SOURCE: COMPILED BY BFAP, 2023

Although the saturated SID shows the total range of influences, a simple, more elegant SID should
make the core of the system more understandable. Figure 11 is a cleaned version of Figure 10,
where the directions of influence that unnecessarily complicate the diagram have been removed
so that it can be interpreted more easily. It is the simplest form in which the system can be explained
and depicted. The method followed to remove the unnecessary links is as follows: starting from the
largest to the smallest delta, as per Table 11, all the direct links between relationships are removed,
unless there is no indirect route (via another relationship) by which the influence can be transferred.

19
 Financial
Output quality
implications (cash
& volume
flow & profitability)
Operational
Biological, current
capacity &
& fixed assets
scheduling

Input supply & Socio-

availability economics

Opex & Capex Product selling

price

FIGURE 11: UNCLUTTERED SYSTEMS INFLUENCE DIAGRAM

SOURCE: COMPILED BY BFAP, 2023

From this uncluttered SID the chain of events caused by loadshedding on the agricultural sector
of the Western Cape, the causes and effects, starts to become clearer. This figure also already
indicates that there appears to be feedback loops in this system. The final SID, Figure 12, contains
the exact same details as Figure 11, but it is presented in a more elegant manner to provide a clear
view as to the causes and effects. This figure also highlights that four feedback loops exist in the
system, as indicated by the arrows. Not only does this strengthen the argument of complexity and
interconnectedness in the agricultural value chains, but it also exposes the risk continued
loadshedding poses to the sector.

Operational
capacity &
scheduling

Financial
Input supply & Biological, current
implications (cash
availability & fixed assets
flow & profitability)

Output quality &

volume

Product selling Socio-

Opex & Capex
price economics

Feedback loop 1 Feedback loop 2 Feedback loop 3 Feedback loop 4

FIGURE 12: F INAL SYSTEMS INFLUENCE DIAGRAM
SOURCE: COMPILED BY BFAP, 2023

20
 While each inter-relationships in Table 11 can be explained as it has been described in the
interviews, the emphasis of the discussion of the causal relationships falls on uncluttered SID, which
explains the critical path of influence in the system. In total, 11 causal relationships form part of this
critical path. A brief description of each element and each of these inter-relationships are provided
in Table 12.

T ABLE 12: DESCRIPTION OF ELEMENTS AND RELATIONSHIPS

“Cause” Description of element “Effect” Description of relationship
element element (impact of “cause” on “effect”)
Operational Level at which operations can continue Socio- Changes in labour demand, shift
capacity & under different stages of loadshedding economics schedules and work hours;
scheduling and the extent of scheduling issues changes in supply to consumers
role-players have to deal with due to constraints
Socio- Socio-economic impacts, including Product Consumer push-back (reduction in
economics impacts on agri workers and on selling price demand) on the cost passed on in
consumers the value chain
Product The price at which role-players in the Financial Changes in product prices
selling price value chain sell the outputs implications affecting cash flow and profit
Financial Profitability of operations and the Biological, Selling of assets/delayed
implications extent of cash flow interruptions and/or current & replacement of assets due to
changes fixed assets financial constraints
Biological, The different assets of role-players that Socio- Reduced asset structure requires
current & forms part of their operations economics smaller workforce, negatively
fixed assets affecting employment
Financial See above Input supply Inability to source inputs in a timely
implications & availability manner, when available
Input supply All inputs into the various value chains, Opex & Changes in the supply and
& availability the extent of supply interruptions and Capex availability of inputs, including
the extent to which role-players electricity, changes the
downstream can rely on upstream operational budgets and capital
input supply availability outlay of role-players
Opex & Operational and capital expenses of Product Recovering expenditure from
Capex role-players in value chains selling price produce prices
Input supply See above Output Changes in production due to
& availability quality & reduction in quantity/quality in
volume available/affordable inputs
Output The quantity and quality of outputs of Product Different prices for different quality
quality & role-players in value chains selling price products; equilibrium price
volume changes due to volume changes
Input supply See above Operational Changes in timing and volume of
& availability capacity & inputs changes capacity limit and
scheduling timing of operational activities
SOURCE: COMPILED BY BFAP, 2023

While the SID indicates four feedback loops, the flow of impact in the system can, of course, run
concurrently through multiple loops, and it can switch between feedback loops. What this means,
is that the product selling price has financial implications, which can simultaneously affect an agri-
business’ ability to retain assets and its ability to procure inputs, if available. Also, at any system
element that forms part of multiple feedback loops, i.e., ‘Input supply & availability’, ‘Product selling
price’, and ‘Financial implications’, the course of impact can be redirected out of one feedback
loop into another.

21
 5.2. Impact on operations
The impact of loadshedding on agricultural operations in the Western Cape can be broadly
categorised as direct and indirect impacts. Throughout these integrated value chains both
dependent and independent loadshedding impacts can be observed. The objective of this section
is to highlight the biggest risks for businesses in these value chains – how and when operations are
affected. The following section – impact of loadshedding on volume and price – will expand on the
quantified impact.
A value chain is only as strong as its weakest link. Thus, the highest level of risk of operational
failure lies within breakages in the value chain. Although impossible to accurately qualify breakages
in value chains, it can generally be assumed that under a certain level of stress, a chain can
temporarily or permanently break. An example of a temporary break could be where all operations
within a vegetable packhouse cannot run during loadshedding. The results could be a backlog in
delivery to the market, which, if frequent enough, could result in temporary over- and
undersupplying of the market. An oversupply situation will impact farm level profitability, whilst an
undersupply situation will increase the price paid by consumers. In addition, it could also affect
operations at farm level – calling for a stoppage in harvesting, which, in turn, could affect quality,
sizing, and waste issues. It is likely to also increase the cost of production. An example of a
permanent break is when operations are ceased. This is likely to be the result of an inability to absorb
or pass cost on in the chain. An example is provided in Box 4 – which presents a case study on Apple
production.
Table 13 provides a Likert scale schematic overview of the risk posed by different levels of
loadshedding, as derived from surveys and interviews with industry stakeholders. It is assumed that
businesses are primarily dependent on Eskom to supply energy. The colour scheme varies from green
(level 1), indicating that most role-players are, on average, comfortable to manage/continue
normal/close to normal operations under a certain level of loadshedding, to red (level 5), indicating
that managing/continuing operations under a certain level of loadshedding is extremely difficult
thus negative impacts on output would be expected. The lighter green (level 2), yellow (level 3) and
orange (level 4) indicates a gradual increase in the difficulty to manage the impact of
loadshedding on operations. Black indicates the ceasing of operations or severe output reduction,
effectively disrupting the whole value chain and causing severe knock-on effects. The colour
scheme is also indicative of the magnitude to role-players negatively affected (or unable to cope)
under certain stages of loadshedding.
As stated, the table indicates the average, which implied that there is a range where some role-
players are less affected, or, more able to mitigate the impact, whereas others are more exposed
to the risks posed by various stages of loadshedding. From the interviews with stakeholders, it
became clear that smaller role-players are more vulnerable. This holds true throughout the different
value chains, but we would like to highlight emerging producers and informal processors, together
with smaller commercial producers. One could, to a large extent, assume that impact of
loadshedding on these role-players are typically one level higher than what is indicated in Table 13
and operational activities of these producers and agro-processors would be disrupted at one stage
of loadshedding earlier than for the average indicated in the table. There are indications that some
of these smaller operators have also closed down in the last 12 months. On the other hand, large
scale producers and agro-processors who have already invested extensively in alternatives can
temporarily absorb more of the impact of various stages of loadshedding than indicated in the
table.

22
T ABLE 13: M ATRIX INDICATING THE IMPACT OF DIFFERENT STAGES OF LOADSHEDDING ON OPERATIONS
Loadshedding stage Black
1 2 3 4 5 6 7 8 out
Inputs Packaging
Fertiliser & chemicals
Water
Production Dryland field crops
Irrigated field crops
Dryland horticulture
Irrigated horticulture
Extensive livestock production
Intensive livestock production
Processing/value-adding Packing
Juicing
Canning
Cellars
Cold storage
Crushing
Milling
Meat processing3
Frozen storage
Distribution & marketing Distribution centres
Fresh produce markets
Ports
Scale: Level 1 Level 2 Level 3 Level 4 Level 5 Disruption of value chain
SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023

B OX 2: I MPACT OF LOADSHEDDING ON THE LIVESTOCK INDUSTRY – B ROILER CHICKEN CASE STUDY

Poultry production is the largest agricultural subsector in South Africa and its controlled production
environment requires consistent electricity supply. The sector is also the single biggest consumer of animal
feed and is therefore highly influential on both the animal feed sector and the production of raw materials
used in the manufacture of feeds.
Given the importance of consistent electricity supply, both on farm to maintain the production
environment and at meat processing level to ensure throughput, most of the larger producers and
processing companies have already invested in backup power. Nevertheless, generator use is more
expensive than Eskom power and loadshedding adds significantly to operational expenditure, both on farm
and at meat processing level. Implementation of stage 6 loadshedding was estimated to add
approximately R0.90 per kg to total production costs. This amounts to a 3% increase in total production
costs, as electricity remains a small share of total costs relative to other factors such as feed and day-old
chicks. It accounts only for the direct cost on poultry and does not include possible additional costs related
to the manufacture of animal feeds and the raw materials to produce feed.
In order to illustrate the impact of these additional costs both on poultry production and the broader
agricultural sector, an illustrative scenario was simulated using BFAP’s partial equilibrium model of the South
African agricultural sector. The model is dynamic and recursive in nature and maintains relationships across
sectors, ensuring that any shock in livestock production also influences field crops through the derived
demand for animal feed.

3 Meat processing includes abattoir services, as well as deboning and other processing activities.

23
 The relative impact of a stage 6 loadshedding scenario on poultry production, consumption and trade
ultimately depends on the extent to which additional costs can be passed through to consumers. In the
poultry sector, where imports still comprise around 20% of domestic consumption, the scope to pass
additional costs on to consumers is limited, as Davids & Meyer (2017) note that the price of imported
products is the most important determinant of domestic chicken prices, with input costs also found to be
significant, but less elastic in its impact. The additional costs associated with the use of backup power
therefore influences both the cost of production and the price of poultry products – with the effect on prices
smaller than that on production costs.

FIGURE 13: I MPACT OF LOADSHEDDING 45 0.75%

R/kg
RELATED COSTS ON CHICKEN PRICES IN
SOUTH A FRICA – B ASELINE VS . STAGE 6 40 0.60%
LOADSHEDDING SCENARIO
SOURCE: COMPILED BY BFAP, 2023 35 0.45%

Figure 13 presents the baseline

30 0.30%
outlook for chicken prices in South
Africa in the absence of further large-
scale loadshedding, with the 25 0.15%
associated cost structure. This baseline
outlook represents a business-as-usual 20 0.00%
scenario, that is used as a benchmark
against which the impact of
% Change - Scenario vs. Baseline Baseline Scenario
loadshedding can be measured and
understood. The alternative scenario in the same figure reflects the additional costs associated with stage
6 loadshedding. Additional costs were introduced into the model for a 3-year period, from 2023 to 2025,
with a reduced impact in 2026 and no further impact from 2027 onwards, based on the assumption that
current investments into independent power production will start to bear fruit. Based on the elasticities
estimated by Davids & Meyer (2017), only 20% of the estimated 3% increase in production costs, are passed
through to consumers, resulting in an average increase in chicken prices of 0.6%, or 20c per kg above
baseline levels from 2023 to 2025. Although seemingly minimal, an impact on production, imports and
consumption are recorded as a result.

4 FIGURE 14: A BSOLUTE CHANGE IN

Thousand tonnes

PRODUCTION , CONSUMPTION AND IMPORT

VOLUMES AS A RESULT OF STAGE 6
2
LOADSHEDDING , EXPRESSED RELATIVE TO THE
BASELINE PROJECTION FROM 2023 – 2030
0 SOURCE: COMPILED BY BFAP, 2023

Figure 14 presents the combined

-2 impact of the price increase, and the
additional cost of production on
production, consumption and imports
-4
from 2023 to 2025, as well as in 2030. Given
that producers have to absorb some of
-6 the additional costs, the production
2023 2024 2025 2030
response to the shock exceeds that of
Production Imports Consumption
consumption. The capital-intensive nature
of production, combined with highly specific nature of production assets, implies that the supply response
takes time, with the peak impact observed in 2025 through a reduction of 5 thousand tonnes per annum in
production volumes. The increase in prices also results in an annual average reduction in consumption of
4.6 thousand tonnes relative to the baseline projection. Given that South African producers are less
competitive relative to international counterparts as a result of the additional costs, imports are expected
to rise by 3.8 thousand tonnes per annum by 2025.

24
 The numbers presented in this case study are indicative and reflect only the impact on the poultry
sector, without accounting for other agricultural sectors. Given the small share of electricity in total
production costs, they may seem small, but the risk to chicken producers is immense and consistent running
on backup power implies massive risk of losses if that backup power should fail. The backup equipment is
neither designed to operate long hours on end nor to endure frequent stop-starts. While production volume
changes may seem small, producers absorb significant additional production costs. At 90c per kg
produced, the total additional cost to the broiler industry will be R1.55 billion per annum, of which only R311
million is recovered in price. This implies a loss of R1.24 billion per annum in GDP that the industry could have
generated had it not been for the impact of loadshedding. For the Western Cape, the cost equates to R286
million per annum, of which of R57 million is recovered in price.
While the poultry industry is the largest subsector in agriculture, it still accounts for only 15% of total
agricultural production value, hence the effect of additional costs across the agricultural sector will be
larger than the simulated impacts in poultry alone.

5.3. Impact on volume and price

Several factors influence the impact of loadshedding on the volume and prices of agriculture
and agro-processing products. The response from agri-businesses to the increased cost associated
with producing the same unit of output, though small (1-3% of total costs), will vary considerably
across the spectrum of size of business, current capacity to generate energy and value chain
specific considerations. Also, the current macro-economic environment in which businesses
operate is one characterised by high food inflation, sluggish economic growth and record-high
unemployment levels. Although the Western Cape fares better in most of these indicators, the
overall narrative stays the same for all agri-businesses in that additional costs both on the farm and
down the value chain will need to be absorbed by someone, either the consumer, or somewhere
within the agricultural value chain. Consequently, these impacts could affect exports, national food
security and food price inflation.
From our extensive feedback from industry stakeholders a number of observations can be made
as we assess the impact of loadshedding in the value chain. Most established processors in the
Western Cape, and producers that export fruit and companies that provide services such as
warehousing and storage, have already invested in or are busy implementing energy solutions.
However, for the moment, many of these solutions are short- to medium-term, such as diesel
generators, and not long-term or green alternatives, such as solar. Those that have done so already
have indicated that they intend to continue with operations until it becomes economically and
managerially impossible to do so. Thus, either through generating own electricity through solar, gas,
generators or storage, firms are spending significantly more on energy. However, not all farms and
firms are in this position. The unfortunate characteristic of the loadshedding impact on agriculture is
that it will disproportionately impact smaller businesses that does not have the capital, nor the
cashflow available to invest in own generation. For these agri businesses there will be an impact on
the volume of output and the prices received in the market as operation are affected.
When investigating investment in renewables, consideration is given to the outline of primary
agricultural energy consumption in 2022 (Table 2 and Table 3) and the LCOS and PPA of alternatives
(Figure 7). Given that LCOS accounts for all costs incurred, including the cost of replacement in the
case of batteries and that PPA assumes a repayment on investment by third party in solar PV, the
annual expenditure calculated on the total demand implicitly discounts the investment and running
cost of such infrastructure, with the latter part a small component of the total cost. In Table 14, we
estimated the cost per annum at current prices to supply the 2 TWh of electricity demanded by
primary production and agro-processing in the Western Cape to amount to R11.1 billion, excluding

25
additional investment in inverters, securing of infrastructure and other necessary monitoring
equipment. For this calculation, a 1600 kWh/kWp/annum from 1 kw of solar PV is assumed, with
additional solar PV installations to store energy in Lithium-ion batteries to supply energy during sub-
optimal solar hours. Different stages of loadshedding would thus theoretically incur a proportional
annual cost compared to completely operating primary production and agro-processing
operations off the grid. However, given the variability in loadshedding stages throughout the year,
a cost per stage of loadshedding is of little value, unless an agreement to fix the stage of
loadshedding can be negotiated and implemented. This cost of alternative energy to be absorbed
is not accounting for any other additional cost incurred by producers and agro-processors, e.g.,
infrastructure and labour cost incurred to manager changeovers and any other relevant costs.

T ABLE 14: A NNUAL COST OF ALTERNATIVE ENERGY SUPPLY PER STAGE OF LOADSHEDDING : 2022 EQUIVALENT
Stage of loadshedding: 1 2 3 4 5 6 7 8 Blackout
Loadshedding indicators
Loadshedding 1 GW 2 GW 3 GW 4 GW 5 GW 6 GW 7 GW 8 GW 16 GW
Loadshedding hours per year 624 1 144 1 664 2 184 2 808 3 224 3 848 4 368 8 760
Total hours per year 8 760 8 760 8 760 8 760 8 760 8 760 8 760 8 760 8 760
% Eskom supply loss 7% 13% 19% 25% 32% 37% 44% 50% 100%
On-farm (1 200 GWh) – Rand billion
Solar PV & Lithium-ion
0.46 0.85 1.24 1.62 2.09 2.39 2.86 3.24 6.50
(LCOS & PPA R bn) 1 kWh = R5.42
Diesel generator
0.45 0.82 1.20 1.57 2.02 2.32 2.77 3.14 6.30
(LCOS R bn) 1 kWh = R5.25
Eskom saving (R bn) 1 kWh = R2.15 -0.18 -0.34 -0.49 -0.64 -0.83 -0.95 -1.13 -1.29 -2.58
Net cost impact* R bn 0.27 0.50 0.73 0.95 1.23 1.41 1.68 1.91 3.82
Agro-processing (844 GWh) – Rand billion
Solar PV & Lithium-ion
0.33 0.60 0.87 1.14 1.47 1.68 2.01 2.28 4.57
(LCOS & PPA R bn) 1 kWh = R5.42
Diesel generator
0.32 0.58 0.84 1.10 1.42 1.63 1.95 2.21 4.43
(LCOS R bn)1 kWh = R5.25
Eskom saving (R bn) 1 kWh = R1.50 -0.09 -0.17 -0.24 -0.32 -0.41 -0.47 -0.56 -0.63 -1.27
Net cost impact* R bn 0.23 0.42 0.61 0.81 1.04 1.19 1.42 1.61 3.24
SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023
NOTE: * CONSIDERS AN EVEN SPLIT BETWEEN THE TWO ALTERNATIVES (SOLAR PV & LITHIUM-ION AND DIESEL GENERATOR) FROM WHICH ESKOM SAVINGS ARE DEDUCTED

If we assume the case studies (Box 2, Box 3, and Box 4) are indicative of the impact on volume
and price by sub-sector, the impact can be summarised as follows. For livestock, 20% of the cost
incurred due to loadshedding is passed on to the consumer, with 80% absorbed in the value chain.
Although production volume is marginally affected in the short run, and increased imports are
triggered, it mostly reverts to baseline conditions in the long run, assuming that the energy situation
normalises due to current investments in private generation capacity. Thus, while adding to food
price inflation, availability should not be affected, as imports can replace the production
contraction.
For field crops, it is assumed that one third of the additional cost incurred due to loadshedding
can be passed onto consumers, with one third pushed to producers and one third absorbed by the
agro-processors. Contraction of area and volume of 2-3% in the short run could be expected, which
also curtails exports, where applicable, somewhat. Similar to livestock, a recovery to baseline levels
over the latter part of the outlook is expected. Prices are well integrated in global markets and while

26
the need to import may increase, food availability should not be affected. Since wheat is already
mostly priced at import parity, price impacts will be limited, but imports will rise to ensure availability.
The horticultural sub-sector could be split into two: produce predominantly cultivated for
exports, e.g., fruit, and produce cultivated primarily for local consumption, e.g., vegetables.
Regarding the former, a negative impact of up to 10% GPV is projected under a “conservative”
scenario modelled for loadshedding stage 6. Negative quality and volume impacts – up to a 12-
15% decrease in exports – in the short run could have long run structural implications for the industry,
as water limitations emanating from increased loadshedding could reduce the area under
cultivation. Although not modelled, the vegetable industry would emulate grains to the extent
where the cost of loadshedding is partially passed on to the consumer as volume reductions will
increase the prices of fresh produce for consumers. A product like wine, which has a large domestic
and international footprint is likely to experience a combination of both the fruit and vegetable
impacts. The most critical component to surviving this crisis is sustained supply from water schemes
and irrigation at farm level.

B OX 3: I MPACT OF LOADSHEDDING ON THE FIELD CROP INDUSTRY – CANOLA CASE STUDY

Over the past decade, canola was South Africa’s fastest growing field crop with total area under
production (all planted in the Western Cape) rising from around 40 000 ha in 2010 to more than 120 000 ha
in 2022. Canola has also proved itself as efficient in a rotation system with other winter crops. Industry yields
made a step change in the past three years despite the rapid area expansion, and South African producers
have benefitted from international seed technology. Production levels have increased sharply, reaching
210 000 tonnes in 2022, which triggered further investment in local crushing and oil refining capacity.
Southern Oil (SOILL) in Swellendam currently remains the main buyer and processor of canola and has
established a range of premium value-added products in the market. Due to the sharp rise in production
over the past two years, South Africa was able to export around 35 000 tonnes to Europe annually.
SOILL has expanded processing capacity to more than 200 000 tonnes. This additional canola
processing capacity will contribute towards additional replacement of presently imported vegetable oil
and the oilcake has ample offtake in dairy and pork production systems in the Western Cape.
When it comes to the impact of loadshedding, the processing industry has already incurred significant
losses, estimated at more than R40 million in 2022. This equates to approximately R280 of additional costs
for each tonne of canola that was processed. Furthermore, downtime due to loadshedding resulted in a
reduction in processing of approximately 5%. Apart from significant waiting periods at silos to offload their
crop, canola producers were not directly affected by loadshedding since the crop is grown under dryland
conditions. (Note: Only a few trails of canola production under irrigation are currently conducted in
Limpopo and the North-West Province).
From the survey it became evident that the strong growth momentum in the industry and overall bullish
investment environment have also spilled over into the industry’s response to loadshedding. Major
investments in diesel generators towards the end of 2022 implies that the crushing and refining facilities can
now run uninterrupted during all stages of loadshedding. However, profit margins decline sharply due to
additional diesel costs as the stages of loadshedding escalate.
To quantify the likely impact of these additional costs on the industry, an illustrative scenario was
simulated using BFAP’s partial equilibrium model of the South African agricultural sector. The model
maintains relationships across sectors, ensuring that any shock in field crops also influence livestock
production. However, it must be noted that contrary to the case study on broilers that is presented in Box
2, the canola industry is small and consequently the knock-on effect on related industries is smaller.
For the purpose of the illustrative scenario, additional costs were introduced into the model for a 3-year
period, from 2023 to 2025, with a reduced impact in 2026 and no further impact from 2027 onwards, based
on the assumption that current investments into independent power production will start to bear fruit. The
estimated additional costs for 2022 (R280 per tonne of canola processed) as provided by the industry, were

27
 introduced in the model. Although SOILL is currently the only main buyer and processor of canola, the
products that are produced, i.e. canola oil and feed cake, are marketed into highly competitive vegetable
oil complex and protein meal for the animal feed industry. In both markets, South Africa is a net importer
with imports providing a natural ceiling of prices. With record soybean crops in recent years, soybean
crushers in the Northern parts of the country can also offer significant discounts on soybean meal to feed
mills in the Western Cape.
Consequently, for the purpose of the scenario, it was assumed that the additional costs of
loadshedding will be split equally with crushers absorbing one third of the costs and pushing one third back
to producers by lowering canola prices and another third to the retail market by increasing the wholesale
prices of vegetable oil. The net impact of approximately R90/tonne (one third of the costs) on canola
producers is relatively small. The simulated reduction in area as a result of the decline amounts to 3 000
hectares, with an associated revenue loss of approximately R20 million.

FIGURE 15: A BSOLUTE CHANGE IN 0

Thousand tonnes
CRUSH VOLUME , CAKE AND OIL -1
PRODUCTION AS A RESULT OF STAGE 6
LOADSHEDDING , EXPRESSED RELATIVE -2
TO THE BASELINE PROJECTION FROM -3
2023 – 2026
SOURCE: COMPILED BY BFAP, 2023 -4

Figure 15 presents the implied -5

drop in canola processing over the -6
next three years. It is important to note
that this presents a drop of -7
approximately 7 000 tonnes per -8
annum from the baseline where no 2023 2024 2025 2026
loadshedding would occur. Canola crush volume Canola cake production
Projections still reflect additional crush Canola oil production
volumes over the next few years from
current levels, despite loadshedding. This is due to an expansion in production and local processing
facilities, but this growth could have been stronger if loadshedding was not prevalent.

3.00 0% FIGURE 16: GROSS VALUE OF

R billion

CANOLA PRODUCTION : BASELINE

VS SCENARIO : 2023-2026
2.25 -1% SOURCE: COMPILED BY BFAP, 2023

1.50 -2% Figure 16 presents a drop in

Gross Production Value for the
industry of 3.5% in the first year
0.75 -3% and then gradually declining as
alternative sources of energy are
introduced or some of ESKOM’s
0.00 -4% power generation is restored and
2020 2021 2022 2023 2024 2025 2026 less backup generation is
% Change: Baseline vs. Scenario Baseline Scenario required.

5.4. Impact on profitability

Loadshedding clearly impacts on operations, throughput volumes and prices. Consequently, the
impact on profitability is undeniable, as has been highlighted in the systems influence diagram
(Figure 11). This section focuses on highlighting the drivers and impact of loadshedding on the

28
profitability of the Western Cape agricultural sector, which in itself is part of what drives reduced
production volumes in the medium term, as producers exit the industry.
The true extent to which on-farm and off-farm profitability is affected by loadshedding is perhaps
impossible to compute, given the complexity of linkages within these value chains. However, an
attempt at illustrating how the impact can vary in magnitude is highlighted in the case study
analyses (Box 2, Box 3, and Box 4). In these analyses, two models from BFAP’s suite were employed,
namely the multi-market Partial Equilibrium (PE) model and the whole farm financial simulation
(FinSim) budgeting model.
The PE model utilised in this analysis has been developed and refined by BFAP over two
decades. The PE model is a dynamic, recursive partial equilibrium framework, based on balance
sheet principles to establish equilibrium, where total supply (production, imports and stocks) must
equal total demand (consumption, export and ending stock). The strengths of the PE framework lie
in the ability to capture intricate market and policy details and elasticities that closely mimic the
real-world situation for specific commodities. This also enables detailed scenario analysis when
changes occur in any of the existing variables or relationships.
Model specification is generally based on proven structures and correlations of key supply and
demand drivers, with prices based on a combination of import or export parity, and domestic supply
and demand dynamics, depending on the market situation for each commodity. The modelling
framework ensures consistency in supply and demand relationships and is able to simulate price
impacts of alternative scenarios, as well as dynamic supply and demand responses over time.
The current situation or Baseline projection assumes that current international as well as domestic
agricultural policies will be maintained throughout the period under review (in this case 2023-2032).
In a global setting, this implies that all countries adhere to bilateral and multilateral trade obligations,
including WTO commitments. On the domestic front, current policies are assumed to be maintained.
To some extent, the baseline simulations are driven by the outlook for a number of key
macroeconomic indicators. Projections for these indicators are mostly, but not exclusively based on
information provided by the OECD, the IMF and the BER.
The FinSim model considers the elements applicable in a whole farm budget to project a set of
profitability indicators per hectare under a certain set of assumptions on variables. These variables
are defined in the PE model. The base year data consist of, amongst other variables, farm size,
orchard age distribution, cultivar selection and performance, establishment and production cost,
and the cost and yield curves associated with non-bearing, bearing and full bearing orchards. The
tool can be used to model alternative scenarios, such as changes in the macro-environment,
additional cost or changes in the yields or marketing channels. The effect of these changes can
then be compared to the baseline to inform decision-making.
The three case studies – one in each of the agricultural sub-sectors – shows vastly different
impacts on profitability. In the case of poultry, the additional cost of broiler production was partly
passed onto the consumer, with a feedback loop pushing back into the value chain, resulting in a
slight decrease in production. In the case of canola, it was assumed that the additional cost at the
processing node was equally spread between producers, processors and consumers. The
consequence of the analysis was a slight contraction of hectares at farm level, with the processing
node and consumers also expected to carry some of the burden. In the horticultural case study,
where the impact of loadshedding was simulated on apples, the impact at industry and farm level
are quite severe. The two main reasons for the result are that the producer remains the owner of the
produce until the consumer buys it, and that apples are mostly produced for export, thus competing
internationally with an extremely limited window of opportunity to pass cost onto the consumer.

29
 The main considerations with respect to the impact on profitability can be summarised as follows:
• The first key indicator is the extent to which the value chain relies on electricity (and in
particular on Eskom) to run operations.
• The second key indicator is the ability of a particular operator in the value chain to push
the additional cost incurred onto other operators upstream or downstream, including
consumers. It is assumed that the business will absorb the cost if unable to shift it.
• The third key indicator is the length of production cycles (monthly, annually, multiyear,
etc.), which also drives the extent of short-term and longer-term impacts.
• The fourth key indicator is the availability of and ability to practically implement
alternative sources of electricity. Many challenges, including access to capital,
availability of equipment, affordability of equipment under current conditions and layout
of operations play a role.
The main conclusions with respect to the impact on profitability can be summarised as follows:
• Profitability is negatively affected by an increase in cost in the chain, which has to be
absorbed at the node where it occurs or absorbed upstream or downstream in the chain.
• Profitability is negatively affected by reduced demand for product (whether inputs or
produce), resulting in facilities running below capacity, increasing the burden of
overheads per unit of production.
• Negative impacts on profitability could either be short term or have long term structural
impacts. From our analysis, it appears that the impact on profitability is substantially worse
over the long run on perennial crops.

B OX 4: I MPACT OF LOADSHEDDING ON THE HORTICULTURE INDUSTRY – A PPLE CASE STUDY

The South African apple area has incrementally expanded over the last decade, from 22 166 hectares
in 2012 to 24 956 hectares in 2021. Over the same period, production volume increased by 43% (350 000
tonnes), indicating that the productivity per hectare increased substantially. The industry makes a valuable
contribution to agriculture in the Western Cape, with approximately 85% of those hectares established in
the province, followed by the Eastern Cape (12%), with the complement established in the Free State,
Mpumalanga, and Limpopo (Hortgro, 2022).
When it comes to the impact of loadshedding, dependency on Eskom runs deep in the apple value
chain. Consequently, the industry is affected at different nodes throughout the value chain, from inputs
(e.g., water schemes and packaging material), to primary production (e.g., irrigation), to agro-processing
(e.g., packing, canning, juicing and cold storage) to distribution and marketing (e.g., transport, ports and
fresh produce markets). Since the industry is orientated towards fresh exports, competing on the
international market with both Southern and Northern Hemisphere producers, since the technological
advancements on the storage of apples in controlled atmosphere (CA) cold rooms allows for all year-round
supply to market.
Despite only exporting 46% of production, exports contribute 78% of GPV. Consequently, the industry is
exposed to both domestic and international challenges, and the impact on profitability has already filtered
through to decision-making with respect to planted hectares – a small decline in planted hectares can
already be observed. Since 2020, when producers came out of the drought affecting water availability
and production in the Western Cape, they were exposed to market closures due to Covid-19, a global
logistic crisis with port delays and freight rate hikes, the consequences of Russia’s invasion of Ukraine, sharp
increases in labour cost and more recently, substantial hours of loadshedding per day.
To quantify the impact stage 6 loadshedding, consideration is given to the cost of running on
alternative energy, mostly diesel generators, to operate packaging material plants, irrigation pumps at farm
level, packing lines at packhouses and cold storage facilities. It is expected that the additional cost in the
value chain will largely have to be absorbed by the producer, since the producer remains the owner of the
product until it is sold. The calculated impact equates to R19 547 per hectare (+3.13%) on total production

30
cost, which includes off-farm activities. The calculation considers the additional cost for 2022, for which the
apple production budget is an inflation adjusted 2021-budget (Hortgro, 2022).
To illustrate the likely impact of these additional costs on the industry, a scenario was simulated using
BFAP’s partial equilibrium model of the South African agricultural sector. The setup of the scenario is
potentially conservative, as it does not account for the additional cost that could be passed to the
producer from the juicing and canning industries.
For the scenario, similar to the broiler and canola examples case studies, additional costs were
introduced into the model for a 3-year period, from 2023 to 2025, with a reduced impact in 2026 and no
further impact from 2027 onwards, based on the assumption that current investments into independent
power production will start to bear fruit. The simulated impact on the apple industry can be summarised as
follows:
• Increase in the cost of production (alternative energy sources to irrigate) and upstream and
downstream activities (3.13% increase in total production cost).
• Reduction in yield, especially when irrigation cycles can’t be completed in critical periods (6%
reduction in yield for 2023-2025, with 3% in 2026).
• Reduction in export volumes – quality and CA storage window impact (10% reduction in exports for
2023-2025, with 5% in 2026).
• Reduction in total area – accelerated removal of older, marginal orchards, due to limited water
availability as a result of loadshedding.
Figure 17 presents the potential decrease in apple industry’s GPV as a result of the introduction of the
scenario outlined above. The impact on GPV is projected to be around 10% per annum for the period 2023-
2025 and over 6% in 2026, after which is tapers off to 1.3-2.6% for the rest of the simulated period. The short-
term impact reflects impact on direct and opportunity cost, whereas the longer-term impact reflects the
structural impact on area, which consequently reduces volume. From 2023-2032, the total impact in
absolute terms on GPV is projected to equate to R5.11 billion.
FIGURE 17: IMPACT OF DESCRIBED
18 0% SCENARIO ON GPV FROM 2020 – 2032
R billion

SOURCE: COMPILED BY BFAP, 2023

15 -2%
Given the challenges described, the
12 -4% baseline already reflects a contraction in
production area, resulting in a projection
9 -6%
of 23 000 hectares in 2030. For the
6 -8%
simulated scenario, an additional area
contraction of 500 hectares is projected.
3 -10% With 30% of the industry’s orchards older
than 25 years and potentially marginal,
0 -12% especially when put under stress with
additional cost to be covered, the
contraction in area is conservative and
% change - Scenario vs. Baseline
Baseline likely could be higher (Hortgro, 2022).
Scenarios
Figure 18 presents the impact of the
scenario compared to the baseline on the profitability of the apple component on the Witzenberg
prototype farm. A normal replacement cycle is assumed, meaning that there is full bearing, bearing and
non-bearing orchards on the farm. Against an already challenging baseline situation, the scenario adds
additional cash flow and profitability constraints of R27 500 to R30 000 per hectare from 2023-2025, reduced
to R14 400 per hectare by 2026. It is projected that these constraints are likely to result in a reduction of
planted area as producers cannot sustain normal replacement under these conditions and will also remove
older, less productive orchards at an accelerated tempo.

31
 FIGURE 18: IMPACT OF DESCRIBED
SCENARIO ON W ITZENBERG PROTOTYPE 80 000

EBITA R/ha
FARM FROM 2022 – 2032
60 000
SOURCE: COMPILED BY BFAP, 2023

40 000
The marginal improvement of the farm
level profitability from 2027 onwards is 20 000
the consequence of slightly better
market prices due to lower -
marketable volumes, a result of area
(20 000)
reduction. Thus, while the impact is
assumed to be wholly absorbed by (40 000)
the producer in the short to medium
term, consumers experience the
delayed impact through price Absolute change - Scenario vs. Baseline
increases because of the impact on Baseline
producers. Scenario

5.5. Socio-economic impact

There are several ways in which the escalation in loadshedding over the past few months are
expected to impact Western Cape households and workers employed in the various industries in
the agricultural value chain. Furthermore, a significant impact on livelihoods is anticipated on
emerging producers and Small and Medium Sized Enterprises (SSMEs) particularly in the agro-
processing sector. Though it falls out of the scope of this report to conduct a full socio-economic
study of loadshedding, we’ll briefly synthesise and discuss some of the major implications as it relates
to agriculture. Important to note, is that the impact of loadshedding compounds the overarching
and current macroeconomic conditions affecting especially poor households in terms of food
affordability and access. The bullets below contextualise the current socio-economic landscape in
the Western Cape.
• The country is currently in a monetary tightening phase in which the South Africa Reserve
Bank (SARB) has been lifting interest rates in an attempt to lower overall inflation which is
currently still trending at 7.1% for March 2022, compared to the same month in 2021 (StatsSA,
2023). This is still outside of the Bank’s target range of 3-6% and significantly higher than the
mid-point target of 4.5%. Over the medium term, the aim of lowering prices is important, but
in the short term the impact of higher interest rates is affecting households, of whom a large
share of lower income groups is already heavily in debt. The aggregate impact on
households spending, food security and livelihoods coping strategies are significant, whilst
having to cope with extreme power cuts.
• Though the Western Cape performs better than most other provinces in terms of
unemployment, economic growth and a few other metrics, Western Cape households will
not escape the impact of a stagnant South African economy hampered not only by
loadshedding, but several other structural challenges limiting progress. The latest GDP
forecast released by the IMF (2023) for South Africa is the lowest projection to date; a mere
0.1% growth for 2023. This is what several CEOs of retailers and processing firms have
described as an extremely difficult trading environment, of which the agricultural value chain
is dependent on to sell produce.
• The current Western Cape unemployment rate is 23% (33% in South Africa). At such high level,
combined with those that earn income from wages, it will continue to weigh in consumer
spending in a high inflation environment exacerbated by loadshedding (StatsSA, 2023).

32
 • As has been observed in the apple case study (Box 4), the risk of losing production area due
to unprofitable operations as a result of loadshedding is a real and tangible threat.
Approximately 136 000 agri workers are employed on farms in the horticultural sub-sector in
the province, with many more in horticulture related agro-processing facilities. Large scale
uprooting of planted hectares, volume and/or quality changes are putting these jobs at risk.
As indicated in Section 5.1, the knock-on effect reaches far wider than only the producer,
the agri worker and the livelihoods of those linked to the agri worker.
• This leads us to the importance of having stable energy supply to enable food security, both
in terms of access, affordability and food utilisation. Figure 19 shows the annualised food
inflation rate in the Western Cape, indicating the relative share of each food group to the
overall picture. Prior to the pandemic, food inflation was trending at a modest 2%, after which
food prices increased but stabilised at around 6% prior to the Russian invasion of Ukraine in
March 2022. Since then, food prices have increased to around 13%, driven largely by
increases in bread and cereals and meat inflation. These have such a large bearing on food
inflation not only because prices for these products have risen in the past year, but also
because these food items make out a relatively larger share of the weights used to calculate
inflation, which in turn is based on balancing consumption levels in South Africa.
14%
Food inflation %

12%

10%

8%

6%

4%

2%

0%
2019 2020 2021 2022 2023
-2%
Bread and cereals Meat Milk, eggs and cheese
Oils and fats Fruit & veg Sugar, sweets and deserts
Other food WC Food Inflation
FIGURE 19: W ESTERN CAPE FOOD INFLATION AND CONTRIBUTION PER FOOD GROUP
SOURCE: STATSSA, 2023

The impact of higher food prices at retail level results in a dual challenge of affording food,
which, as we’ve pointed out is already a challenge in an economy where the level of
unemployment is so high and income growth stifled by low economic growth prospects. One of the
biggest challenges presented by the current energy supply constraints is that for most parts, current
levels of food inflation has been caused by global factors. Our uniquely South Africa problem with
loadshedding will work against the economic forces supposed to bring down food and other prices
in that loadshedding adds costs to produce food. As noted earlier, it is not clear to what extent
higher prices in the supply chain can be passed to the consumer, but consumers will ultimately suffer
if loadshedding impacts wage rate growth or lead to job losses.
Our analysis show that there are currently around 186 000 farm workers in the Western Cape,
whilst another 131 000 workers are employed in occupations directly related to agro-processing.
The Western Cape has in recent years been conducting a series of Agri Worker Household Census

33
surveys in an attempt to better understand the household profiles and livelihoods of those working
on farms. The first iteration was completed in 2017 and used as the baseline, whilst a second round
was concluded in 2020 (WC DoA, Agri Worker Household Census: Provincial Report Cycle 2, 2021).
The last completed survey captured close to 25 000 individuals aggregated into 6 460 households,
which allows us to get a better understanding of the access to electricity and other services. Around
95% of all participants reported to have electricity in their homes, of which the bulk (93%) of those
residing on farms stayed in brick houses. Agri workers had either piped tap water in their homes
(83%) or piped tap water on their dwelling site (12%).
One can get a sense of the impact of loadshedding on these households by means of assessing
to what extent workers own assets powered by electricity. Around 80% had refrigerators, 82%
electrical stoves and 51% microwave ovens. This suggest that rural workers on farms are fairly
dependent on electricity for activities such as cooking and keeping food preserved using cooling.
An important finding from the census as it relates the impact of electricity disruption and the cost
increases over time is given in Figure 20. Respondents were asked who provides and pays for
services to households for electricity and water services. The households with access to electricity
stated that 59% received access to electricity through paying producers, which implies that these
households are serviced indirectly by Eskom’s provision of electricity to the farming enterprise but
pays for the electricity to the producers, who then pays Eskom. A further 19% of farm workers
received electricity as an in-kind payment from producers that supply worker houses with electricity
at no charge. Another 19% receives electricity by buying directly from the municipality, whilst
around 3% received free electricity from municipalities.

FIGURE 20: W ESTERN CAPE AGRI WORKER HOUSEHOLD PROVISION OF SERVICES

SOURCE: WC DOA, 2017

The provision of water to households was mainly done by producers, of which 73% were
distributed for free, whilst another 7% needed to pay producers for this service. Though slightly more
indirect, the provision of water to farm worker households are impacted by loadshedding in cases
where water needs to be delivered to households using electric pumps.

5.6. Impact on government objectives

The wide-ranging impacts of loadshedding, not only value chain partners, but also stakeholders
such as government and civil society operating within the agricultural economy in the Western
Cape, will be severe. This is particularly true for the provincial government, which needs plan and
mitigate (reallocation of resources) to deal with the energy shortages to ensure the continued
delivery of services. If loadshedding persist well into 2024 at current high levels, some of the

34
overarching government objectives might not be met due to the combined impact of
loadshedding on the economy. Though such causal inferences are difficult to predict, we briefly
touch on the impact of loadshedding on the WCG’s objectives and that of the WC DoA.
In aiming to realise their vision of a safe Western Cape where everyone prospers will be made
much more difficult under current levels of loadshedding. The same applies to the Vision-inspired
Priorities (VIP) of growth and jobs, empowering people, mobility and spatial transformation and
innovation and culture, as well as some of the cross-cutting themes as mentioned in the WCG’s
Strategic Plan 2019-2024 (WCG, 2019). The main problem areas identified back when the Strategic
Plan was drafted are now significantly worse than back in 2019, largely attributed by the onset of
global instability caused by the Covid-19 pandemic and the subsequent impact of the Russian
invasion of Ukraine. The significant and additional threat posed by loadshedding will severely
hamper service delivery by government. The WC DoA mainly supports the provincial government
mandate through the VIP 2 (economy and jobs) through which agriculture and agro-processing
aims to grow exports, ensure rural safety and providing support to producers to name a few. As
identified in the Theory of Change adopted by the WC DoA to guide the strategic direction of
service delivery, the impact of loadshedding will impact several of the outcome indicators the
Department are aiming to achieve. Areas in which loadshedding will impact the ability of the
agricultural sector to optimally perform at the primary level includes the ability to irrigate crops and
the available capital gearing to invest in alternative energy sources. Once loadshedding interrupts
producers in terms of their ability to produce at the same scale and quality of produce the
downstream sectors are affected. All additional costs, both on the farm and in the agro-processing
firm, if not accompanied by higher prices in the market will lead to lower Gross Value Added, which
is something the WC DoA aims to grow. Table 15 represents a short description of the anticipated
impact of loadshedding on the WC DoAs main outcome indicators.

T ABLE 15: WC DOA IMPACT OF LOADSHEDDING ON KEY OUTCOME INDICATORS

Outcome Indicators Potential impact of persistent loadshedding
As one moves to different stage of loadshedding, the cost at
each node of the value chain will scale proportionately to the
number of hours of downtime. The impact on production, as
Increase agricultural we've explained in this report depends largely on the ability of
Increased exports by at least producers and firms to generate their own power, or the nature
agricultural 5% over the next 5 of the economic activity will determine to what extent
production in a year; Enhance agri- production can proceed, albeit at higher costs. Given other
sustainable processing capacity economic realities and factors currently affecting the Western
manner at both primary and Cape export performance it is likely that export volumes be
secondary level affected by loadshedding as irrigation and cold chain logistics
are disrupted. A larger share of fruit is expected to be diverted to
local markets and processing capacity is likely to be subdued as
costs per unit scales with each level of loadshedding.
Increase GVA will be constrained as the WC DoA move towards
concluding the strategic plan implementation in 2024.
Loadshedding will impact sustainable production in two ways-
Increase GVA higher costs to produce the same level of output and the farm-
Improved food cost squeeze will dampen farm-gate price support in the market.
through sustainable
security and There is already anecdotal evidence of increased crime in South
agricultural
safety
production Africa related to loadshedding since security services and
technologies are often reliant on electricity to function (camera's,
electrical fences, lighting, alarms etc), whilst the higher risk of total
grid collapse poses a significant risk of looting and social unrest.

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 Continued success on land reform will be severely negatively
affected by loadshedding, largely due to the reality that
absorbing additional costs of production for smaller producers will
Transformed & be constrained, or having no access to additional generation will
Success of likely reduce the volume and quality of produce. Similar to
inclusive
supported land commercial producers, the biggest risk of loadshedding will be
agricultural
reform projects felt on the more than 800 emerging poultry producers and
sectors
another 2 100 emerging irrigation producers in the Western Cape.
Continued success for projects will depend on access to energy
finance by existing and upcoming land reform beneficiaries.
Potential opportunity presented to introduce renewable energy
and other technologies to mitigate the impact of loadshedding,
Develop an which should present new employment opportunities. Also
Innovative and enabling presents an opportunity to reduce the energy dependence on
resilient rural environment to government and potential provide income streams to farming
economies increase agricultural and agro-processors. However, we anticipate that jobs growth
and related jobs throughout the agriculture value chain will be constrained and
likely even see jobs lost due to the accumulation of impacts at
the weakest points in the chain.
SOURCE: COMPILED BY BFAP FROM WC DOA, 2017

6. POTENTIAL INTERVENTIONS
Before delving into the potential implementable interventions to mitigate the impact of
loadshedding on the Western Cape agricultural sector, it is worthwhile to consider the global
environment in which many of these value chain role-players operate. Europe is one of South
Africa’s key trading partners and the pressure to comply with carbon standards and net zero targets
in future, is mounting. Thus, despite the extent to which the current levels of loadshedding are
challenging the agricultural sector in the Western Cape, it does provide some opportunities to gain
momentum towards carbon commitments. According to PwC (2022), “private business is one of the
fastest and most effective agents of change in the world”. When allowed by the regulatory
environment and forced to adapt to remain operational under loadshedding, businesses can rise
to the challenge of decarbonising operations and/or the supply chain. New opportunities and
challenges in the energy sector can broadly be categorised as follows:
• Participation in peer-to-peer electricity trading, enabled by an electricity trading
platform, which allows for the commercialisation of opportunities for private businesses to
generate and/or trade electricity.
• Improvements in the ease of access to clean energy while transitioning away from energy
generated by fossil-fuels.
• Despite the regulatory environment opening up to invite more private participation, more
stringent regulations on the environmental side can be anticipated that will provide rules
and standards regarding the circularity of materials used in energy generation.
• The environmental impact component of ethical business is expected to be expanded
to include renewable energy projects are part of corporate social responsibility
requirements (PwC, 2022).
With this in mind, a set of potential interventions categorised according to the level of
implementation is drafted in Table 16. Differentiation by category is incorporated by grouping
various forms of businesses, industry, and government (e.g., local, provincial, national). To identify
the mandates and competencies for interventions at different nodes in the value chains of the
Western Cape agricultural sector, a non-exhaustive output matrix by category is provided. Where

36
applicable, differentiation by industry (horticulture, field crops and livestock) and sub-industry will
be provided. These potential interventions are supplementary to the initiatives already publicly
available (GreenCape, 2022a; GreenCape, 2022b; GreenCape, 2023a; GreenCape, 2023b;
GreenCape, 2023c) and initiatives coordinated and implemented by the Western Cape
government. Learnings from other industries should also be considered. Implementable
interventions for the season on hand, the rest of 2023 and over a 10-year period are considered.
Given WC DoA preferred method of identifying a limited number of purposively selected outcomes
to drive strategically, quality rather than quantity was the focal point in the construction of this matrix
output.

T ABLE 16: P OTENTIAL INTERVENTIONS TO MITIGATE THE IMPACT OF LOADSHEDDING

Agri-processing /
Period Input suppliers Primary production Distribution & marketing
value adding
Businesses (input suppliers, producers, processors, value-adders, etc.)
Just in case vs.
Store additional Schedule / operational Schedule / operational
This Just in time (carry
water when possible management adjustments management adjustments
season more stock)
• Business Continuity Plans (BCPs) to plan and prioritise actions to minimise operational impact
• Investigate opportunities to improve energy efficiency to reduce total energy expenditure
Rest of • Hire or invest in generators
2023 • Investigate alternatives that aligns with future green energy requirements posed by market
• Investigate options to operate under curtailment (e.g., different irrigation schedules)
2024 -
• Invest in alternatives, unless Western Cape can ensure more sustainable energy supply
2032
Industry (industry bodies, producer and processor organisations, associations, etc.)
This Investigate
season Prioritise curtailment options Investigate curtailment or
Prioritise discussions with
discussions with and potential for other forms of flexible
cold stores and ports
irrigation boards flexi loadshedding loadshedding schedules
Rest of schedules
2023 • Lobby for greater consistency and certainty regarding the stage of loadshedding
• Approach financial institutions to provide innovative and affordable options to invest in energy
supply
• Lobby for the agricultural value chain to be declared an essential service
• Lobby for agriculture to be partially exempted from higher stages of load-shedding to reduce
the likelihood of value chain breakages
• Lobby for higher and broader application of rebates on fuel used for electricity generation
• Conduct a feasibility study regarding the potential to trade load-shedding schedules
• Enable funding of alternatives
2024
• Comprehensively map industries to identify potential for collaboration and reduce impact of
-
direct and indirect impacts
2032
• Lobby for the finalisation of payback tariffs for electricity being put back into the grid
Government (local (L), provincial (P) and national (N))
This
Curtailment or alternatives by line taking the temporal distribution into consideration (P)
season
• Prioritise understanding, analysing and mitigation of electricity supply interruptions on water
supply infrastructure (L, P, N)
• Analyse and attempt to negotiate temporal distribution within the province to prioritise spatial
Rest of differentiation in peak requirement periods within and outside of the agricultural sector (P)
2023 • Determine the extent of large scale, commercial investment in alternative energy in the
province and the status of supply into the grid (P)
• Research alternative systems, technologies, cost ranges, and risks to enable investment
decisions (L, P, N)

37
 • Real, tangible incentives to encourage businesses and individuals to invest in renewable
energy and increase electricity generation to help reduce pressure on the grid and ease
loadshedding (e.g., Western Cape Enterprise Resource Planning enabler roll-out) (P, N)
• Enable the subsidising and funding of alternatives (P, N)
• Reduction in regulator procedures, i.e., streamline application process (N)
2024 • Enable large scale private alternative energy suppliers to feed into the grid (P, N)
- • Ensure sustainable sourcing for the Western Cape, ideally low carbon energy, with the
2032 potential of getting CoCT off the grid (P)
• Development of new power projects (L, P, N)
• Restore energy security through attracting private sector participation in the electricity market
and addressing Eskom’s operational and financial deficiencies (N)
• Implement the Just Energy Transition Investment Plan (JET-IP) to achieve the country’s
ambitious climate goals while simultaneously addressing the energy supply crisis (L, P, N)
SOURCE: COMPILED BY BFAP FROM VARIOUS SOURCES, 2023, INCLUDING AGRISA, 2023, ENERGY CAPITAL POWER, 2023A, 2023B, 2023C, IMF, 2023, PWC, 2022

From the interventions outlined above, the short-term mitigation strategies are mostly structured
around remaining operational while investigating, planning and rolling out longer term, green
energy solutions. GreenCape (2023a) estimates that South Africa’s agricultural sector market
opportunity for energy efficiency investment is R66.8 billion with an identified potential energy saving
of 19.4 TWh/annum. Energy efficiency refers to the “implementation of behaviour changes or
technology to reduce energy consumption, while producing the same or greater outputs”. While
the Western Cape share of national agricultural electricity expenditure in 2017 equated to 22.4%,
off-farm agricultural processes can vastly differ for the Western Cape relative to the national total.
Rather than assuming that the Western Cape’s energy efficiency investment can be directly
derived, one can consider an average cost of R3.44/kWh.
In addition, the direct annual cost to be incurred by primary producers and agro-processors, on
average, equate to R5.42/kWh for solar PV and Lithium-ion batteries and R5.25/kWh for diesel
generators. Given that these alternatives are replacing energy sourced from Eskom, some savings
on Eskom electricity should be realised. Unfortunately, the magnitude of investment in these
alternatives does require a more consistent level of loadshedding, e.g., consistently on a specific
stage, to effectively plan for the energy supply to be replaced and secure the capital to invest in
alternative energy supply. It is also worth noting that the impact on the grid (energy availability) and
implementation of different solutions are vastly different. Table 17 summarises some interventions by
impact on supply and the relative ease or complexity of implementation. This serves to guide
decision-makers into prioritising some of the interventions outlined in Table 16.

T ABLE 17: M ATRIX OUTPUT ON SUPPLY IMPACT AND IMPLEMENTATION OF ENERGY SOLUTIONS
High Own generation Procuring from Independent
Impact on energy supply

(large scale) Power Producers (IPPs),

including large scale
wheeling
Medium Minimise leakage and non- Wheeling (the process of
technical losses delivering energy from a
generator to an end-user
located in another area)
Low Own generation Supporting microgrids and
(small scale) Small-Scale Embedded
Generation (SSEG)
Low Medium High
Ease of implementation (Low = complex; High = easy)
SOURCE: ADAPTED FROM PWC, 2022

38
7. CONCLUSION
The primary objective of this study was to analyse the on- and off-farm impact of the
loadshedding situation on the Western Cape agricultural sector. In addition, given the findings in
terms of the energy dependency and the impact of loadshedding of producers, value chains,
consumers and agri workers, a set of recommendations on potential interventions that can be
implemented was required. In this regard, a special focus on green energy generation options were
of particular interest.
To determine the dependency on Eskom and provide an overview of the temporal and spatial
distribution of the agricultural sector’s electricity demand, existing literature with respect to
electricity use in the Western Cape and in particular the agricultural sector (primary production and
agro-processing) was consulted. While the City of Cape Town metro is responsible for approximately
70% of the 16 TWh electricity use in the province, use by primary production and agro-processing
was estimated at approximately 2 TWh per annum.
An analysis of the spatial and temporal distribution revealed that most intensive livestock
operations, i.e., dairies, chicken batteries, piggeries and feedlots, in the Western Cape are situated
in the Swartland, Hessequa, Drakenstein, City of Cape Town, Swellendam and George
municipalities. Considering the irrigated area and water demand of various field and horticultural
crops, the municipalities identified to have the biggest electricity demand for irrigation purposes,
are the Witzenberg, Langeberg, Breede Valley, Oudtshoorn, Theewaterskloof and Cederberg
municipalities. Demand for electricity is much higher from October to March than from April to
September. From the surveys conducted by industry associations and verified by stakeholder
interviews, it was estimated that approximately 95% of producers are dependent on Eskom as their
primary, or only, source of electricity, not accounting for the temporary solutions implemented
during loadshedding. Furthermore, approximately 75% of agro-processing facilities source electricity
from Eskom directly, with the complement being supplied via their local municipality.
After determining the baseline spatial and temporal distribution and energy dependency, an
analysis of the impact of loadshedding on the agricultural sector of the Western Cape was
conducted. IQA, a systematic, qualitative research technique was applied to determine causal
relationships that exist. These cause-and-effect relationships showcase the chain of events that
loadshedding causes in agricultural value chains in the Western Cape, where loadshedding initiates
a chain of events, where operational capacity and scheduling, together with input supply are the
biggest drivers of impact in the system. On the receiving end – the factors most affected in the
chain – are product prices and the socio-economic conditions. Multiple feedback loops within the
system, indicating a strengthened and accelerated impact through the various elements in the
system, highlights the complexity and interconnectedness in the agricultural value chains, but it also
exposes the risk continued loadshedding poses to the sector.
To illustrate the short- and longer-term impacts of loadshedding on operations, volume, price
and profitability, four in-depth case studies were conducted. These were done on water
management schemes, and the canola, poultry and apple value chains. Findings from these case
studies, drawing on BFAP’s PE and FinSim modelling, highlighted the relative risk distribution – the
impact on horticultural value chains and role-players are far more severe than on livestock and field
crops, with some of that risk directly related to irrigation water supply. It should be noted that the
risks posed by electricity downtime in the intensive livestock production industry is severe, but,
because of those risks, this industry is, on average, well-equipped to deal with intermittent bouts of
loadshedding. The increase in the cost of production due to running on alternative energy sources,

39
can be pushed at least partly onto the consumer, however, a slight reduction in demand of chicken
could be expected as a result.
In addition to the case studies, an aggregated analysis was conducted to quantify the cost
implication of different stages of loadshedding on primary agriculture and agro-processing. To
replace each rationing of 1 000 MW at primary production and agro-processing, would equate to
an annual (LCOS and/or PPA) cost of R0.79 billion in replacing with Solar PV and Lithium-ion batteries
or R0.76 on diesel generators, not accounting for the savings due to reduced demand from Eskom.
The operational cost equivalent for running uninterrupted for a full year at stage 6 loadshedding will
therefore demand spending of R3.95 to R4.08 billion per annum when switching to diesel generators
or solar PV and Lithium-ion. If we assume that the principles and outcomes of the case studies are
indicative of the manner in which these costs are absorbed in the value chains – upstream,
downstream, at node of incurrence or by consumers – the horticultural sector is the one most
vulnerable to sustained loadshedding. On the other hand, the intensive livestock sector is most at
risk should back-up energy supplies fail.
The impact of loadshedding on operations, volume, price and profitability inevitably affects the
socio-economic aspects of agricultural value chains and the provincial government objectives. This
report reiterates that job opportunities in the horticultural sector, which is the biggest employer of
on-farm and off-farm agri workers in the Western Cape, are most vulnerable, putting those jobs at
risk. The WC DoA aims to create an enabling environment for producers and processors to grow
Value Added and grow jobs. It is clear that the ongoing energy supply shortage are set to influence
some of the major outcome indicators that the Department has set out to achieve moving towards
2024. In this regard, growing exports, value added and ensuring continued success on land reform
projects will be difficult to maintain. A high-level overview of the policy environment applicable to
the study highlighted the slowly changing regulatory environment that still constraints the
implementation of alternatives, especially with respect to the implementation of green energy
options.
The potential implementable interventions were broken down into three categories – business,
industry and government. Strategic actions, taking both a short-term and longer-term view on
actionable items. While the responsibility of generating electricity can be forced upon businesses,
with such a responsibility, businesses still depend on government to create an enabling environment.
This environment encompasses various aspects of enablement, including regulatory, incentivisation
to invest in renewable energy, access to low cost and innovative funding models to finance capital
expenditure. At the same time, if any level of government strategically plans and implement
alternative energy solutions to reduce/remove the impact of loadshedding, these implementations
could ease the responsibility on businesses to invest in their own electricity generation. In that case,
and in the current constrained economic environment with low to no profit margins and high interest
rates, putting additional constraints on the cash flows and balance sheet ratios of individual
agribusinesses could be avoided. Lastly industry organisations, associations and bodies can ensure
the effective communication of the strategic actions taken at various levels of government with
agribusinesses, while providing mandates inputs into government plans that are valuable, industry
specific, and aggregated or disaggregated to the level most suited.
In conclusion, every attempt has been made to reflect the true state of energy dependency,
the impact of loadshedding and the potential implementable interventions to mitigate the impact
on the Western Cape agricultural sector within the timeframes provides. However, ample scope
exists to refine, enrich and expand the research in collaboration with businesses, industry and
government.

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