research-article

Forecasting household electricity demand with complex event processing: insights from a prototypical solution

Authors:

Christoph Doblander,

Christoph Goebel,

Hans-Arno JacobsenAuthors Info & Claims

Middleware Industry '13: Proceedings of the Industrial Track of the 13th ACM/IFIP/USENIX International Middleware Conference

Article No.: 2, Pages 1 - 6

https://doi.org/10.1145/2541596.2541598

Published: 09 December 2013 Publication History

Abstract

The increasing use of renewable energy is leading to a paradigm shift in operating electrical grids. Production is moving away from centralized power plants to decentralized sources like solar panels and windmills. One consequence of this development is the need for managing supply and demand in local distribution grids in a "smart" way, which also implies the capability to forecast the demand for electric power closer to the end consumer and on shorter time scales than today. In this paper, we describe a system prototype for electricity demand forecasting based on highly disaggregated data from sensors deployed in homes and evaluate its performance both with respect to forecasting accuracy and ICT resource requirements. The data we use for our evaluation was collected in a pilot trial. Our system prototype combines complex event processing with state-of-the-art forecasting capabilities. For short-term forecasts, we observed average error reductions of up to 98 percentage points compared to average demand profiles. Our experiments also show the applicability of our approach at large scale. We were able to run the forecasting service for 1,000 households in parallel on one off-the-shelf server.

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Cited By

Kumar SAgarwal SChandra RKumar A(2023)Predictive Stream Analytics for Threshold based Approach:A Case Study of Temperature Anomaly2023 IEEE 7th Conference on Information and Communication Technology (CICT)10.1109/CICT59886.2023.10455674(1-6)Online publication date: 15-Dec-2023
https://doi.org/10.1109/CICT59886.2023.10455674
Kriechbaumer TJacobsen H(2018)BLOND, a building-level office environment dataset of typical electrical appliancesScientific Data10.1038/sdata.2018.485:1Online publication date: 27-Mar-2018
https://doi.org/10.1038/sdata.2018.48
Carvalho ORoloff ENavaux PAnjum ASill AFox GChen Y(2017)A Distributed Stream Processing based Architecture for IoT Smart Grids MonitoringCompanion Proceedings of the10th International Conference on Utility and Cloud Computing10.1145/3147234.3148105(9-14)Online publication date: 5-Dec-2017
https://dl.acm.org/doi/10.1145/3147234.3148105
Show More Cited By

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Forecasting household electricity demand with complex event processing: insights from a prototypical solution

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cover image ACM Conferences

Middleware Industry '13: Proceedings of the Industrial Track of the 13th ACM/IFIP/USENIX International Middleware Conference

December 2013

41 pages

ISBN:9781450325509

DOI:10.1145/2541596

Program Chairs:
Angelo Corsaro
PrismTech, France
,
Tiancheng Liu
IBM Research, China

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 December 2013

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Middleware '13: 14th International Middleware Conference

December 9 - 13, 2013

Beijing, China

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Overall Acceptance Rate 5 of 23 submissions, 22%

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Cited By

Kumar SAgarwal SChandra RKumar A(2023)Predictive Stream Analytics for Threshold based Approach:A Case Study of Temperature Anomaly2023 IEEE 7th Conference on Information and Communication Technology (CICT)10.1109/CICT59886.2023.10455674(1-6)Online publication date: 15-Dec-2023
https://doi.org/10.1109/CICT59886.2023.10455674
Kriechbaumer TJacobsen H(2018)BLOND, a building-level office environment dataset of typical electrical appliancesScientific Data10.1038/sdata.2018.485:1Online publication date: 27-Mar-2018
https://doi.org/10.1038/sdata.2018.48
Carvalho ORoloff ENavaux PAnjum ASill AFox GChen Y(2017)A Distributed Stream Processing based Architecture for IoT Smart Grids MonitoringCompanion Proceedings of the10th International Conference on Utility and Cloud Computing10.1145/3147234.3148105(9-14)Online publication date: 5-Dec-2017
https://dl.acm.org/doi/10.1145/3147234.3148105
Kriechbaumer TUl Haq AKahl MJacobsen H(2017)MEDALProceedings of the Eighth International Conference on Future Energy Systems10.1145/3077839.3077844(216-221)Online publication date: 16-May-2017
https://dl.acm.org/doi/10.1145/3077839.3077844
Leonardi AZiekow HStrohbach MKikiras P(2016)Dealing with Data Quality in Smart Home Environments—Lessons Learned from a Smart Grid PilotJournal of Sensor and Actuator Networks10.3390/jsan50100055:1(5)Online publication date: 3-Mar-2016
https://doi.org/10.3390/jsan5010005
Strohbach MZiekow HGazis VAkiva N(2015)Towards a Big Data Analytics Framework for IoT and Smart City ApplicationsModeling and Processing for Next-Generation Big-Data Technologies10.1007/978-3-319-09177-8_11(257-282)Online publication date: 2015
https://doi.org/10.1007/978-3-319-09177-8_11
Veit AGoebel CTidke RDoblander CJacobsen HCrowcroft JPenty RLe Boudex JShenoy P(2014)Household electricity demand forecastingProceedings of the 5th international conference on Future energy systems10.1145/2602044.2602082(233-234)Online publication date: 11-Jun-2014
https://dl.acm.org/doi/10.1145/2602044.2602082
Doblander CRabl TJacobsen H(2012)Processing Big Events with Showers and StreamsRevised Selected Papers of the First Workshop on Specifying Big Data Benchmarks - Volume 816310.1007/978-3-642-53974-9_6(60-71)Online publication date: 17-Dec-2012
https://dl.acm.org/doi/10.1007/978-3-642-53974-9_6

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