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A graphical approach to carbon-efficient spot market scheduling for Power-to-X applications

Author

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  • Neeraj Bokde
  • Bo Tranberg
  • Gorm Bruun Andresen
Abstract
In the Paris agreement of 2015, it was decided to reduce the CO2 emissions of the energy sector to zero by 2050 and to restrict the global mean temperature increase to 1.5 degree Celcius above the pre-industrial level. Such commitments are possible only with practically CO2-free power generation based on variable renewable technologies. Historically, the main point of criticism regarding renewable power is the variability driven by weather dependence. Power-to-X systems, which convert excess power to other stores of energy for later use, can play an important role in offsetting the variability of renewable power production. In order to do so, however, these systems have to be scheduled properly to ensure they are being powered by low-carbon technologies. In this paper, we introduce a graphical approach for scheduling power-to-X plants in the day-ahead market by minimizing carbon emissions and electricity costs. This graphical approach is simple to implement and intuitively explain to stakeholders. In a simulation study using historical prices and CO2 intensity for four different countries, we find that the price and CO2 intensity tends to decrease with increasing scheduling horizon. The effect diminishes when requiring an increasing amount of full load hours per year. Additionally, investigating the trade-off between optimizing for price or CO2 intensity shows that it is indeed a trade-off: it is not possible to obtain the lowest price and CO2 intensity at the same time.

Suggested Citation

  • Neeraj Bokde & Bo Tranberg & Gorm Bruun Andresen, 2020. "A graphical approach to carbon-efficient spot market scheduling for Power-to-X applications," Papers 2009.03160, arXiv.org.
  • Handle: RePEc:arx:papers:2009.03160
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    References listed on IDEAS

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    1. Bo Tranberg & Olivier Corradi & Bruno Lajoie & Thomas Gibon & Iain Staffell & Gorm Bruun Andresen, 2018. "Real-Time Carbon Accounting Method for the European Electricity Markets," Papers 1812.06679, arXiv.org, revised May 2019.
    2. Bailera, Manuel & Lisbona, Pilar & Romeo, Luis M. & Espatolero, Sergio, 2017. "Power to Gas projects review: Lab, pilot and demo plants for storing renewable energy and CO2," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 292-312.
    3. Blanco, Herib & Faaij, André, 2018. "A review at the role of storage in energy systems with a focus on Power to Gas and long-term storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1049-1086.
    4. Koj, Jan Christian & Wulf, Christina & Zapp, Petra, 2019. "Environmental impacts of power-to-X systems - A review of technological and methodological choices in Life Cycle Assessments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 865-879.
    5. Prakash, Vrishab & Ghosh, Sajal & Kanjilal, Kakali, 2020. "Costs of avoided carbon emission from thermal and renewable sources of power in India and policy implications," Energy, Elsevier, vol. 200(C).
    6. Mills, Andrew D. & Levin, Todd & Wiser, Ryan & Seel, Joachim & Botterud, Audun, 2020. "Impacts of variable renewable energy on wholesale markets and generating assets in the United States: A review of expectations and evidence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    7. Neeraj Bokde & Andrés Feijóo & Daniel Villanueva & Kishore Kulat, 2019. "A Review on Hybrid Empirical Mode Decomposition Models for Wind Speed and Wind Power Prediction," Energies, MDPI, vol. 12(2), pages 1-42, January.
    8. Mohammadi Rad, Amin & Barforoushi, Taghi, 2020. "Optimal scheduling of resources and appliances in smart homes under uncertainties considering participation in spot and contractual markets," Energy, Elsevier, vol. 192(C).
    9. Panos, Evangelos & Kober, Tom & Wokaun, Alexander, 2019. "Long term evaluation of electric storage technologies vs alternative flexibility options for the Swiss energy system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    10. Yao, Xing & Yi, Bowen & Yu, Yang & Fan, Ying & Zhu, Lei, 2020. "Economic analysis of grid integration of variable solar and wind power with conventional power system," Applied Energy, Elsevier, vol. 264(C).
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Manisha Sawant & Sameer Thakare & A. Prabhakara Rao & Andrés E. Feijóo-Lorenzo & Neeraj Dhanraj Bokde, 2021. "A Review on State-of-the-Art Reviews in Wind-Turbine- and Wind-Farm-Related Topics," Energies, MDPI, vol. 14(8), pages 1-30, April.
    2. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2022. "A Survey of Efficient Demand-Side Management Techniques for the Residential Appliance Scheduling Problem in Smart Homes," Energies, MDPI, vol. 15(8), pages 1-34, April.
    3. Iva Ridjan Skov & Noémi Schneider & Gerald Schweiger & Josef-Peter Schöggl & Alfred Posch, 2021. "Power-to-X in Denmark: An Analysis of Strengths, Weaknesses, Opportunities and Threats," Energies, MDPI, vol. 14(4), pages 1-14, February.
    4. Manisha Sawant & Rupali Patil & Tanmay Shikhare & Shreyas Nagle & Sakshi Chavan & Shivang Negi & Neeraj Dhanraj Bokde, 2022. "A Selective Review on Recent Advancements in Long, Short and Ultra-Short-Term Wind Power Prediction," Energies, MDPI, vol. 15(21), pages 1-24, October.
    5. Zbigniew Skibko & Magdalena Tymińska & Wacław Romaniuk & Andrzej Borusiewicz, 2021. "Impact of the Wind Turbine on the Parameters of the Electricity Supply to an Agricultural Farm," Sustainability, MDPI, vol. 13(13), pages 1-15, June.

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