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State-of-the-art short-term electricity market operation with solar generation: A review

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  • Yin, S.
  • Wang, J.
  • Li, Z.
  • Fang, X.

Abstract

With the accelerating penetration of solar energy in energy systems, market operations concerning the solar-associated intermittency are widely discussed. How to correctly model the solar generation in the market and solve the uncertainty-based operation problems call for solutions. Unlike other renewable resources, solar power can be more easily applied to the demand side through behind-the-meter installations in a distributed manner with significant future extensibility. The corresponding operational rules in the markets are largely being revised. Over the past two decades, with the development of deregulated power markets, numerous studies related to uncertainty-based market operations tend to transform the market from a deterministic and centralized framework to a stochastic and decentralized one. As the relevant literature is most recent, this paper reviews their contributions to electricity market operations with solar integration and underlines the research directions of this topic and ongoing industry practices. A thorough review of the electricity markets worldwide with solar energy is provided. A variety of proposed mathematical solutions to the problem are also discussed.

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  • Yin, S. & Wang, J. & Li, Z. & Fang, X., 2021. "State-of-the-art short-term electricity market operation with solar generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:rensus:v:138:y:2021:i:c:s136403212030931x
    DOI: 10.1016/j.rser.2020.110647
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    1. Christos N. Dimitriadis & Evangelos G. Tsimopoulos & Michael C. Georgiadis, 2021. "A Review on the Complementarity Modelling in Competitive Electricity Markets," Energies, MDPI, vol. 14(21), pages 1-27, November.
    2. Doumen, Sjoerd C. & Nguyen, Phuong & Kok, Koen, 2022. "Challenges for large-scale Local Electricity Market implementation reviewed from the stakeholder perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    3. Zhao, Ning & You, Fengqi, 2022. "Sustainable power systems operations under renewable energy induced disjunctive uncertainties via machine learning-based robust optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    4. Rezaeimozafar, Mostafa & Monaghan, Rory F.D. & Barrett, Enda & Duffy, Maeve, 2022. "A review of behind-the-meter energy storage systems in smart grids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    5. Lei, Shunbo & Pozo, David & Wang, Ming-Hao & Li, Qifeng & Li, Yupeng & Peng, Chaoyi, 2022. "Power economic dispatch against extreme weather conditions: The price of resilience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).

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