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Aggregator-mediated demand response: Minimizing imbalances caused by uncertainty of solar generation

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  • Okur, Özge
  • Voulis, Nina
  • Heijnen, Petra
  • Lukszo, Zofia

Abstract

The high level of uncertainty of renewable energy sources generation creates differences between electricity supply and demand, endangering the reliable operation of the power system. Demand response has gained significant attention as a means to cope with uncertainty of renewable energy sources. Demand response of residential and service sector consumers, when accumulated and managed by aggregators, can play a role in existing electricity markets. This paper addresses the question to what extent aggregator-mediated demand response can be used to deal with the impacts of the uncertainty of solar generation. Uncertain solar generation leads to imbalances of an aggregator. These imbalances can be reduced by shifting flexible loads, which is called demand response for internal balancing. The aim of this paper is to assess the impact of demand response from loads in residential and service sectors for internal balancing to reduce the imbalances of an aggregator, caused by uncertain solar generation. For this purpose, a Model Predictive Control model which minimizes the imbalances of the aggregator through load shifting is presented. The model is applied to a realistic case study in the Netherlands. The results show that demand response for internal balancing succeeds in reducing imbalances. Even though this is favorable from the power system’s perspective, economic analysis shows that the aggregator is not financially incentivized to implement demand response for internal balancing.

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  • Okur, Özge & Voulis, Nina & Heijnen, Petra & Lukszo, Zofia, 2019. "Aggregator-mediated demand response: Minimizing imbalances caused by uncertainty of solar generation," Applied Energy, Elsevier, vol. 247(C), pages 426-437.
    • Handle: RePEc:eee:appene:v:247:y:2019:i:c:p:426-437
    DOI: 10.1016/j.apenergy.2019.04.035
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    15. Heider, Anya & Huber, Jill & Farhat, Yamshid & Hertig, Yves & Hug, Gabriela, 2024. "How to choose a suitable network tariff? - Evaluating network tariffs under increasing integration of distributed energy resources," Energy Policy, Elsevier, vol. 188(C).
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    18. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N. & Burmester, Daniel, 2021. "Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation," Applied Energy, Elsevier, vol. 287(C).
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    20. Oprea, Simona-Vasilica & Bâra, Adela & Ciurea, Cristian-Eugen, 2022. "A novel cost-revenue allocation computation for the competitiveness of balancing responsible parties, including RES. Insights from the electricity market," Renewable Energy, Elsevier, vol. 199(C), pages 881-894.
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