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Urban virtual power plant operation optimization with incentive-based demand response

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  • Zhou, Kaile
  • Peng, Ning
  • Yin, Hui
  • Hu, Rong

Abstract

Urban virtual power plant (VPP) shows great potential in alleviating urban power shortage or power supply-demand imbalance. This study proposes a bi-layer optimization model considering incentive-based demand response (IDR) to optimize the operation scheduling of urban VPP. The bi-layer optimization model includes the lower-layer IDR model and the upper-layer urban VPP optimal operation scheduling model. In the lower-layer IDR model, user satisfaction, comfort and preference are considered. Users mainly participate in the scheduling of urban VPP by IDR. The demand response resources obtained by urban VPP through providing incentives for users can effectively alleviate the energy supply pressure. In the upper-layer urban VPP optimal operation scheduling model, the scheduling plans for generating units and trading plans for the electricity wholesale market can be determined. Through upper-layer scheduling, it can not only meet the energy demand of users, but also minimize the urban VPP operation cost. The experimental results show that the proposed bi-layer optimization model for urban VPP operation considering IDR can achieve urban energy resources optimal allocation and support urban energy supply-demand balance, on the premise of ensuring economic benefits.

Suggested Citation

  • Zhou, Kaile & Peng, Ning & Yin, Hui & Hu, Rong, 2023. "Urban virtual power plant operation optimization with incentive-based demand response," Energy, Elsevier, vol. 282(C).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223020947
    DOI: 10.1016/j.energy.2023.128700
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    2. Liu, Xin & Li, Yang & Wang, Li & Tang, Junbo & Qiu, Haifeng & Berizzi, Alberto & Valentin, Ilea & Gao, Ciwei, 2024. "Dynamic aggregation strategy for a virtual power plant to improve flexible regulation ability," Energy, Elsevier, vol. 297(C).

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