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Hybrid energy sharing considering network cost for prosumers in integrated energy systems

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  • Li, Ruizhi
  • Yan, Xiaohe
  • Liu, Nian

Abstract

The integrated energy system (IES) is developed to enhance the flexibility and efficiency of prosumers in the energy system. However, the current energy sharing method normally focuses on the energy cost and ignores the network cost, which constitutes a quarter of the prosumers’ electricity bills. It impacts energy sharing significantly. This paper proposes a hybrid energy sharing strategy for prosumers considering the electric and thermal network cost, to reduce the total cost. Firstly, the total cost of the prosumer is modelled based on joint energy-network cost. Secondly, the impact of uncertainty from renewables on the total cost is evaluated via the conditional value at risk. Thirdly, the non-cooperative game among prosumers is modelled and the existence of pure strategy equilibrium is proved. Then, the iterated best response algorithm based on differential evolution using limited information is proposed to protect personal privacy. Finally, the rationality and effectiveness of the model and the optimization method are verified by a coupled electricity-heat IES. The results show that the proposed model can reduce the energy consumption cost of prosumers and improve the penetration of renewable energy.

Suggested Citation

  • Li, Ruizhi & Yan, Xiaohe & Liu, Nian, 2022. "Hybrid energy sharing considering network cost for prosumers in integrated energy systems," Applied Energy, Elsevier, vol. 323(C).
    • Handle: RePEc:eee:appene:v:323:y:2022:i:c:s0306261922009291
    DOI: 10.1016/j.apenergy.2022.119627
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    5. Zhihan Shi & Guangming Zhang & Xiaoxiong Zhou & Weisong Han & Mingxiang Zhu & Zhiqing Bai & Xiaodong Lv, 2023. "Research on Integrated Energy Distributed Sharing in Distribution Network Considering AC Power Flow and Demand Response," Sustainability, MDPI, vol. 15(22), pages 1-23, November.
    6. Li, Yang & Bu, Fanjin & Li, Yuanzheng & Long, Chao, 2023. "Optimal scheduling of island integrated energy systems considering multi-uncertainties and hydrothermal simultaneous transmission: A deep reinforcement learning approach," Applied Energy, Elsevier, vol. 333(C).

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