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A two-stage benefit optimization and multi-participant benefit-sharing strategy for hybrid renewable energy systems in rural areas under carbon trading

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  • Zhang, Lihui
  • Li, Songrui
  • Nie, Qingyun
  • Hu, Yitang

Abstract

Hybrid renewable energy systems (HRESs) are a promising tool for reducing emissions in rural areas. Suitable transaction mechanisms and impartial benefit-sharing strategies are the basis for sustainable HRESs. An HRES that focuses on biomass energy comprising three participants, is proposed and a two-stage benefit optimization and sharing model that is based on a reward-punishment-tiered carbon trading (CT) policy is established in this study. To ensure that maximum benefits are gained from HRESs, impartial benefit-sharing strategies such as minimum cost-retaining savings, Nash negotiation, and an improved Shapley value are selected. The results of the first stage show that the benefits of an alliance between the three participants increased by $22621.08 and $11497.49, respectively, under CT. The results of the second stage show that a suitable benefit-sharing strategy can be selected according to the needs of different cooperation models, with the contribution of all participants fully reflected under the improved Shapley value method. The use of a two-stage optimization model improved the willingness of participants to cooperate, based on the premise of maximum benefits. Additionally, new ideas for promoting the development of rural energy can further be provided.

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  • Zhang, Lihui & Li, Songrui & Nie, Qingyun & Hu, Yitang, 2022. "A two-stage benefit optimization and multi-participant benefit-sharing strategy for hybrid renewable energy systems in rural areas under carbon trading," Renewable Energy, Elsevier, vol. 189(C), pages 744-761.
    • Handle: RePEc:eee:renene:v:189:y:2022:i:c:p:744-761
    DOI: 10.1016/j.renene.2022.03.048
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    8. Du, Sipeng & Wu, Di & Dai, Zhong & Li, Guiqiang & Lahaxibai, Shala, 2023. "Regional collaborative planning equipped with shared energy storage under multi-time scale rolling optimisation method," Energy, Elsevier, vol. 277(C).

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