Optimal decision model and application of electricity purchasing and selling ofelectricity retailer in electricity market
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TM863

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    Abstract:

    The phenomenon of resigning annual contracts in China medium-term and long-term electricity market highlights the theoretical and policy issues of optimal power combination decision making by multiple investors considering risk factors in 2021. Based on the independent decision making for power purchase in wholesale market and tariff packages in retail market, the decision making model of optimal power ratio of power salez business based on conditional value at risk (CVaR) is constructed for power companies, numerical calculation and analysis are carried out. According to the typical power purchase and sales business scenario for power companies based on the current provincial power market, this paper proposes a corresponding revenue or cost calculation method; uses CVaR as the risk assessment index, and takes the purchase ratio of different trading varieties in the wholesale market and the sales ratio of different tariff packages in the retail market as the decision variables. The optimal revenue-risk decision model aims to maximize the revenues. The impact of typical power transaction combinations and different confidence levels on the structure, revenue and risks of power transactions by power companies is calculated by combining the actual data of Guangdong power market. The paper analyzes the reasons for resigning contracts based on the objective models and simulation, and provides a basis for investors, including power companies, to make decisions on power purchase and sales considering risk management and the government's annual market trading scheme.

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汤旸,刘翊枫,王静,高雄,叶泽,陈磊,刘畅.电力市场售电公司最优购售电量决策模型及其应用[J].电力科学与技术学报英文版,2022,37(4):3-12. Tang Yang, Liu Yifeng, Wang Jing, Gao Xiong, Ye Ze, Chen Lei, Liu Chang. Optimal decision model and application of electricity purchasing and selling ofelectricity retailer in electricity market[J]. Journal of Electric Power Science and Technology,2022,37(4):3-12.

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  • Received:
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  • Online: September 23,2022
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