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考虑可再生能源消纳责任权重的年度合同电量月度分解方法
引用本文:姜曼,司马琪,鲍玉昆,刘定宜.考虑可再生能源消纳责任权重的年度合同电量月度分解方法[J].电力系统自动化,2021,45(16):208-215.
作者姓名:姜曼  司马琪  鲍玉昆  刘定宜
作者单位:国家电网公司华中分部,湖北省武汉市 430077;华中科技大学管理学院,湖北省武汉市 430074
基金项目:国家自然科学基金资助项目(71871101)。
摘    要:在可再生能源电力消纳保障机制的政策背景下,作为电力系统运行的主要参与者之一,省级电力交易中心需要积极承担可再生能源电力消纳责任,通过编制合理、有效的月度电能交易计划,促进可再生能源电力的消纳和政策的落实.文中提出了一种考虑可再生能源电力消纳责任权重的年度合同电量月度滚动分解方法.该方法基于优化和决策理论,通过对影响可再生能源电力消纳的因素的分析,建立了考虑可再生能源电力消纳责任权重指标完成难度和空气污染指数的双目标优化模型.除此之外,模型通过对剩余月份合同电量的整体优化,保证了电量执行的可行性和分配的公平性.算例结果验证了所提方法的合理性和有效性.

关 键 词:消纳责任权重  空气污染指数  合同电量分解  多目标优化
收稿时间:2020/9/5 0:00:00
修稿时间:2021/2/16 0:00:00

Monthly Decomposition Method of Annual Contract Considering Responsibility Weight of Renewable Energy Accommodation
JIANG Man,SIMA Qi,BAO Yukun,LIU Dingyi.Monthly Decomposition Method of Annual Contract Considering Responsibility Weight of Renewable Energy Accommodation[J].Automation of Electric Power Systems,2021,45(16):208-215.
Authors:JIANG Man  SIMA Qi  BAO Yukun  LIU Dingyi
Affiliation:1.Central China Branch of State Grid Corporation of China, Wuhan 430077, China;2.School of Management, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract:In the policy background of the guarantee mechanism for renewable energy accommodation, the provincial power trading center, as one of the major players in the operation of the power system, needs to actively fulfill the responsibility of renewable energy accommodation, and promote the renewable energy accommodation and the implementation of policies by formulating a reasonable and effective monthly electricity trading scheme. This paper proposes a monthly rolling decomposition method of an annual contract considering the responsibility weight of renewable energy accommodation. Based on the theories of optimization and decision-making, this method establishes a dual-objective optimization model considering the difficulty of completing the responsibility weight index of renewable energy accommodation and air pollution index through the analysis of the factors that affect the renewable energy accommodation. In addition, through the overall optimization of the contract of the remaining months, the model ensures the feasibility of electricity contract execution and the fairness of distribution. The rationality and effectiveness of the proposed method are verified by the results of the case study.
Keywords:responsibility weight of accommodation  air pollution index  contract decomposition  multi-objective optimization
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