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计及风险规避的电力零售商平衡市场交易模型
引用本文:方绍凤,周任军,彭院院,李斌,许福鹿,石亮缘.计及风险规避的电力零售商平衡市场交易模型[J].电力系统及其自动化学报,2020(2):22-27.
作者姓名:方绍凤  周任军  彭院院  李斌  许福鹿  石亮缘
作者单位:湖南省清洁能源与智能电网协同创新中心(长沙理工大学);国网福建省电力有限公司漳州供电公司;广州供电局有限公司
基金项目:国家自然科学基金资助项目(51277016,71331001,91746118)。
摘    要:由于新能源出力以及终端负荷需求的不确定性,电力零售商在日前市场的竞标电量与实时市场的购买电量之间存在不平衡而产生惩罚成本风险。引入用户侧可控负荷作为平衡资源参与市场交易,提出了一种风险规避程度指标,以此来度量交易前后电量偏差程度,以信息熵度量残差序列离散程度计算风险规避程度指标。以电力零售商运行收益、用户需求响应满意度以及风险规避程度最大为目标建立多目标风险规避模型,采用自适应权重粒子群算法进行模型求解。通过算例表明,所提出的模型从电网-电力零售商-用户多个角度去考虑电力零售商参与平衡市场交易策略,能够有效提高电力零售商的运行效益以及用户满意度,同时可以提高电力市场管理的可靠性与安全性。

关 键 词:电力零售商  不平衡电量  风险规避  多目标优化

Trading Model in Balanced Market for Power Retailers Considering Risk Aversion
FANG Shaofeng,ZHOU Renjun,PENG Yuanyuan,LI Bin,XU Fulu,SHI Liangyuan.Trading Model in Balanced Market for Power Retailers Considering Risk Aversion[J].Proceedings of the CSU-EPSA,2020(2):22-27.
Authors:FANG Shaofeng  ZHOU Renjun  PENG Yuanyuan  LI Bin  XU Fulu  SHI Liangyuan
Affiliation:(Hunan Province Collaborative Innovation Center of Clean Energy and Smart Grid(Changsha University of Science and Technology),Changsha 410114,China;Zhangzhou Power Supply Company,State Grid Fujian Electric Power Company,Zhangzhou 363000,China;Guangzhou Power Supply Bureau Co.,Ltd,Guangzhou 510620,China)
Abstract:Due to the uncertainties in new energy output and terminal load demand,there exists an imbalance between the bidding power of power retailers in the day-ahead market and the purchase of electricity in the real-time market,thus causing a penalty cost risk.In this paper,controllable user-side load is introduced as balancing resources to partici?pate in market transactions,and a risk aversion index is proposed to measure the deviation of power consumption before and after the transaction.Moreover,information entropy is used to measure the discrete degree of residue series and fur?ther calculate the risk aversion index.A multi-objective risk aversion model is established,which sets the maximization of power retailer profit,user demand response satisfaction,and the degree of risk aversion as its objective and is solved by the adaptive weighted particle swarm optimization algorithm.The result of an example shows that by taking into ac?count the strategy for power retailers participating in the balanced market transactions from aspects of grid,power retail?ers,and users,the proposed model can effectively improve the operation profit of power retailers as well as the user sat?isfaction degree.Meanwhile,it can improve the reliability and security of power market management.
Keywords:power retailer  unbalanced power  risk aversion  multi-objective optimization
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