基于改进CVaR的售电公司电力现货日前申报优化策略OA北大核心CSTPCD
Optimization Strategy for Electricity Retailer's Day-Ahead Bidding in the Electricity Spot Market Based on Improved CVaR
在电力现货市场环境下,售电公司需要面向市场电价及用户负荷的双重不确定性,在日前申报的环节易造成额外购电成本.然而现有基于条件风险价值(conditional value at risk,CVaR)等随机优化方法的购电方案与风险管理策略中存在等概率缩减关键场景与主观进行置信度选值的问题,为此基于传统的中性风险模型及CVaR优化模型,引入基于K-means的场景聚类缩减方法,提出基于外推内插法的置信度选值优化方法,综合形成改进CVaR的售电公司日前申…查看全部>>
In the electricity spot market,electricity retailers face dual uncertainties that arise from market electricity prices and user loads.The day-ahead bidding process can incur additional purchasing costs owing to these uncertainties.However,existing stochastic optimization methods for electricity purchasing strategies and risk management,such as the conditional value at risk(CVaR),suffer from problems related to equiprobable reduction in key scenarios and subj…查看全部>>
叶海;杨苹;王雨
华南理工大学电力学院,广州市 510640华南理工大学电力学院,广州市 510640华南理工大学电力学院,广州市 510640
动力与电气工程
改进CVaR模型售电公司日前申报风险管理
improved CVaR modelelectricity retailerday-ahead biddingrisk management
《电力建设》 2024 (5)
131-140,10
This work is supported by National Natural Science Foundation of China(No.51937005)and Key Research and Development Program of Guangdong Province(No.2021B0101230003). 国家自然科学基金项目(51937005)广东省重点领域研发计划项目(2021B0101230003)
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