电力建设2024，Vol.45Issue(5)：131-140,10.DOI:10.12204/j.issn.1000-7229.2024.05.013
基于改进CVaR的售电公司电力现货日前申报优化策略
Optimization Strategy for Electricity Retailer's Day-Ahead Bidding in the Electricity Spot Market Based on Improved CVaR
摘要
Abstract
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 subjective confidence level selection.To address these challenges,this study introduces a scenario reduction method based on k-means and a confidence level optimization method based on extrapolation-interpolation,proposing an improved CVaR day-ahead bidding optimization model and its solution strategy based on the traditional neutral risk model and CVaR optimization model.The simulation results validate that the improved CVaR optimization model effectively reduces the overall purchasing costs and potential risk losses for the electricity retailer.This study explores the impact of the day-ahead bidding optimization strategy under different levels of risk aversion and market volatility,demonstrating the applicability and robustness of the improved optimization strategy.关键词
改进CVaR模型/售电公司/日前申报/风险管理Key words
improved CVaR model/electricity retailer/day-ahead bidding/risk management分类
信息技术与安全科学引用本文复制引用
叶海,杨苹,王雨..基于改进CVaR的售电公司电力现货日前申报优化策略[J].电力建设,2024,45(5):131-140,10.基金项目
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) （No.51937005）
广东省重点领域研发计划项目(2021B0101230003) （2021B0101230003）
