With the development of clean energy,the issue of clean energy consumption has received increasing attention.This paper considers thermal power,wind power,hydropower (adjustable and non-adjustable) and nuclear power to participate in monthly contract market,and introduces a penalty cost coefficient to quantify the additional costs caused by wind power and non-adjustable hydropower forecast deviations.In addition,this paper also takes into account the relationship between the monthly contract market and day-ahead market,and refines the monthly power purchase optimization to daily.In view of the uncertainty of wind power,non-adjustable hydropower,load and market price,the CVaR is used to measure the loss.The sum of the monthly electricity purchase cost and the day-ahead purchase cost is used as an indicator to evaluate the economy of purchasing electricity,and a model of expected electricity purchase cost-loss risk is established.Based on the analysis of specific examples,the monthly power purchase optimization results are obtained,and the influences of wind power prediction error,penalty cost coefficient and risk preference on the optimization results are analyzed.
