Research On Energy Procurement And Marketing Decision For Electricity Retailer Considering Risk Aversion In Electricity Market

In 1985,the government began to raise a fund to develop the e lectric power industry,and began to reform the industry.In 2015,the government issued “Several Opinions about Further Deepening the Reformation of Electric Power System”,encouraged establishing six kinds of electricity subjects,opened the sale busines s of electricity to social capital orderly,and promoted the further reformation progress of retail electricity market.Electricity retailer plays the role of a middleman who purchase power from wholesale market and balancing market,then sell it to consumer.At the same time,electricity retailer faces both volatility risk from market price and user side load.Therefore,studying characteristics of risk aversion of the power purchasing and selling contracts,and making reasonable composite trading strategy and sale price are key problems to electricity retailer.This paper focuses on the trading strategy for electricity retailer considering risk aversion in wholesale market and balancing market.In wholesale market,the composite trading strategy which is made up of four kinds of power purchasing methods and two kinds of power selling methods is studied.Power purchasing methods consist of Long-term bilateral contract?option contract?interruptible load contracts and the day-ahead spot market transaction.Power selling methods consists of fixed time-of-use power price contract and real-time price contract.A model of mixed integer nonlinear programming strategy is built and the conditional value at risk is adopted as a method of trade risk evaluation.The paper sets maximization of electricity retailer profit and minimization of risk loss as objective.The BONMIN is used to solve the model.In balancing market,user side load is regarded as balancing resources in this paper where an optimal trading strategy cons idering interruptible load,power acquisition and critical load price is proposed.A model of non-linear model trade strategy is built based on stochastic programming where conditional value at risk is adopted as a method of trade risk evaluation.Based on idea of bi-level programming,the paper sets maximization of electricity retailer profit and minimization of risk loss as upper level objective while maximization of user satisfaction as lower level objective.Adaptive genetic algorithm and the second generation of inferior sorting genetic algorithm are introduced to solve the model.Case study validates the effectiveness and rationality of the proposed model.The first case indicates that different kinds of power purchasing contracts and power selling contracts have different characteristics of income and risk aversion.Electricity retailer should make reasonable composite trading strategy and sale price according to its individual risk preference.The second case indicates that risk preference and the volatility of market price have an obvious effect on the profit and expected risk loss of electricity retailer.The trading strategy considering interruptible load,power acquisition and critical load price which is proposed in this paper could optimize profit and reduce risk loss of electricity retailer obviously,and realize win-win between electricity retailer and consumer.