Research On Operation Strategy Of Electricity Sales Subject Considering Demand Response

Advanced metering infrastructure led by smart meters is gradually popularized,smart grid construction and two-way communication technology are accelerating,and the development of demand response has lowered the threshold for demand-side resources to participate in power system regulation.At the same time,the release of the "No.9" in 2015 has given China’s power industry model another chance to innovate,and a wave of reforms on the electricity sales side is imperative.In the fierce market competition,it is difficult for the electricity sales company to obtain a prominent competitive advantage only through the basic business of profiting from the difference between the wholesale and retail sides.Therefore,how to enhance the core competitiveness of the electricity sales subject is a highly focused issue in the reform process.On the one hand,this paper draws on the development process of more mature power markets in foreign developed countries,and deeply analyzes the power market model at various stages.The analysis focuses on the market composition,reform priorities,and market characteristics of each stage.On the other hand,this article combines the market framework of “medium and long-term trading + centralized spot trading” in the Guangdong electricity market,based on the market transactions and profit and loss of electricity sales entities from 2017 to 2019,clarifies the market risk of electricity sales entities,and establishes a reasonable Risk measurement indicators,and analyze the operation strategies of power sales entities considering risk management.Then,based on the load curve of the power user,this paper analyzes the user’s electricity consumption behavior,and proposes a customized electricity price design model that considers the user’s electricity consumption characteristics.First,the clustering algorithm is used to obtain the difference in the load curve shape of each user group,and then according to the power demand of each type of power user,the model takes the maximum sales revenue of the power sales company and the highest power user satisfaction as the optimization goals.The peak-valley electricity price period and electricity price level of various users are optimized,so as to obtain the electricity price package scheme of various users,and the validity of the model is verified through simulation.Finally,this article studies the uncertainty risk in the transaction process of the electricity sales entity,which is also a problem that the electricity sales company must face and urgently need to solve in the electricity purchase and sale strategy.This paper analyzes the uncertainty of user-side load forecasting of electricity sales companies and the risk of price volatility in the spot market,and uses Monte Carlo random sampling and back-generation scenario reduction to establish typical random scenarios that take into account uncertainty.Then,a multi-stage electricity sales company trading strategy model framework under a long-term scale that combines the mid-to-long-term market and the spot market is proposed to maximize the expected return and minimize the transaction risk as an optimization goal.Optimize decision-making including electricity sales companies’ mid-to-long-term electricity purchase ratios,retail electricity price levels,and DR programs based on demand-side repurchases,and use U.S.electricity market data to conduct simulation experiments to prove that the model is balancing expected income and income fluctuation Good results can be achieved between risks.