Research On Optimal Technology Of Operation Decision Of Electricity Retail Company In Market Environment

With the reform of the electricity sales side market,the number of electricity retail companies has increased sharply and they have become the main players in the emerging market.The competitive power market structure of "multi-buyers-multi-sellers" has gradually formed,In addition,with the construction of the electricity spot market,electricity retail companies are facing the challenge of the uncertainty in the electricity price of the spot market,in this regard,electricity retail companies have insufficient experience in operating decision-making.Besides,factors such as the market is complex and changeable,the system is imperfect,and the competition of electricity retail companies is fierce have brought huge risks to the electricity sales company.The operation decision-making optimization technology of the retail electricity company in the market environment is the key to its development,how to win customer resources,reduce power purchase costs,understand user power characteristics,tap high-quality users,formulate appropriate power purchase and sales strategies,and avoid the risk of uncertainty in spot market power prices This is an issue that electricity retail companies need to study urgently。This article first analyzes the impact of load factor on electricity cost from the perspective of coal consumption cost and transportation cost,and obtains the relationship between load rate and power purchase cost.On the user side,considering the complementary characteristics of the user’s load,a load portfolio optimization model with the goal of maximizing the revenue of the retail company is proposed,and an improved greedy algorithm is proposed to solve the problem,the user group of the electricity sales company is obtained;then,considering the the transferable load,the demand response subsidy is formulated to further improve the load characteristics.The calculation examples show that the load characteristic optimization strategy studied in this chapter can help the retail company select user groups with complementary load characteristics,formulate appropriate demand response subsidies,improve load characteristics,increase load rates,and reduce power purchase costs.It provides a suitable basis of user load curves for the Subsequent research on user power usage portraits and power purchases and sales.Secondly,after obtaining user groups,a multi-dimensional load characteristic mining index system was constructed for the various user load data obtained in the operation of the electricity retail company.including five comprehensive load characteristics of user temperature sensitivity,load stability,electricity price sensitivity,load economic value,user interaction capability and various evaluation indicators.The comprehensive weight calculation method based on AHP and EWM and the TOPSIS comprehensive evaluation method are used to comprehensively evaluate the various indicators of the load characteristics.Finally,the user is subdivided through fuzzy C-mean clustering,and the power consumption portraits of different user groups are analyzed.Help the retail company to further understand the load characteristics of different users and tap high-quality users.Finally,a joint optimization model for the purchase and sale of electricity by electricity retail companies considering the utility of electricity consumption by users is established.The wholesale side of the electricity sales company purchases electricity through the medium and long-term market and the spot market,and the retail side uses fixed electricity price and timeof-use electricity price packages to sell electricity.The user has signed an interruptible load as a virtual power source to avoid the risk of extreme electricity prices in the spot market,and takes into account the user’s electricity utility to jointly optimize the power purchase combination and the price of the electricity price package.CVa R is used to measure the risk of uncertainty in the spot market electricity price to achieve sales.The goal of maximum revenue and minimum risk for power companies.The calculation example analyzes the strategies of retail power companies under different risk preferences and compares the benefits of joint optimization and unilateral optimization of power purchase portfolios.The results verify the first joint optimization strategy proposed in this paper.On the one hand,it helped the electricity sales company to increase the income of electricity purchase and sale,and at the same time,the user-side welfare was improved,achieving a win-win result between the electricity sales company and the user.