Research On Risk Analysis And Response Of Power Supply Company In The Competitive Market

March 2015 "on the further deepening of the reform of electric power system" (No. [2015]9) and a series of reform documents have been introduced, marking a new round of electricity reform officially launched. "Release transmission and distribution outside the competition part of the price, release placing electrical business, release the public interest and the regulation of outside power plan, trading institutions are relatively independent, strengthen government supervision, to strengthen the power of overall planning" is the power to change the focus of, for a new round of electricity reform, derivatives give birth to many of the problems we need to further study.This article in the analysis between enterprises of electric power market transaction mode based on, in a competitive electricity market, power as the greatest characteristics of goods is not effective storage, which leads to the elasticity of demand is very small, resulting in price susceptible to influence of power supply and demand, prone to dramatic swings in prices, focuses on the research of power supply enterprise under the new market competition link purchase sector and the retail sector is facing the risk, and according to the characteristics of risk analysis and countermeasure research. This paper through the power purchase model of data analysis, according to the modern portfolio theory, establish the optimal purchasing power portfolio decision model using genetic algorithm optimization, scientific distribution of purchase of electricity purchased part of electricity price risk and load risk.This paper through the power purchase model of data analysis, according to the modern portfolio theory, establish the optimal purchasing power portfolio decision model using genetic algorithm optimization, scientific distribution of purchase of electricity purchased part of electricity price risk and load risk.In the retail sector analysis, based on the power supply enterprise electricity recycling process in huge arrears risk, this paper is comprehensive evaluation of electricity customers credit and easy to collect data of principle in the analysis of the influencing factors on the basis, from electricity customers own ability and previous credit situation of set electricity customer credit evaluation index system. Using genetic algorithm to optimize the weights and thresholds of BP neural network to establish the model of customer credit evaluation and genetic algorithm to BP neural network into local minima of the possibility of greatly reduced, but also improves the training speed of BP neural network. According to the results of credit evaluation, different management methods are adopted to avoid the risk of electricity recovery, and the validity of the model is verified by an example. At the same time, this paper makes a preliminary discussion on the development direction of the marketing business of power supply enterprises under the situation of market competition.Finally, this paper makes a preliminary discussion on the development direction of the marketing business of power supply enterprises under the situation of market competition.