Risk Avoidance Model Of Power Sales Company Considering User Satisfaction

Under the new round of power system reform in China,power sales channels have gradually opened up,and power sales companies have entered the market.The sales company bears the responsibility of buying electricity from the market and then selling electricity to users.Due to the inaccuracy of user-side load forecasting and the inability to balance power in real time,power sales companies are faced with two risks,one is the uncertainty of user demand.The other is the volatility of market prices.This will pose a huge threat to the sales company’s revenue,and the competitive pressure brought by the increasing number of power sales companies will cause the sales company to consider how to optimize its services,improve user satisfaction and maximize user satisfaction..Therefore,this paper starts from the risk aversion method of the power sales company and the user satisfaction evaluation,and deeply studies the risk aversion model of the sales company that takes into account the user satisfaction.Aiming at the uncertainty of user demand uncertainty,this paper proposes a user demand risk avoidance method based on improved density peak clustering.Firstly,a typical user daily load curve extraction method is presented,which uses the kernel density estimation idea to extract the user’s typical daily load curve.Then,the sample daily load curve is processed by the improved density peak load clustering algorithm,and the sample day user data is equally divided to obtain the sample daily electricity data density peak;finally,the sample data value is merged,and the initial cluster center iteration of the row is performed.Clustering and clustering were used to evaluate clustering results using ICS and DFSC evaluation indicators.The simulation experiment proves the superiority of the proposed clustering algorithm,and effectively clusters the user load curve to understand the user’s power consumption characteristics and achieve effective avoidance of the user’s demand uncertainty risk.The response evasion mechanism provides the basis for the user group load curve.Aiming at the risk of electricity price volatility,this paper proposes a market price risk avoidance method based on demand response.Firstly,the model of electricity purchase and sales of electricity sales companies is modeled;then the method of using user-side demand response resources to avoid risks is proposed,and each demand response strategy is formulated and modeled.Finally,the risk measurement method based on CVaR is introduced to evaluate its risk and build The electricity price risk avoidance function of the electricity sales company.The effectiveness of the method was verified by several experiments on the impact of the sales company’s revenue and the degree of market electricity price avoidance.It provides the necessary theoretical support for the construction of the risk aversion model later.Based on the above two methods of risk aversion and user satisfaction,a risk aversion model for sales companies that takes into account user satisfaction is designed.Firstly,the user’s electricity comfort satisfaction and user electricity cost satisfaction are modeled separately,and the user’s comprehensive satisfaction evaluation model based on multi-objective optimization is constructed.Then,based on the sales company’s maximum revenue and the user’s comprehensive satisfaction,the user satisfaction is considered.A two-sided multi-objective risk avoidance model is proposed.Finally,a bidirectional hybrid particle swarm optimization algorithm based on behavioral correction is proposed to solve the model interactively.The case study shows that the risk aversion model can effectively avoid risks,improve the profit of power sales companies,reduce energy consumption,improve user satisfaction,and achieve a win-win situation.