Risk Optimization of Electricity Retailer’s Revenue Considering User Utility

After the electric selling market opened, various types of electricity retail companies will face fierce competition. Electricity retail companies are in urgent need of revenue and risk optimization. This paper uses the Conditional Value-at-Risk method to establish a power sales decision model based on maximizing user utility. This model provides users with three kinds of hedging contracts and introduces demand price elasticity functions. Finally, according to the proportion of users participating in demand response, an improved harmony search algorithm is used to analyze the changed load and electricity price. Through simulation comparison analysis, the results show that electricity retailers can guide users to respond to demand through value-added services, which can not only improve user utility, but also effectively reduce the degree of fluctuation of demand-side load and reduce the revenue risk of electricity retailers.