Dynamic Bidding Strategy for Electricity Retailers Considering Multi-type Demand Response

As the new stakeholders in the distribution network, electricity retailers purchase electricity from wholesale market and sell it to users. In this process, they bear the double uncertainty of real-time market price and load demand. Firstly, the uncertainty of electricity retailers trading is modeled by stochastic programming, and the power purchase behavior of electricity retailers in multi-time scale market is analyzed. Two types of electricity sale contracts are proposed: fixed price and time-of-use (TOU) price. Secondly, two kinds of incentive demand responses (DR), interruptible load (IL) and transferable load (TL), are introduced to realize the dynamic bidding strategy of electricity retailers, and the trading risk is measured by conditional value at risk (CVaR). Moreover, the mixed integer nonlinear multi-objective optimization model is constructed to maximize the comprehensive profit of electricity retailers and user satisfaction. Finally, the model is linearized based on Big-M and other methods, and transformed into a single objective optimization problem by entropy weight method and dimensionless processing. The effectiveness of the model and method is verified by a practical example, which provides help for the operation of electricity retailers.