Research on real-time pricing strategy for load serving entity based on simultaneous perturbation stochastic approximation

As one of the main participant in the electricity market, load serving entities (LSE) purchase electricity in the wholesale market, and provide different types of electricity package to users in the retail market. LSE’s profit mainly comes from the difference between the cost of purchasing electricity and the benefit of selling electricity. To reduce the cost, LSE can optimize electricity consumption characteristics of various types of users through real-time price adjustment, which can help to improve the shape of electricity purchase curve and implement demand side response. In this paper, a real-time pricing strategy based on synchronous perturbation stochastic approximation algorithm (SPSA) is proposed. This method considers the difference between diverse users synthetically. Depending on the historical electricity consumption and historical price data, the user side response function is constructed, and the real-time electricity price is formulated with the objective of minimizing load curve’s peak-valley difference. Finally, the effectiveness and advantages of the proposed method are verified by comparing the load curve and the power purchase cost before and after the price adjustment.