Demand-side management plays a critical role in the secure and efficient operation of smart grids. Traditional real-time pricing generally takes social welfare maximization as the only objective, while ignoring the benefit balance among electricity suppliers, grid company and users. This will lead to uneven benefit distribution among stakeholders and impair the long-term stable operation of power systems. To solve this problem, a bilevel real-time pricing strategy based on tripartite welfare equilibrium is proposed in this paper. The upper-level model minimizes the welfare differences among electricity suppliers, grid company and users to ensure fair benefit allocation, and the lower-level model maximizes the total social welfare so as to guarantee the economic efficiency of the system. The model adopts different utility functions for residential and industrial users to describe user heterogeneity. By using the Karush–Kuhn–Tucker conditions, the original bilevel model is transformed into a single-level optimization problem with complementarity constraints. The CHKS smoothing function and pseudo-Huber function are introduced to deal with complementarity constraints and absolute-value objective functions respectively. Combined with the central difference method, a modified rolling penalty function algorithm is developed for numerical solution. The 24 h simulation results show that the prices of four time periods converge steadily to equilibrium values as iterations proceed. Compared with the total social welfare maximization model, the proposed bilevel model effectively reduces the peak-to-average load ratio. It reduces the welfare disparities among the three stakeholders while maintaining the total social welfare at a stable level. Furthermore, it still maintains excellent applicability and robustness when the user scale is expanded.
Jia et al. (Mon,) studied this question.
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