Stackelberg game based transactive pricing for optimal demand response in power distribution systems

Abstract

With the implementation of smart distribution technology, the real-time pricing scheme has emerged as a critical subject for energy management systems. In this paper, we propose a bilevel optimization model that computes a transactive price signal representing the impact of wholesale market locational marginal prices on retail customers’ demand response participation. At the upper level of the proposed model, the electricity utility company (EUC) determines the optimal energy procurement and transactive price signals for demand response aggregator (DRA). At the lower level, each DRA adjusts its electricity consumption profile using the transactive price signals. The adjusted DRA consumption profile is fed back to the upper level problem as the iteration continues. The interactions among DRAs are simulated as a non-cooperative game. The proposed model is transformed into a mixed-integer quadratically constrained programming through using the Karush-Kuhn-Tucker (KKT) conditions. The generalized disjunctive programming is introduced when linearizing the bilinear terms in KKT conditions by applying piecewise McCormick relaxation and big-M disjunctive constraints. The numerical results demonstrate the effectiveness of our model and the proposed solution method.