Optimal scheduling of demand response contracts for a strategic aggregator in wholesale electricity market

Demand response, as a program for managing electricity demand, serves as an important source of flexibility in the use of electrical energy. Because the demand response contribution from individual customers is relatively small, they cannot participate directly in market competition. This is where the demand response aggregator (DRA) comes in, acting as an important intermediary between consumers and the system operator in electricity markets. This paper proposes a new model designed to determine the participation strategy of the DRA, positioning it as a price maker in the electricity market. The proposed framework is structured as a bi-level optimization problem: the upper level aims to maximize the aggregator’s profit from participating in the day-ahead market, while the lower level addresses the market clearing problem. Two types of contracts—load curtailment (LC) and load shifting (LS)—are considered strategies for demand response. The bi-level optimization problem is reformulated into a single-level mathematical program with equilibrium constraints (MPEC) by applying the Karush-Kuhn-Tucker (KKT) conditions. It is then transformed into a mixed-integer linear programming (MILP) problem using the duality theorem. To test the model, simulations were conducted using both a 4-bus test system and the IEEE Reliability Test System (RTS). The results show that, while transmission network limitations can reduce the DRA’s profit by 25.63%, the aggregator can adapt its strategy to continue participating in the market successfully and maintain profitability.