Metaheuristic Optimization Solving Demand Response Contract Markets with Network Validation

This article evaluates the performance of different metaheuristics (evolutionary algorithms) solving a cost mini-mization problem in demand response contract markets. The problem considers a contract market in which a distribution system operator (DSO) requests flexibility from aggregators with DR capabilities. We include a network validation approach in the evaluation of solutions, i.e., the DSO determines losses and voltage limit violations depending on the location of aggregators in the network. The validation of the network increases the complexity of the objective function since new network constraints are included in the formulation. Therefore, we advocate the use of metaheuristic optimization and a simulation procedure to overcome this issue. We compare different evolutionary algorithms, including the well-known differential evolution and other two more recent algorithms, the vortex search and the hybrid-adaptive differential evolution with decay function. Results demonstrate the effectiveness of these approaches in solving the proposed complex model under a realistic case study.