Demand Response Based Optimal Microgrid Scheduling Problem Using A Multi-swarm Sine Cosine Algorithm

Demand response (DR) refers to the customers' active reaction with respect to the changes of market pricing or incentive policies.DR plays an important role in improving network reliability, minimizing operational cost and increasing end users' benefits.Hence, the integration of DR in the microgrid (MG) management is gaining increasing popularity nowadays.This paper proposes a day-ahead MG scheduling framework in conjunction with DR and investigates the impact of DR in optimizing load profile and reducing overall power generation costs.A linear responsive model considering time of use (TOU) price and incentive is developed to model the active reaction of customers' consumption behaviors.Thereafter, a novel multi-swarm sine cosine algorithm (MSCA) is proposed to optimize the total power generation costs in the framework.In the proposed MSCA, several sub-swarms search for better solutions simultaneously which is beneficial for improving the population diversity.A cooperative learning scheme is developed to realize knowledge dissemination in the population and a competitive substitution strategy is proposed to prevent local optima stagnation.The simulation results obtained by the proposed MSCA are compared with other meta-heuristic algorithms to show its effectiveness in reducing overall generation costs.The outcomes with and without DR suggest that the DR program can effectively reduce the total generation costs and improve the stability of the MG network.