Integrated Optimization of Demand-Side Management and Battery Storage in a Microgrid for Cost-Effective and Reliable Operation

This paper proposes an integrated scheduling framework for demand-side management (DSM) and battery energy storage systems (BESS) in renewable energy-integrated microgrids to achieve cost-effective and reliable operation. A novel water wave optimization (WWO) algorithm is developed to minimize total operating cost while ensuring load satisfaction, operational constraints, and renewable variability. The optimization model simultaneously determines the optimal dispatch of DSM, BESS, grid power, and diesel generator (DG), while maintaining strict hourly power balance and zero energy not supplied (ENS). The WWO algorithm emulates the dynamic behavior of ocean waves—propagation, refraction, and breaking—to navigate complex solution spaces with rapid convergence. Simulation results over a 24-hour horizon demonstrate that the WWO-based strategy achieves superior performance compared to a genetic algorithm (GA), a non-dominated sorting genetic algorithm (NSGA-II), and a particle swarm optimization (PSO) algorithm, with a 25.2% cost reduction over the GA and convergence within 83 iterations. The results validate the potential of DSM-BESS coordination and metaheuristic optimization for efficient, reliable, and sustainable microgrid operations.