Day-Ahead Multi-Objective Microgrid Dispatch Optimization Based on Demand Side Management Via Particle Swarm Optimization

The rapid growth of electricity demands for recent years leads to many global concerns, including greenhouse, energy risk, and large size brownouts, which require modern energy management system to provide environmental-friendly power supply service with less cost and higher reliability. However, most of previous studies separately focus on improving prediction accuracy or reducing cost and emission of power supply solution by dispatch optimization. To exploit the benefits of microgrid system furthermore, this paper firstly proposes a comprehensive day-ahead multi-objective microgrid optimization framework that combines forecasting technology, demand side management (DSM) with economic and environmental dispatch (EED) together. Then, two versions of particle swarm optimization are implemented for obtaining load control plan from DSM model and power supply plan from EED model, respectively. Moreover, two different microgrids' applied scenarios are simulated with detailed sensitivities analysis on key parameters. Experiment results demonstrate effectiveness of the proposed framework, which can obtain load demands profile with better reliability, as well as power supply solution with less cost and lower emission. Meanwhile, beneficial decision supports are provided to manager for their references.