Optimal Robust Unit Commitment of Microgrid using Hybrid Particle Swarm Optimization with Sine Cosine Acceleration Coefficients

This paper introduces a Hybrid Particle Swarm Optimization with Sine Cosine Acceleration Coefficients (H-PSO-SCAC) for solving the Unit Commitment (UC) problem of grid connected Microgrid (MG). The optimal set point of MG's generation units is determined for a Day Ahead (DA) power market to supply the required demand. The studied MG consists of one Wind Turbine (WT) generator, one Photovoltaic (PV) panel and three Diesel Generators (DGs). The new algorithm is employed to minimize the fuel cost of DGs and the transaction costs of transferable power trade whilst taking into consideration load balance constraint and MG's generation units constraints. The performance of the new H-PSO-SCAC is examined by comparing with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The effectiveness of these methods is analyzed by using different criteria of the objective function. MATLAB environment is used to code H-PSO-SCAC, PSO, GA, and the system under study. The simulation results prove the robustness of the proposed method and approve its potential to get closer to the global optimum solution.