Optimal Dispatch of Medium-Voltage Microgrid Using an Adaptive PSO Algorithm

Abstract

This paper proposes an improved particle swarm optimization (PSO) algorithm with adaptive weight and acceleration coefficients (AWCPSO) for solving the economic, environmental and health dispatch model of a micro grid (MG). The model considers the real-time characteristics of distributed energy resources (DER) and load fluctuations, as well as line loss, real-time electricity prices of the main grid and the environmental impact of pollution emissions. The weight and acceleration coefficients are updated adaptively by using an evolution speed and aggregation degree based on the objective function. By using the adaptation algorithm, the active powers of the DER units in a medium-voltage MG benchmark are optimized to have faster convergence speeds and to avoid being trapped in a local optimal solution. The superiority of the improved AWCPSO algorithm and the validity of the power flow strategy it develops for a medium-voltage micro grid are demonstrated in simulations by comparing model results against the results from three other PSO algorithms.