A voltage regulation strategy with state of charge management using battery energy storage optimized by a self-learning particle swarm optimization

Abstract

With the proliferation of photovoltaic penetration, present distribution networks are vulnerable to voltage deviations. Therefore, this study presents a voltage regulation strategy using battery energy storage (BES) with state of charge (SoC) management. The voltage regulation strategy was designed based on an adaptive droop characteristic to alleviate the voltage deviations considering the BES SoC constraints. The SoC management was designed to compensate the BES power for SoC restoration regarding its required restoring power and restriction coefficient characteristics. In addition, a self-learning particle swarm optimization (SLPSO) was utilized to determine optimal BES operation. A simulation study was conducted to verify the proposed strategy’s performance compared with that of a system without BES, a droop-based voltage regulation without SoC management, a droop-based voltage regulation with battery SoC holder, and a droop-based voltage regulation with constant SoC management. The simulation results indicate that the proposed strategy achieved superior performance: up to 12.09% compared with the existing strategies.