Optimization method of energy storage system based on improved VSG control algorithm

This paper presents a comprehensive analysis of a novel optimization method for energy storage systems under unbalanced load conditions, leveraging an enhanced control algorithm designed for Virtual Synchronous Generators (VSG). The primary aim of this method is to substantially improve the stability of the output voltage within power grids, addressing critical challenges in energy distribution. The methodology begins by establishing a detailed mathematical model for the photovoltaic energy storage system, utilizing the transient behavior of motors to predict and assess system dynamics effectively. A key innovation in this approach is the advanced phase-sequence control strategy that integrates a Dual-Second Order Generalized Integrator (DSOGI) for precise extraction of the positive and negative sequence elements of the three-phase grid voltage. At the core of this technique is the strategic use of negative-sequence virtual complex impedance, specifically designed to mitigate the voltage drop caused by negative-sequence currents stemming from unbalanced loads on the line impedance. This approach effectively eliminates double-frequency components in the grid and robustly prevents imbalances in the three-phase voltage load. To empirically validate the efficacy of the proposed optimization method, a detailed simulation model was developed using Matlab/Simulink software, which simulated the operation of the VSG system under unbalanced load conditions. The results from these simulations indicate that the implementation of this optimization method has led to a significant reduction in the degree of voltage imbalance during the steady-state process, from 2.7 % to 0.6 %. Furthermore, the peak value of voltage imbalance during the transient process was reduced from 3.2 % to 2.1 %. These notable improvements underscore the algorithm's effectiveness and highlight its considerable potential in enhancing voltage quality within microgrids for practical applications. Additionally, the deployment of this technology provides essential technical support for the stability and reliable operation of future power systems, particularly when addressing the challenges posed by the rapid integration of renewable energy sources and the modernization of electrical grids. This method represents a pivotal advancement in managing grid stability and improving power quality in an era of increasing reliance on diverse energy sources.