Adaptive grid-forming strategy for a photovoltaic storage system based on edge transfer PSO algorithm

In existing grid-forming control schemes for photovoltaic storage systems, fixed-parameter strategies provide a certain level of active frequency support but often result in power overshoot and prolonged response times during significant disturbances. Additionally, the manual selection of parameters is complex and labor-intensive. To overcome these challenges, this study proposes a frequency support strategy based on Particle Swarm Optimization (PSO). Initially, a stability analysis of the proposed system determines the range of values for the inertia coefficient. An adaptive margin transition algorithm with adjustable inertia weight and radius regulation coefficient proactively sets this coefficient for steady-state operation. Subsequently, this study explores the transient power-frequency characteristics under external disturbances and analyzes the relationship between these characteristics and the grid-forming control parameters, using the calculated inertia coefficient as the baseline for control settings. An adaptive strategy for adjusting inertia and damping coefficients is proposed to enhance transient performance. Finally, simulations in Matlab/Simulink confirm that this strategy effectively mitigates frequency fluctuations, improves power overshoot, reduces response times, and lessens labor demands, showing significant potential for engineering applications.