Adaptive optimization of virtual synchronous generator based on fuzzy logic control and differential evolution

Abstract

Maintaining frequency stability in low inertia microgrids with high renewable energy source (RES) penetration is a major problem. To resolve this issue, the use of the virtual synchronous generator (VSG) was proposed in the literature. VSGs can provide damping and inertial response mimicking the operation of synchronous generators, hence the name. However, the damping and inertia coefficients of VSGs are typically fixed which limits the capabilities of VSG in stabilizing the frequency. Higher frequency oscillations may develop due to the fixed damping factor and virtual inertia constants. This paper proposes an optimization method that sets the VSG damping and inertia coefficients in an adaptive manner based on the fuzzy logic controller (FLC). Further, the differential evolution (DE) algorithm is used to solve the formulated multi-objective function to optimize the FLC gains. In this way, the damping and virtual coefficients are continuously and adaptively adjusted to provide optimal frequency stabilization. To verify the efficiency of the proposed optimization and control method, a comprehensive nonlinear simulation analysis was carried out using MATLAB/Simulink to compare the proposed method with the conventional VSG. The simulation was performed under multiple renewable penetration levels. The proposed method showed remarkable performance during disturbances and at varied RES penetration levels with 7.3% less frequency deviation and 46% less rate of change of frequency.

Keywords

• Differential evolution
• Fuzzy logic controller
• Low inertia grids
• Microgrids
• Virtual synchronous generator