Modified Golden Jackal Optimization Assisted Adaptive Fuzzy PIDF Controller for Virtual Inertia Control of Micro Grid with Renewable Energy

Frequency regulation of low inertia symmetric micro grids with the incorporation asymmetric renewable sources such as solar and wind is a challenging task. Virtual Inertia Control (VIC) idea increasing grids’ by energy storage systems. In current study, an adaptive fuzzy PID structure derivative filter (AFPIDF) controller suggested for VIC grid sources. To optimize proposed controllers, modified Golden Jackal Optimization (mGJO) has been proposed, where variable Sine Cosine adopted Scaling Factor (SCaSF) employed to adjust Jackal’s location in course search process improve exploration exploitation capability original (GJO) algorithm. The performance mGJO algorithm verified equating it GJO, well Grey Wolf (GWO), Particle Swarm (PSO), Gravitational Search Algorithm (GSA), Teaching Learning Based (TLBO) Ant Lion Optimizer (ALO), considering various standard benchmark test functions. next stage, conventional FPIDF parameters are optimized using technique superiority over other optimization algorithms demonstrated. robustness also investigated under intermittent load disturbances, different levels RESs integration.