Optimal Model Predictive Control for Virtual Inertia Control of Autonomous Microgrids

For the time being, renewable energy source (RES) penetration has significantly increased in power networks, particularly microgrids. The overall system inertia is dramatically decreased by replacing traditional synchronous machines with RES. This negatively affects microgrid dynamics under uncertainties, lowering frequency stability, specifically islanded mode of operation. Therefore, this work aims to enhance resilience using virtual control concept. Additionally, optimal model predictive (MPC) employed inertial model. optimum design MPC attained an optimization algorithm, African Vultures Optimization Algorithm (AVOA). To certify efficacy proposed controller, AVOA-based compared a conventional proportional–integral (PI) controller that optimally designed various techniques. actual data RES utilized, and random load pattern applied achieve practical simulation outcomes. paradigm contains battery storage (BES) units for enhancing transient stability. findings show effectiveness improving resilience. Furthermore, results secure role BES responses domain simulations. outcomes are obtained MATLAB software.