Frequency Regulation of Microgrid with Renewable Sources Using Intelligent Adaptive Virtual Inertia Control Approach

Abstract

Frequency control of small inertia microgrids (MGs) with amalgamation of renewable energies like wind and solar is a difficult job. Virtual inertia control (VIC) scheme is the concept of enhancing the MGs inertia employing storage elements. In the present study, an optimized fuzzy adaptive virtual inertia control strategy has been proposed for adaptive allocation of virtual inertia constant. To tune the suggested controllers, an improved golden jackal optimization (i-GJO) is projected in which priority is given to the better jackal’s during the search process, and also sine cosine adopted scaling factor is used to modify the jackal’s position throughout search process. The effectiveness of i-GJO method is evaluated by comparing the results with golden jackal optimization (GJO) and other similar recently proposed optimization algorithms. Then, proportional-integral-derivative controllers are tuned in VIC environment with fixed virtual inertia constant (KVT ) using proposed i-GJO technique, and the superiority of i-GJO over genetic algorithm, particle swarm optimization, and GJO is demonstrated. Finally, fuzzy based controller with constant KVT as well as fuzzy adaptive KVT has been designed using the proposed i-GJO technique. The sensitivity of the controller is also examined under irregular load changes and various rates of RES amalgamation.