Optimal Control Strategy for Stability Performance Improvement of Hybrid Power Systems With Electric Vehicle Integration

ABSTRACT The present article explores the frequency control of hybrid power systems integrated with electric vehicles (EVs). The hybrid power system is a complicated nonlinear entity that highlights the significant issue of dynamic control owing to inadequate damping under fluctuating load conditions. In this respect, the present article explores the application of fuzzy logic based advanced controller for power system operations. The proposed controller's efficacy is demonstrated by a comparison of outcomes with other currently established controllers. We compare the fuzzy logic approach against an evolutionary algorithm namely COVID‐19 technique. The results show that fuzzy logic works much better than the COVID‐19 technique at reducing frequency variations. This is shown by the objective function values and demerit index calculations. The settling time of a fuzzy logic‐optimized‐PID (FPID) controller is more than 10 percent faster than that of a COVID‐19‐optimized PID controller. Further, fuzzy logic is used to optimize the MSPID controller. We found that the MSFPID has a 13.8 percent improvement in settling time with respect to FPID. We also conducted an investigation into the impact of EV integration on system stability. Results indicate that system dynamics improve with the increased presence of EVs. A new investigation with EVs for continuous load demand showed fast response from EVs against each load change. Furthermore, the proposed secondary controller exhibits robustness against practical system variations, hence confirming the healthiness of optimized gains. Finally, we test the secondary controller in a more complex dual‐area hybrid power system, confirming its effectiveness.