A Hybrid Honey Badger-Anfis Approach For Statcom-Based Reactive Power Compensation In Microgrids

Abstract

Maintaining voltage stability and power quality in microgrids powered by hybrid renewable energy sources (HRES) continues to pose a great challenge due to the intermittency and finger-like action of solar/wind energies. This paper proposed a hybrid control structure to optimize a Static Synchronous Compensator (STATCOM) for reactive power compensation using an Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Honey Badger Algorithm (HBA). The hybrid HBA-ANFIS controller has the capacity to adjust the nonlinear parameters of ANFIS while improving the STATCOM's dynamic response to enable faster voltage regulation at the point of common coupling (PCC). MATLAB/Simulink was used to develop an extensive simulation model of a microgrid including solar PV, a wind-based doubly-fed induction generator (DFIG), and a diesel generator to test the proposed method. Performance comparisons were made with standard PI based controllers and other optimization-based adaptive controllers including PID-GA, PI-ACO, and MPA-PIDA based controllers to measure settling time, voltage overshoot, as well as overall efficiency of the system. The results showed that the HBA-ANFIS controller had the best performance with an overall efficiency of 99.1% and a settling time of 0.4671 s with a voltage overshoot of only 11% meaning it is viable for voltage regulation in intelligent microgrid applications of the future.