Mitigate power quality issues in PV solar inverter using hybrid optimized light GBM-based controller

Abstract

In the digital era, power systems are continuously implementing positive modifications on both the source and load sides. Further, power electronics interfaces are used to integrate dispersed generators, unconventional/nonlinear loads, charging stations, and so on. Consequently, frequent power quality disturbances appear in the system that are to be mitigated at the earliest to sustain the performance. Hence, this research proposes a novel intelligent power quality detection technique to identify and categorize PQ events, as mitigation requires detection. The proposed hybrid beetle formica optimized light GBM (HBFO-light GBM) offers a versatile solution by maintaining voltage control in power systems during critical operational scenarios to maintain power quality. The research at its core seeks to develop an advanced solar PV system model with a smart STATCOM, focusing on the effective preservation of energy within battery storage systems. The integration of ant colony and beetle swarm algorithms serves as a novel hybrid beetle formica optimization (HBFO) for system optimization, specifically focusing on stabilizing the output power of the shunt voltage converter within the PV system. This optimization enhances the classifier’s ability to effectively stabilize the output power, addressing potential fluctuations and biases in the system. The recorded values for various parameters in the system are as follows: the attained PV voltage, Q grid, Q inv, Q load, Vpcc, Pgrid, Pinv, Pload, PV current, and PV power are 561.49 V, 418.59 VAR, 418.59 VAR, 418.59 VAR, 176.34 V, 82.7042 W, 166.95 W, 82.70 W, 404.48 A and 193.012 KW, respectively.