Enhancing Power Quality and Mitigating Power Oscillations in Commercial and Industrial Systems through an Integrated Approach

Abstract

The integration and operational performance of Distributed Energy Resources (DERs) like solar photovoltaic (PV), wind energy systems, and battery energy storage systems (BESS) in commercial and industrial settings are having an increasing impact on grid power quality. Voltage stability, power factor, and overall power quality all improve when DERs efficiently produce and deliver active power to the grid. However, power oscillations that impair system performance can be introduced by the intermittent nature of renewable energy as well as the presence of nonlinear and unbalanced loads. In order to address these issues, the hybrid control framework described in this paper combines a novel control strategy for multifunctional grid-tied inverters based on the Conservative Power Theory (CPT) with an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller for DER coordination. While the CPT-based control directly extracts and compensates oscillatory power terms in the ABC frame, the ANFIS controller allows adaptive and intelligent regulation of active power injection from solar, wind, and battery DERs. A three-phase inverter with an LCL filter is used to effectively reduce power oscillations and provide load compensation when working with linear, nonlinear, and unbalanced loads, such as a three-phase induction motor. Verified by MATLAB/Simulink simulation results, the suggested approach improves power quality, lowers Total Harmonic Distortion (THD), stabilizes motor operation, and permits reliable DER-grid interaction. The results demonstrate how the suggested system could improve grid power quality in commercial and industrial power networks.