Power quality improvement of grid interfaced solar PV system using an improved least mean square‐based unified control technique

Abstract

SummaryThis article presents an improved least mean square (LMS) algorithm‐based control approach for a three‐phase grid interfaced solar photovoltaic (GISPV) system for smart building applications. The SPV is primarily utilized to supply household loads, and the absence or intermittency of SPV is curbed by utilizing power from the grid. The majority of household loads are nonlinear loads that affect the grid power quality (PQ). However, the effects of both linear and nonlinear loads on grid PQ have been analyzed in this article. This article proposes a Gaussian Kernel function‐based normalized LMS (GKNLMS) algorithm to calculate the active peak weight component of the load current, thereby utilizing it to obtain a sinusoidal reference current. Considering a higher step size and utilizing the Gaussian Kernel function for reduced mean square error (MSE) improves both the convergence rate and accuracy of estimation in the conventional LMS. The proposed control technique effectively addresses system anomalies caused by dynamic solar irradiance, load variation, and unbalanced loading conditions. Furthermore, the system response with the GKNLMS algorithm is assessed in MATLAB/Simulink and validated by developing a laboratory setup of the system for experimentation.