An Integrated Multi-Objective Optimization Algorithm for Parameter Estimation and Maximum Power Point Tracking in Photovoltaic Systems

Abstract

The Maximum Power Point Tracking (MPPT) algorithm subjected the PV parameters to changes under faulty and weather operations conditions during runtime, which influenced the results obtained. The aim of this research is to provide an interconnected algorithm for online optimization of PV parameters. The MPPT algorithm will dynamically adjust its operations, ensuring continual optimization in response to each update of PV parameters. We choose a custom block over other simulation techniques to allow parameter updating and provide more flexibility and customization options. This paper proposes a combined meta-heuristic algorithm based on multi-objective optimization for both parameter estimation and MPPT. The simulation results under different algorithms show the efficacy of this combination in online optimization and the capability of its implementation in the real-time optimization controller. The paper also discusses the results of simulations using different candidate algorithms. Finally, this paper recommends the adaptation of this approach for multiple problems that include parameter estimation at the first level and suggests the use of advanced algorithms and techniques for the sake of accelerating time processing.