Design and Simulation of Grid-Connected Photovoltaic System’s Performance Analysis with Optimal Control of Maximum Power Point Tracking Based on Artificial Intelligence

Abstract

The research presented in this paper is part of a more significant effort to improve the dynamic and static performance of power generation systems using solar panels under specific climatic conditions. The solar panel can produce the greatest power only at the specified voltage and electric current levels. Environmental variables, such as random atmospheric oscillations, have a significant effect on the performance of a solar system connected to the network. Irradiation and ambient temperature are the two inputs to a PV (photovoltaic) system. Because solar radiation varies in nature, the PV system efficiency is low. To improve the efficiency of a solar PV system, several maximum power point tracking (MPPT) approaches are used. The purpose of this paper is to improve the performance of DC/DC chopper controllers and PV inverters in the face of abrupt climate change. To that end, the primary goal of this paper is to compare the following maximum power point search (MPPT) algorithms: the incremental conductance (IC) algorithm, the fuzzy logic (FL) algorithm, VSI controller, and the particle swarm optimization (PSO) strategy. These algorithms were evaluated in terms of efficiency, stability, and speed. A 100 kW PV system is design using MATLAB software 2021a version.

Modeling and simulation of PV system with three phase inverter along PV, IV curves using MATLAB/Simulink

“…Peak sun hours is the average number of hours of sunlight per day at the installation location. System efficiency is overall efficiency of the PV system, accounting for losses due to factors like module efficiency, inverter efficiency, shading, soiling, and temperature [6].…”

“…𝑃𝑉 𝐴𝑟𝑟𝑎𝑦 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑘𝑊𝑝) ×𝐼𝑛𝑣𝑒𝑟𝑡𝑒𝑟 𝑂𝑣𝑒𝑟𝑠𝑖𝑧𝑖𝑛𝑔 𝐹𝑎𝑐𝑡𝑜𝑟 𝐼𝑛𝑣𝑒𝑟𝑡𝑒𝑟 𝐸𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 (6) 𝐴𝑛𝑛𝑢𝑎𝑙 𝑒𝑛𝑒𝑟𝑔𝑦 𝑦𝑖𝑒𝑙𝑑 (𝑘𝑊ℎ) = 𝑃𝑉 𝐴𝑟𝑟𝑎𝑦 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑘𝑊𝑝) × 𝐴𝑛𝑛𝑢𝑎𝑙 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 𝑅𝑎𝑡𝑖𝑜 (𝐴𝑃𝑅) × 𝐴𝑛𝑛𝑢𝑎𝑙 𝑆𝑜𝑙𝑎𝑟 𝑅𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 (𝑘𝑊ℎ/𝑚²)…”

Design optimization of irregularity RC structure based on ANN-PSO

“…On the other hand, the hybridization of PSO with ANN improves performance and yields promising results for solving complex processes and engineering problems [ 60 , 61 ]. In addition, in some studies, compared to the GA algorithm, PSO has fast convergence and a lower number of computational formulations [ 62 , 63 ]. The PSO algorithm demonstrated that it is an efficient method with the combination of ANN for modeling complex problems in various scientific fields [ 64 , 65 ].…”

Solving Multispecies Lotka–Volterra Equations by the Daftardar-Gejji and Jafari Method

“…Tese kinds of issues often come up in the actual world when algebra, geometry, and calculus are applied, and they also include continuous variables. Tese issues arise in all areas of study, including the scientifc and social sciences, engineering, health care, and business [1][2][3][4][5][6][7][8][9]. Numerical analysis introduced realistic mathematical models which have become more prevalent in science and engineering over the last 50 years as a result of the expansion in the power and accessibility of digital computers.…”