Performance Evaluation of Solar PV System for Power Generation in Surface Mines

Abstract

This thesis presents a study of Solar Photo-Voltaic (PV) energy system from the environmental impact analysis and its effects point of view and the enhancement factors affecting the Solar Photovoltaic (PV) module by the tilt angles variation on power output of MPPT and dust accumulation on solar PV panel. For the energy utilization in mining industry this thesis proposes a hybrid technique to recover the efficiency of solar photovoltaic (PV) energy system from the environmental impacts and the approach to improve the performance of photovoltaic (PV) system and track the maximum power from the system. For this, the proposed Hybrid techniques followed is the combination of sparrow search algorithm (SSA) and gradient boosting decision tree; thus, it is named as SSA-GBDT method and the combination of Tunicate Swarm Algorithm (TSA) and Radial Basis Function Neural Network (RBFNN), hence it is called TSA-RBFNN. The purpose of the proposed techniques is to improve the efficiency of solar PV energy system and maximization of power removal from PV arrays and to “achieve the best output from solar system by tilt angles variations and environmental effects, like dust accumulation, water drops, partial shading, and maximum power point tracking (MPPT) of the solar PV panel. Here, tilt angle and orientation angles are important factor for obtaining the maximal power of the photovoltaic system with consequently the power fed to load in the PV system. The voltage, current, and PV system power are used to analyze the effect of any particle size and any weight of dust for the performance of PV modules. An Experimental study and a specific investigation on dust deposition effect on the solar photovoltaic (PV) panel, its power loss and overall efficiency of the solar panel are made. The Scanning Electron Microscope (SEM) analysis is carried out for the collected dust samples from the mines, and obtained images are also analyzed. A specific investigation on dust samples like Iron ore, Coal, Limestone, Sandstone of different weights, and three different irradiation levels of 500,700,900W/m2 is done and the following data collected. In this study, measuring of voltage current, power in the solar photovoltaic (PV) panel is also done. According to the accumulation of dust particles on the solar panel the minimum power of the solar panel is observed for deposition of coal dust on the solar PV panel and the maximum power of the solar PV panel is observed for deposition of iron ore dust on the solar PV module. The performance of PV under normal condition, dust accumulation condition, water drops condition and partial shading conditions are the considered cases. In these cases, photovoltaic irradiance and temperature, PV current, voltage and generated power, active and reactive power, grid current and voltage, inverter power are also evaluated. In addition, the determination of cleaning frequency is also developed for dirty PV modules depending upon the dust deposition velocity, then the correlation among deposited dust density including power performance of photovoltaic module. Then, the proposed techniques are implemented on the MATLAB/Simulink platform and the performance is compared with existing techniques. Furthermore, optimum solutions for proposed technique, the current, voltage, power are also analyzed.