Abstract
For lifelong and reliable operation, advanced solar photovoltaic (PV) equipment is designed to minimize the faults. Irrespectively, the panel degradation makes the fault inevitable. Thus, the quick detection and classification of panel degradation is pivotal. Among various problems that promote panel degradation, hot spots and micro-cracks are the prominent reliability problems which affect the PV performance. When these types of faults occur in a solar cell, the panel gets heated up and it reduces the power generation hence its efficiency considerably. In this study, the effect of the hotspot is studied and a comparative fault detection method is proposed to detect different PV modules affected by micro-cracks and hotspots. The classification process is accomplished by utilizing Feed Forward Back Propagation Neural Network technique and Support Vector Machine (SVM) techniques. The investigation of both the techniques permits a complete analysis of choosing an effective technique in terms of accuracy outcome. Six input parameters like percentage of power loss (PPL), Open-circuit voltage (VOC), Short circuit current (ISC), Irradiance (IRR), Panel temperature and Internal impedance (Z) are accounted to detect the faults. Experimental investigation and simulations using MATLAB are carried out to detect five categories of faulty and healthy panels. Both methods exhibited a promising result with an average accuracy of 87% for feed-forward back propagation neural network and 99% SVM technique which exposes the potential of this proposed technique.
Highlights
In photovoltaic (PV) panels, hot-spotting is a solidity problem
AND DISCUSSIONS a few highlights of the proposed fault detection system are compared with existing literature (Dhimish and Badran, 2019) using fuzzy systems
On the other side, the Support Vector Machine (SVM) method has achieved an average accuracy of 99% which is a state-of-the-art approach that can perform well at any condition than the conventional approaches
Summary
In photovoltaic (PV) panels, hot-spotting is a solidity problem. It can be characterized when the adjacent solar cells heat up to a remarkable level and decrease the optimum power generation of the PV panel (Dhimish et al, 2018a). PV degradation is enhanced and a high probability for the occurrence of permanent damage to PV panels prevails (Simon and Meyer, 2010) Another solidity problem that affects the PV panels is discontinuation [6], Maximum Power Point Tracking (MPPT) faults (Rakhshan et al, 2018; Dhimish et al, 2019; Pendem et al, 2020; Manoharan et al, 2020; Pradhan et al, 2020), microcracks (Dimish et al, 2017) and variations in the wind speed and humidity (Stoichkov et al, 2018). The above-mentioned problems affect the performance of output power in a PV panel but, the parameters such as temperature coefficient will decrease its annual energy production. These studies only state the effect of hot-spotting in PV panels but
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
