Artificial Intelligence in Photovoltaic Technologies – Review of Prospects

Abstract

This article considered integration of Artificial Intelligence (AI) and Photovoltaic (PV) technology, with emphasis on integral effects towards optimizing electrical energy generation in seamless in existing grids. Focusses are AI's pivotal role in forecasting, troubleshooting, predictive maintenance, and overall system management. AI's precision enhances grid integration, schedules
energy efficiently, and mitigates power fluctuations, thereby promoting grid stability. It proves instrumental in the swift identification and resolution of potential malfunctions, streamlining maintenance processes, and reducing downtime for a more reliable PV system. The implementation of predictive maintenance introduces a proactive dimension, predicting component failures in advance to minimize disruptions and extend system lifespan. Optimal management, encompassing Maximum Power Point Tracking (MPPT) and battery storage optimization, utilizes AI algorithms to dynamically adjust operational parameters, maximizing energy generation and grid stability. Despite challenges such as data availability, computational cost, and algorithm interpretability, AI presents vast opportunities in the PV domain. Tailored AI solutions for specific PV systems promise heightened accuracy and effectiveness. Furthermore, edge computing and decentralization offer reduced latency, enhanced data privacy, and
decentralized decision-making. The seamless integration with other renewable energy sources facilitates coordinated grid management and maximizes overall renewable energy utilization.
Nevertheless, AI emerges as a transformative force propelling PV system towards heightened efficiency, reliability, and cost-effectiveness with a view to unlocking the full potential of solar energy for a sustainable future