Applications of Artificial Intelligence to Photovoltaic Systems: A Review

Abstract

This article analyzes the relationship between artificial intelligence (AI) and photovoltaic (PV) systems. Solar energy is one of the most important renewable energies, and the investment of businesses and governments is increasing every year. AI is used to solve the most important problems found in PV systems, such as the tracking of the Max Power Point of the PV modules, the forecasting of the energy produced by the PV system, the estimation of the parameters of the equivalent model of PV modules or the detection of faults found in PV modules or cells. AI techniques perform better than classical approaches, even though they have some limitations such as the amount of data and the high computation times needed for performing the training . Research is still being conducted in order to solve these problems and find techniques with better performance. This article analyzes the most relevant scientific works that use artificial intelligence to deal with the key PV problems by searching terms related with artificial intelligence and photovoltaic systems in the most important academic research databases. The number of publications shows that this field is of great interest to researchers. The findings also show that these kinds of algorithms really have helped to solve these issues or to improve the previous solutions in terms of efficiency or accuracy.

A Review on Machine Learning Applications for Solar Plants

“…The long-term contribution, including increased capacity of solar energy, depends on solving the remaining tasks of grids integration, high costs, and low efficiency, mainly through the research and development of a smart solar plant system based on integration of cutting-edge technologies, including DNN [ 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 ]. To attain the smart optimization and high efficiency of solar energy, the cloud, big data, ML, EC, IoT, quantum, and sensor technologies need to be adaptively combined and implemented as smart grid, home, and city applications.…”

Synthetic Dataset of Electroluminescence Images of Photovoltaic Cells by Deep Convolutional Generative Adversarial Networks

“…When applied to PV systems, different AI methods such as fuzzy logic, meta-heuristics, or neural networks have been used to solve problems [3]. The most important problems include [4] max power point tracking, output power forecasting, parameter estimation, and defect detection.…”

Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage

“…Photovoltaic (PV) energy is one of the most important and widely available renewable energies, and with the energy crisis and the need to protect the environment, investment in it by states and companies is increasing every year, especially in the area of artificial intelligence (AI) applications in PV systems [1][2][3]. PV systems are widely used in residential applications in Poland and Europe due to growing environmental concerns and the price of fossil fuels.…”

“…In the area of PV systems management, AI methods and techniques often perform better than previously used traditional approaches, and the high involvement of scientists and engineers has encouraged the finding of new solutions or improvement of previous ones, so that AI algorithms can improve the efficiency and accuracy of the solutions used. This is not altered by the limitations of AI, including the significant amounts of data and computational time required to learn solutions based on a data-driven approach (ML) [1]. ML is indeed a subset of AI.…”