A Review of Solar Power Control Using AI

A Review of Solar Power Control Using AI

Author Name : Shashikant Bhardwaj, Manish Shrivastava

DOI: https://doi.org/10.56025/IJARESM.2023.11423802

ABSTRACT

Performance and management of renewable energy sources may be better modelled, analysed, and predicted with the use of artificial intelligence (AI) methods. To model, control, or anticipate the performance of energy systems, engineers must use complex algorithms that need differential equations, lots of computing power, and lots of time. Artificial intelligence methods may discover the important or wind data, are required for the design, control, and operation of solar energy systems. Such long-term measures are either not available for many of the areas of interest or, if they are, they have a variety of drawbacks. Artificial intelligence (AI) approaches stand out as a promising option for solving these issues. Primarily focusing on neural networks, fuzzy logic, and evolutionary algorithms, this chapter presents an introduction of popular AI approaches utilised in solar energy. This chapter provides an overview of how artificial intelligence may be used to solar power. Applications such as solar radiation forecast and modelling, solar photovoltaic (PV) system sizing, performance, and control, and other related topics are explored in detail, with an emphasis on solutions using an AI approach.

Keywords-Machine learning; MPPT; AI; fuzzy logic control; ANN; GA; swarm intelligence; (ML).