Evaluation of the Use of Artificial Neural Networks in Solar Energy

Abstract

Artificial neural network (ANN) is initially used to forecast the solar insolation level and followed by the particle swarm optimisation (PSO) to optimise the power generation of the PV system based on the solar insolation level, cell temperature, efficiency of PV panel, and output voltage requirements. Genetic algorithm is a general-purpose optimization algorithm that is distinguished from conventional optimization techniques by the use of concepts of population genetics to guide the optimization search. Tabu search algorithm is a conceptually simple and an elegant iterative technique for finding good solutions to optimization problems. Simulated annealing algorithms appeared as a promising heuristic algorithm for handling the combinatorial optimization problems. Fuzzy logic algorithms set theory can be considered as a generation of the classical set theory. The artificial neural network (ANN)-based solar insolation forecast has shown satisfactory results with minimal error, and the generated PV power can be optimised significantly with the aids of the PSO algorithm.