Sizing of photovoltaic systems: a review

Abstract

Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming popular more and more nowadays. AI techniques have the following features: can learn from examples; are fault tolerant in the sense that they are able to handle noise and incomplete data; are able to deal with non-linear problems; and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a myriad of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI have been used and applied in different sectors, such as engineering, economic, medicine, military, marine, etc. They have also been applied for modelling, identification, optimization, prediction, forecasting, and control of complex systems. The main objective of this paper is to present an overview of the alternative approach and AI techniques for sizing of photovoltaic (PV) systems: stand-alone PV, grid-connected PV system, PV-wind hybrid system, etc). Published literature works presented in this paper show the potential of AI as a design tool in the optimal sizing of PV systems. Additionally the advantage of using an AIbased sizing of PV systems is that it provides good optimisation, especially in isolated areas, where the weather data are not always available.