Sizing of photovoltaic systems : a review

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.

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