A comparative study based on the Genetic Algorithm (GA) method for the optimal sizing of the standalone photovoltaic system in the Ngoundiane site

Sadio, A. and Mbodji, S. and Fall, I. and Sow, P. L. T. (2019) A comparative study based on the Genetic Algorithm (GA) method for the optimal sizing of the standalone photovoltaic system in the Ngoundiane site. EAI Endorsed Transactions on Energy Web, 6 (21): e1. ISSN 2032-944X

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Abstract

We study a sizing method using Artificial Intelligence Techniques (AI) to find the optimal sizes of a standalone photovoltaic system in Ngoundiane, Senegal. The sizing of the PV system is considered here as a mono-objective problem and the Total Life Cycle Cost (TLCC) is the « Objective » function to minimize. Based on some constraints and after 10 simulations, the optimisation gives, as a result, an optimal value of TLCC corresponding to the combination of 225750 WC/8100 Ah. This result show that the method using Genetic Algorithm (GA) increases considerably the photovoltaic capacity compared to the intuitive and numerical methods used in our previous works. The GA method better covers the load demand, with more long time, when compared with those obtained with numerical method. These results confirm that this method is effective and reliable because it allows the design of a PV system that satisfies the load demand of the Ngoundiane site with a lower cost.

Item Type: Article
Uncontrolled Keywords: Standalone PV System, Optimization, Genetic Algorithm, «Objective» function
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor II.
Date Deposited: 21 Sep 2020 13:26
Last Modified: 21 Sep 2020 13:26
URI: https://eprints.eudl.eu/id/eprint/499

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