Genetic Algorithm optimisation of stand-alone Photovoltaic energy systems

A. Benatiallah, L. Kadi and B. Dakyo

International Journal of Global Energy Issues, 2009, vol. 31, issue 2, 157-168

Abstract: This article presents the methodology for calculation of the optimum size of a Photovoltaic (PV) system. Long-term data of PV radiation were used to calculate the average power generated by a PV generator for every hour of a typical day in a month. A load of a typical house in the south of Algeria (desert area) was used as a load demand of the system. For a given load and a mixed multiple criteria were used for programming problem, the types and sizes of PV modules generators was calculated based on the minimum cost of system. We investigated the Genetic Algorithm (GA) for optimally sizing a PV power system. We define that the objective function is the total cost where it is the sum of the initial cost, the operation cost and the maintenance cost. We determine an optimal configuration of PV generating systems where the total cost is more optimal using GA. A computer program has been developed to size system components to match the load of the site in the most cost. A cost of electricity, an overall system cost is also calculated for each configuration. The study was performed using a graphical user interface programmed in MATLAB.

Keywords: Algeria; cost function; fitness function; GAs; genetic algorithms; inverters; Lagrange methods; modelling; optimal configuration; photovoltaic energy; global PV energy systems; programming systems; optimum sizing; stand-alone; synchrony machine; PV radiation. (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=23892 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijgeni:v:31:y:2009:i:2:p:157-168

Access Statistics for this article

More articles in International Journal of Global Energy Issues from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().