DocumentCode :
2731499
Title :
Sizing grid-connected photovoltaic system using genetic algorithm
Author :
Sulaiman, Shahril Irwan ; Rahman, Titik Khawa Abdul ; Musirin, Ismail ; Shaari, Sulaiman
Author_Institution :
Fac. of Electr. Eng., Univ. Teknol. MARA, Shah Alam, Malaysia
fYear :
2011
fDate :
25-28 Sept. 2011
Firstpage :
505
Lastpage :
509
Abstract :
This paper presents an intelligent-based algorithm for sizing grid-connected photovoltaic (GCPV) system using Genetic Algorithm (GA). GA had been used to determine the optimal PV module and inverter from pre-developed PV module and inverter databases such that the expected technical performance of the design could be optimized. In addition, the technical sizing outputs such as the number of photovoltaic (PV) modules, PV array configuration and inverter-to-PV array sizing factor were computed. The GA had outperformed the Evolutionary Strategies (ES) during the sizing process in terms of producing better optimum results. Low error had also been produced by GA when compared to a benchmark sizing algorithm using iterative sizing approach.
Keywords :
genetic algorithms; invertors; iterative methods; photovoltaic power systems; power grids; power system interconnection; evolutionary strategy; genetic algorithm; grid-connected photovoltaic system; intelligent algorithm; inverter databases; inverter-to-PV array; iterative sizing; optimal PV module; photovoltaic array configuration; sizing factor; technical sizing outputs; Algorithm design and analysis; Arrays; Artificial intelligence; Genetic algorithms; Inverters; Photovoltaic systems; PV module; genetic algorithm (GA); grid-connected photovoltaic (GCPV); inverter; photovoltaic (PV);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications (ISIEA), 2011 IEEE Symposium on
Conference_Location :
Langkawi
Print_ISBN :
978-1-4577-1418-4
Type :
conf
DOI :
10.1109/ISIEA.2011.6108763
Filename :
6108763
Link To Document :
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