Contribution for optimal sizing of grid-connected PV-systems using PSO

Aris Kornelakis and Yannis Marinakis

Renewable Energy, 2010, vol. 35, issue 6, 1333-1341

Abstract: Particle Swarm Optimization (PSO) is an optimization algorithm considered to be highly efficient for the solution of complicated problems. This paper presents the application of this method for the design optimization of photovoltaic grid-connected systems (PVGCSs). The purpose of the proposed methodology is to locate the optimal number of system devices and the optimal values of the PV module installation details, such that the total net economic benefit achieved during the system operational lifetime period is maximized. The optimization's decision variables are the optimal number of the PV modules, the PV modules optimal tilt angle, the optimal placement of the PV modules within the available installation area and the optimal distribution of the PV modules among the DC/AC converters. The objective function of the proposed optimization process is the lifetime system's total net profit which is calculated according to the method of the Net Present Value (NPV). The methodology's resulting system structures are economically evaluated through the methods of the discounted payback time and the Internal Rate of Return (IRR). The PSO algorithm is compared to the application of Genetic Algorithms (GAs) in terms of efficiency for the current problem.

Keywords: Photovoltaic systems; Grid-connected; Sizing; Particle swarm optimization (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (23)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:35:y:2010:i:6:p:1333-1341

DOI: 10.1016/j.renene.2009.10.014

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