Optimal sizing of a grid integrated solar photovoltaic system. Issue 1 (1st January 2014)

• Record Type: Journal Article
• Authors: Khare, Anula; Rangnekar, Saroj
• Is Part Of: IET renewable power generation. Volume 8:Issue 1(2014)
• Page Start: 67
• Page End: 75
• Publication Date: 2014-01-01
• Subjects: maintenance engineering -- particle swarm optimisation -- photovoltaic power systems -- power grids; empirical relations -- MATLAB platform -- particle swarm optimisation algorithm -- multivariable problem -- nonlinear problem -- sizing optimisation -- maintenance -- cost function -- grid‐integrated SPV system -- optimal sizing -- SPV system -- solar photovoltaic system -- optimal sizing methodology -- grid integrated solar photovoltaic system; Renewable energy sources -- Periodicals; 333.79405
• DOI: 10.1049/iet-rpg.2012.0382
• Languages: English
• ISSNs: 1752-1416

Abstract

Abstract : This study proposes an optimal sizing methodology for a solar photovoltaic (SPV) system considering lifetime cost requirements. The aim of the design is optimal sizing of SPV system, which is obtained by calculating SPV system output power at certain location, taking into account the calculated optimal number of SPV modules, optimal number of inverters, optimal tilt angle, for a given dimension of land. This design is aimed for minimising the annual cost of grid‐integrated SPV system over its life or years of operation. The cost function takes into account the capital cost of installation, operation and maintenance, for each component of the system and the cost of selling energy to the grid. The sizing optimisation has been formulated as a non‐linear, multi‐variable problem and the particle swarm optimisation algorithm has been tested using MATLAB platform for a particular location to swot up the feasibility of integrated system. The monthly averaged daily and hourly solar radiation data for a given location is calculated using empirical relations on MATLAB platform. Other inputs are specifications of commercially available devices and meteorological details of location.