eprintid: 10479
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/04/79
datestamp: 2023-11-09 16:37:05
lastmod: 2023-11-09 16:37:05
status_changed: 2023-11-09 16:31:30
type: article
metadata_visibility: show
creators_name: Ali, A.
creators_name: Mohd Nor, N.
creators_name: Ibrahim, T.
creators_name: Fakhizan Romlie, M.
title: Sizing and placement of solar photovoltaic plants by using time-series historical weather data
ispublished: pub
keywords: Energy dissipation; Genetic algorithms; Integer programming; Meteorology; Optimization; Photovoltaic cells; Probability density function; Solar concentrators; Solar radiation; Time series, Distribution generation; Electrical networks; Historical weather datum; Mixed integer optimization; Objective functions; Optimization problems; Solar photovoltaic plants; Solar photovoltaics, Solar power generation
note: cited By 7
abstract: The integration of distribution generation (DG) in distribution networks with improper planning adversely influences the quality of the electrical networks. Conventionally, the outputs from the intermittent DGs, such as solar photovoltaic (PV) plants, are assumed dispatchable. The intermittency of solar irradiance on the outputs of the PV modules has been ignored in most studies on the sizing and placement of DGs. By looking at this problem, this paper presents the sizing and placement of a distributed solar photovoltaic plant (DSPP) by using time series historical weather data. To predict the output from the PV modules, 15 years of solar data were modeled with the aid of a beta probability density function. The total energy loss index was formulated as the main objective function, and the optimization problem was solved by mixed integer optimization by using genetic algorithm. By adopting a time-varying commercial load, the proposed algorithm was applied on IEEE 33 bus and IEEE 69 bus distribution networks. The numerical studies on the two distribution networks show the advantages of the proposed approach for minimizing the total energy losses and improving the bus voltage profiles. It was revealed that up to 38 of the total energy losses in distribution networks could be reduced at sites with solar insolation of 5.65 peaks sun hours. In contrast to existing methods, planning for DGs by using weather data provided more realistic results for DSPP in distribution networks. © 2018 Author(s).
date: 2018
publisher: American Institute of Physics Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85043339439&doi=10.1063%2f1.4994728&partnerID=40&md5=12c26b628cdd72870be301a1bfcd8881
id_number: 10.1063/1.4994728
full_text_status: none
publication: Journal of Renewable and Sustainable Energy
volume: 10
number: 2
refereed: TRUE
issn: 19417012
citation:   Ali, A. and Mohd Nor, N. and Ibrahim, T. and Fakhizan Romlie, M.  (2018) Sizing and placement of solar photovoltaic plants by using time-series historical weather data.  Journal of Renewable and Sustainable Energy, 10 (2).   ISSN 19417012