eprintid: 10692
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/06/92
datestamp: 2023-11-09 16:37:18
lastmod: 2023-11-09 16:37:18
status_changed: 2023-11-09 16:31:59
type: conference_item
metadata_visibility: show
creators_name: Ali, A.
creators_name: Romlie, M.F.
creators_name: Nor, N.M.
creators_name: Ibrahim, T.
title: Optimization for the planning of distributed renewable generators using genetic algorithm
ispublished: pub
keywords: Distributed power generation; Electric power system planning; Renewable energy resources, Distributed generator (DGs); Distributed generators; Electrical distribution networks; Heuristic optimization technique; Optimization problems; Optimization techniques; Power system planning; Renewable energies, Genetic algorithms
note: cited By 2; Conference of 5th IET International Conference on Clean Energy and Technology, CEAT 2018 ; Conference Date: 5 September 2018 Through 6 September 2018; Conference Code:144672
abstract: The integration of distributed generators (DGs) considering renewable energy provides great benefits to the distribution networks, such as, reductions in power loss and improvements of voltage profile. However, such benefits to the distribution networks are constrained with the installation of DGs with proper sizes and locations. In this paper, the optimization for sizing and placement of distributed renewable generators (DRGs) in the electrical distribution networks is presented. The optimum sizes and locations for the DRGs are determined to reduce the power loss in the distribution networks. The genetic algorithm (GA) has been used to solve the optimization problem using MATLAB. For the validation, results of this study are compared with other well-known heuristic optimization techniques and analytical approaches. The numerical studies on the IEEE 33 bus distribution network have revealed that the proposed algorithm is capable for finding the optimum size and place of DRG in the distribution networks. The optimization results using GA are seen very competitive with the result by other well-known heuristic optimization techniques and analytical approaches that have been used for the similar studies. The results from this study signify the use of GA in the research related to planning of renewable energy and power system. © 2018 Institution of Engineering and Technology. All rights reserved.
date: 2018
publisher: Institution of Engineering and Technology
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061353052&partnerID=40&md5=69251e2fbbb4f48554951ab4924d838c
full_text_status: none
publication: IET Conference Publications
volume: 2018
number: CP749
refereed: TRUE
isbn: 9781785618161; 9781785618437; 9781785618468; 9781785618871; 9781785619427; 9781785619694; 9781839530036; 9781785617911
citation:   Ali, A. and Romlie, M.F. and Nor, N.M. and Ibrahim, T.  (2018) Optimization for the planning of distributed renewable generators using genetic algorithm.  In: UNSPECIFIED.