Probabilistic load flow�based optimal placement and sizing of distributed generators

Electric load flow; Environmental impact; Genetic algorithms; Investments; Location; Operating costs; Probability distributions; Distributed generation; Distributed generation resources; Distributed generators; Distribution network; Electrical energy demand; Flow based; Location optimization; Optima...

Full description

Saved in:
Bibliographic Details
Main Authors: Hossain F.A., Rokonuzzaman M., Amin N., Zhang J., Mishu M.K., Tan W.-S., Islam M.R., Roy R.B.
Other Authors: 57353864100
Format: Article
Published: MDPI 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-25867
record_format dspace
spelling my.uniten.dspace-258672023-05-29T17:05:21Z Probabilistic load flow�based optimal placement and sizing of distributed generators Hossain F.A. Rokonuzzaman M. Amin N. Zhang J. Mishu M.K. Tan W.-S. Islam M.R. Roy R.B. 57353864100 57190566039 7102424614 56274769100 57192669693 55336912400 55765000567 56603588300 Electric load flow; Environmental impact; Genetic algorithms; Investments; Location; Operating costs; Probability distributions; Distributed generation; Distributed generation resources; Distributed generators; Distribution network; Electrical energy demand; Flow based; Location optimization; Optimal placement and sizings; Probabilistic load flow; Distributed power generation Distributed generation (DG) is gaining importance as electrical energy demand increases. DG is used to decrease power losses, operating costs, and improve voltage stability. Most DG resources have less environmental impact. In a particular region, the sizing and location of DG resources significantly affect the planned DG integrated distribution network (DN). The voltage profiles of the DN will change or even become excessively increased. An enormous DG active power, inserted into an improper node of the distribution network, may bring a larger current greater than the conductor�s maximum value, resulting in an overcurrent distribution network. Therefore, DG sizing and DG location optimization is required for a systematic DG operation to fully exploit distributed energy and achieve mutual energy harmony across existing distribution networks, which creates an economically viable, secure, stable, and dependable power distribution system. DG needs to access the location and capacity for rational planning. The objective function of this paper is to minimize the sum of investment cost, operation cost, and line loss cost utilizing DG access. The probabilistic power flow calculation technique based on the two-point estimation method is chosen for this paper�s load flow computation. The location and size of the DG distribution network are determined using a genetic algorithm in a MATLAB environment. For the optimum solution, the actual power load is estimated using historical data. The proposed system is based on the China distribution system, and the currency is used in Yuan. After DG access, active and reactive power losses are reduced by 53% and 26%, respectively. The line operating cost and the total annual cost are decreased by 53.7% and 12%, respectively. � 2021 by the authors. Licensee MDPI, Basel, Switzerland. Final 2023-05-29T09:05:21Z 2023-05-29T09:05:21Z 2021 Article 10.3390/en14237857 2-s2.0-85120006435 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85120006435&doi=10.3390%2fen14237857&partnerID=40&md5=a559ae7af27cd65b02a06c963a677fc3 https://irepository.uniten.edu.my/handle/123456789/25867 14 23 7857 All Open Access, Gold MDPI Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Electric load flow; Environmental impact; Genetic algorithms; Investments; Location; Operating costs; Probability distributions; Distributed generation; Distributed generation resources; Distributed generators; Distribution network; Electrical energy demand; Flow based; Location optimization; Optimal placement and sizings; Probabilistic load flow; Distributed power generation
author2 57353864100
author_facet 57353864100
Hossain F.A.
Rokonuzzaman M.
Amin N.
Zhang J.
Mishu M.K.
Tan W.-S.
Islam M.R.
Roy R.B.
format Article
author Hossain F.A.
Rokonuzzaman M.
Amin N.
Zhang J.
Mishu M.K.
Tan W.-S.
Islam M.R.
Roy R.B.
spellingShingle Hossain F.A.
Rokonuzzaman M.
Amin N.
Zhang J.
Mishu M.K.
Tan W.-S.
Islam M.R.
Roy R.B.
Probabilistic load flow�based optimal placement and sizing of distributed generators
author_sort Hossain F.A.
title Probabilistic load flow�based optimal placement and sizing of distributed generators
title_short Probabilistic load flow�based optimal placement and sizing of distributed generators
title_full Probabilistic load flow�based optimal placement and sizing of distributed generators
title_fullStr Probabilistic load flow�based optimal placement and sizing of distributed generators
title_full_unstemmed Probabilistic load flow�based optimal placement and sizing of distributed generators
title_sort probabilistic load flow�based optimal placement and sizing of distributed generators
publisher MDPI
publishDate 2023
_version_ 1806426427790196736
score 13.188404