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Effective method for optimal allocation of distributed generation units in meshed electric power systems

Improper placement of distributed generation (DG) units in power systems would not only lead to an increased power loss, but could also jeopardise the system operation. To avert these scenarios and tackle this optimisation problem, this study proposes an effective method to guide electric utility di...

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Main Authors: Akorede, Mudathir Funsho, Hizam, Hashim, Aris, Ishak, Ab Kadir, Mohd Zainal Abidin
Format: Article
Language:English
Published: IET 2011
Online Access:http://psasir.upm.edu.my/id/eprint/23067/1/Effective%20method%20for%20optimal%20allocation%20of%20distributed%20generation%20units%20in%20meshed%20electric%20power%20systems.pdf
http://psasir.upm.edu.my/id/eprint/23067/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5702383&tag=1
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spelling my.upm.eprints.230672019-11-20T08:25:56Z http://psasir.upm.edu.my/id/eprint/23067/ Effective method for optimal allocation of distributed generation units in meshed electric power systems Akorede, Mudathir Funsho Hizam, Hashim Aris, Ishak Ab Kadir, Mohd Zainal Abidin Improper placement of distributed generation (DG) units in power systems would not only lead to an increased power loss, but could also jeopardise the system operation. To avert these scenarios and tackle this optimisation problem, this study proposes an effective method to guide electric utility distribution companies (DISCOs) in determining the optimal size and best locations of DG sources on their power systems. The approach, taking into account the system constraints, maximises the system loading margin as well as the profit of the DISCO over the planning period. These objective functions are fuzzified into a single multi-objective function, and subsequently solved using genetic algorithm (GA). In the GA, a fuzzy controller is used to dynamically adjust the crossover and mutation rates to maintain the proper population diversity (PD) during GA's operation. This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The results obtained on IEEE 6-bus and 30-bus test systems with the proposed method are evaluated with the simulation results of the classical grid search algorithm, which confirm its robustness and accuracy. This study also demonstrates DG's economic viability relative to upgrading substation and feeder facilities, when the incremental cost of serving additional load is considered. IET 2011 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/23067/1/Effective%20method%20for%20optimal%20allocation%20of%20distributed%20generation%20units%20in%20meshed%20electric%20power%20systems.pdf Akorede, Mudathir Funsho and Hizam, Hashim and Aris, Ishak and Ab Kadir, Mohd Zainal Abidin (2011) Effective method for optimal allocation of distributed generation units in meshed electric power systems. IET Generation, Transmission & Distribution, 5 (2). pp. 276-287. ISSN 1751-8687; ESSN: 1751-8695 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5702383&tag=1 10.1049/iet-gtd.2010.0199
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Improper placement of distributed generation (DG) units in power systems would not only lead to an increased power loss, but could also jeopardise the system operation. To avert these scenarios and tackle this optimisation problem, this study proposes an effective method to guide electric utility distribution companies (DISCOs) in determining the optimal size and best locations of DG sources on their power systems. The approach, taking into account the system constraints, maximises the system loading margin as well as the profit of the DISCO over the planning period. These objective functions are fuzzified into a single multi-objective function, and subsequently solved using genetic algorithm (GA). In the GA, a fuzzy controller is used to dynamically adjust the crossover and mutation rates to maintain the proper population diversity (PD) during GA's operation. This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The results obtained on IEEE 6-bus and 30-bus test systems with the proposed method are evaluated with the simulation results of the classical grid search algorithm, which confirm its robustness and accuracy. This study also demonstrates DG's economic viability relative to upgrading substation and feeder facilities, when the incremental cost of serving additional load is considered.
format Article
author Akorede, Mudathir Funsho
Hizam, Hashim
Aris, Ishak
Ab Kadir, Mohd Zainal Abidin
spellingShingle Akorede, Mudathir Funsho
Hizam, Hashim
Aris, Ishak
Ab Kadir, Mohd Zainal Abidin
Effective method for optimal allocation of distributed generation units in meshed electric power systems
author_facet Akorede, Mudathir Funsho
Hizam, Hashim
Aris, Ishak
Ab Kadir, Mohd Zainal Abidin
author_sort Akorede, Mudathir Funsho
title Effective method for optimal allocation of distributed generation units in meshed electric power systems
title_short Effective method for optimal allocation of distributed generation units in meshed electric power systems
title_full Effective method for optimal allocation of distributed generation units in meshed electric power systems
title_fullStr Effective method for optimal allocation of distributed generation units in meshed electric power systems
title_full_unstemmed Effective method for optimal allocation of distributed generation units in meshed electric power systems
title_sort effective method for optimal allocation of distributed generation units in meshed electric power systems
publisher IET
publishDate 2011
url http://psasir.upm.edu.my/id/eprint/23067/1/Effective%20method%20for%20optimal%20allocation%20of%20distributed%20generation%20units%20in%20meshed%20electric%20power%20systems.pdf
http://psasir.upm.edu.my/id/eprint/23067/
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5702383&tag=1
_version_ 1651869025183989760
score 13.211869

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