Optimal placement of multi-type FACTS devices using hybrid evolutionary algorithm

In this paper, a new hybrid evolutionary algorithm (HEA) based on evolutionary programming (EP), tabu search (TS), and simulated annealing (SA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer c...

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Main Author: Peerapol Jirapong
Format: Conference Proceeding
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=74549210057&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/48996
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-489962018-08-16T02:08:12Z Optimal placement of multi-type FACTS devices using hybrid evolutionary algorithm Peerapol Jirapong Computer Science In this paper, a new hybrid evolutionary algorithm (HEA) based on evolutionary programming (EP), tabu search (TS), and simulated annealing (SA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer capability (TTC) and minimize the system real power loss of power transfers in deregulated power systems. Multi-objective optimal power flow (OPF) with FACTS devices including TTC, power loss, and penalty functions is used to evaluate the feasible maximum TTC value and minimum power loss within real and reactive power generation limits, thermal limits, voltage limits, stability limits, and FACTS devices operation limits. Four types of FACTS devices are included: thyristor-controlled series capacitor (TCSC), thyristor-controlled phase shifter (TCPS), unified power flow controller (UPFC), and static var compensator (SVC). Test results on the modified IEEE 30-bus system indicate that optimally placed OPF with FACTS by the HEA approach could enhance TTC far more than those from EP, TS, hybrid TS/SA, and improved EP (IEP) algorithms, leading to much efficient utilization of the existing transmission system. 2018-08-16T02:08:12Z 2018-08-16T02:08:12Z 2009-12-01 Conference Proceeding 2-s2.0-74549210057 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=74549210057&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/48996
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Computer Science
spellingShingle Computer Science
Peerapol Jirapong
Optimal placement of multi-type FACTS devices using hybrid evolutionary algorithm
description In this paper, a new hybrid evolutionary algorithm (HEA) based on evolutionary programming (EP), tabu search (TS), and simulated annealing (SA) is proposed to determine the optimal placement of multi-type flexible AC transmission system (FACTS) devices to simultaneously maximize the total transfer capability (TTC) and minimize the system real power loss of power transfers in deregulated power systems. Multi-objective optimal power flow (OPF) with FACTS devices including TTC, power loss, and penalty functions is used to evaluate the feasible maximum TTC value and minimum power loss within real and reactive power generation limits, thermal limits, voltage limits, stability limits, and FACTS devices operation limits. Four types of FACTS devices are included: thyristor-controlled series capacitor (TCSC), thyristor-controlled phase shifter (TCPS), unified power flow controller (UPFC), and static var compensator (SVC). Test results on the modified IEEE 30-bus system indicate that optimally placed OPF with FACTS by the HEA approach could enhance TTC far more than those from EP, TS, hybrid TS/SA, and improved EP (IEP) algorithms, leading to much efficient utilization of the existing transmission system.
format Conference Proceeding
author Peerapol Jirapong
author_facet Peerapol Jirapong
author_sort Peerapol Jirapong
title Optimal placement of multi-type FACTS devices using hybrid evolutionary algorithm
title_short Optimal placement of multi-type FACTS devices using hybrid evolutionary algorithm
title_full Optimal placement of multi-type FACTS devices using hybrid evolutionary algorithm
title_fullStr Optimal placement of multi-type FACTS devices using hybrid evolutionary algorithm
title_full_unstemmed Optimal placement of multi-type FACTS devices using hybrid evolutionary algorithm
title_sort optimal placement of multi-type facts devices using hybrid evolutionary algorithm
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=74549210057&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/48996
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