Performance enhancement of AGC under open market scenario using TDOFPID and IPFC controller

Mishra, DK; Panigrahi, TK; Ray, PK; Mohanty, A

Performance enhancement of AGC under open market scenario using TDOFPID and IPFC controller

Mishra, DK Panigrahi, TK Ray, PK Mohanty, A

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Publisher:: IOS PRESS
Publication Type:: Journal Article
Citation:: Journal of Intelligent and Fuzzy Systems, 2018, 35, (5), pp. 4933-4943
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Mishra, DK
dc.contributor.author	Panigrahi, TK
dc.contributor.author	Ray, PK
dc.contributor.author	Mohanty, A
dc.date.accessioned	2022-12-03T23:12:22Z
dc.date.available	2022-12-03T23:12:22Z
dc.date.issued	2018-01-01
dc.identifier.citation	Journal of Intelligent and Fuzzy Systems, 2018, 35, (5), pp. 4933-4943
dc.identifier.issn	1064-1246
dc.identifier.issn	1875-8967
dc.identifier.uri	http://hdl.handle.net/10453/164070
dc.description.abstract	Present work introduces a most popular evolution based algorithm and application of two degree of freedom proportional integral Derivative (TDOFPID) Controller based multi area power system. Differential Evolution (DE) optimization technique is applied here to tune the TDOFPID gains. Each area consists of Automatic generation control with addition of non-linarites. In this model time delay, Generation rate constraints (GRC) and reheat turbine are added to introduce non-linearity. At first attempt simulation is being done in two areas with DE optimization technique. Further a series connected Flexible Alternating Current Transmission (FACT) device such as interline power flow controller (IPFC) is included into the system and simulated. DE is also used to get the optimum value of TDOFPID controller having Integral time absolute error (ITAE) as the objective function. At last robustness analysis is done with varying parameter and different loading conditions. It is seen that, TDOFPID with IPFC gives better response compared to others.
dc.language	English
dc.publisher	IOS PRESS
dc.relation.ispartof	Journal of Intelligent and Fuzzy Systems
dc.relation.isbasedon	10.3233/JIFS-169777
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 1702 Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Performance enhancement of AGC under open market scenario using TDOFPID and IPFC controller
dc.type	Journal Article
utslib.citation.volume	35
utslib.location.activity	New Delhi, INDIA
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	1702 Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access	*
dc.date.updated	2022-12-03T23:12:20Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	35
utslib.citation.issue	5

Abstract:

Present work introduces a most popular evolution based algorithm and application of two degree of freedom proportional integral Derivative (TDOFPID) Controller based multi area power system. Differential Evolution (DE) optimization technique is applied here to tune the TDOFPID gains. Each area consists of Automatic generation control with addition of non-linarites. In this model time delay, Generation rate constraints (GRC) and reheat turbine are added to introduce non-linearity. At first attempt simulation is being done in two areas with DE optimization technique. Further a series connected Flexible Alternating Current Transmission (FACT) device such as interline power flow controller (IPFC) is included into the system and simulated. DE is also used to get the optimum value of TDOFPID controller having Integral time absolute error (ITAE) as the objective function. At last robustness analysis is done with varying parameter and different loading conditions. It is seen that, TDOFPID with IPFC gives better response compared to others.

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http://hdl.handle.net/10453/164070