Distributed slack bus model formulation for the holomorphic embedding load flow method

Ortega, J; Molina, T; Muñoz, JC; Oliva H., S

Distributed slack bus model formulation for the holomorphic embedding load flow method

Ortega, J Molina, T Muñoz, JC Oliva H., S

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Publisher:: Wiley
Publication Type:: Journal Article
Citation:: International Transactions on Electrical Energy Systems, 2020, 30, (3)
Issue Date:: 2020-03-01

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Field	Value	Language
dc.contributor.author	Ortega, J
dc.contributor.author	Molina, T
dc.contributor.author	Muñoz, JC
dc.contributor.author	Oliva H., S
dc.date.accessioned	2021-03-15T02:36:36Z
dc.date.available	2021-03-15T02:36:36Z
dc.date.issued	2020-03-01
dc.identifier.citation	International Transactions on Electrical Energy Systems, 2020, 30, (3)
dc.identifier.issn	2050-7038
dc.identifier.issn	2050-7038
dc.identifier.uri	http://hdl.handle.net/10453/147141
dc.description.abstract	© 2020 John Wiley & Sons, Ltd. Distributed slack bus (DSB) models for the resolution of power flow problems are a more realistic approach than the classical single slack bus concept. DSB models have been widely implemented in iterative approaches such as in Newton-Raphson power flow methods. However, iterative algorithms may lead to incorrect solutions or may fail to reach convergence under inappropriate initial estimations. The holomorphic embedding load-flow method (HELM) deals with the solution of the nonlinear power flow equations by means of complex analysis techniques, resulting in a deterministic and noniterative method, which is independent of initial estimations. As such, this paper proposes, from two different methodologies, a novel formulation and implementation of the DSB model for the HELM, which overcomes in that way the disadvantages of iterative methods and also incorporates the inherent advantages of DSB models. Moreover, this paper performs convergence and speed capability tests of the two proposed methodologies using two real-size benchmark systems.
dc.language	English
dc.publisher	Wiley
dc.relation.ispartof	International Transactions on Electrical Energy Systems
dc.relation.isbasedon	10.1002/2050-7038.12253
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	Energy
dc.title	Distributed slack bus model formulation for the holomorphic embedding load flow method
dc.type	Journal Article
utslib.citation.volume	30
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	0906 Electrical and Electronic Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Research)
pubs.organisational-group	/University of Technology Sydney/DVC (Research)/Institute For Sustainable Futures
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2021-03-15T02:36:31Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	30
utslib.citation.issue	3

Abstract:

© 2020 John Wiley & Sons, Ltd. Distributed slack bus (DSB) models for the resolution of power flow problems are a more realistic approach than the classical single slack bus concept. DSB models have been widely implemented in iterative approaches such as in Newton-Raphson power flow methods. However, iterative algorithms may lead to incorrect solutions or may fail to reach convergence under inappropriate initial estimations. The holomorphic embedding load-flow method (HELM) deals with the solution of the nonlinear power flow equations by means of complex analysis techniques, resulting in a deterministic and noniterative method, which is independent of initial estimations. As such, this paper proposes, from two different methodologies, a novel formulation and implementation of the DSB model for the HELM, which overcomes in that way the disadvantages of iterative methods and also incorporates the inherent advantages of DSB models. Moreover, this paper performs convergence and speed capability tests of the two proposed methodologies using two real-size benchmark systems.

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http://hdl.handle.net/10453/147141