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Article: Coordinating generation and load pickup during load restoration with discrete load increments and reserve constraints

TitleCoordinating generation and load pickup during load restoration with discrete load increments and reserve constraints
Authors
Issue Date2015
Citation
IET Generation, Transmission & Distribution, 2015, v. 9 n. 15, p. 2437-2446 How to Cite?
AbstractAfter a major outage happens, the independent system operator, transmission owners (TOs), generation owners (GOs), and distribution owners (DOs) should coordinate control actions to restore the power system timely and reliably. This study proposes a methodology to establish load restoration plans for the coordination among these participants. This methodology models the load restoration as a multi-stage decision-making process. At each stage, a mixed-integer nonlinear load restoration model (MINLR) is formulated to maximise load pickup subject to AC power flow and reserve constraints. Comprehensive load characteristics are considered in this model. The solution of the MINLR model provides power set points for GOs/TOs and load pickup amount for DOs. A complete load restoration plan is obtained by solving a series of MINLR models. To solve MINLR models efficiently, a branch-and-cut solver is constructed by identifying efficient cutting planes and a reliable problem-specific branching method. The applicability of cutting planes is proven. This methodology is tested using a 24-bus system with 170 interrupted load increments, and a 118-bus system with 637 interrupted load increments. The simulation results show that the proposed methodology can be efficiently applied to aid restoration participants pickup load increments within the TO's islands, while maintaining adequate reserve margins.
Persistent Identifierhttp://hdl.handle.net/10722/229183
ISSN
2015 Impact Factor: 1.576
2015 SCImago Journal Rankings: 1.332

 

DC FieldValueLanguage
dc.contributor.authorQin, Z-
dc.contributor.authorHou, Y-
dc.contributor.authorLiu, CC-
dc.contributor.authorLiu, S-
dc.contributor.authorSun, W-
dc.date.accessioned2016-08-23T14:09:31Z-
dc.date.available2016-08-23T14:09:31Z-
dc.date.issued2015-
dc.identifier.citationIET Generation, Transmission & Distribution, 2015, v. 9 n. 15, p. 2437-2446-
dc.identifier.issn1751-8687-
dc.identifier.urihttp://hdl.handle.net/10722/229183-
dc.description.abstractAfter a major outage happens, the independent system operator, transmission owners (TOs), generation owners (GOs), and distribution owners (DOs) should coordinate control actions to restore the power system timely and reliably. This study proposes a methodology to establish load restoration plans for the coordination among these participants. This methodology models the load restoration as a multi-stage decision-making process. At each stage, a mixed-integer nonlinear load restoration model (MINLR) is formulated to maximise load pickup subject to AC power flow and reserve constraints. Comprehensive load characteristics are considered in this model. The solution of the MINLR model provides power set points for GOs/TOs and load pickup amount for DOs. A complete load restoration plan is obtained by solving a series of MINLR models. To solve MINLR models efficiently, a branch-and-cut solver is constructed by identifying efficient cutting planes and a reliable problem-specific branching method. The applicability of cutting planes is proven. This methodology is tested using a 24-bus system with 170 interrupted load increments, and a 118-bus system with 637 interrupted load increments. The simulation results show that the proposed methodology can be efficiently applied to aid restoration participants pickup load increments within the TO's islands, while maintaining adequate reserve margins.-
dc.languageeng-
dc.relation.ispartofIET Generation, Transmission & Distribution-
dc.titleCoordinating generation and load pickup during load restoration with discrete load increments and reserve constraints-
dc.typeArticle-
dc.identifier.emailHou, Y: yhhou@hku.hk-
dc.identifier.authorityHou, Y=rp00069-
dc.identifier.doi10.1049/iet-gtd.2015.0240-
dc.identifier.hkuros260912-
dc.identifier.volume9-
dc.identifier.issue15-
dc.identifier.spage2437-
dc.identifier.epage2446-

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