Parallel-differential evolution approach for optimal event-driven load shedding against voltage collapse in power systems

Event-driven load shedding is an effective countermeasure against voltage collapse in power systems. Conventionally, its optimisation relies on sensitivity-based linear methods, which, however, could suffer from unrealistic assumptions and sub-optimality. In this study, an alternative approach based...

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Bibliographic Details
Published inIET generation, transmission & distribution Vol. 8; no. 4; pp. 651 - 660
Main Authors Xu, Yan, Dong, Zhao Yang, Luo, Fengji, Zhang, Rui, Wong, Kit Po
Format Journal Article
LanguageEnglish
Published Stevenage The Institution of Engineering and Technology 01.04.2014
Institution of Engineering and Technology
The Institution of Engineering & Technology
Subjects
VSA
VSA
Online AccessGet full text
ISSN1751-8687
1751-8695
DOI10.1049/iet-gtd.2013.0385

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Summary:Event-driven load shedding is an effective countermeasure against voltage collapse in power systems. Conventionally, its optimisation relies on sensitivity-based linear methods, which, however, could suffer from unrealistic assumptions and sub-optimality. In this study, an alternative approach based on parallel-differential evolution (P-DE) is proposed for efficiently and globally optimising the event-driven load shedding against voltage collapse. Working in a parallel structure, the approach consists of candidate buses selection, voltage stability assessment (VSA) and DE optimisation. Compared with conventional methods, it fully considers the non-linearity of the problem and is able to effectively escape from local optima and not limited to system modelling and unrealistic assumptions. Besides, any type of objective functions and VSA techniques can be used. The proposed approach has been tested on the IEEE 118-bus test system considering two cases for preventive control and corrective control, respectively, and compared with the two existing methods. Simulation results have verified its effectiveness and superiority over the compared methods.
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ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2013.0385