A Sectionalizing Method in Power System Restoration Based on WAMS

Sarmadi, S. Arash Nezam; Dobakhshari, Ahmad Salehi; Azizi, Sadegh; Ranjbar, Ali Mohammad

doi:10.1109/tsg.2011.2105510

Cited by 71 publications

(85 citation statements)

References 13 publications

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“…Following parameters remained same for both strategies under test: the number of partitions M = 2, the set of black-start generators V BS = {v 33 , v 37 }, the sets of cranking groups V (5,6) , e (6,7) , e (6,11) , e (10,11) , e (13,14) , e (15,16) , e (21,22) , e (23,24) , e (26,29) , e (28,29) }.…”

Section: A Ieee 39-bus Power Systemmentioning

confidence: 99%

“…The algorithm is based on real-time data measured by a phasor measurement unit, which is not applicable to partition the entire system in a complete blackout. A partitioning strategy based on a wide area measurement system is proposed in [7], which ensures the observability of all partitions so as to guarantee a fast and secure restoration. In [8], an ordered binary decision diagram based three-phase strategy is introduced for parallel restoration, which provides guidance to the transmission system operators on how parallel restoration could be performed.…”

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confidence: 99%

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Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

Ganganath

Wang

Xu³

et al. 2018

IEEE Trans. Ind. Inf.

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Abstract-After a blackout, it is essential to restore the blackout area rapidly to minimize possible losses. In parallel restoration, the blackout area is first partitioned into several subsystems which will then be restored in parallel to accelerate the restoration process. In order to ensure restoration reliability, each subsystem should have enough generation power and satisfy a set of constraints before triggering the parallel restoration process. This paper models this as a constrained optimization problem and proposes a partitioning strategy to solve it in three steps. In the first step, some existing methods and expert knowledge are used for initialization of partitioning process. The second step ensures the satisfaction of modelled constraints. The third step operates greedily to find suitable partitions for parallel restoration. The proposed strategy is implemented and evaluated on IEEE 39-and 118-bus power systems. Evaluation results show that it provides adequate subsystems for parallel restoration. Unlike some existing partitioning strategies, the proposed strategy can be used to partition a power system into multiple subsystems in a single execution.

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Section: A Ieee 39-bus Power Systemmentioning

confidence: 99%

mentioning

confidence: 99%

Agglomerative Clustering-Based Network Partitioning for Parallel Power System Restoration

Ganganath

Wang

Xu³

et al. 2018

IEEE Trans. Ind. Inf.

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“…Ref. [33] presents a novel sectionalization method based on the wide area measurement system (WAMS) for the build-up strategy in power system restoration. In [34], a new method is proposed to divide systems for restoration based on the community structure of complex network theory.…”

Section: Sectionalization Strategymentioning

confidence: 99%

“…In [33], a novel sectionalizing method is proposed for the build-up strategy including two processes, restoring separated parts (islands) in the power system and then interconnecting them afterwards. Each island ensures observability and provides the phase angle difference between adjacent stations using the WAMS.…”

Section: Wams and Cyber-attackmentioning

confidence: 99%

Power system restoration: a literature review from 2006 to 2016

Liu

Fan

Terzija

2016

J. Mod. Power Syst. Clean Energy

237

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Power system restoration has attracted more attention and made great progress recently. Research progress of the power system restoration from 2006 to 2016 is reviewed in this paper, including black-start, network reconfiguration and load restoration. Some emerging methods and key techniques are also discussed in the context of the integration of variable renewable energy and development of the smart grid. There is a long way to go to achieve automatic self-healing in bulk power systems because of its extreme complexity. However, rapidly developing artificial intelligence technology will eventually enable the step-by-step dynamic decision-making based on the situation awareness of supervisory control and data acquisition systems (SCADA) and wide area measurement systems (WAMS) in the near future.

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“…Typically, the importance of transmission lines and substations are evaluated first, and then employed in forming an optimal restoration subsystem division [18][19][20][21][22]. However, there are not agreeable opinions on the appropriate establishment of weights in evaluating the importance of transmission lines and nodes.…”

Section: Temporal Conditionsmentioning

confidence: 99%