Group decision support system for backbone-network reconfiguration

Liu, Yutian; Sun, Pengbo; Wang, Chunyi

doi:10.1016/j.ijepes.2015.03.006

Cited by 22 publications

(14 citation statements)

References 37 publications

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“…Ref. [47] presents a group decision support system which combines multiple attribute decision-making and group decision-making to aggregate different attributes and multiple experts' opinions to make decision-making more reasonable. In order to evaluate candidate restoration schemes, multiple types of attributes including crisp data, fuzzy numbers, interval numbers and linguistic terms are employed in [48].…”

Section: Backbone-network Determinationmentioning

confidence: 99%

Power system restoration: a literature review from 2006 to 2016

Liu

Fan

Terzija

2016

J. Mod. Power Syst. Clean Energy

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238

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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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Section: Backbone-network Determinationmentioning

confidence: 99%

Power system restoration: a literature review from 2006 to 2016

Liu

Fan

Terzija

2016

J. Mod. Power Syst. Clean Energy

Self Cite

238

View full text Add to dashboard Cite

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“…Consequently the shortest restoration path can be obtained with Dijkstra algorithm (Johnson, 1973). In each subsystem, the restoration goals are determined by a three-stage restoration strategy (Liu, Sun, & Wang, 2015). In different stages different restoration goals are focused on.…”

Section: Establishment Of Candidate Restoration Schemesmentioning

confidence: 99%

Hybrid multiple attribute group decision-making for power system restoration

Sun

Liu

Qiu

et al. 2015

Expert Systems with Applications

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“…Decision‐making methods have been proposed to solve the network reconfiguration problem. These methods were applied to evaluate the unit's start‐up sequence, 11,14‐16 to build the skeleton network, 17 and to obtain restoration paths 16,18‐20 . Aiming to obtain the global optimal solutions, several optimization techniques such as numerical methods 4,21,22 and optimization algorithms 9,13,23‐33 have been applied to solve network reconfiguration problem.…”

Section: Introductionmentioning

confidence: 99%

Review on optimization methodologies in transmission network reconfiguration of power systems for grid resilience

Aziz

Liu

Waseem

et al. 2020

Int Trans Electr Energ Syst

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Background When a power system blackout occurs, it affects the economy of the country and every aspect of human life. Cascading failures can easily occur and cause a major blackout in the power grid due to the breakdown or failure of important nodes or links. Recently, transmission network reconfiguration (TNR) becomes a hot topic and has made many concerns after major blackouts of power systems. Aims TNR is the second‐stage action plan to restore power systems and plays a major role in the process of power system restoration. On the other hand, grid resilience involves a quick dynamic reconfiguration of power systems to minimize the propagation of attack influences on the grid. The motivations to include the works in this survey are based on the quality of the research performed in the transmission network reconfiguration problem for grid resilience. In this article, the state‐of‐the‐art review of recent progress in the network reconfiguration problem of the transmission system for grid resilience is discussed with practical challenges, technical issues, and power industry practices. Materials & Methods In this paper, complex network theory‐based indices with advantages, disadvantages, and their applications have been discussed to assess the important nodes and lines for network reconfiguration problem during sudden disturbances in power systems. Furthermore, optimization models have been presented with objective functions as well as their constraints. Taken together, optimization methodologies have been discussed to solve network reconfiguration problem with merits and demerits. Results This survey paper presents current trends in research and future research directions concerning transmission network reconfiguration for academic researchers and practicing engineers. Furthermore, the most current studies in improving transmission network reconfiguration problem are reviewed by highlighting their advantages and limitations. Discussion Based on a thorough comparison of literature some future perspectives are also discussed for transmission network reconfiguration problem for grid resilience. Conclusion This review paper provides a comprehensive review of current practices applied to transmission network reconfiguration. The core focus of this paper will remain on complex network theory‐based indices, optimization models, optimization methodologies, challenges, and technical issues, and discusses future direction for transmission network reconfiguration problem for grid resilience. Furthermore, the most current studies in improving transmission network reconfiguration problem are reviewed by highlighting their advantages and limitations.

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Group decision support system for backbone-network reconfiguration

Cited by 22 publications

References 37 publications

Power system restoration: a literature review from 2006 to 2016

Power system restoration: a literature review from 2006 to 2016

Hybrid multiple attribute group decision-making for power system restoration

Review on optimization methodologies in transmission network reconfiguration of power systems for grid resilience

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