Optimal Robustness in Power Grids From a Network Science Perspective

Haicheng Tu, Yongxiang Xia, Herbert Ho Ching Iu, Xi Chen

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

In recent years, the frequent occurrences of large-scale blackouts highlight the necessity of enhancing the robustness of power grids. In this paper, based on the cascading failure model which considers both the network topology and electrical characteristics running in power grids, we study how the topological metrics affect the robustness of power grids. The topological metrics considered include both the connectivity of the network and the distribution of generators. We compare the results in typical complex network models and IEEE 118-bus network. Moreover, by using the simulated annealing method, we find the optimal network topology to achieve the best network robustness, and compare the topological metrics before and after the optimization to verify our findings. The results show that in order to enhance the robustness of power grids, it is better to make the network sparsely connected, and place the generators as hubs and decentralize these generators.

Original languageEnglish
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
DOIs
Publication statusE-pub ahead of print - 3 May 2018

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Topology
Complex networks
Simulated annealing

Cite this

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title = "Optimal Robustness in Power Grids From a Network Science Perspective",
abstract = "In recent years, the frequent occurrences of large-scale blackouts highlight the necessity of enhancing the robustness of power grids. In this paper, based on the cascading failure model which considers both the network topology and electrical characteristics running in power grids, we study how the topological metrics affect the robustness of power grids. The topological metrics considered include both the connectivity of the network and the distribution of generators. We compare the results in typical complex network models and IEEE 118-bus network. Moreover, by using the simulated annealing method, we find the optimal network topology to achieve the best network robustness, and compare the topological metrics before and after the optimization to verify our findings. The results show that in order to enhance the robustness of power grids, it is better to make the network sparsely connected, and place the generators as hubs and decentralize these generators.",
keywords = "Generators, Measurement, optimization, Power grids, power grids, Power system faults, Power system protection, Power transmission lines, Robustness, robustness, simulated annealing, topological analysis.",
author = "Haicheng Tu and Yongxiang Xia and Iu, {Herbert Ho Ching} and Xi Chen",
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Optimal Robustness in Power Grids From a Network Science Perspective. / Tu, Haicheng; Xia, Yongxiang; Iu, Herbert Ho Ching; Chen, Xi.

In: IEEE Transactions on Circuits and Systems II: Express Briefs, 03.05.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Optimal Robustness in Power Grids From a Network Science Perspective

AU - Tu, Haicheng

AU - Xia, Yongxiang

AU - Iu, Herbert Ho Ching

AU - Chen, Xi

PY - 2018/5/3

Y1 - 2018/5/3

N2 - In recent years, the frequent occurrences of large-scale blackouts highlight the necessity of enhancing the robustness of power grids. In this paper, based on the cascading failure model which considers both the network topology and electrical characteristics running in power grids, we study how the topological metrics affect the robustness of power grids. The topological metrics considered include both the connectivity of the network and the distribution of generators. We compare the results in typical complex network models and IEEE 118-bus network. Moreover, by using the simulated annealing method, we find the optimal network topology to achieve the best network robustness, and compare the topological metrics before and after the optimization to verify our findings. The results show that in order to enhance the robustness of power grids, it is better to make the network sparsely connected, and place the generators as hubs and decentralize these generators.

AB - In recent years, the frequent occurrences of large-scale blackouts highlight the necessity of enhancing the robustness of power grids. In this paper, based on the cascading failure model which considers both the network topology and electrical characteristics running in power grids, we study how the topological metrics affect the robustness of power grids. The topological metrics considered include both the connectivity of the network and the distribution of generators. We compare the results in typical complex network models and IEEE 118-bus network. Moreover, by using the simulated annealing method, we find the optimal network topology to achieve the best network robustness, and compare the topological metrics before and after the optimization to verify our findings. The results show that in order to enhance the robustness of power grids, it is better to make the network sparsely connected, and place the generators as hubs and decentralize these generators.

KW - Generators

KW - Measurement

KW - optimization

KW - Power grids

KW - power grids

KW - Power system faults

KW - Power system protection

KW - Power transmission lines

KW - Robustness

KW - robustness

KW - simulated annealing

KW - topological analysis.

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SN - 1549-7747

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