Critical node identification in active distribution network using resilience and risk theory

Zhang, Wen; Liu, Keyan; Sheng, Wanxing; Du, Songhuai; Jia, Dongli

doi:10.1049/iet-gtd.2019.1781

Cited by 20 publications

(11 citation statements)

References 39 publications

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“…where Ω r represents the top r nodes obtained by the method proposed in this study, R(i ) is the critical ranking of node i obtained using the proposed method, and R o (i ) is the critical ranking of node i obtained using another method. We compared the proposed method with the active power degree (APD) [23], active power flow betweenness (APFB) [24], and method proposed in [27]. The results for 21:00 are shown in Table 3.…”

Section: Feasibility Verification Of Key Node Identification Resultsmentioning

confidence: 99%

“…From Table 3, it can be observed that the ranking results obtained using the proposed method and the other three methods have a certain similarity. From a quantitative perspective, the similarities between the key node ranking results obtained by the proposed method and the APD index [23], APFB index [24], and index proposed in [27] were 80%, 70%, and 80%, respectively. Although each method identifies key nodes from different perspectives, most are included in the set of key nodes identified in this study, which verifies the effectiveness of the proposed method in this study.…”

Section: Feasibility Verification Of Key Node Identification Resultsmentioning

confidence: 99%

“…We compared the proposed method with the active power degree (APD) [23], active power flow betweenness (APFB) [24], and method proposed in [27]. The results for 21:00 are shown in Table 3.…”

Section: Case Studymentioning

confidence: 99%

“…Although each method identifies key nodes from different perspectives, most are included in the set of key nodes identified in this study, which verifies the effectiveness of the proposed method in this study. From the perspective of ranking, the DD index is the smallest between the node criticality ranking results obtained by the method in this study and the method in [27]. The APD and APFB indices comprehensively consider the network structure and actual operation characteristics of the distribution network, whereas the key node identification index in [27] comprehensively considers the importance of nodes in the network structure and the impact of nodes on the safe and economic operation of the distribution network.…”

Section: Case Studymentioning

confidence: 99%

See 3 more Smart Citations

Dynamic identification of key nodes in active distribution network for operation optimisation requirements

Liu

Sheng

et al. 2022

IET Generation Trans & Dist

Self Cite

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Accurate and dynamic identification of key nodes that can efficiently improve the safety and economy of active distribution network (ADN) is of great significance for optimising the operation level of ADN with time‐varying characteristics. In this study, a dynamic identification method for the key nodes of ADN operation optimisation requirements is proposed. Firstly, considering the influence of nodes on ADN operation performance, the importance of nodes in the network structure, and the controllable potential of nodes, a multi‐angle key node identification index system is constructed. Secondly, considering the influence of the ADN operation state on node importance, the classification boundary of ADN operation state was set to determine the operation state of the ADN at different times. Thirdly, the order relation analysis method and variation coefficient method were used to comprehensively evaluate the key nodes of the ADN under different operating states. Finally, the technique for order preference by similarity to an ideal solution is used to sort the comprehensive evaluation results of key nodes to achieve the effective identification of key nodes. The effectiveness and feasibility of the proposed method are verified on 33‐bus and 118‐bus test systems considering the time sequence variation in distributed generation and load.

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Section: Feasibility Verification Of Key Node Identification Resultsmentioning

confidence: 99%

Section: Feasibility Verification Of Key Node Identification Resultsmentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

Section: Case Studymentioning

confidence: 99%

See 2 more Smart Citations

Dynamic identification of key nodes in active distribution network for operation optimisation requirements

Liu

Sheng

et al. 2022

IET Generation Trans & Dist

Self Cite

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show abstract

“…Literature [22][23] studied the risks in the operation of the distribution network, and proposed an index system suitable for evaluating the operation risk of the distribution network. Literature [24] classifies and evaluates the urban distribution network from the perspective of safety and economy, and carries out a conceptual introduction to the development of power grids. It lacks a quantitative analysis from the perspective of the evolution of power grid development.…”

Section: Introductionmentioning

confidence: 99%

Research on Differentiated Classification System of Distribution Network Based on Grading and Zoning

Zhou

Deng²,

et al. 2021

IEEE Access

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In order to cope with multiple pressures such as ensuring the safe operation of the distribution network, promoting market-oriented operation, and satisfying rigid investment needs, power grid companies must implement a lean management approach. In response to the lack of systematic classification and evaluation methods for the distribution network in precise investment and future planning, this paper proposes a multi-dimensional hierarchical sub-regional distribution network differentiation classification system covering provinces, cities (counties), urban power supply units, towns, and villages. In the dimensions of provinces and cities (counties), based on the data fitting analysis of per capita electricity consumption, the classification method of the development stage of the power grids is obtained, and the provinces and cities (counties) are classified into pioneering benefits, steady improvement, and excellence three stages; in the dimension of urban power supply units, based on the combination of "top-down" and "bottom-up", the urban power supply units are divided into three categories: A+, A, and B; in the dimensions of towns and villages, according to characteristics indicators and construction models, proposed classification schemes for towns and villages. Finally, the results of an example analysis show that the differentiated classification system proposed in this paper can achieve an accurate assessment of the current development status of the distribution network, and provide important guidance for the precise investment of the distribution network in the future.

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Statistical method for identification of weak nodes in power system based on voltage magnitude deviation

Yusuff

Mosetlhe

Ayodele

2021

Electric Power Systems Research

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Critical node identification in active distribution network using resilience and risk theory

Cited by 20 publications

References 39 publications

Dynamic identification of key nodes in active distribution network for operation optimisation requirements

Dynamic identification of key nodes in active distribution network for operation optimisation requirements

Research on Differentiated Classification System of Distribution Network Based on Grading and Zoning

Statistical method for identification of weak nodes in power system based on voltage magnitude deviation

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