Power network robustness analysis based on electrical engineering and complex network theory

Zhou, Dongyue; Hu, Funian; Wang, Shuliang

doi:10.1016/j.physa.2020.125540

Cited by 36 publications

(10 citation statements)

References 16 publications

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“…The term "robustness" in this paper is primarily concerned with the drop in performance of a power grid when a disruption occurs [18]. Several metrics have been proposed in the literature to study and improve the system robustness against node/link failures [3], [6], [10], [18], [19]. These approaches can be divided into three classes, namely network (topology) based, performance (power flow, system dynamics) based and hybrid which combines topology with electrical properties of the network.…”

Section: Robustness Metricsmentioning

confidence: 99%

“…• Active power flow loss (APL): The power supplied (PS) is an essential measurement in DC power flow model. Its loss can be evaluated as [10]:…”

Section: ) Performance-based Metricsmentioning

confidence: 99%

“…of the system. Therefore, there is a growing interest in combining both the factors to obtain novel metrics that can better capture network robustness to failures [10]. Some of the hybrid metrics that have been found to work well are presented below: • Electrical betweenness (EBW): The electrical betweenness centrality of a node u in a network of N nodes is defined as [23];…”

Section: ) Hybrid Metricsmentioning

confidence: 99%

“…Network theorybased metrics solely involve topological characteristics such as degree, betweenness, etc., whereas performance-based metrics deal with the electrical properties of the network like power flow, and branch impedances [6], [8]. There are also several works in the literature that take a hybrid approach of fusing both these classes [9], [10]. This fusion leads to more effective metrics for quantifying a node's role in determining the entire system's robustness to failures caused by extreme natural events and/or cyber intrusions.…”

Section: Introductionmentioning

confidence: 99%

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Robustness of Power Distribution System: A Comparative Study of Network and Performance Based Metrics

2022

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Improving the resilience of the power distribution networks is becoming a top priority for the utility companies. Robustness is a key part of resilience, and is often studied through failure-based analysis. Furthermore, with the increasingly dynamic nature of the grid, voltage fluctuation is an important factor to consider while assessing system robustness. Very few metrics exist for capturing robustness to voltage fluctuations, primarily due to their complex computation process. While several failure-based robustness metrics have been proposed in the literature, there is no strict consensus regarding the applicability of these metrics. Therefore, this paper addresses two key gaps in robustness analysis of power distribution networks. First, this paper presents a systematic study of different failure-based robustness metrics by comparing their similarity and dissimilarity in ranking critical nodes of the power distribution network. Secondly, the efficacy of these metrics in characterizing voltage fluctuations is evaluated by comparing their ranking to that of voltage influencing scores. From experimental results, it is shown that hybrid failure-based metrics can quantify voltage fluctuations to a reasonable extent. We highlight the major shortcomings of current metric formulations and discuss possible future research directions related to robustness characteristics and analysis.

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Section: Robustness Metricsmentioning

confidence: 99%

“…• Active power flow loss (APL): The power supplied (PS) is an essential measurement in DC power flow model. Its loss can be evaluated as [10]:…”

Section: ) Performance-based Metricsmentioning

confidence: 99%

Section: ) Hybrid Metricsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robustness of Power Distribution System: A Comparative Study of Network and Performance Based Metrics

2022

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“…For the three stages during the resilience process, the previous studies have proposed various models and methods to enhance power network resilience. A large number of scholars have modeled cascading failure and studied the impact of different critical factors on performance from a network science perspective by abstracting the power network into graphs [14][15][16][17][18]. Indeed, power network resilience is largely determined by the recovery process that occupies the largest portion of the whole resilience process.…”

Section: Introductionmentioning

confidence: 99%

Bottlenecks Identification and Resilience Improvement of Power Networks in Extreme Events

Zhang

Xia

et al. 2022

Front. Phys.

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Extreme events are always accompanied with extensive failures and sharp performance degradation in the power network. This study aims to derive an effective scheme to identify the transmission bottlenecks and improve the power network’s resilience under extreme events. A greedy search scheme is designed for the quick and slow restoration stage to obtain the largest power supply (LPS), which is a significant engineering indicator of the power network. In the quick restoration stage, we use interior point optimization to adjust the operating parameters of undamaged components and maximize the LPS with limited resources. It is worth pointing out that the LPS cannot be further improved, even by increasing the capacities of most transmission links. This phenomenon is due to the existence of transmission bottlenecks, which operate at their capacity limits. Thus, in the slow restoration stage, we identify these transmission bottlenecks and further improve the LPS by expanding the capacities of these links. Case studies show that the proposed greedy search scheme can not only greatly improve the LPS available to the post-disaster network but can also accurately identify the transmission bottlenecks. This work provides practical insights for building resilient infrastructures, although the power network is the object of study.

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A novel vulnerability measure based on complex network communities

Jouyban,

Hosseini

2024

Softw Pract Exp

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This article introduces a novel vulnerability measure, based on the structure of complex network communities, to assess the significance and security of network communities, influencing complex network security, connectivity, and the prevention of cascading failures. Initially, the spectral clustering algorithm is applied to identify the communities of complex networks. Determining the appropriate number of communities is crucial in the proposed vulnerability measure and security approach. The number of communities is estimated based on the characteristics of the normalized Laplace matrix within the algorithm. Subsequently, leveraging the community structure, a vulnerability measure is proposed for community evaluation by considering three aspects of internal criteria, external criteria and node location criterion. Weight parameters are also incorporated to customize the measure according to the importance of each factor in varying security scenarios. Finally, the effectiveness of the proposed vulnerability measure as a security strategy is evaluated on ten real‐world complex networks from different categories. The experimental results demonstrate the effectiveness and efficiency of the proposed measure in assessing community vulnerability and consequently using appropriate maps and policies for the complex network security.

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Power network robustness analysis based on electrical engineering and complex network theory

Cited by 36 publications

References 16 publications

Robustness of Power Distribution System: A Comparative Study of Network and Performance Based Metrics

Robustness of Power Distribution System: A Comparative Study of Network and Performance Based Metrics

Bottlenecks Identification and Resilience Improvement of Power Networks in Extreme Events

A novel vulnerability measure based on complex network communities

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