Critical Node Identification Method of Power Grid Based on the Improved Entropy Weight Method

Li, G.H.; Zhang, Lixia; Wang, Yang; Kang, Zhengming

doi:10.3390/electronics12112439

Cited by 5 publications

(1 citation statement)

References 24 publications

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“…The power supply capacity is an indicator that characterizes the effective capacity of a distribution network to supply power, and it reflects the network's ability to transmit power during operation [29]. If a node failure results in a significant decrease in the system's power supply capacity, it suggests that the node has a more significant impact.…”

Section: Verification Methods For Vulnerable Nodesmentioning

confidence: 99%

Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory

Jiang,

Zhang,

Xue

et al. 2023

IET Generation Trans & Dist

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A method for identifying vulnerable nodes in distribution networks is proposed, which is based on complex networks and optimized TOPSIS. This method aims to address the issues of one‐sided evaluation indicators and inaccurate indicator weights that are present in existing methods for identifying vulnerable nodes in distribution networks. Based on the theory of complex networks, a comprehensive set of vulnerability indicators for distribution network nodes is constructed by considering both the topology structure and system operation status of the distribution network. The TOPSIS comprehensive evaluation model for optimization is proposed to enhance the selection process of optimal and worst indicator values. The advantages and disadvantages of each indicator are characterized using Mahalanobis distance. The calculation of proximity is optimized by establishing a virtual negative ideal solution, which makes the identification of vulnerable nodes more reasonable. The simulation results demonstrate that this method is more effective in identifying vulnerable nodes in the power grid compared to traditional methods, and has significant practical applications.

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Section: Verification Methods For Vulnerable Nodesmentioning

confidence: 99%

Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory

Jiang,

Zhang,

Xue

et al. 2023

IET Generation Trans & Dist

View full text Add to dashboard Cite

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Exploration of the utilization of a new land degradation index in Lake Ebinur Basin in China

Shi,

An,

Peng

et al. 2024

Sci Rep

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Land degradation significantly impacts regional economic development and food security, particularly in arid river basins where soil and water conservation is crucial. Understanding the extent and causes of land degradation is pivotal for effectively prevention and management. This study employs the soil adjusted vegetation index (SAVI), the temperature vegetation dryness index (TVDI), and the salinization detection index (SDI), combined with the analytic hierarchy process and the entropy weight method, to construct a comprehensive land degradation index (LDI). Sen’s slope trend analysis and the Mann-Kendall significance test were used to analyze land degradation trends in the Ebinur Lake watershed from 2002 to 2022. Additionally, the optimal parameters-based geographical detector was used to examine the underlying mechanisms of land degradation. The results indicate the following: (1) From 2002 to 2012, the degree of land degradation in the Ebinur Lake watershed worsened, particularly in the eastern and southeastern parts, as well as in the southern region of Toli County. From 2012 to 2022, land degradation significantly improved, with a notable reduction in degraded land area. (2) Over the period of 2002-2022, of the land in the research region exhibited a declining LDI trend, showed no change, and only showed an increasing LDI trend. (3) Moderate, severe, and very severe degradation mainly occurred on grassland and unused land, while light degradation and non-degradation primarily occurred on forest land and cultivated land. (4) Unreasonable land use and overgrazing were identified as the primary factors influencing land degradation, with elevation being a secondary factor. The interaction between land use and other factors was found to be most significant, followed by the synergistic effects of grazing quantity with elevation, annual average temperature, gross domestic product, soil moisture, and elevation with annual average precipitation, and temperature. The results of this study offer an empirical basis and taking decisions assistance for land degradation control in the Ebinur Lake Basin, as well as examples and references for assessing land degradation in other places.

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Decision-making for stochastic multi-objective dispatch of integrated electrical and heating systems

Xu,

Li,

et al. 2023

Journal of Renewable and Sustainable Energy

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In the realm of modern energy systems, addressing the challenges of enhancing flexibility and efficiency under uncertain conditions is of paramount importance. This paper explores the stochastic multi-objective optimal multi-energy flow problem within the context of integrated electrical and heating systems (IEHS). First, the electrical network, the heating network, and the energy hubs were modeled in a completely linearized form. The linear weighted sum method with variable weights was used to transform the multi-objective problem into a single-objective problem and generate a large number of Pareto-optimal solutions. Second, the input stochastic variables were divided into multi-interval scenarios by employing the Cartesian product. For each interval scenario, the interval satisfaction degree level was proposed to convert the constraints involving interval numbers into deterministic ones. Third, a multiple attributes decision analysis (MADA) approach was proposed based on evidential reasoning theory. Six evaluation attributes, namely, the power purchase cost and pollution gas emissions of IEHS, the sum of power loss and sum of voltage deviation in the electrical system, the sum of temperature drop in the heating system, and the interval probability value of the multi-interval scenarios, were considered to rank the Pareto-optimal solutions collected from the multi-interval scenarios and determine the final dispatch solution (called the Utopia solution). Numerical simulations demonstrated that the Utopia solution can comprehensively evaluate various attributes, making it the most suitable option for meeting the operational requirements of IEHS.

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Critical Node Identification Method of Power Grid Based on the Improved Entropy Weight Method

Cited by 5 publications

References 24 publications

Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory

Vulnerable node identification method for distribution networks based on complex networks and improved TOPSIS theory

Exploration of the utilization of a new land degradation index in Lake Ebinur Basin in China

Decision-making for stochastic multi-objective dispatch of integrated electrical and heating systems

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