2022
DOI: 10.3390/sym14050985
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TOPSIS-Based Algorithm for Resilience Indices Construction and the Evaluation of an Electrical Power Transmission Network

Abstract: In the context of energy transformation, new energy technologies are developing rapidly, the penetration rate of new energy is increasing, and the energy structure tends to be low-carbon, which leads to the asymmetry between traditional energy and new energy. At present, the smart power grid can be conceived as a complex cyber-physical system, and its resilience assessment in the face of extreme disasters needs more holistic consideration. Therefore, considering the impact of massive access to new energy on th… Show more

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Cited by 4 publications
(2 citation statements)
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“…In a similar study, Babatunde and Ighravwe (2019) presented a viable analysis to deploy a hybrid renewable energy system within low-income household using the CRITIC-TOPSIS technique. The same model was propounded by Gu and Liu (2022) to address the evaluation of the main power grid resilience under the background of energy transformation considering the impacts of extreme disasters. In Bangladesh, Ali et al (2020) developed a novel CRITIC-CODAS model to investigate the feasibility of deploying hybrid RES within the coastal regions.…”
Section: Related Literaturementioning
confidence: 99%
“…In a similar study, Babatunde and Ighravwe (2019) presented a viable analysis to deploy a hybrid renewable energy system within low-income household using the CRITIC-TOPSIS technique. The same model was propounded by Gu and Liu (2022) to address the evaluation of the main power grid resilience under the background of energy transformation considering the impacts of extreme disasters. In Bangladesh, Ali et al (2020) developed a novel CRITIC-CODAS model to investigate the feasibility of deploying hybrid RES within the coastal regions.…”
Section: Related Literaturementioning
confidence: 99%
“…Additionally, Diakoulaki et al [47] presented the CRITIC technique, which uses correlation analysis to identify comparisons between criteria, decreasing the influence of partially correlated indicators and further reducing indicator information overlap. The calculation is also carried out using Matlab software [48,49]. Assuming that the three methods have the same relevance [50,51] and setting α = β = γ = 1/3, the cumulative weights are as follows:…”
Section: Calculation Of Indicator Data Weightingmentioning
confidence: 99%