A Safety Evaluation Method for a Power System Influenced by a Geomagnetic Storm

Shu-ming, Zhang; Liu, Lianguang

doi:10.1109/access.2020.2994644

Cited by 6 publications

(1 citation statement)

References 17 publications

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“…In [26] ， The insufficient ramping resource expectation (IRRE) metric is proposed to measure power system flexibility for use in longterm planning, and is derived from traditional generation adequacy metrics. In [27], Based on the mechanisms of the cascading failures caused by geomagnetic storms, the technical requirements for the power system safety assessment of geomagnetic storm disasters are analyzed, and an evaluation method is proposed. Through the improvement of research methods, the comprehensiveness of distribution network research has been improved.…”

Section: B Different Research Methodsmentioning

confidence: 99%

Adaptability Evaluation of Distributed Power Sources Connected to Distribution Network

2021

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At present, the distribution network is in an important opportunity period of rapid development and improvement of efficiency. A large amount of new energy and distributed energy are connected to the distribution network, which is beyond the capacity of some power grids. Therefore, the influence of nearby access of distributed power sources such as wind power and solar power on the distribution network is taken into account. This paper evaluates and studies the adaptability of distribution network after distributed power supply is connected to distribution network. Firstly, a new definition of the adaptability of distribution network is given. and the adaptability evaluation system of distribution network is sorted out and identified based on this, and the index system of adaptability evaluation of distribution network is constructed. Then the combined weight of the evaluation model is determined by the Analytic Hierarchy Process (AHP) and Entropy Weight method (EM). Then, a distribution network adaptability evaluation model based on quantum adaptive particle swarm optimization support vector machine (QAPSO-SVM) is constructed. Finally, through the comparative analysis of examples and the sensitivity analysis of the results, the superiority of the quantum adaptive particle swarm optimization support vector machine model in the adaptability evaluation of distribution network is proved.INDEX TERMS Distribution network adaptability, analytic hierarchy process, entropy weight method, combined weight, sensitivity analysis, QAPSO-SVM.

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Section: B Different Research Methodsmentioning

confidence: 99%