Based on The Multi-index Quantitative Evaluation Model of Health Status of Distributed Distribution Network
Year: 2024
Type: article
Abstract: With the rapid development of smart grids, accurate and timely assessment of the health status of distribution networks is crucial. This article proposes a multi-indicator quantitative evaluation model based on the health status of distributed distribution networks. The model incorporates diverse pivotal metrics about the distribution network, encompassing voltage stability, equipment senescence, and fault occurrence frequencies. Leveraging sophisticated data analytics techniques facilitates a quantitative appraisal of the network’s overall health status. To delve deeper into the efficacy of intelligent distribution network situational awareness, this study presents a comprehensive evaluation framework encompassing a robust index system and evaluation methodologies. The comprehensive evaluation index system includes five primary indicators, as well as a total of 17 secondary indicators, to objectively quantify the effectiveness of intelligent distribution network situational awareness. This paper uses a subjective and objective mixed evaluation method based on the binomial coefficient and multi-objective planning methods to weight the comprehensive evaluation index system. The comprehensive evaluation model for the implementation effect of intelligent distribution network situational awareness proposed in this article objectively and accurately reflects the operation status of the distribution network, eliminates the one-sidedness of a single evaluation method, effectively improves the observability of the intelligent distribution network, and realizes the analysis of weak links and potential risks in the distribution network.
Authors: Yao Zhang, Zhongqiang Zhou, Yin Lian, Kun Zhou, Qihong Shi
Language: English
Topic: Smart Grid and Power Systems
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4407979644