Reliability evaluation of an aggregate power conversion unit in the off-grid PV-battery-based DC microgrid from local energy communities under dynamic and transient operation

Kuo, Tsai‐Chi; Pham, Trang; Bùi, Dương Minh; Le, Phuong; Van, Tan Luong; Huang, PoTsang B.

doi:10.1016/j.egyr.2022.03.190

Cited by 17 publications

(1 citation statement)

References 39 publications

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“…As a real-time dynamic system, the HSoE in the distribution court is not only determined by its own operating conditions, but also greatly affected by the changes in the external environment and its own needs. Therefore, its evaluation system needs not only the theory and tools of the system but also the extension of the research object from the equipment to the network as well as the development of a data platform supporting the health theory of the distribution system (Envelope et al, 2022;Song et al, 2022). How to evaluate the overall health status of a large quantity of equipment and systems in the complex dynamic DN poses a key challenge in the development of SG.…”

Section: Introductionmentioning

confidence: 99%

Health Assessment Method of Equipment in Distribution Court Based on Big Data Analysis in the Framework of Distribution Network of Things

Long

Wang

Liang³

et al. 2023

International Journal of Information Technologies and Systems Approach

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Focusing on the problem that the quantity of equipment in the distribution court is huge and the operation status is difficult to reliably control, a method of equipment health status assessment in the distribution court based on big data analysis in the distribution network of things architecture is proposed. Firstly, based on the internet of things for power distribution, the evaluation system of equipment status in the distribution court is designed to ensure the efficient analysis of massive data through the cooperation of cloud center and edge computing. Then, at the edge of the system, the grey correlation analysis algorithm and the Granger hypothesis method are used to obtain the correlation and causality of the failure rate of equipment components and the influencing factors so as to understand the accurate failure rate of equipment components. Finally, the weight of factors affecting the equipment failure rate is identified by using the dynamic variable weight analytic hierarchy process, and it is corrected in the cloud center; and the overall health degree of the equipment in the distribution court is obtained through transformation. Based on the selected station area model, the proposed method is experimentally demonstrated. The results show that it can accurately obtain the real-time health status of the court equipment and the evaluation accuracy is close to 98%, which provides theoretical support for the operation and maintenance of the distribution network.

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Section: Introductionmentioning

confidence: 99%