دورية أكاديمية

Situation awareness method of the distribution network based on EMD-SVD and Elman neural network

التفاصيل البيبلوغرافية
العنوان: Situation awareness method of the distribution network based on EMD-SVD and Elman neural network
المؤلفون: Yanhong Luo, Qiang Cheng, Shijie Yan, Dongsheng Yang
المصدر: Energy Reports, Vol 8, Iss , Pp 632-639 (2022)
بيانات النشر: Elsevier, 2022.
سنة النشر: 2022
المجموعة: LCC:Electrical engineering. Electronics. Nuclear engineering
مصطلحات موضوعية: Distribution network, EMD, SVD, Elman neural network, Situation awareness, Singular value entropy, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: In order to ensure reliability and security of power supply, the situation awareness of some elements in the distribution network is studied in this paper. Considering the influence of the interference signal, Empirical Mode Decomposition (EMD) is introduced to reduce it. Subsequently, according to operation characteristics of the actual distribution network, several evaluation indexes are proposed to describe the operation situation of the overall distribution network and internal elements, especially evaluation of fragile nodes. Based on these indexes and characteristics of actual distribution network, the comprehensive evaluation method of fragile nodes (CEMFN) is constructed, which mainly aims at the fragile nodes in the distribution network and synthesizes the single index coefficient to realize the identification of fragile nodes. Through the simulation calculation, it can be seen that the result of CEMFN is more accurate than that of the traditional evaluation model, which provides an important theoretical support for the operation and maintenance of distribution network and reliable power supply.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2352-4847
Relation: http://www.sciencedirect.com/science/article/pii/S2352484722010630; https://doaj.org/toc/2352-4847
DOI: 10.1016/j.egyr.2022.05.212
URL الوصول: https://doaj.org/article/7532b2ddb389454e9f85522321524924
رقم الأكسشن: edsdoj.7532b2ddb389454e9f85522321524924
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:23524847
DOI:10.1016/j.egyr.2022.05.212