Data-driven real-time risk assessment of resilient distribution system during typhoon weather

التفاصيل البيبلوغرافية
العنوان: Data-driven real-time risk assessment of resilient distribution system during typhoon weather
المؤلفون: Liang Yi, Fei Liu, Xin Li, Huili Tian, Gengfeng Li, Liyin Zhang, Chaofan Lin, Zhaohong Bie
المصدر: 2020 4th International Conference on HVDC (HVDC).
بيانات النشر: IEEE, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Scheme (programming language), Computer science, business.industry, Data-driven, Reliability engineering, Software, Typhoon, Entropy (information theory), Tropical cyclone, business, Risk assessment, computer, Risk management, computer.programming_language
الوصف: Coastal distribution systems are vulnerable to typhoon weather. An efficient and accurate real-time risk assessment is very necessary in providing timely warning information for decision making. However, the conventional risk assessment methods are subject to varied typology, parameters and uncertainties. While in current data-driven methods, the effect of complex factors such as resilient resources and emergency response are difficult to be analytically incorporated in risk assessment procedure. To solve the problems, this paper proposes an improved data-driven real-time risk assessment method for resilient distribution systems during typhoon weather. A comprehensive risk-oriented database with 25 indexes is constructed based on practical experience in system operation. And then the effects of various complex factors on distribution system risk are characterized by entropy weights and gray correlation degrees. The case study on a modified 33-node system has validated the proposed method in real-time risk assessment. The whole scheme can be helpful for the software and hardware update of resilient distribution systems.
DOI: 10.1109/hvdc50696.2020.9292744
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::272868ab1ddae0df52caf25ce5fce0a0
https://doi.org/10.1109/hvdc50696.2020.9292744
Rights: CLOSED
رقم الانضمام: edsair.doi...........272868ab1ddae0df52caf25ce5fce0a0
قاعدة البيانات: OpenAIRE
الوصف
DOI:10.1109/hvdc50696.2020.9292744