کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5483169 1522312 2017 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Fault location and detection techniques in power distribution systems with distributed generation: A review
ترجمه فارسی عنوان
محل ناهنجاری و تکنیک های تشخیص در سیستم های توزیع برق با تولید توزیع شده: بررسی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
Distribution systems are continuously exposed to fault occurrences due to various reasons, such as lightning strike, failure of power system components due to aging of equipment and human errors. These phenomena affect the system reliability and results in expensive repairs, lost of productivity and power loss to customers. Since fault is unpredictable, a fast fault location and isolation is required to minimize the impact of fault in distribution systems. Therefore, many methods have been developed since the past to locate and detect faults in distribution systems with distributed generation. The methods can be divided into two categories, conventional and artificial intelligence techniques. Conventional techniques include travelling wave method and impedance based method while artificial intelligence techniques include Artificial Neural Network (ANN), Support Vector Machine (SVM), Fuzzy Logic, Genetic Algorithm (GA) and matching approach. However, fault location using intelligent methods are challenging since they require training data for processing and are time consuming. In this paper, most of the techniques that have been developed since the past and commonly used to locate and detect faults in distribution systems with distributed generation are reviewed. Research works in fault location area, the working principles, advantages and disadvantages of past works related to each fault location technique are highlighted in this paper. Hence, from this review, the opportunities in fault location research area in power distribution system can be explored further.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Renewable and Sustainable Energy Reviews - Volume 74, July 2017, Pages 949-958
نویسندگان
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