Fault Detection and Location in DC Microgrids by Recurrent Neural Networks and Decision Tree Classifier
نویسندگان
چکیده مقاله:
Microgrids have played an important role in distribution networks during recent years. DC microgrids are very popular among researchers because of their benefits. Protection is one of the significant challenges in the way of microgrids progress. As a result, in this paper, a fault detection and location scheme for DC microgrids is proposed. Due to advances in Artificial Intelligence (AI) and suitable performance of smart protection methods in AC microgrids, Recurrent Neural Networks (RNNs) are used in the proposed method for fault location in DC microgrids. In this method, the fault detection and location are done by measuring feeders current and main bus voltage. Further, the performance of the proposed method is assessed in grid-connected, and islanded operation modes of the microgrid. The result will confirm the efficiency of the proposed scheme. In this paper, MATLAB and DIgSILENT are used to design RNNs and DC microgrid simulation respectively.
منابع مشابه
fault location in power distribution networks using matching algorithm
چکیده رساله/پایان نامه : تاکنون روشهای متعددی در ارتباط با مکان یابی خطا در شبکه انتقال ارائه شده است. استفاده مستقیم از این روشها در شبکه توزیع به دلایلی همچون وجود انشعابهای متعدد، غیر یکنواختی فیدرها (خطوط کابلی، خطوط هوایی، سطح مقطع متفاوت انشعاب ها و تنه اصلی فیدر)، نامتعادلی (عدم جابجا شدگی خطوط، بارهای تکفاز و سه فاز)، ثابت نبودن بار و اندازه گیری مقادیر ولتاژ و جریان فقط در ابتدای...
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عنوان ژورنال
دوره 11 شماره 4
صفحات 0- 0
تاریخ انتشار 2022-01
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