AI-based fault recognition and classification in the IEEE 9-bus system interconnected to PV systems

IF 2.4 Q2 MULTIDISCIPLINARY SCIENCES

Smart Science Pub Date : 2023-11-23 DOI:10.1080/23080477.2023.2285275

Hinal Shah, Nilesh G. Chothani, Jaydeep Chakravorty

引用次数: 0

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与光伏系统互联的 IEEE 9 总线系统中基于人工智能的故障识别和分类

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Smart Science Engineering-Engineering (all)

CiteScore

4.70

自引率

4.30%

发文量

期刊介绍： Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials