Recent Research Trends of Artificial Intelligence Applications in Power Electronics

被引：0
|
作者：
Kurokawa, Fujio [1 ]
Tanaka, Masaharu [1 ]
Furukawa, Yudai [1 ,2 ]
Matsui, Nobumasa [1 ]
机构：
[1] Nagasaki Inst Appl Sci, Inst Innovat Sci & Technol, Nagasaki, Japan
[2] Fukuoka Univ, Fac Engn, Fukuoka, Japan
来源：
INTERNATIONAL JOURNAL OF RENEWABLE ENERGY RESEARCH | 2021年 / 11卷 / 03期
关键词：
Artificial Intelligence (AI); Convolutional Neural Network (CNN); Evolutionary Multi-Objective Optimization (EMO); IEEE Xplore; Neural Network (NN); Power Electronics; Renewable Energy System; NEURAL-NETWORK; GENETIC ALGORITHM; ENERGY MANAGEMENT; OPTIMIZATION; SYSTEM; CONVERTERS; OPERATION;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
artificial intelligence (AI) is one of the most significant topics to obtain an optimal solution in various applications. Focusing on the AI applications to the power electronics, this paper presents their tendency and future trend systematically and exhaustively. In the process, IEEE Xplore is chosen for the paper investigation and the result is arranged chronologically. Furthermore, several considerable AI methods for the power electronics, such as the neural network, deep learning, genetic algorithm, particle swarm optimization, and multi-objective optimization, are explained. Several published papers with respect to AI applications to the power electronics in the renewable energy system are also introduced.
引用
收藏
页码：1370 / 1381
页数：12
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