Smart Charging Strategy for Electric Vehicles Using an Optimized Fuzzy Logic System

被引：0
|
作者：
Gholami, M. [1 ,2 ,3 ]
Mehrasa, M. [1 ,2 ]
Razi, R. [4 ]
Hajar, K. [4 ]
Hably, A. [4 ]
Bacha, S. [1 ,2 ,5 ]
Labonne, A.
机构：
[1] Univ Grenoble Alpes, CNRS, Grenoble INP, Grenoble, France
[2] G2Elab, Grenoble, France
[3] Univ Kurdistan, Fac Engn, Sanandaj, Iran
[4] GIPSA Lab, Grenoble, France
[5] Univ Grenoble Alpes, SuperGrid Inst, Inst Engn, Grenoble, France
来源：
2022 24TH EUROPEAN CONFERENCE ON POWER ELECTRONICS AND APPLICATIONS (EPE'22 ECCE EUROPE) | 2022年
关键词：
Electric vehicle; Energy management; Optimized Fuzzy system; Genetic algorithm; Smart charging;
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：
The increasing growth of electric vehicles (EVs) may arise as a challenge of increasing the load. Therefore, energy management in microgrids, including renewable energy resources such as PV systems, would be essential. Moreover, providing a smart charging pattern can optimize the overall cost of energy in a microgrid. In this paper, a genetic algorithm-based optimized fuzzy technique is developed, which has simple implementation such as rule-based methods and provides the optimal operation. The proposed scheme is simulated in MATLAB/Simulink environment for a case study. Results show the effectiveness of the proposed approach in comparison to conventional models.
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收藏
页数：9
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