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.

引用

页数：9

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