A Fuzzy-Genetic-Based Integration of Renewable Energy Sources and E-Vehicles

Himanshi Agrawal, Akash Talwariya, Amandeep Gill, Aman Singh, Hashem Alyami, Wael Alosaimi and Arturo Ortega-Mansilla
Additional contact information
Himanshi Agrawal: Department of Electrical Engineering, JECRC University, Rajasthan 303905, India
Akash Talwariya: Department of Electrical Engineering, JECRC University, Rajasthan 303905, India
Amandeep Gill: Department of Electrical Engineering, Chandigarh University, Punjab 140413, India
Aman Singh: Higher Polytechnic School, Universidad Europea del Atlántico, C/Isabel Torres 21, 39011 Santander, Spain
Hashem Alyami: Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
Wael Alosaimi: Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia
Arturo Ortega-Mansilla: Higher Polytechnic School, Universidad Europea del Atlántico, C/Isabel Torres 21, 39011 Santander, Spain

Energies, 2022, vol. 15, issue 9, 1-15

Abstract: E-Vehicles are used for transportation and, with a vehicle-to-grid optimization approach, they may be used for supplying a backup source of energy for renewable energy sources. Renewable energy sources are integrated to maintain the demand of consumers, mitigate the active and reactive power losses, and maintain the voltage profile. Renewable energy sources are not supplied all day and, to meet the peak demand, extra electricity may be supplied through e-Vehicles. E-Vehicles with random integration may cause system unbalancing problems and need a solution. The objective of this paper is to integrate e-Vehicles with the grid as a backup source of energy through the grid-to-vehicle optimization approach by reducing active and reactive power losses and maintaining voltage profile. In this paper, three case studies are discussed: (i) integration of renewable energy sources alone; (ii) integration of e-Vehicles alone; (iii) integration of renewable energy sources and e-Vehicles in hybrid mode. The simulation results show the effectiveness of the integration and the active and reactive power losses are minimum when we used the third case.

Keywords: renewable energy sources; E-Vehicle charging station; fuzzy logic approach; genetic algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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