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Chupradit, S., Widjaja, G., Mahendra, S. J., Ali, M. H., Tashtoush, M. A., Surendar, A., Kadhim, M. M., Oudah, A. Y., Fardeeva, I., Firman, F.. (1402). Modeling and Optimizing the Charge of Electric Vehicles with Genetic ‎Algorithm in the Presence of Renewable Energy Sources. سامانه مدیریت نشریات علمی, 11(1), 33-38. doi: 10.22098/joape.2023.9970.1707
S. Chupradit; G. Widjaja; S. J. Mahendra; M. H. Ali; M. A. Tashtoush; A. Surendar; M. M. Kadhim; A. Y. Oudah; I. Fardeeva; F. Firman. "Modeling and Optimizing the Charge of Electric Vehicles with Genetic ‎Algorithm in the Presence of Renewable Energy Sources". سامانه مدیریت نشریات علمی, 11, 1, 1402, 33-38. doi: 10.22098/joape.2023.9970.1707
Chupradit, S., Widjaja, G., Mahendra, S. J., Ali, M. H., Tashtoush, M. A., Surendar, A., Kadhim, M. M., Oudah, A. Y., Fardeeva, I., Firman, F.. (1402). 'Modeling and Optimizing the Charge of Electric Vehicles with Genetic ‎Algorithm in the Presence of Renewable Energy Sources', سامانه مدیریت نشریات علمی, 11(1), pp. 33-38. doi: 10.22098/joape.2023.9970.1707
Chupradit, S., Widjaja, G., Mahendra, S. J., Ali, M. H., Tashtoush, M. A., Surendar, A., Kadhim, M. M., Oudah, A. Y., Fardeeva, I., Firman, F.. Modeling and Optimizing the Charge of Electric Vehicles with Genetic ‎Algorithm in the Presence of Renewable Energy Sources. سامانه مدیریت نشریات علمی, 1402; 11(1): 33-38. doi: 10.22098/joape.2023.9970.1707

Modeling and Optimizing the Charge of Electric Vehicles with Genetic ‎Algorithm in the Presence of Renewable Energy Sources

Journal of Operation and Automation in Power Engineering
دوره 11، شماره 1، تیر 2023، صفحه 33-38    اصل مقاله (562.7 K)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22098/joape.2023.9970.1707
نویسندگان
S. Chupradit1؛ G. Widjaja* 2؛ S. J. Mahendra3؛ M. H. Ali4؛ M. A. Tashtoush5، 6؛ A. Surendar7؛ M. M. Kadhim8، 9، 10؛ A. Y. Oudah9، 10؛ I. Fardeeva11؛ F. Firman12
1Department of Occupational Therapy, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, ‎‎50200, Thailand‎
2Faculty of Public Health, Universitas Indonesia; Faculty of Law, Universitas Krisnadwipayana
3Department of Medical Electronics, M S Ramaiah Institute of Technology, Bengaluru.‎
4Al-Nisour University College, Iraq
5AL-Balqa Applied University , AL-Huson College University , P. O. Box 50, AL-Huson 21510, Jordan, AL-Huson
6Sohar University, Faculty of Education & Arts, Sultanate of Oman
7Department of Pharmacology, saveetha dental College and hospital, saveetha institute of medical and technical ‎sciences, chennai, india
8Department of Dentistry, Kut University College, Kut, Wasit, 52001, Iraq
9Department of Computer Sciences, College of Education for Pure Science, University of Thi-Qar, Iraq
10Information and Communication Technology Research Group, Scientific Research Center, Al-Ayen University, Thi-‎Qar, Iraq
11Department of Legal Disciplines, Kazan Federal Uninersity, Kazan, Russia
12‎Institut Agama Islam Negeri Palopo, Indonesia
چکیده
In recent years, as a result of remarkable increase in energy industry, discrimination between lower and higher loads as well as economic crisis which pestered a majority of countries; hence the usage of power plants became a significant issue. In addition, growing consumption of power and inexistence of valid source in satisfying the requirements has brought different problems such as diminish of fossil fuel resources, adversarial environmental influences, universal growth of Greenhouse Gases (GHGs). The associated issues have created technologies compatible with situations including Electric Vehicles (EVs). Regarding the efficiency of two-side exchange of energy within these vehicles, if there was a connection among the number of them and net under management and intelligent monitor of organization stability, so they can treat like a virtual tiny energy plant with start- up speed and free of cost. This paper presented the modeling and optimizing of the charge of electric vehicles with genetic algorithm in the presence of renewable energy sources. According to the results of this study, the cost of the HEV charge connected to the net is 75.88% less than the EV compared to the payment costs of the car (dis)charge in optimal patterns.
کلیدواژه‌ها
Electric Vehicles (EVs)؛ Genetic Algorithm؛ Optimizing؛ Modeling؛ Renewable Energy Sources.‎
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