Scipediacontent: Scipediacontent moved page Draft Content 801758523 to Alci Dogan 2017a

2021-02-16T09:17:43Z

Scipediacontent moved page Draft Content 801758523 to Alci Dogan 2017a

Scipediacontent: Created page with " == Abstract == It is expected that electric vehicles (EVs) will be important part of smart gird, not only in form of load but also as distributed energy source in Vehicle to..."

2021-02-16T09:17:37Z

Created page with " == Abstract == It is expected that electric vehicles (EVs) will be important part of smart gird, not only in form of load but also as distributed energy source in Vehicle to..."

New page

== Abstract ==

It is expected that electric vehicles (EVs) will be important part of smart gird, not only in form of load but also as distributed energy source in Vehicle to Grid (V2G) system. As increase of EVs integration, V2G contributes to improve flexibility, reliability and stability of grid by providing ancillary services. These services, however, could accelerate degradation of battery whose price is almost half of EV. Thus, battery degradation cost must be considered while scheduling of EV charging. In this paper, a battery degradation cost model of EV lithium-ion batteries was incorporated in the optimal charging schedule of 400 EVs. EVs are located to 33 bus system in order to consider network losses in calculations. Heuristic algorithms such as Genetic Algorithm (GA), Differential Evolution (DE), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) are used for solving the associated optimization problem. The objective function aims to maximize user profit under dynamic pricing. Also, distribution system and EVs constraints are considered during optimization. The numerical results illustrate that each of the used heuristic algorithms able to mitigate peak loads and improve voltage levels. GA presents the most profitable charging scheduling in terms of EV owners. DOI: http://dx.doi.org/10.5755/j01.eie.24.6.22283

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.5755/j01.eie.24.6.22283 http://dx.doi.org/10.5755/j01.eie.24.6.22283]

* [http://eejournal.ktu.lt/index.php/elt/article/download/22283/9691 http://eejournal.ktu.lt/index.php/elt/article/download/22283/9691]

* [https://avesis.erciyes.edu.tr/publication/details/31c6b77a-0d59-4316-a3b8-a000f8cd3063/oai https://avesis.erciyes.edu.tr/publication/details/31c6b77a-0d59-4316-a3b8-a000f8cd3063/oai]

* [http://eejournal.ktu.lt/index.php/elt/article/view/22283 http://eejournal.ktu.lt/index.php/elt/article/view/22283],
: [http://eejournal.ktu.lt/index.php/elt/article/view/22283/9691 http://eejournal.ktu.lt/index.php/elt/article/view/22283/9691],
: [https://avesis.erciyes.edu.tr/yayin/31c6b77a-0d59-4316-a3b8-a000f8cd3063/heuristic-optimization-of-ev-charging-schedule-considering-battery-degradation-cost https://avesis.erciyes.edu.tr/yayin/31c6b77a-0d59-4316-a3b8-a000f8cd3063/heuristic-optimization-of-ev-charging-schedule-considering-battery-degradation-cost],
: [https://academic.microsoft.com/#/detail/2907356271 https://academic.microsoft.com/#/detail/2907356271]

* [http://eejournal.ktu.lt/index.php/elt/article/view/22283 http://eejournal.ktu.lt/index.php/elt/article/view/22283],
: [https://doaj.org/toc/1392-1215 https://doaj.org/toc/1392-1215],
: [https://doaj.org/toc/2029-5731 https://doaj.org/toc/2029-5731]

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Alci Dogan 2017a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 801758523 to Alci Dogan 2017a

Scipediacontent: Created page with " == Abstract == It is expected that electric vehicles (EVs) will be important part of smart gird, not only in form of load but also as distributed energy source in Vehicle to..."