A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network
<p dir="ltr">The transportation sector is one of the most prevalent fossil fuel users worldwide. Therefore, to mitigate the impacts of carbon-dioxide emissions and reduce the use of non-environmentally friendly traditional energy resources, the electrification of the transportation s...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , |
| Published: |
2022
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1864513539447717888 |
|---|---|
| author | Fareed Ahmad (134672) |
| author2 | Imtiaz Ashraf (16876050) Atif Iqbal (5504636) Mousa Marzband (17148343) Irfan Khan (640146) |
| author2_role | author author author author |
| author_facet | Fareed Ahmad (134672) Imtiaz Ashraf (16876050) Atif Iqbal (5504636) Mousa Marzband (17148343) Irfan Khan (640146) |
| author_role | author |
| dc.creator.none.fl_str_mv | Fareed Ahmad (134672) Imtiaz Ashraf (16876050) Atif Iqbal (5504636) Mousa Marzband (17148343) Irfan Khan (640146) |
| dc.date.none.fl_str_mv | 2022-11-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.egyr.2022.09.058 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/A_novel_AI_approach_for_optimal_deployment_of_EV_fast_charging_station_and_reliability_analysis_with_solar_based_DGs_in_distribution_network/24551368 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Automotive engineering Electrical engineering Information and computing sciences Artificial intelligence Artificial Intelligence Fast-charging stations Bald eagle search algorithm Optimal placement Electric vehicle Reliability |
| dc.title.none.fl_str_mv | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The transportation sector is one of the most prevalent fossil fuel users worldwide. Therefore, to mitigate the impacts of carbon-dioxide emissions and reduce the use of non-environmentally friendly traditional energy resources, the electrification of the transportation system, such as the development of electric vehicles (EV), has become crucial. For impeccable EVs deployment, a well-developed charging infrastructure is required. However, the optimal placement of fast charging stations (FCSs) is a critical concern. Therefore, this article provides a functional approach for identifying the optimal location of FCSs using the east delta network (EDN). In addition, the electrical distribution network’s infrastructure is susceptible to changes in electrifying the transportation sector. Therefore, actual power loss, reactive power loss, and investment cost are three areas of consideration in deploying FCSs. Furthermore, including FCSs in the electricity distribution network increases the energy demand from the electrical grid. Therefore, this research paper recommends integrating solar-based distributed generations (SDGs) at selected locations in the distribution network, to mitigate the burden of FCSs on the system. Hence, making the system self-sustaining and reliable. In addition, the reliability of the distribution system is also analyzed after deploying the FCSs and SDGs. Furthermore, six case studies (CS) have been proposed to deploy FCSs with or without DG integration. Consequently, the active power loss went from 1014.48 kW to 829.68 kW for the CS-6.</p><h2>Other Information</h2><p dir="ltr">Published in: Energy Reports<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.egyr.2022.09.058" target="_blank">https://dx.doi.org/10.1016/j.egyr.2022.09.058</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_54ec1f896d9c43a8c5c0569794191b30 |
| identifier_str_mv | 10.1016/j.egyr.2022.09.058 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24551368 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution networkFareed Ahmad (134672)Imtiaz Ashraf (16876050)Atif Iqbal (5504636)Mousa Marzband (17148343)Irfan Khan (640146)EngineeringAutomotive engineeringElectrical engineeringInformation and computing sciencesArtificial intelligenceArtificial IntelligenceFast-charging stationsBald eagle search algorithmOptimal placementElectric vehicleReliability<p dir="ltr">The transportation sector is one of the most prevalent fossil fuel users worldwide. Therefore, to mitigate the impacts of carbon-dioxide emissions and reduce the use of non-environmentally friendly traditional energy resources, the electrification of the transportation system, such as the development of electric vehicles (EV), has become crucial. For impeccable EVs deployment, a well-developed charging infrastructure is required. However, the optimal placement of fast charging stations (FCSs) is a critical concern. Therefore, this article provides a functional approach for identifying the optimal location of FCSs using the east delta network (EDN). In addition, the electrical distribution network’s infrastructure is susceptible to changes in electrifying the transportation sector. Therefore, actual power loss, reactive power loss, and investment cost are three areas of consideration in deploying FCSs. Furthermore, including FCSs in the electricity distribution network increases the energy demand from the electrical grid. Therefore, this research paper recommends integrating solar-based distributed generations (SDGs) at selected locations in the distribution network, to mitigate the burden of FCSs on the system. Hence, making the system self-sustaining and reliable. In addition, the reliability of the distribution system is also analyzed after deploying the FCSs and SDGs. Furthermore, six case studies (CS) have been proposed to deploy FCSs with or without DG integration. Consequently, the active power loss went from 1014.48 kW to 829.68 kW for the CS-6.</p><h2>Other Information</h2><p dir="ltr">Published in: Energy Reports<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.egyr.2022.09.058" target="_blank">https://dx.doi.org/10.1016/j.egyr.2022.09.058</a></p>2022-11-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.egyr.2022.09.058https://figshare.com/articles/journal_contribution/A_novel_AI_approach_for_optimal_deployment_of_EV_fast_charging_station_and_reliability_analysis_with_solar_based_DGs_in_distribution_network/24551368CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/245513682022-11-01T00:00:00Z |
| spellingShingle | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network Fareed Ahmad (134672) Engineering Automotive engineering Electrical engineering Information and computing sciences Artificial intelligence Artificial Intelligence Fast-charging stations Bald eagle search algorithm Optimal placement Electric vehicle Reliability |
| status_str | publishedVersion |
| title | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network |
| title_full | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network |
| title_fullStr | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network |
| title_full_unstemmed | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network |
| title_short | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network |
| title_sort | A novel AI approach for optimal deployment of EV fast charging station and reliability analysis with solar based DGs in distribution network |
| topic | Engineering Automotive engineering Electrical engineering Information and computing sciences Artificial intelligence Artificial Intelligence Fast-charging stations Bald eagle search algorithm Optimal placement Electric vehicle Reliability |