Hanna et al 2016a - Revision history

Scipediacontent at 06:06, 2 February 2021

2021-02-02T06:06:07Z

Scipediacontent: Scipediacontent moved page Draft Content 401143252 to Hanna et al 2016a

2021-01-25T09:49:06Z

Scipediacontent moved page Draft Content 401143252 to Hanna et al 2016a

Scipediacontent: Created page with " == Abstract == The mass adoption of plug-in electric vehicles (PEVs) requires the deployment of public charging stations. Such facilities are expected to employ distributed..."

2021-01-25T09:49:01Z

Created page with " == Abstract == The mass adoption of plug-in electric vehicles (PEVs) requires the deployment of public charging stations. Such facilities are expected to employ distributed..."

New page

== Abstract ==

The mass adoption of plug-in electric vehicles (PEVs) requires the deployment of public charging stations. Such facilities are expected to employ distributed generation and storage units to reduce the stress on the grid and boost sustainable transportation. While prior work has made considerable progress in deriving insights for understanding the adverse impacts of PEV chargings and how to alleviate them, a critical issue that affects the accuracy is the lack of real world PEV data. As the dynamics and pertinent design of such charging stations heavily depend on actual customer demand profile, in this paper we present and evaluate the data obtained from a $17$ node charging network equipped with Level $2$ chargers at a major North American University campus. The data is recorded for $166$ weeks starting from late $2011$. The result indicates that the majority of the customers use charging lots to extend their driving ranges. Also, the demand profile shows that there is a tremendous opportunity to employ solar generation to fuel the vehicles as there is a correlation between the peak customer demand and solar irradiation. Also, we provided a more detailed data analysis and show how to use this information in designing future sustainable charging facilities.

== Original document ==

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

* [http://arxiv.org/abs/1602.02943 http://arxiv.org/abs/1602.02943]

* [http://arxiv.org/pdf/1602.02943 http://arxiv.org/pdf/1602.02943]

* [https://strathprints.strath.ac.uk/70709/1/Bayram_etal_IEEE2016_On_evaluation_plug_in_electric_vehicle_data_campus_charging_network.pdf https://strathprints.strath.ac.uk/70709/1/Bayram_etal_IEEE2016_On_evaluation_plug_in_electric_vehicle_data_campus_charging_network.pdf]

* [http://xplorestaging.ieee.org/ielx7/7507294/7513868/07514026.pdf?arnumber=7514026 http://xplorestaging.ieee.org/ielx7/7507294/7513868/07514026.pdf?arnumber=7514026],
: [http://dx.doi.org/10.1109/energycon.2016.7514026 http://dx.doi.org/10.1109/energycon.2016.7514026]

* [https://dblp.uni-trier.de/db/journals/corr/corr1602.html#BayramZHK16 https://dblp.uni-trier.de/db/journals/corr/corr1602.html#BayramZHK16],
: [https://arxiv.org/pdf/1602.02943.pdf https://arxiv.org/pdf/1602.02943.pdf],
: [https://escholarship.org/uc/item/0hc2604z https://escholarship.org/uc/item/0hc2604z],
: [http://ui.adsabs.harvard.edu/abs/2016arXiv160202943S/abstract http://ui.adsabs.harvard.edu/abs/2016arXiv160202943S/abstract],
: [https://www.scipedia.com/public/Bayram_et_al_2016a https://www.scipedia.com/public/Bayram_et_al_2016a],
: [https://strathprints.strath.ac.uk/70709 https://strathprints.strath.ac.uk/70709],
: [https://arxiv.org/abs/1602.02943 https://arxiv.org/abs/1602.02943],
: [http://export.arxiv.org/pdf/1602.02943 http://export.arxiv.org/pdf/1602.02943],
: [https://pureportal.strath.ac.uk/en/publications/on-the-evaluation-of-plug-in-electric-vehicle-data-of-a-campus-ch https://pureportal.strath.ac.uk/en/publications/on-the-evaluation-of-plug-in-electric-vehicle-data-of-a-campus-ch],
: [https://export.arxiv.org/abs/1602.02943 https://export.arxiv.org/abs/1602.02943],
: [https://academic.microsoft.com/#/detail/2255008403 https://academic.microsoft.com/#/detail/2255008403]

← Older revision		Revision as of 06:06, 2 February 2021
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	The mass adoption of plug-in electric vehicles (PEVs) requires the deployment of public charging stations. Such facilities are expected to employ distributed generation and storage units to reduce the stress on the grid and boost sustainable transportation. While prior work has made considerable progress in deriving insights for understanding the adverse impacts of PEV chargings and how to alleviate them, a critical issue that affects the accuracy is the lack of real world PEV data. As the dynamics and pertinent design of such charging stations heavily depend on actual customer demand profile, in this paper we present and evaluate the data obtained from a $17$ node charging network equipped with Level $2$ chargers at a major North American University campus. The data is recorded for $166$ weeks starting from late $2011$. The result indicates that the majority of the customers use charging lots to extend their driving ranges. Also, the demand profile shows that there is a tremendous opportunity to employ solar generation to fuel the vehicles as there is a correlation between the peak customer demand and solar irradiation. Also, we provided a more detailed data analysis and show how to use this information in designing future sustainable charging facilities.		The mass adoption of plug-in electric vehicles (PEVs) requires the deployment of public charging stations. Such facilities are expected to employ distributed generation and storage units to reduce the stress on the grid and boost sustainable transportation. While prior work has made considerable progress in deriving insights for understanding the adverse impacts of PEV chargings and how to alleviate them, a critical issue that affects the accuracy is the lack of real world PEV data. As the dynamics and pertinent design of such charging stations heavily depend on actual customer demand profile, in this paper we present and evaluate the data obtained from a $17$ node charging network equipped with Level $2$ chargers at a major North American University campus. The data is recorded for $166$ weeks starting from late $2011$. The result indicates that the majority of the customers use charging lots to extend their driving ranges. Also, the demand profile shows that there is a tremendous opportunity to employ solar generation to fuel the vehicles as there is a correlation between the peak customer demand and solar irradiation. Also, we provided a more detailed data analysis and show how to use this information in designing future sustainable charging facilities.
		+
		+	Comment: Accepted by IEEE Energycon 2016

← Older revision	Revision as of 09:49, 25 January 2021
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