@article{
 title = {Optimal fast charging station placing and sizing},
 type = {article},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {Charging,Electric vehicle,Location,Loss of charging,Reliability,Station},
 pages = {289-299},
 volume = {125},
 websites = {http://www.sciencedirect.com/science/article/pii/S0306261914003171},
 month = {7},
 id = {a99c0886-8bf6-373d-90d0-7308ce2c9836},
 created = {2015-01-13T16:35:41.000Z},
 accessed = {2014-12-21},
 file_attached = {false},
 profile_id = {9696f304-db07-31d9-a8cd-d208939f9889},
 group_id = {062cfb24-9ce4-3a92-a41f-541a783d7b95},
 last_modified = {2017-03-09T15:29:23.010Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Sadeghi-Barzani2014},
 private_publication = {false},
 abstract = {Fast charging stations are vital components for public acceptance of electric vehicle (EV). The stations are connected to the electric grid and can recharge an electric vehicle in less than 20min. Charging station development is highly influenced by the government policy in allocating station development costs. This paper presents a Mixed-Integer Non-Linear (MINLP) optimization approach for optimal placing and sizing of the fast charging stations. The station development cost, EV energy loss, electric gird loss as well as the location of electric substations and urban roads are among the factors included in the proposed approach. Geographic information has been used to determine EV energy loss and station electrification cost. The optimization problem is solved using genetic algorithm technique. Application of the proposed approach to analyze the impact of different station development policies has been discussed. The impact of electric grid reliability on charging station place and size has been evaluated using a proposed index to evaluate loss of charging cost. Results showed the robustness and efficacy of the proposed method to determine optimal place and size of the charging stations.},
 bibtype = {article},
 author = {Sadeghi-Barzani, Payam and Rajabi-Ghahnavieh, Abbas and Kazemi-Karegar, Hosein},
 journal = {Applied Energy}
}

{"_id":"kxyGAWtQhicwK89Gk","bibbaseid":"sadeghibarzani-rajabighahnavieh-kazemikaregar-optimalfastchargingstationplacingandsizing-2014","downloads":0,"creationDate":"2017-10-12T19:32:23.663Z","title":"Optimal fast charging station placing and sizing","author_short":["Sadeghi-Barzani, P.","Rajabi-Ghahnavieh, A.","Kazemi-Karegar, H."],"year":2014,"bibtype":"article","biburl":null,"bibdata":{"title":"Optimal fast charging station placing and sizing","type":"article","year":"2014","identifiers":"[object Object]","keywords":"Charging,Electric vehicle,Location,Loss of charging,Reliability,Station","pages":"289-299","volume":"125","websites":"http://www.sciencedirect.com/science/article/pii/S0306261914003171","month":"7","id":"a99c0886-8bf6-373d-90d0-7308ce2c9836","created":"2015-01-13T16:35:41.000Z","accessed":"2014-12-21","file_attached":false,"profile_id":"9696f304-db07-31d9-a8cd-d208939f9889","group_id":"062cfb24-9ce4-3a92-a41f-541a783d7b95","last_modified":"2017-03-09T15:29:23.010Z","read":false,"starred":false,"authored":false,"confirmed":"true","hidden":false,"citation_key":"Sadeghi-Barzani2014","private_publication":false,"abstract":"Fast charging stations are vital components for public acceptance of electric vehicle (EV). The stations are connected to the electric grid and can recharge an electric vehicle in less than 20min. Charging station development is highly influenced by the government policy in allocating station development costs. This paper presents a Mixed-Integer Non-Linear (MINLP) optimization approach for optimal placing and sizing of the fast charging stations. The station development cost, EV energy loss, electric gird loss as well as the location of electric substations and urban roads are among the factors included in the proposed approach. Geographic information has been used to determine EV energy loss and station electrification cost. The optimization problem is solved using genetic algorithm technique. Application of the proposed approach to analyze the impact of different station development policies has been discussed. The impact of electric grid reliability on charging station place and size has been evaluated using a proposed index to evaluate loss of charging cost. Results showed the robustness and efficacy of the proposed method to determine optimal place and size of the charging stations.","bibtype":"article","author":"Sadeghi-Barzani, Payam and Rajabi-Ghahnavieh, Abbas and Kazemi-Karegar, Hosein","journal":"Applied Energy","bibtex":"@article{\n title = {Optimal fast charging station placing and sizing},\n type = {article},\n year = {2014},\n identifiers = {[object Object]},\n keywords = {Charging,Electric vehicle,Location,Loss of charging,Reliability,Station},\n pages = {289-299},\n volume = {125},\n websites = {http://www.sciencedirect.com/science/article/pii/S0306261914003171},\n month = {7},\n id = {a99c0886-8bf6-373d-90d0-7308ce2c9836},\n created = {2015-01-13T16:35:41.000Z},\n accessed = {2014-12-21},\n file_attached = {false},\n profile_id = {9696f304-db07-31d9-a8cd-d208939f9889},\n group_id = {062cfb24-9ce4-3a92-a41f-541a783d7b95},\n last_modified = {2017-03-09T15:29:23.010Z},\n read = {false},\n starred = {false},\n authored = {false},\n confirmed = {true},\n hidden = {false},\n citation_key = {Sadeghi-Barzani2014},\n private_publication = {false},\n abstract = {Fast charging stations are vital components for public acceptance of electric vehicle (EV). The stations are connected to the electric grid and can recharge an electric vehicle in less than 20min. Charging station development is highly influenced by the government policy in allocating station development costs. This paper presents a Mixed-Integer Non-Linear (MINLP) optimization approach for optimal placing and sizing of the fast charging stations. The station development cost, EV energy loss, electric gird loss as well as the location of electric substations and urban roads are among the factors included in the proposed approach. Geographic information has been used to determine EV energy loss and station electrification cost. The optimization problem is solved using genetic algorithm technique. Application of the proposed approach to analyze the impact of different station development policies has been discussed. The impact of electric grid reliability on charging station place and size has been evaluated using a proposed index to evaluate loss of charging cost. Results showed the robustness and efficacy of the proposed method to determine optimal place and size of the charging stations.},\n bibtype = {article},\n author = {Sadeghi-Barzani, Payam and Rajabi-Ghahnavieh, Abbas and Kazemi-Karegar, Hosein},\n journal = {Applied Energy}\n}","author_short":["Sadeghi-Barzani, P.","Rajabi-Ghahnavieh, A.","Kazemi-Karegar, H."],"urls":{"Website":"http://www.sciencedirect.com/science/article/pii/S0306261914003171"},"bibbaseid":"sadeghibarzani-rajabighahnavieh-kazemikaregar-optimalfastchargingstationplacingandsizing-2014","role":"author","keyword":["Charging","Electric vehicle","Location","Loss of charging","Reliability","Station"],"downloads":0},"search_terms":["optimal","fast","charging","station","placing","sizing","sadeghi-barzani","rajabi-ghahnavieh","kazemi-karegar"],"keywords":["charging","electric vehicle","location","loss of charging","reliability","station"],"authorIDs":[]}