TY - JOUR
T1 - The active and reactive power dispatch for charging station location impact factors analysis
AU - Wang, Cheng
AU - Dunn, Roderick
AU - Yang, Qingqing
AU - Lian, Bo
AU - Yuan, Weijia
AU - Li, Jianwei
PY - 2016/12/1
Y1 - 2016/12/1
N2 - With the increasing number of Electric Vehicles (EVs) in modern society, a number of challenges and opportunities are presenting themselves. For example, how to choose charging station locations to minimize the Distribution Network's (DN) power loss when a large number of EVs are connected to the DN. How impact factors, such as different load patterns, EVs' charging locations and network topology, affect charging station location is becoming vital. In this paper a new charging station location methodology informed by impact factor analysis is proposed by using the Active and Reactive Power Dispatch of charging stations in terms of power loss minimization. Results for the 36 DN with three different scenarios are presented. In addition, a more realistic model based on EV's daily travel patterns is built to illustrate how these impact factors affect charging station location. It is demonstrated that the optimal charging station location in terms of power loss minimization can be found by using the new methodology, and it is not affected by the EVs' charging location and load patterns, it is affect by the network topology.
AB - With the increasing number of Electric Vehicles (EVs) in modern society, a number of challenges and opportunities are presenting themselves. For example, how to choose charging station locations to minimize the Distribution Network's (DN) power loss when a large number of EVs are connected to the DN. How impact factors, such as different load patterns, EVs' charging locations and network topology, affect charging station location is becoming vital. In this paper a new charging station location methodology informed by impact factor analysis is proposed by using the Active and Reactive Power Dispatch of charging stations in terms of power loss minimization. Results for the 36 DN with three different scenarios are presented. In addition, a more realistic model based on EV's daily travel patterns is built to illustrate how these impact factors affect charging station location. It is demonstrated that the optimal charging station location in terms of power loss minimization can be found by using the new methodology, and it is not affected by the EVs' charging location and load patterns, it is affect by the network topology.
KW - charging stations
KW - distribution networks
KW - electric vehicle
KW - impact factors
UR - http://www.scopus.com/inward/record.url?scp=85010903498&partnerID=8YFLogxK
UR - http://dx.doi.org/10.1016/j.egypro.2016.11.279
UR - http://dx.doi.org/10.1016/j.egypro.2016.11.279
U2 - 10.1016/j.egypro.2016.11.279
DO - 10.1016/j.egypro.2016.11.279
M3 - Article
AN - SCOPUS:85010903498
SN - 1876-6102
VL - 103
SP - 237
EP - 243
JO - Energy Procedia
JF - Energy Procedia
ER -