The Active and Reactive Power Dispatch for Charging Station Location Impact Factors Analysis

Abstract 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.

[1]  L.H. Walker,et al.  10 MW GTO converter for battery peaking service , 1988, Conference Record of the 1988 IEEE Industry Applications Society Annual Meeting.

[2]  Yue Yuan,et al.  Modeling of Load Demand Due to EV Battery Charging in Distribution Systems , 2011, IEEE Transactions on Power Systems.

[3]  Aouss Gabash,et al.  Active-Reactive Optimal Power Flow in Distribution Networks With Embedded Generation and Battery Storage , 2012, IEEE Transactions on Power Systems.

[4]  Zhipeng Liu,et al.  Optimal Planning of Electric-Vehicle Charging Stations in Distribution Systems , 2013, IEEE Transactions on Power Delivery.

[5]  A. Gabash,et al.  Evaluation of reactive power capability by optimal control of wind-vanadium redox battery stations in electricity market , 2011 .

[6]  Shaolei Ren,et al.  Operation Analysis of Fast Charging Stations With Energy Demand Control of Electric Vehicles , 2015, IEEE Transactions on Smart Grid.

[7]  Cheng Wang,et al.  Power loss reduction for electric vehicle penetration with embedded energy storage in distribution networks , 2014, 2014 IEEE International Energy Conference (ENERGYCON).

[8]  Kit Po Wong,et al.  Traffic-Constrained Multiobjective Planning of Electric-Vehicle Charging Stations , 2013, IEEE Transactions on Power Delivery.

[9]  Ching-Tzong Su,et al.  Optimal Size and Location of Capacitors Placed on a Distribution System , 2008 .

[10]  Zhenpo Wang,et al.  Research on Quantitative Models of Electric Vehicle Charging Stations Based on Principle of Energy Equivalence , 2013 .

[11]  Jianbin Qiu,et al.  Model Reduction for Discrete-Time Markovian Jump Systems with Deficient Mode Information , 2013 .

[12]  N.W. Miller,et al.  Design and commissioning of a 5 MVA, 2.5 MWh battery energy storage system , 1996, Proceedings of 1996 Transmission and Distribution Conference and Exposition.

[13]  Kara M. Kockelman,et al.  Locating Electric Vehicle Charging Stations , 2013 .