Electric Vehicle Charging Station Planning

With the rapid development of economy, lack of resources and environmentalpollution problems are getting worse. People are increasingly concerned about theirhealth and living conditions. Currently, the huge vehicle market is not onlyintensifying resource-intensive, but also adding more pressure to the urbanenvironment. Because of its energy-saving and environment-friendly features, theelectric vehicle is becoming the main direction of the automotive industry. With thenational policy support and the active participation of the major car manufacturers, thetechnical level of the electric vehicle is increasing. Up to now, part of the electricvehicle has been formed and put into the demonstration run. Industrialization andcommercialization mode of the electric vehicle is gradually improving. As thepenetration increases, the charging of electric vehicles will become another importantload. There will be a very big impact on the grid. As the infrastructure and supporting,the charging station must first be planning and construction.In this paper, some problems have been studied for large-scale application ofelectric vehicles, such as charging demand forecasting, charging stations locating andsizing, service scoping, etc. The main work in this dissertation is summarized asfollows:(1) Electric vehicle charging is closely related to the habits of the residents. So ithas the characteristics of randomness and uncertainty. Based on this, a Monte Carloprediction model was constructed on conventional charging demand and fast chargingdemand. The impact of a large number of disorderly charging on the grid load curvehas been analyzed. In order to decrease this negative effect, Pricing Policy wasstudied to guide the electric vehicle charging orderly. And a peak-valley pricetime-period optimization model was put forward. Through the optimization ofpeak-valley price time-period, the gap between peak load and valley load wasnarrowed and electrical equipment utilization was improved. While optimizing thepeak-valley price time-period, the sensitivity of the user on the Pricing Policy hasbeen considered. Based on the user’s response to different peak-valley price atdifferent time, an integrated optimization model was constructed to coordinate thesefactors. So that it can make orderly charging guide measures to develop more reasonable.(2) Electric vehicle charging station planning in urban areas was studied.Considering the interests of charging station operators and electric vehicle drivers, anoptimization model for charging station planning based on the minimization of fullsocial cost was proposed. In the model, the impact on the charging station locatingand sizing from the road network, the traffic flow and the users’ loss on the way to thestation was analyzed. The role of traffic density in the service areas divided ofcharging stations was reflected by the weights. And the automatic partitioning ofservice areas was implemented by the weighted Voronoi diagram.(3) Taking the distribution network structure and capacity constraints intoaccount, an optimization model for urban charging station planning was proposed.Based on the advantages of queuing theory in the service system design, theoptimization model of the charging station capacity configuration was constructedwith the consideration of charging station operating cost and users’ waiting cost. Inthis way, the capacity of the charging station configuration can not only meet the users’charging requirement, but also achieve the optimal allocation of resources and avoidunnecessary waste.(4) Regarding the influences of the power distribution and the mileage of electricvehicles, a planning model of charging stations on the highway was established. Themaximum expectation of electric vehicles coming to stations for recharge from thehighway was chosen as the objective function for locating the charging station. Andthe number of chargers in the station was optimized in order to minimize the total costof station’s service and customers’ waiting time. In addition, this model also analyzedthe service level and operational efficiency of the charging station using the queuingtheory.