Planning And Operation Of Electric Vehicle Charging Stations

Electric vehicles consume electricity rather than oil, with high energy utilization efficiency, less emissions, low noise, and represent one of the key means to solve the energy and environmental crisis. Currently, the mileage range of electric vehicles is still relatively short due to the limitation of the onboard battery energy density. Therefore, a comprehensive network of charging facilities is needed to guarantee the normal use of electric vehicles. The inappropriate charging station planning will not only affect the convenience of charging, but also result in the increase of power losses and voltage deviations of the distribution system associated. Reasonable siting and sizing of charging stations are important for extensive applications of electric vehicles.In order to meet electric vehicle charging demands in the planning area, the rated capacity of charging stations should not be less than the maximum charging demands. When there are no economic or other means to guide owner’s charging behavior, owners will charge electric vehicles according to their own convenience. Thus charging loads have a great randomness. The Monte Carlo simulation method is applied to simulate a large number of electric vehicle’s charging behavior, then the charging power of different types of electric vehicle is calculated and also impacts of the these free charging load on the secure and economic operation of the distribution system is analyzed.Based on the maximum charging load in the planning area is determined, a multi-objective decision-making model for the optimal planning of electric vehicle charging stations is developed, with the dual attributes of charging stations as ordinary electric facilities and public service facilities of urban traffics taken into account. Three objective functions are defined to respectively minimize the network loss, to minimize the average voltage deviation, and to maximize the captured traffic network flow. The Analytic Hierarchy Process (AHP) is employed to determine the appropriate weights among the three objective functions, and in this way the multi-objective optimization problem is transformed into a single-objective programming one. Then, the enhanced binary particle of swarm optimization (BPSO) is used to solve the single-objective programming model such obtained.Improving charging station revenues is an important issue that operators need to consider. Through technological transformation, charging stations can inject power to the grid, and charging stations can also get a considerable income. This thesis focuses on the operation mode of charging stations and analysis the advantages and disadvantages of several different operation modes of the charging stations. A mathematical model for optimizing revenues of charging stations is developed. This model takes the maximization of revenues of charging stations, and some owner using constraints are considered.