Research On Charging Strategy Of Smart Grid

With the aggravation of traditional energy depletion and the greenhouse effect, the new energy becomes a hot topic, which is more environmental friendly, more recyclable, and lower carbon. And with the good integration of new energy, the Smart Grid is getting more and more people’s attention. The Smart Grid becomes more popular Not only due to the more effective measurement & control and communication system, but also because of the application of smart equipment with integration of new energy. The Smart Grid is regarded as upgrade of the traditional power grid, will lead the integration of multiple research fields. With the development of smart grid, Electric Vehicles have been widely used, which is intelligent and low-carbon. Electric vehicle as the future of means of transport can be highly possible to achieve two-way power grid interaction. On the other hand, when face to the traditional power grid peak, the introduction of a large number of Electric Vehicles is bound to bring "peak over peak" in the grid. How to efficient use of the existing power grid to rationalize the charging and discharging behavior, in the integration of a large number of Electric Vehicles and the growing energy demand scenarios, has become a mainstream topic.This thesis will mainly focus on the study of the charging strategy of the Smart Grid, using game theory and queuing theory to model the user’s charging behavior, and realize the optimization of the charging scheduling strategy. There are three main innovation points in this article.Firstly, on the model of Electric Vehicle charging scheduling related aspects, this article build up model through the real statistical data, which including a model of power load, an Electric Vehicle model and a user model of driving behavior. These models are compared with the traditional one work more efficiently, in the corresponding simulation.Secondly, this thesis analyzes the adaptation of the Group Buying in the smart grid. And according to the purchase factors including the start time, duration, the number of Group Buying and pricing and so on, a group buying charging scheduling strategy is build up, so as the corresponding optimization algorithm. The simulation that base on the Matlab platform is used to verify the effectiveness of the Group Buying algorithm. According to the result, the scheduling algorithm can be effectively adapted to the charge of large-scale Electric Vehicle scheduling, and the result of scheduling can be predictable.Thirdly, according to the slot charging model which is conducive to the integration of the real charging and power grid load information, and considering two aspects of factors including grid scheduling factor and user priority factor to establish the charging priority algorithm. The validity of the algorithm is verified by the simulation in real data. The algorithm is effective in charging scheduling work, which testified by really simulation.