Study Of Electric Vehcle Charging Management In Smart Residential Restrict

With the development of modernization,the problem of global warming,energy crisis and environment pollution is getting worse.Humans begin to search for the solution to it.As the new energy electric vehicles have significant advantages in energy saving,emission reduction and substitution,promoting the development of electric vehicle industry has become the focus of attention in all countries.With the increase number of electric car users,the electric vehicle operator that differs from EV users and power supply side will gradually popularize in the residential restrict.Due to the limited capacity of transformer in the district,it will make transformer run overload for a long time or be aging and also affect the power quality when large number of EVs are charging together at peak time.It becomes an significant research that how to make the reasonable charging strategy to reach the target of win-win for both the electric operators and cars’ owners as much as possible to reduce the influence on power distribution system in the community.The main work of this paper can be described as follows:1、As the total load is consist of normal load(such as lighting load、fans and pumps loads)and the EV charging load.In order to verify the influence on the total load when EVs are charging in the peak time,this paper will use Monte-Carlo method to get the charging load modes of different percentage EVs under the uncoordinated condition and then add the normal load to get the total load mode.2、This paper firstly study the charging strategy under fixed time-sharing electrical price.We build two models arming to minimum both the users’ charging expend and the difference in peak-valley load of power supply side,establish the constraint condition of transformer capacity.Then,we adopt the weight coefficient method transfer the above models to a final objective function and use Particle-Swarm-Optimization algorithm to get the optimal time-sharing charging curves.3、This paper mainly study the control strategy based on users’ charging demand under real-time time-sharing charging service price.We put forward to the concept of user’s sensitivity that’s a proportion of the electric car users who will participate in the operator’s service price system.We do research on the relationship of price、the demand of electricity and the habit of users,building the dynamic model between time-of-use charging service price and EVs charging load that is based on users change their charging habits.In this paper,assuming there are 30% EV users,we use Monte-Carlo method to get the results of EV charging load,total load and time-of –use service price under different users’ sensitivity.According to the results,through dynamic charging service price system to guide part of EV users to change their charging behavior that will improve EV users’ motivation and effectively decrease the amount of peak load,increase the income of EV operator at the same time.4、Propose a commercial mode for EV charging operator to lead EV coordinated charging and then study the selection of charging time and the incomes of different price strategies.It shows that it’s better for operator to adapt the real-time charging service price under the fixed price as it will get more benefits.