Research On Load Optimization Management And Incentives Mechanism Considering The Characteristics Of Electric Vehicle Charging

With the continuous increase of power demand, especially peak load, demand side management (DSM) has been one of the most significant ways for co-ordination power supply and demand. Load management, as an important part of DSM, would play a more important role in relieving the problem. Recently, electric vehicle (EV) attracts lots of attention due to its environment-friendly characteristics. However, the randomness of EV charging load puts forward new problems to load management. In order to fully implement DSM methods, rational mechanism for incentive is necessary.How to model all kinds of load management programs is the foundation of achieving DSM efficiently. Based on the existing research, this paper proposed a load management optimization approach targeting higher economic efficiency. Considering both economics and load profile, the approach applies all kinds of load management methods (load shifting, load translation, load clipping) at the same time. Moreover, piecewise function and binary variables in this model is transformed into a serialization form to make the calculation more convenient.This paper gains expectation curve of EV charging power by model using statistics. Based on the expectation curve, load management optimization with EV charging load is given under battery swapping mode and battery charging mode, and analysis the influences to the grid and load management. Furthermore, this paper studies the effects on applying load management when the battery swapping mode and battery charging mode occupied concurrently.In order to achieve better implementation of load management, establish rational mechanism for incentive is absolutely necessary. On account of information economics, this paper give adverse selection model on principal monopoly for the case between electricity companies and the users and moral hazard model for the case between government and the electricity company. Advices for incentive mechanism were further proposed after the analysis under incomplete information situation.