Abstract
In this paper, a control method for electric vehicles (EVs) participating in grid Frequency regulation is proposed. Firstly, considering dispatching large-scale electric vehicles, the K-means clustering algorithm is applied to cluster EVs with different battery state of charge and with different average vehicle daily travel miles. Then, for each class of electric vehicle group, a multi-objective optimization model considering reducing power imbalance and feeding the driving power demand for electric vehicles is proposed. Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is applied to solve the optimization model and obtain the best control parameters for “virtual synchronous machine”, which is functioned as the power controller between EVs and the power grid. At last, based on a Monte Carlo sampling, the simulation analysis of 50 EVs with the normal distribution of battery state of charge and average vehicle daily travel miles is carried out by using the proposed method. The results show that the proposed method can effectively classify the electric vehicles with different battery state of charge and different average vehicle daily travel miles. The parameters of the power converter controller for different classes of electric vehicles are optimized considering power grid frequency, their battery state of charge and their average daily travel miles, so as to maintain the balance of power grid frequency, and to meet the power needs of EV daily drive.
Highlights
With the development of electric vehicles (EVs), EVs have the potential to replace the traditional diesel locomotives and become the main means of transportation for people to travel in the future.the large-scale application of those battery-based electric vehicles will bring new problems to the operation and planning of existing power grids
The main achievements of this work are: (1) A classification method of electric vehicles travel miles is still between 0 and 50 km, so the 1000 EV group can still be divided into three categories group is proposed, which considering the battery state of charge, as well as the average vehicle daily respectively according to SoC and average daily travel (AVDT)
The control variable of the optimization model is the initial set power and the droop control coefficient of the ”Virtual Synchronous Machine”, which is like a synchronous generator with variable capacity be driven by a prime mover with adjustable output torque
Summary
With the development of electric vehicles (EVs), EVs have the potential to replace the traditional diesel locomotives and become the main means of transportation for people to travel in the future. The References [5,6] pointed out that when an EV is connected to the grid by power electronic devices with bidirectional power control capability, and when the capacity of the electric vehicle is large enough, it can be regarded as the backup energy storage for the grid, to be absorbed by the renewable energy power generation system. The operating mechanism of the VSM is to simulate the inherent electromagnetic transient characteristics of the synchronous motor, so that the inverter has the same internal synchronous operation mechanism and external adjustment characteristics as the conventional synchronous generator, so that the inverter operates closer to the real synchronous generator It can provide the necessary damping and inertia support to the grid [18], which is of great significance for future power systems with the increase of penetration rate of power electronic enabled devices in the power grid [19,20,21].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
