Abstract
To solve the problems that a large number of random and uncontrolled electric vehicles (EVs) connecting to the distribution network, resulting in a decrease in the performance and stability of the grid and high user costs, in this study, a multi-objective comprehensive charging/discharging scheduling strategy for EVs based on improved particle swarm optimization (IPSO) is proposed. In the distribution network, the minimum root-mean-square error and the minimum peak valley difference of system load are first designed as objective functions; on the user side, the lowest charge and discharge cost of electric vehicle users and the lowest battery loss cost are used as objective functions, then a multi-objective optimization scheduling model for EVs is established, and finally, the optimization through IPSO is performed. The simulation results show that the proposed method is effective, which enhances the peak regulating capacity of the power grid, and it optimizes the system load and reduces the user cost compared with the conventional methods.
Highlights
The new energy source has made a great contribution to solving the increasingly serious energy shortage and environmental degradation
The rest of this article is organized as follows: the first section introduces the scheduling system, objective function, and model constraints of V2G; the second section describes the dispatching strategy scheme of electric vehicles (EVs); the third section gives simulation results to prove that the proposed improved particle swarm optimization (IPSO) algorithm has a better power grid peak regulating ability and is beneficial to reducing user costs; the fourth part gives the conclusion
The reducing charging cost is the most important incentive factor for EV owners to participate in the V2G program, but a highfrequency discharge will cause irreversible loss of the battery, which limits the enthusiasm of EV owners to feed the power grid
Summary
The new energy source has made a great contribution to solving the increasingly serious energy shortage and environmental degradation. Ma et al, (2019) studied the load fluctuation of the distribution network and the charge/discharge cost of EVs on the basis of the peak-valley time-of-use (TOU) price, and a coordinated dispatch strategy and an optimized dispatch model were proposed to reduce the peak-valley difference of the power grid and improve the economic benefits of users. The rest of this article is organized as follows: the first section introduces the scheduling system, objective function, and model constraints of V2G; the second section describes the dispatching strategy scheme of EVs; the third section gives simulation results to prove that the proposed IPSO algorithm has a better power grid peak regulating ability and is beneficial to reducing user costs; the fourth part gives the conclusion. The model is related to the battery replacement cost, and the battery aging cost is obtained
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
