AUTHOR=Hu HouPeng , Qian Bin , Xiao YanHong , Tang JianLin , Ou Jiaxiang , Lin XiaoMing , He Peilin , Zhang Fan 

TITLE=Low-carbon scheduling strategy for electric vehicles considering carbon emission flow and dynamic electricity prices

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2024.1519963

DOI=10.3389/fenrg.2024.1519963

ISSN=2296-598X

ABSTRACT=As the global environmental pollution problem intensifies, the carbon reduction transformation of the power system is urgent. In order to solve the problem of unclear carbon flow and distribution in the operation of the power grid, as well as the mismatch between static time of use electricity prices and peak and valley periods in the scheduling of electric vehicle charging loads, a multi period dynamic electricity price guidance strategy based on carbon emission flow theory is proposed. Firstly, based on the accurate power flow results of the power system, a complex power distribution matrix of the power system is constructed to obtain the distribution of the power generated by the generator units in each node of the network; Then, the Monte Carlo random sampling method is used to simulate the load situation of electric vehicles in a disordered charging state. Based on the carbon trading model, a mathematical model is established with the goal of minimizing the load difference at the grid end and maximizing the cost of charging on the user side; Finally, the proposed ordered charging method with multi period dynamic electricity pricing strategy is compared with unordered charging, and considering the participation of electric vehicles in carbon trading, this strategy effectively reduces the peak valley difference of the power grid and user charging costs.