Distributed Charging And Discharging Optimal Control For PEV Populations

With the increasing number of Plug-in Electric Vehicles(PEVs) and the development of battery technology, in order to minimize the charging cost of PEV and realize the load shifting of the power grid load curve, many scholars began to focus on the coordination of the charge-discharge strategy for PEVs. There are two mainly benefits of the correlative research. On the one hand, the batteries’ charge-discharge time and power of the PEVs are flexibly controlled, so as to adjust the difference of peak and valley of the power grid. Thus, the power grid operates more effectively and stably at lower cost. On the other hand, users of PEVs will get some income during the process of power supplying to the grid which brings more benefits to the social welfare.A charge-discharge model of the PEV group connecting to the grid is established and a new charge-discharge strategy for large PEV group under the centralized control is proposed. The proposed distributed iterative algorithm realized the purpose of the effectiveness, stability and inexpensive price of the power grid operation. In the iterative algorithm, the PEVs determine their own charge-discharge strategy according to the on-grid price, and then provide the strategy to the grid as a feedback. Based on the feedback, the power grid updates its prices until the PEVs get a convergent optimized charge-discharge strategy. This paper theoretically proved that the convergent strategy of the distributed charge-discharge optimized controlling algorithm can realizes the load shifting of the power grid’s basic load curve.The convergence of the distributed iterative algorithm is proved in the following work. The result reveals that the distributed charge-discharge optimized controlling algorithm converges if there exists some relationship between the parameters of the price curve function and the battery degradation function. Finally, the proved results is verified through the simulation of the PEV group connecting to the power grid by applying the proposed distributed iterative algorithm.