Abstract
In this paper, the optimal charging and discharging schedules of electric vehicle (EV) are studied considering wind power under the condition of distribution network. In view of the uncertainty of EV charging-discharging demand and wind power output, the Markov decision process is adopted to model the randomness of supply and demand. Considering the dimensional disaster caused by dispatching a large number of EVs’ charging and discharging behavior in a centralized way, this paper proposes the two-layer dispatching model based on Markov decision process. First, the lower EV agents are responsible for collecting the real-time charging-discharging demands for EV and report to the upper dispatching center. Then the upper dispatching center gives the optimal charging and discharging power according to the real-time distribution operating status, wind power output and the EV information reported by each EV agent. Last, the lower agent gives the optimal charging-discharging sequence of each EV according to the upper optimal power. The goal of the upper dispatching center considers the power losses in the distribution network, load variance and the matching degree between EV charging-discharging and wind power output. The goal of the lower EV agent considers the EV charging-discharging fees and costs by EV battery losses. When deciding the optimal charging strategy, we design the two-layer Rollout algorithm to decide the optimal charging-discharging strategy considering the impact on future strategy decisions by current strategy decisions. Finally, the optimal results under four different strategies are simulated on the IEEE 30-bus distribution network system. The simulation results show that the proposed model and strategy can effectively reduce the distribution network losses and load variance, and greatly improve the utilization rate of wind power. Compared to the cost of uncoordinated EV charging, EV charging-discharging fees and battery loss costs by the proposed strategy have been greatly reduced.
Highlights
In recent years, due to the limited reserves of fossil fuels and atmospheric pollution caused by energy problems, new energy sources have drawn wide attention
By 2020, it is expected to build a charging infrastructure system to meet the charge needs of more than 5 million electric vehicles [2]. It is a direction for the green development of the power grid in the future to comprehensively coordinate the conversion of new energy power generation and electric vehicle power conversion, make full use of wind power output, offset the randomness of both sides of supply and demand
In view of the uncertainty of electric vehicle (EV) charging demand and wind power output, a model of randomness of supply and demand is established by using Markov decision process
Summary
Due to the limited reserves of fossil fuels and atmospheric pollution caused by energy problems, new energy sources have drawn wide attention. By 2020, it is expected to build a charging infrastructure system to meet the charge needs of more than 5 million electric vehicles [2] It is a direction for the green development of the power grid in the future to comprehensively coordinate the conversion of new energy power generation and electric vehicle power conversion, make full use of wind power output, offset the randomness of both sides of supply and demand. The grid dispatching agency targets the network loss, wind matching and variance of load curve in the distribution network, taking into account the impact of the decisions made at the current moment in the future on the basis of the optimal charge amount of each electric vehicle agent at this moment. According to the optimal charge-discharge amount, each agent takes the comparative charging costs of the electric vehicle and the battery loss costs as the goal, given the impact of the current decision-making in the future on the basis of the optimal charging and discharging sequence of electric vehicles
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