计及电动汽车违约不确定性的微电网两段式优化调度策略

doi:10.19595/j.cnki.1000-6753.tces.212010

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Abstract In order to cope with the environmental crisis, the popularization of electric vehicles will become a trend, but the random charging/discharging behavior of a large number of electric vehicles may cause harm to the power grid.
Taking the microgrid (MG) as the research object, this paper studies the behavior characteristics of household electric vehicles. Aiming at the matching problem between the electric vehicle discharge process and the supply and demand balance of the MG system, a reservation-default discharge mechanism for electric vehicles taking into account the uncertainty of default is proposed. The charging behavior and reservation discharge mechanism of electric vehicles (EVs), the uncertainty of default of electric vehicles, reservation discharge flow and discharge flow of electric vehicles are described. On this basis, considering the large number of EVs, the large difference of user behavior and the uncertainty of EVs default, a two-stage scheduling including "MG -EV aggregator" and "EV aggregator -EV" is formulated. The first stage of scheduling is dominated by the MG, which publishes the discharge reservation demand of each period to users through EV aggregation, and the EV users make reservations according to their own conditions. The optimization strategy aiming at minimizing the operation cost of the MG is adopted. The subject of the second stage of scheduling is the EV aggregator. According to the quantity of electricity purchased by the micro-grid and the state of EV to pile, the aggregator proposes an allocation strategy considering the state of charge and aiming at minimizing the comprehensive income difference of user discharge. Furthermore, the default uncertainty of electric vehicles is considered, and countermeasures are taken in the aspects of scheduled discharge plan and scheduling strategy. Finally, a small MG system including fan, photovoltaic, energy storage and electric vehicle was established on the MATLAB platform for simulation, and the scheduled discharge information of electric vehicle and the optimal scheduling model of the MG taking electric vehicle discharge into account were obtained. The power distribution results of different EV to pile scenarios and MG default were obtained.
The following conclusions can be drawn from the simulation analysis: (1) The scheduling strategy under the reservation-default discharge mechanism proposed focuses on the information interaction between MG and EV users, and users participate in scheduling in the form of autonomous reservation, which effectively highlights the initiative of users. At the same time, considering the uncertainty of breach of contract reduces the adverse impact of user behavior stochasticity on scheduling, makes the EV to pile discharge situation in each period more matching with the power shortage in each period of the system, and can effectively alleviate the MG peak power supply pressure. (2) The MG-EV two-stage scheduling strategy based on EV aggregator proposed in this paper can make MG purchase less power from the grid to meet the power balance of the system, reduce its electricity cost to a certain extent, and contribute to the development of clean energy in the long run. The EV discharge power allocation strategy takes into account the EV state of charge and the balance of user income. (3) A relatively loose default mechanism is designed on the basis of meeting the normal operation. By providing a reasonable scheduling interval for MG side and measures such as judging default based on the overall power generation and settling default penalty by individual EV side, the flexibility of MG scheduling and user behavior is guaranteed, which is conducive to the development of this model. (4) A series of simulation experiments are carried out to verify the effectiveness of the scheduling strategy under the proposed reservation-default mechanism. In the subsequent research, it will be further improved from the aspects of technical scheme and engineering application based on the actual situation.

Key words： Reservation-default discharge mechanism uncertainty of default micro-grid electric vehicles two-stage optimal scheduling strategy

Received: 10 December 2021

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TM732

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	Li Changyun
	Xu Minling
	Cai Shuyuan

Cite this article:

Li Changyun,Xu Minling,Cai Shuyuan. Two-Stage Optimal Scheduling Strategy for Micro-Grid Considering EV Default Uncertainty[J]. Transactions of China Electrotechnical Society, 2023, 38(7): 1838-1851.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.212010 OR https://dgjsxb.ces-transaction.com/EN/Y2023/V38/I7/1838

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