Peak and valley regulation of distribution network with electric vehicles

Li, Fucun; Guo, Hongwei; Jing, Zhen; Wang, Zhaojun; Wang, Xinku

doi:10.1049/joe.2018.8540

Cited by 13 publications

(4 citation statements)

References 7 publications

(7 reference statements)

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“…The purpose of using the combined forecasting method is to minimize the forecasting error and determine the combined coefficients by establishing a quadratic plan. The analysis of the gray prediction model described above is as follows, suppose the original data series [6] x (�)…”

Section: Road Network Traffic Forecastmentioning

confidence: 99%

Forecasting method of electric vehicle load time-space distribution considering traffic distribution

Liu

Xie

et al. 2020

E3S Web Conf.

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The main work of this paper is to establish an electric vehicle(EV) load forecasting model based on road network traffic distribution for urban and inter-city transportation networks. This paper established a road network model considering the traffic impedance for the EV load forecasting of the urban fast charging network, and studied the prediction method of the time-space distribution of EV charging demand in the fast charging mode .Based on the expressway, the method for predicting the time-space distribution of EV load in the inter-city fast charging network is studied, and a time-space distribution load forecasting model is established. Based on the time-space distribution of traffic flow, combined with EV charging characteristics and travel routes, load simulation is performed. By constructing a prediction method for the time-space distribution of EV charging demand in the fast charging mode, it provides theoretical and methodological support for the research of time-sharing and segmented metering and charging strategies for EV fast charging stations,, and provides an important reference for the development of EV charging facilities operating cost benefits, economic performance indicators and calculation models under fast charging mode, which are of great significance to promote the popularization and application of EV fast charging modes.

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Section: Road Network Traffic Forecastmentioning

confidence: 99%

Forecasting method of electric vehicle load time-space distribution considering traffic distribution

Liu

Xie

et al. 2020

E3S Web Conf.

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“…A great quantity of power battery packs in the charging and switching station can absorb power from the power grid during the low power period as controllable load, release the power during the peak power period as controllable power source, reduce the peak load, play the role of peak load filling valley, and suppress the fluctuation of load curve. When the number of participating power batteries reaches a certain scale, charging and switching power stations can even improve power flow distribution, stabilize distribution network voltage, and improve power quality 21 …”

Section: Construction Of Operation Modelmentioning

confidence: 99%

An electric vehicle operation optimization method based on demand‐side management

Gan

Chui-yong

2019

Concurrency and Computation

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Against the background of energy restriction and environmental pollution, in recent years, new energy electric vehicles have developed rapidly with their advantages of energy saving and environmental protection. To realize the benign interaction between electric vehicle charging and switching power stations and power grid, and the demand-side management of electric vehicle charging and switching power stations, the Monte Carlo random sampling method is used to collect the battery-charged state of batteries in one day. Considering the constraints of charging and discharging times of charging stations, the operation model of charging and switching stations for electric vehicles is established, and the interior point optimization method is used to solve the model; thus, the optimal orderly charging and discharging strategy for electric vehicles can be obtained. Finally, simulation results show that the optimized charging mode can effectively reduce the peak-valley difference of the system load and improve the stability of the system compared with the stochastic charging mode. In addition, this mode of charging can effectively develop the economic potential of the electric-vehicle batteries without affecting the use needs of the owners, and it has good prospects for engineering popularization.

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“…[1][2][3] Thus, based on vehicle-to-grid (V2G) technology and under the condition of meeting the demand of car owners, EVs can participate in the regulation of the public power grid, and providing conditions for peak shaving and valley filling. [4][5][6] On the other side, the electric energy stored in EVs can also provide a short-term power supply for residents in case of power failure of the public grid. [7][8][9] However, when the EVs are used as the main power source of the system, that is, the public power grid fails, the system actually operates in islanded mode.…”

Section: Introductionmentioning

confidence: 99%

Finite-time disturbance observer–based funnel voltage control strategy for vehicle-to-grid inverter in islanded mode

Dai

Zhang

Liu

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part I:

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Based on vehicle-to-grid technology, electric vehicles can be used as power sources in the case of power failure. With the aim to reduce voltage overshoot and improve the anti-disturbance ability of the vehicle-to-grid inverter, a high-performance voltage control strategy based on funnel control and finite-time disturbance observer is developed. First, the dynamic model of the inverter in dq-frame is established, and the lumped disturbance including the unmodeled part is considered. Next, a novel funnel variable is proposed to ensure that the voltage tracking error can be stabilized within the prescribed funnel boundary, and thus enhance the transient performance. Then, a novel finite-time disturbance observer is designed to estimate the lumped disturbance in the system such as load fluctuations, and improve the anti-disturbance ability of the controller. Moreover, the second-order sliding mode differentiator is introduced to estimate the derivative of the virtual control law and eliminate the explosion of complexity problem in the derivation process. Finally, the finite-time stability of the proposed voltage control strategy is analyzed via the Lyapunov theory. The effectiveness of the proposed control strategy is verified by two cases.

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Peak and valley regulation of distribution network with electric vehicles

Cited by 13 publications

References 7 publications

Forecasting method of electric vehicle load time-space distribution considering traffic distribution

Forecasting method of electric vehicle load time-space distribution considering traffic distribution

An electric vehicle operation optimization method based on demand‐side management

Finite-time disturbance observer–based funnel voltage control strategy for vehicle-to-grid inverter in islanded mode

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