A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles

Abstract

Coordinated dispatch of plug-in electric vehicles (PEVs) with renewable energies has been proposed in recent years. However, it is difficult to achieve effective PEV dispatch with a win-win result, which not only optimizes power system operation, but also satisfies the requirements of PEV owners. In this paper, a multi-period PEV dispatch framework, combining day-ahead dispatch with real-time dispatch, is proposed. On the one hand, the day-ahead dispatch is used to make full use of wind power and minimize the fluctuation of total power in the distribution system, and schedule the charging/discharging power of PEV stations for each period. On the other hand, the real-time dispatch arranges individual PEVs to meet the charging/discharging power demands of PEV stations given by the day-ahead dispatch. To reduce the dimensions of the resulting large-scale, non-convex problem, PEVs are clustered according to their travel information. An interval optimization model is introduced to obtain the problem solution of the day-ahead dispatch. For the real-time dispatch, a priority-ordering method is developed to satisfy the requirements of PEV owners with fast response. Numerical studies demonstrate the effectiveness of the presented framework.

Forecasting the State of Health of Electric Vehicle Batteries to Evaluate the Viability of Car Sharing Practices

“…However, our results derived from empirical data analysis confirm findings from Lacey et al [39], Peterson et al [43], and Le et al [41], where, based on experimental results under controllable conditions, the SoC and DoD were found to affect battery degradation significantly. Given that a literature review reveals that most of the published work on battery SoH is simulation with very little verification with the experimental results [38,[41][42][43][44][45]63], this insight seems particularly valuable. From a business point of view, knowing that the battery is the most expensive part of an EV and accounts for about 54% of the total production costs of the vehicle [64], this research provides a valuable reference on the effects of different car-sharing practices and driving and charging behaviors on EV battery degradation.…”

“…Their simulation results indicate the effectiveness of the methods for SoH estimation. EV lithium-ion battery cell models and simulations, among others, were also explored by Ramadesigan et al [42], Peterson et al [43], Zhang et al [44], and Huang et al [45]. Summarizing the results from the literature on EV Lithium-ion battery degradation, the capacity loss in lithium-ion batteries (CL Lithium-ion ) may be attributed to two main elements:…”

Charge Control and Operation of Electric Vehicles in Power Grids: A Review

“…In [37,74,[87][88][89][90], RT charge management mechanisms were proposed. However, provision of regulation services was not considered in [37,74,[87][88][89], and market mechanisms were not considered in [90]. In [91], a three-stage framework for DA and RT charge management for an EVA providing regulation services is presented.…”

Linearized Stochastic Scheduling of Interconnected Energy Hubs Considering Integrated Demand Response and Wind Uncertainty

“…Constraints (14) and (15) represent the limits on gas well production and nodal pressure. Natural gas flow is modeled by the nonlinear Weymouth function as constraint (16), which is determined by the incremental pressure between two end nodes of pipeline, and Q s mn,t = (Q out,s mn,t + Q in,s mn,t )/2 is the average gas flow of pipeline mn. Constraint (17) represents the limit on nodal gas balance.…”