[论文解读] Value of Optimal Trip and Charging Scheduling of Commercial Electric Vehicle Fleets with Vehicle-to-Grid in Future Low Inertia Systems

Alicia Blatiak, Federica Bellizio+2 more|arXiv (Cornell University)|Apr 25, 2022

Electric Vehicles and Infrastructure参考文献 24被引用 32

一句话总结

本文提出一种混合整数线性规划模型，用于优化低惯性电力系统中具备车网互动（V2G）能力的商用电动汽车（EV）车队的行程与充电调度。通过协调每日行程时间与实时电能及辅助服务价格，该模型在夏季可使车队收入最高提升38%，冬季提升12%，同时通过提供调频服务，实现相当于从电网中移除一台联合循环燃气轮机（CCGT）的效果。

ABSTRACT

The electrification of transport is seen as an important step in the global decarbonisation agenda. With such a large expected load on the power system from electric vehicles (EVs), it is important to coordinate charging in order to balance the supply and demand for electricity. Bidirectional charging, enabled through Vehicle-to-Grid (V2G) technology, will unlock significant storage capacity from stationary EVs that are plugged in. To take this concept a step further, this paper quantifies the potential revenues to be gained by a commercial EV fleet operator from simultaneously scheduling its trips on a day-ahead basis, as well as its charging. This allows the fleet to complete its trips (with user defined trip length and distance), while taking advantage of fluctuating energy and ancillary services prices. A mathematical framework for optimal trip scheduling is proposed, formulated as a mixed-integer linear program, and is applied to several relevant scenarios of the present and future British electricity system. It is demonstrated that an optimal journey start time can increase the revenue of commercial fleets by up to 38% in summer and 12% in winter. This means a single EV from the maintenance fleet can make additional annual revenue of up to {\pounds}729. Flexible trip schedules are more valuable in the summer because keeping EVs plugged in during peak solar output will benefit the grid and the fleet operators the most. It was also found that a fleet of 5,000 EVs would result in the equivalent $ extrm{CO}_2$ of removing one Combined Cycle Gas Turbine from the system. This significant increase in revenue and carbon savings show this approach is worth investigating for potential future application.

研究动机与目标

• 量化在低惯性电力系统中，利用V2G技术优化商用EV车队行程与充电调度所带来的经济与电网效益。
• 评估在英国电力市场中，能源与辅助服务价格波动背景下，灵活行程调度对收入的影响。
• 评估EV车队提供调频服务在减少碳排放方面的潜力，特别是替代基于化石燃料的旋转备用。
• 开发一种可扩展的优化框架，整合现实运营约束与市场动态，服务于车队运营商。

提出的方法

• 构建一种混合整数线性规划（MILP）模型，联合优化商用EV车队的行程开始时间与充电调度。
• 纳入分时电价、上调与下调平衡服务价格，以及调频需求。
• 基于行程距离与持续时间建模车辆能耗，同时考虑电池荷电状态约束及充放电效率。
• 采用最低系统频率约束，量化对同步惯量需求的减少，从而实现CCGT替代量的计算。
• 基于英国电力市场的实际数据，对配送与维护车队进行场景模拟。
• 通过行程延迟、价格波动及可再生能源出力模式的敏感性分析验证结果。

实验结果

研究问题

• RQ1 在动态电力市场中，通过优化行程开始时间与充电调度，商用EV车队能额外获得多少收入？
• RQ2 灵活行程调度对电网惯量支撑的影响如何？其在多大程度上可实现联合循环燃气轮机（CCGT）的替代？
• RQ3 调频服务价格波动与可再生能源出力变化如何影响最优调度的价值？
• RQ4 在城市环境中，交通相关延迟在多大程度上降低优化调度的经济收益？
• RQ5 在季节性条件下，特别是夏季与冬季之间，灵活调度的价值有何差异？

主要发现

• 最优行程调度使车队在夏季收入最高提升38%，冬季提升12%，单辆EV年额外收入可达729英镑。
• 5,000辆EV车队通过提供调频服务，可至少替代一台CCGT机组，每月避免约66,500公斤碳排放。
• 无论调频服务价格水平如何，灵活行程调度均带来23%的收入溢价，优于固定调度。
• 行程延迟一小时使夏季最高收入减少7–11%，冬季减少8–13%；冬季更敏感，因价格波动更高且太阳能发电更少。
• 夏季灵活调度价值更高，因太阳能发电量更大，EV可在光伏出力高峰时段保持充电状态，支持电网。
• 对价格变化的敏感性分析表明，调频价格下降25%导致收入同比减少25%；若进一步下降25%，收入将减少33–34%，表明市场响应具有非线性特征。