Distributed Control of PEV Charging Based on Energy Demand Forecast
Distributed Control of PEV Charging Based on Energy Demand Forecast
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DOI：
10.1109/tii.2017.2705075
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发表时间：
2018
影响因子：
12.3
通讯作者：
M. Kisacikoglu;F. Erden;N. Erdogan
中科院分区：
文献类型：
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作者：
M. Kisacikoglu;F. Erden;N. Erdogan
针对插电式电动汽车并网问题，提出了一种新的分布式智能充电策略。主要目标是平滑每日电网负荷概况，同时确保每辆PEV在出发时具有所需的充电水平状态。在该策略的开发过程中，还考虑了通信和计算开销以及PEV用户隐私。它包括两个阶段：1)离线过程，根据预测的移动能源需求和基本负载概况估计参考运行功率水平；2)实时过程，确定每辆电动汽车的充电功率，使聚合负载跟踪参考负载水平。针对不同的启发式充电方案和PEV渗透水平，在一次和二次配电网上进行了测试。将结果与最优解决方案和其他最先进的技术在方差和峰值方面进行比较，并显示出竞争力。最后，使用商用充电站和电动汽车进行了实际车辆测试。
This paper presents a new distributed smart charging strategy for grid integration of plug-in electric vehicles (PEVs). The main goal is to smooth the daily grid load profile while ensuring that each PEV has a desired state of charge level at the time of departure. Communication and computational overhead, and PEV user privacy are also considered during the development of the proposed strategy. It consists of two stages: 1) an offline process to estimate a reference operating power level based on the forecasted mobility energy demand and base loading profile, and 2) a real-time process to determine the charging power for each PEV so that the aggregated load tracks the reference loading level. Tests are carried out both on primary and secondary distribution networks for different heuristic charging scenarios and PEV penetration levels. Results are compared to that of the optimal solution and other state-of-the-art techniques in terms of variance and peak values, and shown to be competitive. Finally, a real vehicle test implementation is done using a commercial-of-the-shelf charging station and an electric vehicle.