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Real-Time Implementation of Smart Wireless Charging of On-Demand Shuttle Service for Demand Charge Mitigation

机译:实时实施按需班车服务的智能无线充电,需求费用减缓

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This paper presents a smart charge management strategy for an on-demand electric shuttle operating at the National Renewable Energy Laboratory (NREL) campus and supported by an inductive charger at the vehicle's waiting spot. A new control algorithm has been proposed for mitigating the demand charges incurred from the wireless charger. It monitors the shuttle, wireless charger, renewable energy generation, and other loads and regulates charging behavior for demand charge mitigation. Within the control algorithm, an energy prediction is made to estimate the mobility needs of the vehicle and maintain uninterrupted service during operation while still minimizing peak demand. The proposed controller is designed and optimized using a Simulink model for the entire system. It is then implemented and tested in real time at the NREL campus using online cloud services. Two vehicle-use cases-charge-sustaining and charge-depletion operation-are tested under different campus power profiles and drive cycles to assess the controller's performance. The proposed controller showed a robust performance under different driving scenarios, with high correlation between simulation and experimental data. The results show that proper demand response can be achieved, with an average of 94% reduction of charging loads during peak demand events.
机译:本文介绍了在全国可再生能源实验室(NREL)校园内运营的按需电气班车的智能费用管理策略,并由车辆等候景点的电感充电器支持。提出了一种新的控制算法,用于减轻无线充电器所产生的需求费用。它监控班车,无线充电器,可再生能源生成和其他负载,并调节需求费用减缓的充电行为。在控制算法内,使能量预测来估计车辆的移动性需求,并在操作期间保持不间断的服务,同时仍然最小化峰值需求。建议的控制器使用用于整个系统的Simulink模型来设计和优化。然后使用在线云服务在NREL校园实时实现和测试。在不同的校园电源配置文件和驱动循环下测试两个车辆用例抵抗持续和电荷耗尽操作,以评估控制器的性能。所提出的控制器在不同的驾驶场景下表现出强大的性能,模拟和实验数据之间具有高相关性。结果表明,可以实现适当的需求响应,平均达到峰值需求事件期间的充电负荷减少94%。

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