Power System Frequency Control Architecture Combining Open Charge Point Protocol and Electric Vehicle Model Predictive Charge Rate Control
Power System Frequency Control Architecture Combining Open Charge Point Protocol and Electric Vehicle Model Predictive Charge Rate Control
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DOI：
10.1109/access.2022.3211297
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发表时间：
2022
期刊：
影响因子：
3.9
通讯作者：
Kenta Kirihara;T. Kawabe
中科院分区：
文献类型：
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作者：
Kenta Kirihara;T. Kawabe
本研究提出一种利用开放充电点协议的电力系统频率控制架构，开放充电点协议是一种新兴的电动汽车充电速率控制开源协议。与传统的专注于构建高性能控制器的研究不同，本研究侧重于易于部署。具体来说，本研究围绕开源协议的基本功能探索了频率控制架构的设计，同时在不需要良好调优的专门协议的情况下允许大量性能。由于使用开源协议无法提供快速响应，因此所提出的架构通过以下方式减轻了这一限制：(a)利用分层结构模拟更快的控制间隔；(b)提供具有系统完整性保护方案行为的模型预测控制器，以便在大小干扰下都具有足够的性能。根据Simulink上的综合电力系统频率响应模型对总体结构进行了评估，包括大干扰和小干扰。与相同结构的调谐比例积分导数控制器相比，所提出的结构在阶跃扰动测试中平均降低了21.77%的最低点，在负载变化测试中平均降低了36.27%的标称频率标准差。
This research proposes a power system frequency control architecture which leverages Open Charge Point Protocol–a rising open-source protocol for charge rate control of electric vehicles. Unlike conventional research that focused on building a high-performance controller, this research puts emphasis on the ease of deployment. Specifically, this research explores the design of a frequency control architecture around the basic functionality of an open-source protocol while allowing substantial performance without the need for a well-tuned specialized protocol. As the usage of open-source protocols cannot provide a quick response, the proposed architecture alleviates this limitation by (a) utilizing a hierarchical structure to emulate a faster control interval and (b) providing a model predictive controller with system integrity protection scheme behavior to have sufficient performance under both large and small disturbances. The overall architecture is evaluated against an aggregated power system frequency response model on Simulink for both large and small disturbances. Compared to a tuned proportional integral derivative controller on the same architecture, the proposed architecture observed an average reduction of 21.77% in nadir in the step disturbance test and an average reduction of 36.27% in standard deviation from the nominal frequency in the load variation test.