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首页> 外文期刊>Proceedings of the IEEE >Aggregation and Charging Control of PHEVs in Smart Grid: A Cyber–Physical Perspective
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Aggregation and Charging Control of PHEVs in Smart Grid: A Cyber–Physical Perspective

机译：智能电网中PHEV的聚合和充电控制：网络物理角度

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摘要

Modern smart grid, as a typical cyber–physical system (CPS), allows plug-in hybrid electric vehicles (PHEVs) to be a promising candidate for grid services. In this paper, by following the CPS design approach, we propose a novel framework for the local aggregator to estimate the charging status and solve for the charging control signals for PHEVs. The physical battery charging is executed by charging stalls, where charging information is processed in the embedded system and only the generated index information is transmitted to the aggregator via Internet. An aggregation model is developed for the entire cyberspace to inherently guarantee heterogeneous charging requirements, i.e., deadlines for charging. Furthermore, we develop a nonlinear model-predictive control (NMPC) scheme for the overnight valley-filling service. Both the aggregation model and control strategy are designed based on the PHEV population migration probabilities. From the CPS perspective, both the cyber and physical loads of this novel framework are extremely low. As part of this paper, we present a case study to verify the proposed approaches.
机译：作为典型的网络物理系统（CPS），现代智能电网使插电式混合动力汽车（PHEV）成为电网服务的有希望的候选者。在本文中，通过遵循CPS设计方法，我们为本地聚合器提出了一种新颖的框架，用于估计充电状态并求解PHEV的充电控制信号。物理电池充电是由充电站执行的，充电站在嵌入式系统中处理充电信息，只有生成的索引信息通过Internet发送到聚合器。针对整个网络空间开发了一种汇总模型，以内在地保证异构收费要求，即收费期限。此外，我们开发了用于夜间填谷服务的非线性模型预测控制（NMPC）方案。聚集模型和控制策略都是基于PHEV人口迁移概率设计的。从CPS的角度来看，此新颖框架的网络和物理负载都非常低。作为本文的一部分，我们提供了一个案例研究来验证所提出的方法。

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