论文标题
通过新型原始多偶偶有亚级别（SPMDS）算法的新型电动汽车充电控制
Decentralized Electric Vehicle Charging Control via a Novel Shrunken Primal Multi-Dual Subgradient (SPMDS) Algorithm
论文作者
论文摘要
大量电动汽车（EV）的充电过程需要协调和控制，以减轻其对分销网络的影响以及提供各种电网服务的影响。但是，现有的EV充电控制范例的可伸缩性受到电动汽车数量或分销网络维度的限制，这在很大程度上损害了EVS的总服务功能和适用性。为了克服可伸缩性障碍，本文是由瓦利填充服务的最佳调度问题进行的，（1）通过对EV（原始决策变量）进行分组（原始决策变量）进行分组，并在分配网络和（2）开发出一个新的EV组中，提出了一种新的尺寸方法，并建立电压（全球耦合约束）更新，以开发出一个新的EV组。算法解决了这一减少尺寸问题。拟议的基于SPMD的控制框架不需要电动汽车之间的通信，在原始次级更新中降低了43％的计算成本，并且在双重次级更新中最多减少了68％的计算成本。通过改进的IEEE 13总线测试馈线和改进的IEEE 123-BUS测试馈线的模拟证明了所提出算法的效率和功效。
The charging processes of a large number of electric vehicles (EVs) require coordination and control for the alleviation of their impacts on the distribution network and for the provision of various grid services. However, the scalability of existing EV charging control paradigms are limited by either the number of EVs or the distribution network dimension, largely impairing EVs' aggregate service capability and applicability. To overcome the scalability barrier, this paper, motivated by the optimal scheduling problem for the valley-filling service, (1) proposes a novel dimension reduction methodology by grouping EVs (primal decision variables) and establishing voltage (global coupled constraints) updating subsets for each EV group in the distribution network and (2) develops a novel decentralized shrunken primal multi-dual subgradient (SPMDS) optimization algorithm to solve this reduced-dimension problem. The proposed SPMDS-based control framework requires no communication between EVs, reduces over 43% of the computational cost in the primal subgradient update, and reduces up to 68% of the computational cost in the dual subgradient update. The efficiency and efficacy of the proposed algorithm are demonstrated through simulations over a modified IEEE 13-bus test feeder and a modified IEEE 123-bus test feeder.
