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Decentralized Optimal Demand-Side Management for PHEV Charging in a Smart Grid

机译：智能电网中PHEV充电的分散式最优需求侧管理

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摘要

Plug-in hybrid electric vehicles (PHEV) are expected to become widespread in the near future. However, high penetration of PHEVs can overload the distribution system. In smart grid, the charging of PHEVs can be controlled to reduce the peak load, known as demand-side management (DSM). In this paper, we focus on the DSM for PHEV charging at low-voltage transformers (LVTs). The objective is to flatten the load curve of LVTs, while satisfying each consumer’s requirement for their PHEV to be charged to the required level by the specified time. We first formulate this problem as a convex optimization problem and then propose a decentralized water-filling-based algorithm to solve it. A moving horizon approach is utilized to handle the random arrival of PHEVs and the inaccuracy of the forecast nonPHEV load. We focus on decentralized solutions so that computational load can be shared by individual PHEV chargers and the algorithm is scalable. Numerical simulations are given to demonstrate the effectiveness of our algorithm.
机译：插电式混合动力汽车（PHEV）有望在不久的将来变得广泛。但是，插电式混合动力汽车的高渗透率可能会使配电系统过载。在智能电网中，可以控制PHEV的充电以减少峰值负载，这称为需求侧管理（DSM）。在本文中，我们专注于在低压变压器（LVT）上为PHEV充电的DSM。目的是使LVT的负载曲线平坦，同时满足每个消费者的PHEV要求，使其在指定时间内充电到所需水平。我们首先将此问题表述为凸优化问题，然后提出一种基于分散注水的算法来求解。动视线方法用于处理PHEV的随机到达以及预测的非PHEV负荷的不准确性。我们专注于分散式解决方案，以便各个PHEV充电器可以共享计算负载，并且该算法具有可扩展性。数值仿真表明了该算法的有效性。

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