4.7 Article

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

Journal

IEEE TRANSACTIONS ON SMART GRID
Volume 6, Issue 2, Pages 726-736

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2014.2363096

Keywords

Decentralized convex optimization; demand-side management (DSM); plug-in hybrid electric vehicle (PHEV); smart grid; water filling

Funding

  1. National Natural Science Foundation of China [61273113]
  2. Zhejiang Provincial Natural Science Foundation of China [LR13F030002]

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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.

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