Decentralized charging control strategy of the electric vehicle aggregator based on augmented Lagrangian method. (January 2019)

• Record Type: Journal Article
• Authors: Xu, Shaolun; Yan, Zheng; Feng, Donghan; Zhao, Xiaobo
• Is Part Of: International journal of electrical power & energy systems. Volume 104(2019)
• Page Start: 673
• Page End: 679
• Publication Date: 2019-01
• Subjects: Electric vehicle aggregator -- Decentralized charging control strategy -- Augmented Lagrangian method -- Alternating direction multiplier method; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2018.07.024
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Decentralized charge control strategy can obtain the same revenue as the centralized control strategy. Convergence of decentralized charging control strategy is better than the centralized control strategy. Each electric vehicle calculates the charging scheme locally in the decentralized algorithm. Decentralized charge control strategy has a relatively high computing efficiency and fast convergence rate. Abstract: Uncoordinated charging of large-scale electric vehicles can affect the safe and economic operation of distribution power system. As an intermediary between power grid and individual electric vehicle, electric vehicle aggregator can play an important role in the coordination and management of electric vehicle charging. In this paper, we develop a decentralized EV charging control strategy of the electric vehicle aggregator for scheduling the flexible charging demand of plug-in electric vehicles in residential distribution networks. First, the centralized charging control model of the electric vehicle aggregator aiming at the maximization of its revenue under the background of time of use price mechanism is established, meanwhile meeting individual charging requirements and satisfying distribution network constraints. Then a decentralized charging control strategy of the electric vehicle aggregator based on the augmented Lagrangian method and the alternating direction multiplier method is proposed. The electric vehicles can decide their charging plan locally with the decentralized strategy, which can eliminate the problem of high communication cost, low computing efficiency and privacy protection caused by the centralized charging control model in practical application. The effectiveness of the proposed strategy is evaluated with a representative distribution network model.