DocumentCode :
3538137
Title :
Alternating Direction Method of Multipliers for decentralized electric vehicle charging control
Author :
Rivera, Jose ; Wolfrum, Philipp ; Hirche, Sandra ; Goebel, Christoph ; Jacobsen, Hans-Arno
Author_Institution :
Dept. of Comput. Sci., Tech. Univ. Munchen, Garching, Germany
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
6960
Lastpage :
6965
Abstract :
The integration of Electric Vehicles (EVs) into the power grid is a challenging task. From the control perspective, one of the main challenges is the definition of a comprehensive control structure that is scalable to large EV numbers. This paper makes two key contributions: (i) It defines the EV ADMM framework for decentralized EV charging control. (ii) It evaluates EV ADMM using actual data and various EV fleet control problems. EV ADMM is a decentralized optimization algorithm based on the Alternating Direction Method of Multipliers (ADMM). It separates the centralized optimal fleet charging problem into individual optimization problems for the EVs plus one aggregator problem that optimizes fleet goals. Since the individual problems are coupled, they are solved consistently by passing incentive signals between them. The framework can be parameterized to trade-off the importance of fleet goals versus individual EV goals, such that aspects like battery lifetime can be considered. We show how EV ADMM can be applied to control an EV fleet to achieve goals such as demand valley filling and minimal-cost charging. Due to its flexibility and scalability, EV ADMM offers a practicable solution for optimal EV fleet control.
Keywords :
electric vehicles; optimisation; power grids; secondary cells; ADMM framework; aggregator problem; alternating direction method; battery lifetime; charging control; control structure; decentralized electric vehicle; decentralized optimization; demand valley filling; fleet control problems; minimal-cost charging; multipliers; power grid; Batteries; Convergence; Cost function; Couplings; Renewable energy sources; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
ISSN :
0743-1546
Print_ISBN :
978-1-4673-5714-2
Type :
conf
DOI :
10.1109/CDC.2013.6760992
Filename :
6760992
Link To Document :
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