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Journal article

Multi-agent based modeling for electric vehicle integration in a distribution network operation

By Hu, Junjie1,2,3; Morais, Hugo1; Lind, Morten1,2,3,4,5,6; Bindner, Henrik W.1,2,3,5

From

Department of Electrical Engineering, Technical University of Denmark1

Center for Electric Power and Energy, Centers, Technical University of Denmark2

Energy System Management, Center for Electric Power and Energy, Centers, Technical University of Denmark3

Department of Automation, Technical University of Denmark4

Risø National Laboratory for Sustainable Energy, Technical University of Denmark5

Automation and Control, Department of Electrical Engineering, Technical University of Denmark6

The purpose of this paper is to present a multi-agent based modeling technology for simulating and operating a hierarchical energy management of a power distribution system with focus on EVs integration. The proposed multi-agent system consists of four types of agents: i) Distribution system operator (DSO) technical agent and ii) DSO market agents that both belong to the top layer of the hierarchy and their roles are to manage the distribution network by avoiding grid congestions and using congestion prices to coordinate the energy scheduled; iii) Electric vehicle virtual power plant agents are in the middle level of the hierarchy and their roles are to manage the charge process of the electric vehicles; iv) Electric vehicle agents are placed at the bottom layer of the hierarchy and they represent electric vehicle owners with different users’ profiles.

To demonstrate the coordination behavior of the proposed system, a multi-agent simulation platform is developed based on the co-simulation environment of JACK, Matlab and GAMS. The aim of the multi-agent system is to simulate the collaborative (all agents contribute to achieve an optimized global performance) but also competitive environment (each agent will try to increase its utilities or reduce its costs). [All rights reserved Elsevier].

Language: English
Year: 2016
Pages: 341-351
ISSN: 18732046 and 03787796
Types: Journal article
DOI: 10.1016/j.epsr.2016.03.014
ORCIDs: Hu, Junjie , Morais, Hugo , Lind, Morten and Bindner, Henrik W.

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