DocumentCode
635899
Title
Optimal fully electric vehicle load balancing with an ADMM algorithm in Smartgrids
Author
Mercurio, Andrea ; Di Giorgio, Alessandro ; Purificato, Fabio
Author_Institution
Dept. of Comput., Control & Manage. Eng. “Antonio Ruberti”, Univ. of Rome “Sapienza”, Rome, Italy
fYear
2013
fDate
25-28 June 2013
Firstpage
119
Lastpage
124
Abstract
In this paper we present a system architecture and a suitable control methodology for the load balancing of Fully Electric Vehicles at Charging Station (CS). Within the proposed architecture, control methodologies allow to adapt Distributed Energy Resources (DER) generation profiles and active loads to ensure economic benefits to each actor. The key aspect is the organization in two levels of control: at local level a Load Area Controller (LAC) optimally calculates the FEV´s charging sessions, while at higher level a Macro Load Area Aggregator (MLAA) provides DER with energy production profiles, and LACs with energy withdrawal profiles. Proposed control methodologies involve the solution of a Walrasian market equilibrium and the design of a distributed algorithm.
Keywords
distributed control; electric variables control; electric vehicles; smart power grids; ADMM algorithm; DER generation profile; LAC; MLAA; Smartgrids project; Walrasian market equilibrium; alternating direction method of multipliers; charging station; control methodology; distributed algorithm; distributed energy resources; energy production profiles; energy withdrawal profiles; fully electric vehicle load balancing; load area controller; macro load area aggregator; Cost function; Density estimation robust algorithm; Economics; Generators; Load management; Power demand; Production; Distributed systems; Full-Electric Vehicles(FEV); Load Balancing; Power systems; Primal Dual Methods; Renewable energy and Sustainability; Vehicle To Grid (V2G);
fLanguage
English
Publisher
ieee
Conference_Titel
Control & Automation (MED), 2013 21st Mediterranean Conference on
Conference_Location
Chania
Print_ISBN
978-1-4799-0995-7
Type
conf
DOI
10.1109/MED.2013.6608708
Filename
6608708
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