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Authors: Edgar Galván-Lopez 1 ; Marc Schoenauer 2 and Constantinos Patsakis 3

Affiliations: 1 Trinity College Dublin, Ireland ; 2 INRIA Saclay & LRI - Univ. Paris-Sud and CNRS, France ; 3 University of Piraeus, Greece

ISBN: 978-989-758-157-1

Keyword(s): Demand-Side Management, Electric Vehicles, Evolutionary Algorithms, Differential Evolution.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Evolutionary Computing ; Genetic Algorithms ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Representation Techniques ; Soft Computing

Abstract: Evolutionary Algorithms (EAs), or Evolutionary Computation, are powerful algorithms that have been used in a range of challenging real-world problems. In this paper, we are interested in their applicability on a dynamic and complex problem borrowed from Demand-Side Management (DSM) systems, which is a highly popular research area within smart grids. DSM systems aim to help both end-use consumer and utility companies to reduce, for instance, peak loads by means of programs normally implemented by utility companies. In this work, we propose a novel mechanism to design an autonomous intelligent DSM by using (EV) electric vehicles’ batteries as mobile energy storage units to partially fulfill the energy demand of dozens of household units. This mechanism uses EAs to automatically search for optimal plans, representing the energy drawn from the EVs’ batteries. To test our approach, we used a dynamic scenario where we simulated the consumption of 40 and 80 household units over a period of 3 0 working days. The results obtained by our proposed approach are highly encouraging: it is able to use the maximum allowed energy that can be taken from each EV for each of the simulated days. Additionally, it uses the most amount of energy whenever it is needed the most (i.e., high-peak periods) resulting into reduction of peak loads. (More)

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Paper citation in several formats:
Galván-Lopez E., Schoenauer M. and Patsakis C. (2015). Design of an Autonomous Intelligent Demand-Side Management System by using Electric Vehicles as Mobile Energy Storage Units by Means of Evolutionary Algorithms.In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA, ISBN 978-989-758-157-1, pages 106-115. DOI: 10.5220/0005607401060115

@conference{ecta15,
author={Edgar Galván-Lopez and Marc Schoenauer and Constantinos Patsakis},
title={Design of an Autonomous Intelligent Demand-Side Management System by using Electric Vehicles as Mobile Energy Storage Units by Means of Evolutionary Algorithms},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,},
year={2015},
pages={106-115},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005607401060115},
isbn={978-989-758-157-1},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 1: ECTA,
TI - Design of an Autonomous Intelligent Demand-Side Management System by using Electric Vehicles as Mobile Energy Storage Units by Means of Evolutionary Algorithms
SN - 978-989-758-157-1
AU - Galván-Lopez E.
AU - Schoenauer M.
AU - Patsakis C.
PY - 2015
SP - 106
EP - 115
DO - 10.5220/0005607401060115

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