Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1502
Título: Data mining techniques contributions to support electrical vehicle demand response
Autor: Soares, João
Ramos, Sérgio
Vale, Zita
Morais, H.
Faria, Pedro
Palavras-chave: Classification
Clustering
Data mining
Demand response
Electric vehicle
Mixed Integer Non-Linear Programming (MINLP)
Data: 2012
Editora: IEEE
Resumo: The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.
URI: http://hdl.handle.net/10400.22/1502
ISBN: 978-1-4673-1934-8
Versão do Editor: http://ieeexplore.ieee.org/xpl/abstractKeywords.jsp?arnumber=6281444
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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