Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1389
Título: Using data mining techniques to support DR programs definition in smart grids
Autor: Vale, Zita
Morais, H.
Ramos, Sérgio
Soares, João
Faria, Pedro
Palavras-chave: Clustering
Data mining
Demand Response (DR)
Energy resources management
Intelligent power systems
Locational Marginal Prices (LMP)
Mixed Integer No- Linear Programming (MINLP)
Data: 2011
Editora: IEEE
Resumo: In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.
URI: http://hdl.handle.net/10400.22/1389
ISBN: 978-1-4577-1000-1
ISSN: 1944-9925
Versão do Editor: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6039081
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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