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Demand response models with correlated price data: a robust optimization approach

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IIT-12-139A.pdf (1.938Mb)
Fecha
01/08/2012
Autor
Ferreira, Rafael de Sa
Nobrega Barroso, Luiz Augusto
Carvalho, Martha Martins
Estado
info:eu-repo/semantics/publishedVersion
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Resumen
 
 
In the electricity industry, the processes through which consumers respond to price signals embedded in tariffs by changing their consumption patterns is generally referred to as demand response. In such a context, consumers are offered an opportunity to maximize the surplus derived from electricity usage by actively scheduling consumption over time periods with potentially different energy prices. The objective of this work is to analyze the role of correlation in prices of successive periods over which consumption is to be scheduled, in a demand response context. We use robust optimization techniques to propose an optimization model for consumption scheduling when prices of different periods are highly correlated, and also suggest approaches to correctly incorporate real-world correlated price data to this model. Positive results from quantitative case studies indicate that it is of great importance to employ a solution approach that correctly models correlation among prices when scheduling consumption.
 
URI
http://hdl.handle.net/11531/9668
Demand response models with correlated price data: a robust optimization approach
Tipo de Actividad
Artículos en revistas
ISSN
0306-2619
Palabras Clave

Demand response; Correlated data; Robust optimization; Principal component analysis
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Repositorio de la Universidad Pontificia Comillas copyright © 2015  Desarrollado con DSpace Software
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