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24897 Cascaded column generation for scalable predictive demand side management
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Toersche, H.A. and Molderink, A. and Hurink, J.L. and Smit, G.J.M. (2014) Cascaded column generation for scalable predictive demand side management. In: Proceedings of the 2014 IEEE International Energy Conference (ENERGYCON), 13-16 May 2014, Cavtat, Croatia. pp. 1228-1235. IEEE Power & Energy Society. ISBN 978-1-4799-2449-3

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Official URL: http://dx.doi.org/10.1109/ENERGYCON.2014.6850580

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Abstract

We propose a nested Dantzig-Wolfe decomposition, combined with dynamic programming, for the distributed scheduling of a large heterogeneous fleet of residential appliances with nonlinear behavior. A cascaded column generation approach gives a scalable optimization strategy, provided that the problem has a suitable structure. The presented approach extends the TRIANA smart grid framework for predictive demand side management; the main goal of this framework is peak shaving. Simulations validate that the approach is effective, but also show that the performance degrades for smaller group sizes.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-CAES: Computer Architecture for Embedded Systems, EWI-DMMP: Discrete Mathematics and Mathematical Programming
Research Program:CTIT-WiSe: Wireless and Sensor Systems
Research Project:DREAM: Dynamic Real-time Control Of Energy Streams In Buildings
Uncontrolled Keywords:Context, Electricity, Equations, Home appliances, Optimization, Smart grids, Vectors, Energy management, Mathematical programming, Power system management
ID Code:24897
Status:Published
Deposited On:14 August 2014
Refereed:Yes
International:Yes
More Information:statisticsmetis

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