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Title:Adaptive prediction model accuracy in the control of residential energy resources
Authors:R.R. Negenborn, M. Houwing, B. De Schutter, J. Hellendoorn

Conference:2008 IEEE Multi-conference on Systems and Control (MSC 2008)
Address:San Antonio, Texas
Date:September 2008

Abstract:With the increasing use of distributed energy resources and intelligence in the electricity infrastructure, the possibilities for minimizing costs of household energy consumption increase. Technology is moving toward a situation in which automated energy management systems could control domestic energy generation, storage, and consumption. In previous work we have proposed a controller based on model predictive control for controlling an individual household using a micro combined heat and power plant in combination with heat and electricity storages. Although the controller provides adequate performance in computer simulations, the computational time required to determine which actions to take can be significant, due to the precise predictions made over a long prediction horizon. In this paper we propose to make the computations less time consuming by coarsening the quality of the predictions made over the prediction horizon by decreasing their time resolution. In simulation studies we illustrate the performance of the proposed approach.

Reference:R.R. Negenborn, M. Houwing, B. De Schutter, J. Hellendoorn. Adaptive prediction model accuracy in the control of residential energy resources. In Proceedings of the 2008 IEEE Multi-conference on Systems and Control (MSC 2008), San Antonio, Texas, pp. 311-316, September 2008.

BibTeX:
@inproceedings{Negenborn:08a,
  author =    {R. R. Negenborn and M. Houwing and B. {De Schutter} and J. Hellendoorn},
  title =     {Adaptive prediction model accuracy in the control of residential
               energy resources},
  booktitle = {Proceedings of the 2008 IEEE Multi-conference on Systems and Control},
  address =   {San Antonio, Texas},
  pages =     {311--316},
  year =      {2008},
  month =     {September}
}
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