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Balancing Energy Flexibilities Through Aggregation

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Data Analytics for Renewable Energy Integration (DARE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8817))

Abstract

One of the main goals of recent developments in the Smart Grid area is to increase the use of renewable energy sources. These sources are characterized by energy fluctuations that might lead to energy imbalances and congestions in the electricity grid. Exploiting inherent flexibilities, which exist in both energy production and consumption, is the key to solving these problems. Flexibilities can be expressed as flex-offers, which due to their high number need to be aggregated to reduce the complexity of energy scheduling. In this paper, we discuss balance aggregation techniques that already during aggregation aim at balancing flexibilities in production and consumption to reduce the probability of congestions and reduce the complexity of scheduling. We present results of our extensive experiments.

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Acknowledgments

This work was supported in part by the TotalFlex project sponsored by the ForskEL program of Energinet.dk.

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Authors and Affiliations

  1. Department of Computer Science, Aalborg University, Aalborg, Denmark

    Emmanouil Valsomatzis, Katja Hose & Torben Bach Pedersen

Authors
  1. Emmanouil Valsomatzis
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  2. Katja Hose
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  3. Torben Bach Pedersen
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Corresponding author

Correspondence to Emmanouil Valsomatzis .

Editor information

Editors and Affiliations

  1. Masdar Inst. of Science and Technology, Abu Dhabi, Utd.Arab.Emir.

    Wei Lee Woon

  2. Masdar Inst. of Science and Technology, Abu Dhabi, Utd.Arab.Emir.

    Zeyar Aung

  3. MIT Sloan School of Management, Cambridge, Massachusetts, USA

    Stuart Madnick

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© 2014 Springer International Publishing Switzerland

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Valsomatzis, E., Hose, K., Pedersen, T.B. (2014). Balancing Energy Flexibilities Through Aggregation. In: Woon, W., Aung, Z., Madnick, S. (eds) Data Analytics for Renewable Energy Integration. DARE 2014. Lecture Notes in Computer Science(), vol 8817. Springer, Cham. https://doi.org/10.1007/978-3-319-13290-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-13290-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13289-1

  • Online ISBN: 978-3-319-13290-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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