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Short-Scale Stochastic Solar Energy Models: A Datacenter Use Case

Author

Listed:
  • Sara Alouf

    (Inria, Université Côte d’Azur, 06902 Sophia Antipolis, France
    The authors contributed equally to this work.)

  • Alain Jean-Marie

    (Inria, LIRMM, University Montpellier, CNRS, 34095 Montpellier, France
    The authors contributed equally to this work.)

Abstract

Modeling the amount of solar energy received by a photovoltaic panel is an essential part of green IT research. The specific motivation of this work is the management of the energy consumption of large datacenters. We propose a new stochastic model for the solar irradiance that features minute-scale variations and is therefore suitable for short-term control of performances. Departing from previous models, we use a weather-oriented classification of days obtained from past observations to parameterize the solar source. We demonstrate through extensive simulations, using real workloads, that our model outperforms the existing ones in predicting performance metrics related to energy storage.

Suggested Citation

  • Sara Alouf & Alain Jean-Marie, 2020. "Short-Scale Stochastic Solar Energy Models: A Datacenter Use Case," Mathematics, MDPI, vol. 8(12), pages 1-26, November.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:12:p:2127-:d:452262
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    References listed on IDEAS

    as
    1. Gueymard, Christian A., 2014. "A review of validation methodologies and statistical performance indicators for modeled solar radiation data: Towards a better bankability of solar projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1024-1034.
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