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Balancing Wind and Batteries: Towards Predictive Verification of Smart Grids

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NASA Formal Methods (NFM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12673))

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Abstract

We study a smart grid with wind power and battery storage. Traditionally, day-ahead planning aims to balance demand and wind power, yet actual wind conditions often deviate from forecasts. Short-term flexibility in storage and generation fills potential gaps, planned on a minutes time scale for 30–60 min horizons. Finding the optimal flexibility deployment requires solving a semi-infinite non-convex stochastic program, which is generally intractable to do exactly. Previous approaches rely on sampling, yet such critical problems call for rigorous approaches with stronger guarantees. Our method employs probabilistic model checking techniques. First, we cast the problem as a continuous-space Markov decision process with discretized control, for which an optimal deployment strategy minimizes the expected grid frequency deviation. To mitigate state space explosion, we exploit specific structural properties of the model to implement an iterative exploration method that reuses pre-computed values as wind data is updated. Our experiments show the method’s feasibility and versatility across grid configurations and time scales.

This research has been partially funded by NWO grants OCENW.KLEIN.187 and NWA.1160.18.238, and by NWO VENI grant no. 639.021.754.

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Author information

Authors and Affiliations

  1. Department of Software Science, Radboud University, Nijmegen, The Netherlands

    Thom S. Badings, Nils Jansen & Marnix Suilen

  2. University of Twente, Enschede, The Netherlands

    Arnd Hartmanns

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  1. Thom S. Badings
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  2. Arnd Hartmanns
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  3. Nils Jansen
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  4. Marnix Suilen
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Corresponding author

Correspondence to Thom S. Badings .

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Editors and Affiliations

  1. NASA Langley Research Center, Hampton, VA, USA

    Aaron Dutle

  2. National Institute of Aerospace, Hampton, VA, USA

    Mariano M. Moscato

  3. National Institute of Aerospace, Hampton, VA, USA

    Laura Titolo

  4. NASA Langley Research Center, Hampton, VA, USA

    César A. Muñoz

  5. National Institute of Aerospace, Hampton, VA, USA

    Ivan Perez

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Badings, T.S., Hartmanns, A., Jansen, N., Suilen, M. (2021). Balancing Wind and Batteries: Towards Predictive Verification of Smart Grids. In: Dutle, A., Moscato, M.M., Titolo, L., Muñoz, C.A., Perez, I. (eds) NASA Formal Methods. NFM 2021. Lecture Notes in Computer Science(), vol 12673. Springer, Cham. https://doi.org/10.1007/978-3-030-76384-8_1

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  • DOI: https://doi.org/10.1007/978-3-030-76384-8_1

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