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Power Management in a Hydro-Thermal System under Uncertainty by Lagrangian Relaxation

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Decision Making Under Uncertainty

Part of the book series: The IMA Volumes in Mathematics and its Applications ((IMA,volume 128))

Abstract

We present a dynamic multistage stochastic programming model for the cost-optimal generation of electric power in a hydro-thermal system under uncertainty in load, inflow to reservoirs and prices for fuel and delivery contracts. The stochastic load process is approximated by a scenario tree obtained by adapting a SARIMA model to historical data, using empirical means and variances of simulated scenarios to construct an initial tree, and reducing it by a scenario deletion procedure based on a suitable probability distance. Our model involves many mixed-integer variables and individual power unit constraints, but relatively few coupling constraints. Hence we employ stochastic Lagrangian relaxation that assigns stochastic multipliers to the coupling constraints. Solving the Lagrangian dual by a proximal bundle method leads to successive decomposition into single thermal and hydro unit subproblems that are solved by dynamic programming and a specialized descent algorithm, respectively. The optimal stochastic multipliers are used in Lagrangian heuristics to construct approximately optimal first stage decisions. Numerical results are presented for realistic data from a German power utility, with a time horizon of one week and scenario numbers ranging from 5 to 100. The corresponding optimization problems have up to 200,000 binary and 350,000 continuous variables, and more than 500,000 constraints.

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Author information

Authors and Affiliations

  1. Institute of Mathematics, Humboldt University Berlin, Berlin, Germany

    Nicole Gröwe-Kuska, Matthias P. Nowak, Werner Römisch & Isabel Wegner

  2. Systems Research Institute, Warsaw, Poland

    Krzysztof C. Kiwiel

Authors
  1. Nicole Gröwe-Kuska
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  2. Krzysztof C. Kiwiel
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  3. Matthias P. Nowak
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  4. Werner Römisch
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  5. Isabel Wegner
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Editor information

Editors and Affiliations

  1. IBM Watson Research Center, Hawthorne, NY, 10532, USA

    Claude Greengard

  2. Department of Management Science and Information Systems, Rutgers University, Piscataway, NJ, 08854, USA

    Andrzej Ruszczynski

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Gröwe-Kuska, N., Kiwiel, K.C., Nowak, M.P., Römisch, W., Wegner, I. (2002). Power Management in a Hydro-Thermal System under Uncertainty by Lagrangian Relaxation. In: Greengard, C., Ruszczynski, A. (eds) Decision Making Under Uncertainty. The IMA Volumes in Mathematics and its Applications, vol 128. Springer, New York, NY. https://doi.org/10.1007/978-1-4684-9256-9_3

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  • DOI: https://doi.org/10.1007/978-1-4684-9256-9_3

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  • Print ISBN: 978-1-4419-3014-9

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