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A stochastic model for the daily coordination of pumped storage hydro plants and wind power plants

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  • Maria Vespucci
  • Francesca Maggioni
  • Maria Bertocchi
  • Mario Innorta

Abstract

We propose a stochastic model for the daily operation scheduling of a generation system including pumped storage hydro plants and wind power plants, where the uncertainty is represented by the hourly wind power production. In order to assess the value of the stochastic modeling, we discuss two case studies: in the former the scenario tree is built so as to include both low and high wind power production scenarios, in the latter the scenario tree is built on historical wind speed data covering a time span of one and a half year. The Value of the Stochastic Solution, computed by a modified new procedure, shows that in scenarios with low wind power production the stochastic solution allows the producer to obtain a profit which is greater than the one associated to the deterministic solution. In-sample stability of the optimal function values for increasing number of scenarios is reported. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Maria Vespucci & Francesca Maggioni & Maria Bertocchi & Mario Innorta, 2012. "A stochastic model for the daily coordination of pumped storage hydro plants and wind power plants," Annals of Operations Research, Springer, vol. 193(1), pages 91-105, March.
    • Handle: RePEc:spr:annopr:v:193:y:2012:i:1:p:91-105:10.1007/s10479-010-0756-4
    DOI: 10.1007/s10479-010-0756-4
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    References listed on IDEAS

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    1. Latorre, Jesus M & Cerisola, Santiago & Ramos, Andres, 2007. "Clustering algorithms for scenario tree generation: Application to natural hydro inflows," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1339-1353, September.
    2. Philpott, A. B. & Craddock, M. & Waterer, H., 2000. "Hydro-electric unit commitment subject to uncertain demand," European Journal of Operational Research, Elsevier, vol. 125(2), pages 410-424, September.
    3. Jitka Dupačová & Giorgio Consigli & Stein Wallace, 2000. "Scenarios for Multistage Stochastic Programs," Annals of Operations Research, Springer, vol. 100(1), pages 25-53, December.
    4. Matthias Nowak & Werner Römisch, 2000. "Stochastic Lagrangian Relaxation Applied to Power Scheduling in a Hydro-Thermal System under Uncertainty," Annals of Operations Research, Springer, vol. 100(1), pages 251-272, December.
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    Cited by:

    1. Densing, M., 2013. "Dispatch planning using newsvendor dual problems and occupation times: Application to hydropower," European Journal of Operational Research, Elsevier, vol. 228(2), pages 321-330.
    2. Picarelli, Athena & Vargiolu, Tiziano, 2021. "Optimal management of pumped hydroelectric production with state constrained optimal control," Journal of Economic Dynamics and Control, Elsevier, vol. 126(C).
    3. Francesca Maggioni & Elisabetta Allevi & Marida Bertocchi, 2014. "Bounds in Multistage Linear Stochastic Programming," Journal of Optimization Theory and Applications, Springer, vol. 163(1), pages 200-229, October.
    4. Toufani, Parinaz & Nadar, Emre & Kocaman, Ayse Selin, 2022. "Short-term assessment of pumped hydro energy storage configurations: Up, down, or closed?," Renewable Energy, Elsevier, vol. 201(P1), pages 1086-1095.
    5. Elisabetta Allevi & Adriana Gnudi & Igor V. Konnov & Giorgia Oggioni, 2017. "Dynamic Spatial Auction Market Models with General Cost Mappings," Networks and Spatial Economics, Springer, vol. 17(2), pages 367-403, June.

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