IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v193y2012i1p91-10510.1007-s10479-010-0756-4.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-010-0756-4
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-010-0756-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yonghan Feng & Sarah Ryan, 2016. "Solution sensitivity-based scenario reduction for stochastic unit commitment," Computational Management Science, Springer, vol. 13(1), pages 29-62, January.
    2. Hongling, Liu & Chuanwen, Jiang & Yan, Zhang, 2008. "A review on risk-constrained hydropower scheduling in deregulated power market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(5), pages 1465-1475, June.
    3. Cerisola, Santiago & Latorre, Jesus M. & Ramos, Andres, 2012. "Stochastic dual dynamic programming applied to nonconvex hydrothermal models," European Journal of Operational Research, Elsevier, vol. 218(3), pages 687-697.
    4. Wim Ackooij & Jérôme Malick, 2016. "Decomposition algorithm for large-scale two-stage unit-commitment," Annals of Operations Research, Springer, vol. 238(1), pages 587-613, March.
    5. Anthony Papavasiliou & Shmuel S. Oren, 2013. "Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network," Operations Research, INFORMS, vol. 61(3), pages 578-592, June.
    6. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
    7. Diana Barro & Elio Canestrelli, 2016. "Combining stochastic programming and optimal control to decompose multistage stochastic optimization problems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 711-742, July.
    8. Wim Ackooij, 2014. "Decomposition approaches for block-structured chance-constrained programs with application to hydro-thermal unit commitment," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 80(3), pages 227-253, December.
    9. Séguin, Sara & Fleten, Stein-Erik & Côté, Pascal & Pichler, Alois & Audet, Charles, 2017. "Stochastic short-term hydropower planning with inflow scenario trees," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1156-1168.
    10. Wim Ackooij & Jérôme Malick, 2016. "Decomposition algorithm for large-scale two-stage unit-commitment," Annals of Operations Research, Springer, vol. 238(1), pages 587-613, March.
    11. İ. Esra Büyüktahtakın, 2022. "Stage-t scenario dominance for risk-averse multi-stage stochastic mixed-integer programs," Annals of Operations Research, Springer, vol. 309(1), pages 1-35, February.
    12. Liu, Pei-chen Barry & Hansen, Mark & Mukherjee, Avijit, 2008. "Scenario-based air traffic flow management: From theory to practice," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 685-702, August.
    13. Gulpinar, Nalan & Rustem, Berc & Settergren, Reuben, 2004. "Simulation and optimization approaches to scenario tree generation," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1291-1315, April.
    14. Luis Montero & Antonio Bello & Javier Reneses, 2022. "A Review on the Unit Commitment Problem: Approaches, Techniques, and Resolution Methods," Energies, MDPI, vol. 15(4), pages 1-40, February.
    15. Faezeh Akhavizadegan & Lizhi Wang & James McCalley, 2020. "Scenario Selection for Iterative Stochastic Transmission Expansion Planning," Energies, MDPI, vol. 13(5), pages 1-18, March.
    16. Castro, Jordi & Escudero, Laureano F. & Monge, Juan F., 2023. "On solving large-scale multistage stochastic optimization problems with a new specialized interior-point approach," European Journal of Operational Research, Elsevier, vol. 310(1), pages 268-285.
    17. Murat Köksalan & Ceren Tuncer Şakar, 2016. "An interactive approach to stochastic programming-based portfolio optimization," Annals of Operations Research, Springer, vol. 245(1), pages 47-66, October.
    18. Kostrova, Alisa & Britz, Wolfgang & Djanibekov, Utkur & Finger, Robert, 2016. "Monte-Carlo Simulation and Stochastic Programming in Real Options Valuation: the Case of Perennial Energy Crop Cultivation," Discussion Papers 250253, University of Bonn, Institute for Food and Resource Economics.
    19. Thomas Bittar & Pierre Carpentier & Jean-Philippe Chancelier & Jérôme Lonchampt, 2022. "A decomposition method by interaction prediction for the optimization of maintenance scheduling," Annals of Operations Research, Springer, vol. 316(1), pages 229-267, September.
    20. Chatwattanasiri, Nida & Coit, David W. & Wattanapongsakorn, Naruemon, 2016. "System redundancy optimization with uncertain stress-based component reliability: Minimization of regret," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 73-83.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:193:y:2012:i:1:p:91-105:10.1007/s10479-010-0756-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.