IDEAS home Printed from https://ideas.repec.org/p/zbw/kitiip/10.html
   My bibliography  Save this paper

Two-stage stochastic, large-scale optimization of a decentralized energy system - a residential quarter as case study

Author

Listed:
  • Schwarz, Hannes
  • Bertsch, Valentin
  • Fichtner, Wolf

Abstract

The trend towards decentralized energy systems with an emphasis on renewable energy sources (RES) causes increased fluctuations and non-negligible weather-related uncertainties on the future supply side. Stochastic modeling techniques enable an adequate consideration of uncertainties in the investment and operation planning process of decentralized energy systems. The challenge is that modeling of real energy systems ends up in large-scale problems, already as deterministic program. In order to keep the stochastic problem feasible, we present a module-based, parallel computing approach using decomposing techniques and a hill-climbing algorithm in combination with high-performance computing (HPC) for a two-stage stochastic optimization problem. Consistent ensembles of the required input data are simulated by a Markov process and transformed into sets of energy demand and supply profiles. The approach is demonstrated for a residential quarter using photovoltaic (PV) systems in combination with heat pumps and storages. Depending on the installed technologies, the quarter is modeled either as stochastic linear program (SLP) or stochastic mixed-integer linear program (SMILP). Our results show that thermal storages in such a decentralized energy system prove beneficial and that they are more profitable for domestic hot water than for space heating. Moreover, the storage capacity for space heating is generally larger when uncertainties are considered in comparison to the deterministic optimization, i.e. stochastic optimization can help to avoid bad layout decisions.

Suggested Citation

  • Schwarz, Hannes & Bertsch, Valentin & Fichtner, Wolf, 2015. "Two-stage stochastic, large-scale optimization of a decentralized energy system - a residential quarter as case study," Working Paper Series in Production and Energy 10, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    • Handle: RePEc:zbw:kitiip:10
    DOI: 10.5445/IR/1000049862
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/176736/1/kit-iip-wp-10.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.5445/IR/1000049862?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
    ---><---

    References listed on IDEAS

    as
    1. Rafael Kelman & Luiz Barroso & Mario Pereira, 2005. "Market Power Assessment and Mitigation in Hydrothermal Systems," Game Theory and Information 0508009, University Library of Munich, Germany.
    2. Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
    3. Jochem, Patrick & Schönfelder, Martin & Fichtner, Wolf, 2015. "An efficient two-stage algorithm for decentralized scheduling of micro-CHP units," European Journal of Operational Research, Elsevier, vol. 245(3), pages 862-874.
    4. Yang Yuan & Suvrajeet Sen, 2009. "Enhanced Cut Generation Methods for Decomposition-Based Branch and Cut for Two-Stage Stochastic Mixed-Integer Programs," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 480-487, August.
    5. Alonso-Ayuso, Antonio & Escudero, Laureano F. & Teresa Ortuno, M., 2003. "BFC, A branch-and-fix coordination algorithmic framework for solving some types of stochastic pure and mixed 0-1 programs," European Journal of Operational Research, Elsevier, vol. 151(3), pages 503-519, December.
    6. Stefan Helber & Michael Breitner & Daniel Rösch & Cornelia Schön & Johann-Matthias Graf von der Schu (ed.), 2014. "Operations Research Proceedings 2012," Operations Research Proceedings, Springer, edition 127, number 978-3-319-00795-3, April.
    7. L. Escudero & A. Garín & M. Merino & G. Pérez, 2007. "A two-stage stochastic integer programming approach as a mixture of Branch-and-Fix Coordination and Benders Decomposition schemes," Annals of Operations Research, Springer, vol. 152(1), pages 395-420, July.
    8. Pagès-Bernaus, Adela & Pérez-Valdés, Gerardo & Tomasgard, Asgeir, 2015. "A parallelised distributed implementation of a Branch and Fix Coordination algorithm," European Journal of Operational Research, Elsevier, vol. 244(1), pages 77-85.
    9. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    10. Andrzej Ruszczynski, 1999. "Some advances in decomposition methodsfor stochastic linear programming," Annals of Operations Research, Springer, vol. 85(0), pages 153-172, January.
    11. Diagne, Maimouna & David, Mathieu & Lauret, Philippe & Boland, John & Schmutz, Nicolas, 2013. "Review of solar irradiance forecasting methods and a proposition for small-scale insular grids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 65-76.
    12. Schicktanz, M.D. & Wapler, J. & Henning, H.-M., 2011. "Primary energy and economic analysis of combined heating, cooling and power systems," Energy, Elsevier, vol. 36(1), pages 575-585.
    13. Valentin Bertsch & Hannes Schwarz & Wolf Fichtner, 2014. "Layout Optimisation of Decentralised Energy Systems Under Uncertainty," Operations Research Proceedings, in: Dennis Huisman & Ilse Louwerse & Albert P.M. Wagelmans (ed.), Operations Research Proceedings 2013, edition 127, pages 29-35, Springer.
    14. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    15. Alonso-Ayuso, A. & Escudero, L. F. & Garín, A. & Ortuño, M. T. & Pérez, G., 2005. "On the product selection and plant dimensioning problem under uncertainty," Omega, Elsevier, vol. 33(4), pages 307-318, August.
    16. Willem Klein Haneveld & Maarten van der Vlerk, 1999. "Stochastic integer programming:General models and algorithms," Annals of Operations Research, Springer, vol. 85(0), pages 39-57, January.
    17. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    18. Hawkes, Adam & Leach, Matthew, 2005. "Impacts of temporal precision in optimisation modelling of micro-Combined Heat and Power," Energy, Elsevier, vol. 30(10), pages 1759-1779.
    19. Escudero, L.F. & Garín, M.A. & Merino, M. & Pérez, G., 2010. "An exact algorithm for solving large-scale two-stage stochastic mixed-integer problems: Some theoretical and experimental aspects," European Journal of Operational Research, Elsevier, vol. 204(1), pages 105-116, July.
    Full references (including those not matched with items on IDEAS)

    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. Hannes Schwarz & Valentin Bertsch & Wolf Fichtner, 2018. "Two-stage stochastic, large-scale optimization of a decentralized energy system: a case study focusing on solar PV, heat pumps and storage in a residential quarter," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 265-310, January.
    2. Escudero, L.F. & Garín, M.A. & Merino, M. & Pérez, G., 2010. "An exact algorithm for solving large-scale two-stage stochastic mixed-integer problems: Some theoretical and experimental aspects," European Journal of Operational Research, Elsevier, vol. 204(1), pages 105-116, July.
    3. Savvidis, Georgios & Siala, Kais & Weissbart, Christoph & Schmidt, Lukas & Borggrefe, Frieder & Kumar, Subhash & Pittel, Karen & Madlener, Reinhard & Hufendiek, Kai, 2019. "The gap between energy policy challenges and model capabilities," Energy Policy, Elsevier, vol. 125(C), pages 503-520.
    4. Misconel, S. & Zimmermann, F. & Mikurda, J. & Möst, D. & Kunze, R. & Gnann, T. & Kühnbach, M. & Speth, D. & Pelka, S. & Yu, S., 2024. "Model coupling and comparison on optimal load shifting of battery electric vehicles and heat pumps focusing on generation adequacy," Energy, Elsevier, vol. 305(C).
    5. Pagès-Bernaus, Adela & Pérez-Valdés, Gerardo & Tomasgard, Asgeir, 2015. "A parallelised distributed implementation of a Branch and Fix Coordination algorithm," European Journal of Operational Research, Elsevier, vol. 244(1), pages 77-85.
    6. repec:ehu:biltok:5566 is not listed on IDEAS
    7. Md. Nasimul Islam Maruf, 2019. "Sector Coupling in the North Sea Region—A Review on the Energy System Modelling Perspective," Energies, MDPI, vol. 12(22), pages 1-35, November.
    8. Pineau, Pierre-Olivier & Rasata, Hasina & Zaccour, Georges, 2011. "Impact of some parameters on investments in oligopolistic electricity markets," European Journal of Operational Research, Elsevier, vol. 213(1), pages 180-195, August.
    9. Beltran-Royo, C., 2017. "Two-stage stochastic mixed-integer linear programming: The conditional scenario approach," Omega, Elsevier, vol. 70(C), pages 31-42.
    10. repec:dgr:rugsom:03a14 is not listed on IDEAS
    11. Lunz, Benedikt & Stöcker, Philipp & Eckstein, Sascha & Nebel, Arjuna & Samadi, Sascha & Erlach, Berit & Fischedick, Manfred & Elsner, Peter & Sauer, Dirk Uwe, 2016. "Scenario-based comparative assessment of potential future electricity systems – A new methodological approach using Germany in 2050 as an example," Applied Energy, Elsevier, vol. 171(C), pages 555-580.
    12. Lopion, Peter & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "A review of current challenges and trends in energy systems modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 156-166.
    13. Karni Siraganyan & Amarasinghage Tharindu Dasun Perera & Jean-Louis Scartezzini & Dasaraden Mauree, 2019. "Eco-Sim: A Parametric Tool to Evaluate the Environmental and Economic Feasibility of Decentralized Energy Systems," Energies, MDPI, vol. 12(5), pages 1-22, February.
    14. Gorenstein Dedecca, João & Hakvoort, Rudi A., 2016. "A review of the North Seas offshore grid modeling: Current and future research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 129-143.
    15. Ringler, Philipp & Keles, Dogan & Fichtner, Wolf, 2017. "How to benefit from a common European electricity market design," Energy Policy, Elsevier, vol. 101(C), pages 629-643.
    16. Blanco, Herib & Leaver, Jonathan & Dodds, Paul E. & Dickinson, Robert & García-Gusano, Diego & Iribarren, Diego & Lind, Arne & Wang, Changlong & Danebergs, Janis & Baumann, Martin, 2022. "A taxonomy of models for investigating hydrogen energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    17. L. Aranburu & L. Escudero & M. Garín & G. Pérez, 2012. "A so-called Cluster Benders Decomposition approach for solving two-stage stochastic linear problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(2), pages 279-295, July.
    18. Mehigan, L. & Deane, J.P. & Gallachóir, B.P.Ó. & Bertsch, V., 2018. "A review of the role of distributed generation (DG) in future electricity systems," Energy, Elsevier, vol. 163(C), pages 822-836.
    19. Brian Keller & Güzin Bayraksan, 2012. "Disjunctive Decomposition for Two-Stage Stochastic Mixed-Binary Programs with Generalized Upper Bound Constraints," INFORMS Journal on Computing, INFORMS, vol. 24(1), pages 172-186, February.
    20. Koppelaar, Rembrandt H.E.M. & Keirstead, James & Shah, Nilay & Woods, Jeremy, 2016. "A review of policy analysis purpose and capabilities of electricity system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1531-1544.
    21. E. Mijangos, 2015. "An algorithm for two-stage stochastic mixed-integer nonlinear convex problems," Annals of Operations Research, Springer, vol. 235(1), pages 581-598, December.

    More about this item

    Statistics

    Access and download statistics

    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:zbw:kitiip:10. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://www.iip.kit.edu/ .

    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.