IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i12p3056-d370903.html
   My bibliography  Save this article

A New Methodology to Obtain a Feasible Thermal Operation in Power Systems in a Medium-Term Horizon

Author

Listed:
  • Luis Montero

    (Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain)

  • Antonio Bello

    (Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain)

  • Javier Reneses

    (Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain)

Abstract

Nowadays, electricity market paradigms are constantly changing. On the one hand, the deployment of non-dispatchable renewable energy sources is bringing out the necessity of representing hourly dynamics in medium-term fundamental models. On the other, the promotion of new interconnection capacity and the integration of markets (as is the case of the European market) makes necessary the simultaneous modeling of multiple electricity systems. Thus, the large size of power markets, together with the consideration of uncertainty in some inputs, make it computationally intractable to work rigorously on an hourly detailed time span. Temporal aggregation, integer programming relaxation or less accurate generation modeling are usually employed to obtain reasonable computation times. However, the application of these techniques often leads to infeasible or suboptimal operational outputs. This paper proposes a new soft-linking methodology to meet reliable results from medium-term models, such as hourly prices or aggregated productions, with a feasible and detailed representation of the thermal generation, considering technical constraints and risk aversion. The results of a fundamental model that represents the competitive behavior between market players in a multi-area power system are used as the starting point for the methodology. Then, a post-processing method is applied to optimize and make feasible the thermal portfolio of a market agent. The final output is a feasible hourly scheduling and an ample space for optimization, where the introduction of a strategic term represents the rational behavior of a player who tries to maximize its profit.

Suggested Citation

  • Luis Montero & Antonio Bello & Javier Reneses, 2020. "A New Methodology to Obtain a Feasible Thermal Operation in Power Systems in a Medium-Term Horizon," Energies, MDPI, vol. 13(12), pages 1-17, June.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3056-:d:370903
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/12/3056/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/12/3056/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Niina Helistö & Juha Kiviluoma & Jussi Ikäheimo & Topi Rasku & Erkka Rinne & Ciara O’Dwyer & Ran Li & Damian Flynn, 2019. "Backbone—An Adaptable Energy Systems Modelling Framework," Energies, MDPI, vol. 12(17), pages 1-34, September.
    2. Limpens, Gauthier & Moret, Stefano & Jeanmart, Hervé & Maréchal, Francois, 2019. "EnergyScope TD: A novel open-source model for regional energy systems," Applied Energy, Elsevier, vol. 255(C).
    3. Schaber, Katrin & Steinke, Florian & Hamacher, Thomas, 2012. "Transmission grid extensions for the integration of variable renewable energies in Europe: Who benefits where?," Energy Policy, Elsevier, vol. 43(C), pages 123-135.
    4. Prina, Matteo Giacomo & Fanali, Lorenzo & Manzolini, Giampaolo & Moser, David & Sparber, Wolfram, 2018. "Incorporating combined cycle gas turbine flexibility constraints and additional costs into the EPLANopt model: The Italian case study," Energy, Elsevier, vol. 160(C), pages 33-43.
    5. Pfenninger, Stefan & Keirstead, James, 2015. "Renewables, nuclear, or fossil fuels? Scenarios for Great Britain’s power system considering costs, emissions and energy security," Applied Energy, Elsevier, vol. 152(C), pages 83-93.
    6. Pina, André & Silva, Carlos & Ferrão, Paulo, 2012. "The impact of demand side management strategies in the penetration of renewable electricity," Energy, Elsevier, vol. 41(1), pages 128-137.
    7. Bello, Antonio & Reneses, Javier & Muñoz, Antonio & Delgadillo, Andrés, 2016. "Probabilistic forecasting of hourly electricity prices in the medium-term using spatial interpolation techniques," International Journal of Forecasting, Elsevier, vol. 32(3), pages 966-980.
    8. Heuberger, Clara F. & Rubin, Edward S. & Staffell, Iain & Shah, Nilay & Mac Dowell, Niall, 2017. "Power capacity expansion planning considering endogenous technology cost learning," Applied Energy, Elsevier, vol. 204(C), pages 831-845.
    9. Topi Rasku & Juha Kiviluoma, 2018. "A Comparison of Widespread Flexible Residential Electric Heating and Energy Efficiency in a Future Nordic Power System," Energies, MDPI, vol. 12(1), pages 1-27, December.
    10. Huppmann, Daniel & Egging, Ruud, 2014. "Market power, fuel substitution and infrastructure – A large-scale equilibrium model of global energy markets," Energy, Elsevier, vol. 75(C), pages 483-500.
    11. Zerrahn, Alexander & Schill, Wolf-Peter, 2017. "Long-run power storage requirements for high shares of renewables: review and a new model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1518-1534.
    12. Welsch, Manuel & Deane, Paul & Howells, Mark & Ó Gallachóir, Brian & Rogan, Fionn & Bazilian, Morgan & Rogner, Hans-Holger, 2014. "Incorporating flexibility requirements into long-term energy system models – A case study on high levels of renewable electricity penetration in Ireland," Applied Energy, Elsevier, vol. 135(C), pages 600-615.
    13. Nelson, James & Johnston, Josiah & Mileva, Ana & Fripp, Matthias & Hoffman, Ian & Petros-Good, Autumn & Blanco, Christian & Kammen, Daniel M., 2012. "High-resolution modeling of the western North American power system demonstrates low-cost and low-carbon futures," Energy Policy, Elsevier, vol. 43(C), pages 436-447.
    14. Howells, Mark & Rogner, Holger & Strachan, Neil & Heaps, Charles & Huntington, Hillard & Kypreos, Socrates & Hughes, Alison & Silveira, Semida & DeCarolis, Joe & Bazillian, Morgan & Roehrl, Alexander, 2011. "OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development," Energy Policy, Elsevier, vol. 39(10), pages 5850-5870, October.
    15. 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.
    16. Hirth, Lion, 2016. "The benefits of flexibility: The value of wind energy with hydropower," Applied Energy, Elsevier, vol. 181(C), pages 210-223.
    17. Atabay, Dennis, 2017. "An open-source model for optimal design and operation of industrial energy systems," Energy, Elsevier, vol. 121(C), pages 803-821.
    18. Deane, J.P. & Driscoll, Á. & Gallachóir, B.P Ó, 2015. "Quantifying the impacts of national renewable electricity ambitions using a North–West European electricity market model," Renewable Energy, Elsevier, vol. 80(C), pages 604-609.
    19. Schill, Wolf-Peter & Zerrahn, Alexander, 2018. "Long-run power storage requirements for high shares of renewables: Results and sensitivities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 156-171.
    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. 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.

    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. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    2. Østergaard, P.A. & Lund, H. & Thellufsen, J.Z. & Sorknæs, P. & Mathiesen, B.V., 2022. "Review and validation of EnergyPLAN," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    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. Limpens, Gauthier & Rixhon, Xavier & Contino, Francesco & Jeanmart, Hervé, 2024. "EnergyScope Pathway: An open-source model to optimise the energy transition pathways of a regional whole-energy system," Applied Energy, Elsevier, vol. 358(C).
    5. Chang, Miguel & Thellufsen, Jakob Zink & Zakeri, Behnam & Pickering, Bryn & Pfenninger, Stefan & Lund, Henrik & Østergaard, Poul Alberg, 2021. "Trends in tools and approaches for modelling the energy transition," Applied Energy, Elsevier, vol. 290(C).
    6. Borasio, M. & Moret, S., 2022. "Deep decarbonisation of regional energy systems: A novel modelling approach and its application to the Italian energy transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    7. Prina, Matteo Giacomo & Manzolini, Giampaolo & Moser, David & Nastasi, Benedetto & Sparber, Wolfram, 2020. "Classification and challenges of bottom-up energy system models - A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 129(C).
    8. Niina Helistö & Juha Kiviluoma & Hannele Holttinen & Jose Daniel Lara & Bri‐Mathias Hodge, 2019. "Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.
    9. Dagoumas, Athanasios S. & Koltsaklis, Nikolaos E., 2019. "Review of models for integrating renewable energy in the generation expansion planning," Applied Energy, Elsevier, vol. 242(C), pages 1573-1587.
    10. Chyong, Chi Kong & Newbery, David, 2022. "A unit commitment and economic dispatch model of the GB electricity market – Formulation and application to hydro pumped storage," Energy Policy, Elsevier, vol. 170(C).
    11. Jayadev, Gopika & Leibowicz, Benjamin D. & Kutanoglu, Erhan, 2020. "U.S. electricity infrastructure of the future: Generation and transmission pathways through 2050," Applied Energy, Elsevier, vol. 260(C).
    12. Francesco Gardumi & Manuel Welsch & Mark Howells & Emanuela Colombo, 2019. "Representation of Balancing Options for Variable Renewables in Long-Term Energy System Models: An Application to OSeMOSYS," Energies, MDPI, vol. 12(12), pages 1-22, June.
    13. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    14. Niina Helistö & Juha Kiviluoma & Jussi Ikäheimo & Topi Rasku & Erkka Rinne & Ciara O’Dwyer & Ran Li & Damian Flynn, 2019. "Backbone—An Adaptable Energy Systems Modelling Framework," Energies, MDPI, vol. 12(17), pages 1-34, September.
    15. Heggarty, Thomas & Bourmaud, Jean-Yves & Girard, Robin & Kariniotakis, Georges, 2024. "Assessing the relative impacts of maximum investment rate and temporal detail in capacity expansion models applied to power systems," Energy, Elsevier, vol. 290(C).
    16. Thimet, P.J. & Mavromatidis, G., 2022. "Review of model-based electricity system transition scenarios: An analysis for Switzerland, Germany, France, and Italy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    17. Teichgraeber, Holger & Brandt, Adam R., 2022. "Time-series aggregation for the optimization of energy systems: Goals, challenges, approaches, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    18. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    19. Martin Kittel & Wolf-Peter Schill, 2021. "Renewable Energy Targets and Unintended Storage Cycling: Implications for Energy Modeling," Papers 2107.13380, arXiv.org, revised Sep 2021.
    20. F, Feijoo & A, Pfeifer & L, Herc & D, Groppi & N, Duić, 2022. "A long-term capacity investment and operational energy planning model with power-to-X and flexibility technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

    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:gam:jeners:v:13:y:2020:i:12:p:3056-:d:370903. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.