[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp1659.html
   My bibliography  Save this paper

A Spatial Electricity Market Model for the Power System of Kazakhstan

Author

Listed:
  • Makpal Assembayeva
  • Jonas Egerer
  • Roman Mendelevitch
  • Nurkhat Zhakiyev
Abstract
Kazakhstan envisions a transition towards a green economy in the next decades which poses an immense challenge as the country heavily depends on (hydro-)carbon resources, for both its economy and its energy system. In this context, there is a lack of comprehensive and transparent planning tools to assess possible sustainable development pathways in regard to their technical, economic, and environmental implications. We present such a tool with a comprehensive techno-economic model of the Kazakh electricity system which determines the hourly least-cost generation dispatch based on publicly available data on the technical and economic characteristics of power plants and the transmission infrastructure. This modeling framework accounts for the particularities of the Kazakh electricity system: i) it has a detailed representation of combined heat and power, and ii) line losses are endogenously determined using a linear approximation. Model results are examined for a typical winter week (with annual peak load) and a typical summer week (with the hour of lowest annual load) presenting regionally and temporally disaggregated results for power generation, line utilization, and nodal prices. In an application to market design, the paper compares nodal and zonal pricing as two possible pricing schemes in Kazakhstan for the envisioned strengthening of the day-ahead market. In general, the model can be readily used to analyze the least-cost dispatch of the current Kazakh electricity system and can be easily expanded to assess the sector's development. Among others, possible applications include investment in transmission lines and in the aging power plant fleet, scenarios and policy assessment for emission reduction, and questions of market liberalization and market design.

Suggested Citation

  • Makpal Assembayeva & Jonas Egerer & Roman Mendelevitch & Nurkhat Zhakiyev, 2017. "A Spatial Electricity Market Model for the Power System of Kazakhstan," Discussion Papers of DIW Berlin 1659, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp1659
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.556477.de/dp1659.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Abrell, Jan & Rausch, Sebastian, 2016. "Cross-country electricity trade, renewable energy and European transmission infrastructure policy," Journal of Environmental Economics and Management, Elsevier, vol. 79(C), pages 87-113.
    2. Aiymgul Kerimray & Kanat Baigarin & Rocco De Miglio & Giancarlo Tosato, 2016. "Climate change mitigation scenarios and policies and measures: the case of Kazakhstan," Climate Policy, Taylor & Francis Journals, vol. 16(3), pages 332-352, April.
    3. Gürkan, Gül & Langestraat, Romeo, 2014. "Modeling and analysis of renewable energy obligations and technology bandings in the UK electricity market," Energy Policy, Elsevier, vol. 70(C), pages 85-95.
    4. Alibek Konkakov & Gulaikhan Kubayeva, 2016. "Progress in diversification of the economy in Kazakhstan," Working Papers 2016/8, Maastricht School of Management.
    5. Andreas Ehrenmann & Yves Smeers, 2011. "Generation Capacity Expansion in a Risky Environment: A Stochastic Equilibrium Analysis," Operations Research, INFORMS, vol. 59(6), pages 1332-1346, December.
    6. Després, Jacques & Hadjsaid, Nouredine & Criqui, Patrick & Noirot, Isabelle, 2015. "Modelling the impacts of variable renewable sources on the power sector: Reconsidering the typology of energy modelling tools," Energy, Elsevier, vol. 80(C), pages 486-495.
    7. Nahmmacher, Paul & Schmid, Eva & Hirth, Lion & Knopf, Brigitte, 2016. "Carpe diem: A novel approach to select representative days for long-term power system modeling," Energy, Elsevier, vol. 112(C), pages 430-442.
    8. Sarbassov, Yerbol & Kerimray, Aiymgul & Tokmurzin, Diyar & Tosato, GianCarlo & De Miglio, Rocco, 2013. "Electricity and heating system in Kazakhstan: Exploring energy efficiency improvement paths," Energy Policy, Elsevier, vol. 60(C), pages 431-444.
    9. Atakhanova, Zauresh & Howie, Peter, 2007. "Electricity demand in Kazakhstan," Energy Policy, Elsevier, vol. 35(7), pages 3729-3743, July.
    10. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
    11. 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.
    12. Jonas Egerer, 2016. "Open Source Electricity Model for Germany (ELMOD-DE)," Data Documentation 83, DIW Berlin, German Institute for Economic Research.
    13. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2016. "How much is enough? Optimal support payments in a renewable-rich power system," Energy, Elsevier, vol. 117(P1), pages 300-313.
    14. Florian Leuthold & Hannes Weigt & Christian Hirschhausen, 2012. "A Large-Scale Spatial Optimization Model of the European Electricity Market," Networks and Spatial Economics, Springer, vol. 12(1), pages 75-107, March.
    15. Gómez, Antonio & Dopazo, César & Fueyo, Norberto, 2014. "The causes of the high energy intensity of the Kazakh economy: A characterization of its energy system," Energy, Elsevier, vol. 71(C), pages 556-568.
    16. 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.
    17. Karsten Neuhoff & Benjamin F. Hobbs & David Newbery, 2011. "Congestion Management in European Power Networks: Criteria to Assess the Available Options," Discussion Papers of DIW Berlin 1161, DIW Berlin, German Institute for Economic Research.
    18. Mikkola, Jani & Lund, Peter D., 2016. "Modeling flexibility and optimal use of existing power plants with large-scale variable renewable power schemes," Energy, Elsevier, vol. 112(C), pages 364-375.
    19. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    20. Razeghi, Ghazal & Brouwer, Jack & Samuelsen, Scott, 2016. "A spatially and temporally resolved model of the electricity grid – Economic vs environmental dispatch," Applied Energy, Elsevier, vol. 178(C), pages 540-556.
    21. Deane, J.P. & Chiodi, Alessandro & Gargiulo, Maurizio & Ó Gallachóir, Brian P., 2012. "Soft-linking of a power systems model to an energy systems model," Energy, Elsevier, vol. 42(1), pages 303-312.
    22. Karatayev, Marat & Clarke, Michèle L., 2016. "A review of current energy systems and green energy potential in Kazakhstan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 491-504.
    23. Jonas Egerer & Roman Mendelevitch & Christian von Hirschhausen, 2014. "A Lower Carbon Strategy for the Electricity Sector of Kazakhstan to 2030/50: Scenarios for Generation and Network Development ; Technical Report," DIW Berlin: Politikberatung kompakt, DIW Berlin, German Institute for Economic Research, volume 85, number pbk85.
    24. EHRENMANN, Andreas & SMEERS, Yves, 2011. "Generation capacity expansion in a risky environment: a stochastic equilibrium analysis," LIDAM Reprints CORE 2379, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    25. Fang, Tingting & Lahdelma, Risto, 2016. "Optimization of combined heat and power production with heat storage based on sliding time window method," Applied Energy, Elsevier, vol. 162(C), pages 723-732.
    26. Yihsu Chen & Lizhi Wang, 2013. "Renewable Portfolio Standards in the Presence of Green Consumers and Emissions Trading," Networks and Spatial Economics, Springer, vol. 13(2), pages 149-181, June.
    27. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S. & Kopanos, Georgios M. & Pistikopoulos, Efstratios N. & Georgiadis, Michael C., 2014. "A spatial multi-period long-term energy planning model: A case study of the Greek power system," Applied Energy, Elsevier, vol. 115(C), pages 456-482.
    28. Kunz, Friedrich & Zerrahn, Alexander, 2015. "Benefits of coordinating congestion management in electricity transmission networks: Theory and application to Germany," Utilities Policy, Elsevier, vol. 37(C), pages 34-45.
    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. Assembayeva, Makpal & Egerer, Jonas & Mendelevitch, Roman & Zhakiyev, Nurkhat, 2018. "A spatial electricity market model for the power system: The Kazakhstan case study," Energy, Elsevier, vol. 149(C), pages 762-778.
    2. Athanasios Dagoumas & Nikolaos Koltsaklis, 2020. "Zonal Pricing in Kazakhstan Power System with a Unit Commitment Model," International Journal of Energy Economics and Policy, Econjournals, vol. 10(3), pages 24-36.
    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. Densing, M. & Panos, E. & Hirschberg, S., 2016. "Meta-analysis of energy scenario studies: Example of electricity scenarios for Switzerland," Energy, Elsevier, vol. 109(C), pages 998-1015.
    5. 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.
    6. Yazdanie, M. & Orehounig, K., 2021. "Advancing urban energy system planning and modeling approaches: Gaps and solutions in perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    7. Karatayev, Marat & Hall, Stephen & Kalyuzhnova, Yelena & Clarke, Michèle L., 2016. "Renewable energy technology uptake in Kazakhstan: Policy drivers and barriers in a transitional economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 120-136.
    8. Karl-Kiên Cao & Kai von Krbek & Manuel Wetzel & Felix Cebulla & Sebastian Schreck, 2019. "Classification and Evaluation of Concepts for Improving the Performance of Applied Energy System Optimization Models," Energies, MDPI, vol. 12(24), pages 1-51, December.
    9. Roman Mendelevitch & Pao-Yu Oei, 2015. "The Impact of Policy Measures on Future Power Generation Portfolio and Infrastructure: A Combined Electricity and CCTS Investment and Dispatch Model (ELCO)," Discussion Papers of DIW Berlin 1521, DIW Berlin, German Institute for Economic Research.
    10. 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).
    11. 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.
    12. Clemens Gerbaulet & Casimir Lorenz, 2017. "dynELMOD: A Dynamic Investment and Dispatch Model for the Future European Electricity Market," Data Documentation 88, DIW Berlin, German Institute for Economic Research.
    13. Gils, Hans Christian & Gardian, Hedda & Kittel, Martin & Schill, Wolf-Peter & Zerrahn, Alexander & Murmann, Alexander & Launer, Jann & Fehler, Alexander & Gaumnitz, Felix & van Ouwerkerk, Jonas & Bußa, 2022. "Modeling flexibility in energy systems — comparison of power sector models based on simplified test cases," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    14. Karatayev, Marat & Clarke, Michèle L., 2016. "A review of current energy systems and green energy potential in Kazakhstan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 491-504.
    15. Hach, Daniel & Chyong, Chi Kong & Spinler, Stefan, 2016. "Capacity market design options: A dynamic capacity investment model and a GB case study," European Journal of Operational Research, Elsevier, vol. 249(2), pages 691-705.
    16. van Ouwerkerk, Jonas & Gils, Hans Christian & Gardian, Hedda & Kittel, Martin & Schill, Wolf-Peter & Zerrahn, Alexander & Murmann, Alexander & Launer, Jann & Torralba-Díaz, Laura & Bußar, Christian, 2022. "Impacts of power sector model features on optimal capacity expansion: A comparative study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    17. 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.
    18. Jonas Egerer, 2016. "Open Source Electricity Model for Germany (ELMOD-DE)," Data Documentation 83, DIW Berlin, German Institute for Economic Research.
    19. Prina, Matteo Giacomo & Nastasi, Benedetto & Groppi, Daniele & Misconel, Steffi & Garcia, Davide Astiaso & Sparber, Wolfram, 2022. "Comparison methods of energy system frameworks, models and scenario results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    20. Mertens, Tim & Poncelet, Kris & Duerinck, Jan & Delarue, Erik, 2020. "Representing cross-border trade of electricity in long-term energy-system optimization models with a limited geographical scope," Applied Energy, Elsevier, vol. 261(C).

    More about this item

    Keywords

    Kazakhstan; Central Asia; Electricity sector; Techno-economic modeling; Transmission network; ELMOD;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:diw:diwwpp:dp1659. 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: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    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.