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A spatial electricity market model for the power system: The Kazakhstan case study


  • Assembayeva, Makpal
  • Egerer, Jonas
  • Mendelevitch, Roman
  • Zhakiyev, Nurkhat


Kazakhstan envisions a transition towards a green economy in the next decades, which poses an immense challenge as the country's economy and energy system depends heavily on hydrocarbon resources. Here, it lacks inclusive and transparent tools assessing technical, economic, and environmental implications resulting from changes in its electricity system. We present such a tool: our comprehensive techno-economic unit-commitment model determines the hourly least-cost generation dispatch, based on publicly available data on the technical and economic characteristics of the system. It accounts for particularities of the Kazakh electricity system by representing combined heat and power, and endogenously determining line losses. Model results examine two typical weeks: winter (annual peak load) and summer (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. The model analyze the current Kazakh electricity system and can be easily expanded to assess the sector's future development. Possible applications include investment in generation and transmission infrastructure, policy assessment for renewables integration, carbon pricing, emission reduction, and questions of market design.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:149:y:2018:i:c:p:762-778
    DOI: 10.1016/

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    References listed on IDEAS

    1. Huppmann, Daniel & Egerer, Jonas, 2015. "National-strategic investment in European power transmission capacity," European Journal of Operational Research, Elsevier, vol. 247(1), pages 191-203.
    2. 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.
    3. Alibek Konkakov & Gulaikhan Kubayeva, 2016. "Progress in diversification of the economy in Kazakhstan," Working Papers 2016/8, Maastricht School of Management.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Jonas Egerer, 2016. "Open Source Electricity Model for Germany (ELMOD-DE)," Data Documentation 83, DIW Berlin, German Institute for Economic Research.
    9. 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.
    10. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    11. Kia, Mohsen & Nazar, Mehrdad Setayesh & Sepasian, Mohammad Sadegh & Heidari, Alireza & Siano, Pierluigi, 2017. "Optimal day ahead scheduling of combined heat and power units with electrical and thermal storage considering security constraint of power system," Energy, Elsevier, vol. 120(C), pages 241-252.
    12. 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.
    13. 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.
    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. 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.
    16. Lund, Henrik & Østergaard, Poul Alberg & Connolly, David & Mathiesen, Brian Vad, 2017. "Smart energy and smart energy systems," Energy, Elsevier, vol. 137(C), pages 556-565.
    17. 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.
    18. EHRENMANN, Andreas & SMEERS, Yves, 2011. "Generation capacity expansion in a risky environment: a stochastic equilibrium analysis," CORE Discussion Papers RP 2379, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Mitra, Sumit & Sun, Lige & Grossmann, Ignacio E., 2013. "Optimal scheduling of industrial combined heat and power plants under time-sensitive electricity prices," Energy, Elsevier, vol. 54(C), pages 194-211.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. Atakhanova, Zauresh & Howie, Peter, 2007. "Electricity demand in Kazakhstan," Energy Policy, Elsevier, vol. 35(7), pages 3729-3743, July.
    25. 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.
    26. Kim, Jong Suk & Edgar, Thomas F., 2014. "Optimal scheduling of combined heat and power plants using mixed-integer nonlinear programming," Energy, Elsevier, vol. 77(C), pages 675-690.
    27. 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.
    28. 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.
    29. 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.
    30. 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.
    31. 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.
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    Cited by:

    1. Yang, Zhifang & Zhong, Haiwang & Lin, Wei & Lin, Jeremy & Chen, Yonghong & Xia, Qing & Liu, Wentao & Zhang, Xuan, 2019. "Mapping between transmission constraint penalty factor and OPF solution in electricity markets: analysis and fast calculation," Energy, Elsevier, vol. 168(C), pages 1181-1191.
    2. Grimm, Veronika & Rückel, Bastian & Sölch, Christian & Zöttl, Gregor, 2019. "Regionally differentiated network fees to affect incentives for generation investment," Energy, Elsevier, vol. 177(C), pages 487-502.


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