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Locational-based Coupling of Electricity Markets: Benefits from Coordinating Unit Commitment and Balancing Markets

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  • Adriaan Hendrik van der Weijde

    (Electricity Policy Research Group, University of Cambridge Department of Spatial Economics, VU Amsterdam)

  • Benjamin F. Hobbs

    (Electricity Policy Research Group, University of Cambridge Whiting School of Engineering, The Johns Hopkins University)

Abstract

We formulate a series of stochastic models for committing and dispatching electric generators subject to transmission limits. The models are used to estimate the benefits of electricity locational marginal pricing (LMP) that arise from better coordination of day-ahead commitment decisions and real-time balancing markets in adjacent power markets when there is significant uncertainty in demand and wind forecasts. The unit commitment models optimise schedules under either the full set of network constraints or a simplified net transfer capacity (NTC) constraint, considering the range of possible real-time wind and load scenarios. The NTC-constrained model represents the present approach for limiting day-ahead electricity trade in Europe. A subsequent redispatch model then creates feasible real-time schedules. Benefits of LMP arise from decreases in expected start-up and variable generation costs resulting from consistent consideration of the full set of network constraints both day-ahead and in real-time. Meanwhile, using LMP to coordinate adjacent balancing markets provides benefits because it allows intermarket flow schedules to be adjusted in real-time in response to changing conditions. These models are applied to a stylised four-node network, examining the effects of varying system characteristics on the magnitude of the locational-based unit commitment benefits and the benefits of intermarket balancing. Although previous www.eprg.group.cam.ac.uk EPRG WORKING PAPER studies have examined the benefits of LMP, these usually examine one specific system, often without a discussion of the sources of these benefits, and with simplifying assumptions about unit commitment. We conclude that both categories of benefits are situation dependent, such that small parameter changes can lead to large changes in expected benefits. Although both can amount to a significant percentage of operating costs, we find that the benefits of balancing market coordination are generally larger
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Suggested Citation

  • Adriaan Hendrik van der Weijde & Benjamin F. Hobbs, 2010. "Locational-based Coupling of Electricity Markets: Benefits from Coordinating Unit Commitment and Balancing Markets," Working Papers EPRG 1022, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    • Handle: RePEc:enp:wpaper:eprg1022
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    References listed on IDEAS

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    Cited by:

    1. Van den Bergh, Kenneth & Bruninx, Kenneth & Delarue, Erik, 2018. "Cross-border reserve markets: network constraints in cross-border reserve procurement," Energy Policy, Elsevier, vol. 113(C), pages 193-205.
    2. Simshauser, Paul, 2024. "On static vs. dynamic line ratings in renewable energy zones," Energy Economics, Elsevier, vol. 129(C).
    3. Giorgia Oggioni & Yves Smeers, 2012. "Degrees of Coordination in Market Coupling and Counter-Trading," The Energy Journal, , vol. 33(3), pages 39-90, July.
    4. Ambrosius, M. & Egerer, J. & Grimm, V. & Weijde, A.H. van der, 2020. "Uncertain bidding zone configurations: The role of expectations for transmission and generation capacity expansion," European Journal of Operational Research, Elsevier, vol. 285(1), pages 343-359.
    5. Triolo, Ryan C. & Wolak, Frank A., 2022. "Quantifying the benefits of a nodal market design in the Texas electricity market," Energy Economics, Elsevier, vol. 112(C).
    6. Curtis, John & Lynch, Muireann Á. & Zubiate, Laura, 2016. "The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland," Energy Economics, Elsevier, vol. 58(C), pages 186-198.
    7. Adriaan Weijde & Benjamin Hobbs, 2011. "Locational-based coupling of electricity markets: benefits from coordinating unit commitment and balancing markets," Journal of Regulatory Economics, Springer, vol. 39(3), pages 223-251, June.
    8. Lynch & John Curtis, 2016. "The effects of wind generation capacity on electricity prices and generation costs: a Monte Carlo analysis," Applied Economics, Taylor & Francis Journals, vol. 48(2), pages 133-151, January.
    9. Karsten Neuhoff & Loredana Sasso & Christian Winzer, 2013. "Policies for International Transmission Investment: Unlocking North Africa's Renewable Energy Portfolio - for Local Use and International Exchange ; Final Report," DIW Berlin: Politikberatung kompakt, DIW Berlin, German Institute for Economic Research, volume 74, number pbk74.
    10. Fridrik M. Baldursson & Ewa Lazarczyk & Marten Ovaere & Stef Proost, 2018. "Cross-Border Exchange and Sharing of Generation Reserve Capacity," The Energy Journal, , vol. 39(4), pages 57-84, July.
    11. Simshauser, Paul, 2021. "Renewable Energy Zones in Australia's National Electricity Market," Energy Economics, Elsevier, vol. 101(C).
    12. Giorgia Oggioni and Yves Smeers, 2012. "Degrees of Coordination in Market Coupling and Counter-Trading," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    13. Neuhoff, Karsten & Barquin, Julian & Bialek, Janusz W. & Boyd, Rodney & Dent, Chris J. & Echavarren, Francisco & Grau, Thilo & von Hirschhausen, Christian & Hobbs, Benjamin F. & Kunz, Friedrich & Nabe, 2013. "Renewable electric energy integration: Quantifying the value of design of markets for international transmission capacity," Energy Economics, Elsevier, vol. 40(C), pages 760-772.
    14. Ricardo Bessa & Carlos Moreira & Bernardo Silva & Manuel Matos, 2014. "Handling renewable energy variability and uncertainty in power systems operation," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(2), pages 156-178, March.
    15. E. Allevi & A. Gnudi & I. V. Konnov & G. Oggioni, 2022. "Dynamic Spatial Equilibrium Models: an Application to the Natural Gas Spot Markets," Networks and Spatial Economics, Springer, vol. 22(2), pages 205-241, June.
    16. Geoffrey Mabea, 2023. "Simulating Generalised Locational Marginal Pricing for Power Markets in East Africa," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 450-460, September.
    17. Paul Simshauser & Farhad Billimoria & Craig Rogers, 2021. "Optimising VRE plant capacity in Renewable Energy Zones," Working Papers EPRG2121, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    18. Mirjam Ambrosius & Jonas Egerer & Veronika Grimm & Adriaan H van der Weijde, 2019. "The role of expectations for market design - on structural regulatory uncertainty in electricity markets," Working Papers EPRG1915, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    19. Simshauser, P., 2021. "Renewable Energy Zones in Australia’s National Electricity Market," Cambridge Working Papers in Economics 2119, Faculty of Economics, University of Cambridge.
    20. Joachim Bertsch & Simeon Hagspiel & Lisa Just, 2016. "Congestion management in power systems," Journal of Regulatory Economics, Springer, vol. 50(3), pages 290-327, December.
    21. Jessica Raasch & Christoph Weber, 2017. "Decentralized Local Pricing – Improving Network Usage in a Smart-Grid Environment under Limited Informationation," EWL Working Papers 1704, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised May 2017.
    22. Simshauser, Paul & Billimoria, Farhad & Rogers, Craig, 2022. "Optimising VRE capacity in Renewable Energy Zones," Energy Economics, Elsevier, vol. 113(C).
    23. N. Gülpınar & F. Oliveira, 2014. "Analysis of relationship between forward and spot markets in oligopolies under demand and cost uncertainties," Computational Management Science, Springer, vol. 11(3), pages 267-283, July.
    24. Curtis, John & Lynch, Muireann Á. & Zubiate, Laura, 2016. "Carbon dioxide (CO2) emissions from electricity: The influence of the North Atlantic Oscillation," Applied Energy, Elsevier, vol. 161(C), pages 487-496.
    25. Bertsch, Joachim & Hagspiel, Simeon & Just, Lisa, 2016. "Congestion management in power systems - Long-term modeling framework and large-scale application," EWI Working Papers 2015-3, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).

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    More about this item

    Keywords

    electricity prices; international electricity exchange; electricity market model; electricity transmission;
    All these keywords.

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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