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Wind Providing Balancing Reserves: An Application to the German Electricity System of 2025

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  • Casimir Lorenz
  • Clemens Gerbaulet

Abstract

This paper analyzes the influence of wind turbines as new participants on prices and allocation within balancing markets. We introduce the cost-minimizing electricity sector model ELMOD-MIP, that includes detailed unit-commitment constraints, complex combined heat and power constraints, and minimum bid sizes for balancing capacity reservation. The model also features a novel approach of modeling balancing reservation by considering possible activation costs already during the reservation phase, mimicking the activation anticipation of market participants. The model includes the spot and balancing market of Germany and is applied to scenarios for 2013 and 2025. The results for 2025 show, in comparison to 2013, a price increase for positive and negative reserves, in case no new participants enter the market. With the participation of wind turbines the cost for balancing provision is reduced by 40%, but above 2013 values. The relative cost savings from wind participation are higher for negative reserve provision than positive reserve provision, as wind turbines can use their full capacity if not activated and do not have to be curtailed ex ante. The participation of wind turbines especially reduces the occurrence of peak prices for positive and negative reserves in 2025. This reduction effect occurs even with a relatively low share where wind turbines participate with only five percent of their capacity. Therefore, further fostering the process of allowing wind turbines to participate in the German reserve market seems favorable.

Suggested Citation

  • Casimir Lorenz & Clemens Gerbaulet, 2017. "Wind Providing Balancing Reserves: An Application to the German Electricity System of 2025," Discussion Papers of DIW Berlin 1655, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp1655
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    References listed on IDEAS

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    Cited by:

    1. Sergio Martín‐Martínez & Alberto Lorenzo‐Bonache & Andrés Honrubia‐Escribano & Miguel Cañas‐Carretón & Emilio Gómez‐Lázaro, 2018. "Contribution of wind energy to balancing markets: The case of Spain," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 7(5), September.
    2. Klaus Skytte & Lucien Bobo, 2019. "Increasing the value of wind: From passive to active actors in multiple power markets," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(3), May.
    3. Edmunds, Calum & Martín-Martínez, Sergio & Browell, Jethro & Gómez-Lázaro, Emilio & Galloway, Stuart, 2019. "On the participation of wind energy in response and reserve markets in Great Britain and Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    4. Hugo Algarvio & Fernando Lopes & António Couto & Ana Estanqueiro, 2019. "Participation of wind power producers in day‐ahead and balancing markets: An overview and a simulation‐based study," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.
    5. Konstantin Löffler & Karlo Hainsch & Thorsten Burandt & Pao-Yu Oei & Claudia Kemfert & Christian von Hirschhausen, 2017. "Designing a Global Energy System Based on 100% Renewables for 2050: GENeSYS-MOD: An Application of the Open-Source Energy Modelling System (OSeMOSYS)," Discussion Papers of DIW Berlin 1678, DIW Berlin, German Institute for Economic Research.

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    More about this item

    Keywords

    balancing reserves; electricity sector modeling; power plant dispatch; wind participation;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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