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Wind Power Decreases the Need for Storage in an Interconnected 100% Renewable European Power Sector

Author

Listed:
  • Alexander Roth
  • Wolf-Peter Schill

Abstract

The massive expansion of wind power and solar PV is the primary strategy to reduce greenhouse gas emissions in many countries. Due to their variable generation profiles, power sector flexibility needs to increase. Geographical balancing enabled by electricity grids and temporal flexibility enabled by electricity storage are important options for flexibility. As they interact with each other, we investigate how and why interconnection with neighboring countries reduces storage needs. To do so, we apply a cost-minimizing open-source capacity expansion model to a 100% renewable energy scenario of central Europe. We use a factorization method to disentangle the effect of interconnection on optimal storage through distinct channels: differences in (i) countries’ solar PV and wind power capacity factors, (ii) load profiles, as well as (iii) hydropower and bioenergy capacity. Results show that geographical balancing lowers aggregate storage capacities by around 30% in contrast to a similar system without interconnection. We further find that the differences in wind power profiles between countries explain, on average, around 80% of that effect. Differences in solar PV capacity factors, load profiles, or country-specific capacities of hydropower together explain up to 20%. Our analysis improves the understanding of the benefits of geographical balancing for providing flexibility and its drivers.

Suggested Citation

  • Alexander Roth & Wolf-Peter Schill, 2022. "Wind Power Decreases the Need for Storage in an Interconnected 100% Renewable European Power Sector," Discussion Papers of DIW Berlin 2025, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp2025
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    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.860999.de/dp2025.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. Gaete-Morales, Carlos & Kittel, Martin & Roth, Alexander & Schill, Wolf-Peter, 2021. "DIETERpy: A Python framework for the Dispatch and Investment Evaluation Tool with Endogenous Renewables," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15.
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    More about this item

    Keywords

    Variable renewable energy sources; electricity storage; interconnection; numerical optimization; 100% renewable energy;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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