IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i6p1497-d1614646.html
   My bibliography  Save this article

The Electricity Generation Landscape of Bioenergy in Germany

Author

Listed:
  • Reinhold Lehneis

    (Department of Microbial Biotechnology, Helmholtz Centre for Environmental Research GmbH—UFZ, Permoserstraße 15, 04318 Leipzig, Germany)

Abstract

Disaggregated data on electricity generation from bioenergy are very helpful for investigating the economic and technical effects of this form of renewable energy on the German power sector with a high temporal and spatial resolution. But the lack of high-resolution feed-in data for Germany makes it necessary to apply numerical simulations to determine the electricity generation from biomass power plants for a time period and geographic region of interest. This article presents how such a simulation model can be developed using public power plant data as well as open information from German TSOs as input data. The physical model is applied to an ensemble of 20,863 biomass power plants, most of which are in continuous operation, to simulate their electricity generation in Germany for the year 2020. For this period, the spatially aggregated simulation results correlate well with the official electricity feed-in from bioenergy. The disaggregated time series can be used to analyze the electricity generation at any spatial scale, as each power plant is simulated with its technical parameters and geographical location. Furthermore, this article introduces the electricity generation landscape of bioenergy as a high-resolution map and at the federal state level with meaningful energy figures, enabling comprehensive assessments of this form of renewable energy for different regions of Germany.

Suggested Citation

  • Reinhold Lehneis, 2025. "The Electricity Generation Landscape of Bioenergy in Germany," Energies, MDPI, vol. 18(6), pages 1-12, March.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:6:p:1497-:d:1614646
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/6/1497/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/6/1497/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Wan-Yu & Lin, Chun-Cheng & Yeh, Tzu-Lei, 2017. "Supply chain optimization of forest biomass electricity and bioethanol coproduction," Energy, Elsevier, vol. 139(C), pages 630-645.
    2. Rauner, Sebastian & Eichhorn, Marcus & Thrän, Daniela, 2016. "The spatial dimension of the power system: Investigating hot spots of Smart Renewable Power Provision," Applied Energy, Elsevier, vol. 184(C), pages 1038-1050.
    3. Jussi Ekström & Matti Koivisto & Ilkka Mellin & Robert John Millar & Matti Lehtonen, 2018. "A Statistical Modeling Methodology for Long-Term Wind Generation and Power Ramp Simulations in New Generation Locations," Energies, MDPI, vol. 11(9), pages 1-18, September.
    4. Reinhold Lehneis & Daniela Thrän, 2024. "In 50 Shades of Orange: Germany’s Photovoltaic Power Generation Landscape," Energies, MDPI, vol. 17(16), pages 1-12, August.
    5. Akhtari, Shaghaygh & Sowlati, Taraneh, 2020. "Hybrid optimization-simulation for integrated planning of bioenergy and biofuel supply chains," Applied Energy, Elsevier, vol. 259(C).
    6. Olauson, Jon & Bergkvist, Mikael, 2015. "Modelling the Swedish wind power production using MERRA reanalysis data," Renewable Energy, Elsevier, vol. 76(C), pages 717-725.
    7. Thaker, Jayesh & Höller, Robert, 2024. "Hybrid model for intra-day probabilistic PV power forecast," Renewable Energy, Elsevier, vol. 232(C).
    8. Reinhold Lehneis & Daniela Thrän, 2023. "Temporally and Spatially Resolved Simulation of the Wind Power Generation in Germany," Energies, MDPI, vol. 16(7), pages 1-16, April.
    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. Reinhold Lehneis & Falk Harnisch & Daniela Thrän, 2024. "Electricity Production Landscape of Run-of-River Power Plants in Germany," Resources, MDPI, vol. 13(12), pages 1-12, December.
    2. Reinhold Lehneis & Daniela Thrän, 2023. "Temporally and Spatially Resolved Simulation of the Wind Power Generation in Germany," Energies, MDPI, vol. 16(7), pages 1-16, April.
    3. Reinhold Lehneis & Daniela Thrän, 2024. "In 50 Shades of Orange: Germany’s Photovoltaic Power Generation Landscape," Energies, MDPI, vol. 17(16), pages 1-12, August.
    4. Becker, Raik & Thrän, Daniela, 2017. "Completion of wind turbine data sets for wind integration studies applying random forests and k-nearest neighbors," Applied Energy, Elsevier, vol. 208(C), pages 252-262.
    5. Maria Taljegard & Lisa Göransson & Mikael Odenberger & Filip Johnsson, 2021. "To Represent Electric Vehicles in Electricity Systems Modelling—Aggregated Vehicle Representation vs. Individual Driving Profiles," Energies, MDPI, vol. 14(3), pages 1-25, January.
    6. Mikovits, Christian & Wetterlund, Elisabeth & Wehrle, Sebastian & Baumgartner, Johann & Schmidt, Johannes, 2021. "Stronger together: Multi-annual variability of hydrogen production supported by wind power in Sweden," Applied Energy, Elsevier, vol. 282(PB).
    7. Fachrizal Aksan & Vishnu Suresh & Przemysław Janik, 2025. "PV Generation Prediction Using Multilayer Perceptron and Data Clustering for Energy Management Support," Energies, MDPI, vol. 18(6), pages 1-16, March.
    8. Jonasson, Erik & Fjellstedt, Christoffer & Temiz, Irina, 2024. "Grid impact of co-located offshore renewable energy sources," Renewable Energy, Elsevier, vol. 230(C).
    9. Nuño, Edgar & Maule, Petr & Hahmann, Andrea & Cutululis, Nicolaos & Sørensen, Poul & Karagali, Ioanna, 2018. "Simulation of transcontinental wind and solar PV generation time series," Renewable Energy, Elsevier, vol. 118(C), pages 425-436.
    10. Marcus Eichhorn & Mattes Scheftelowitz & Matthias Reichmuth & Christian Lorenz & Kyriakos Louca & Alexander Schiffler & Rita Keuneke & Martin Bauschmann & Jens Ponitka & David Manske & Daniela Thrän, 2019. "Spatial Distribution of Wind Turbines, Photovoltaic Field Systems, Bioenergy, and River Hydro Power Plants in Germany," Data, MDPI, vol. 4(1), pages 1-15, February.
    11. Matti Koivisto & Kaushik Das & Feng Guo & Poul Sørensen & Edgar Nuño & Nicolaos Cutululis & Petr Maule, 2019. "Using time series simulation tools for assessing the effects of variable renewable energy generation on power and energy systems," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(3), May.
    12. Zhaoyuan He & Paul Turner, 2021. "A Systematic Review on Technologies and Industry 4.0 in the Forest Supply Chain: A Framework Identifying Challenges and Opportunities," Logistics, MDPI, vol. 5(4), pages 1-22, December.
    13. Youngjin Kim & Sojung Kim, 2025. "Optimization and Simulation in Biofuel Supply Chain," Energies, MDPI, vol. 18(5), pages 1-24, February.
    14. Rabbani, R. & Zeeshan, M., 2020. "Exploring the suitability of MERRA-2 reanalysis data for wind energy estimation, analysis of wind characteristics and energy potential assessment for selected sites in Pakistan," Renewable Energy, Elsevier, vol. 154(C), pages 1240-1251.
    15. Li, Zhengbing & Liang, Yongtu & Ni, Weilong & Liao, Qi & Xu, Ning & Li, Lichao & Zheng, Jianqin & Zhang, Haoran, 2022. "Pipesharing: economic-environmental benefits from transporting biofuels through multiproduct pipelines," Applied Energy, Elsevier, vol. 311(C).
    16. Santibañez-Aguilar, José Ezequiel & Quiroz-Ramírez, Juan José & Sánchez-Ramírez, Eduardo & Segovia-Hernández, Juan Gabriel & Flores-Tlacuahuac, Antonio & Ponce-Ortega, José María, 2022. "Marginalization index as social measure for Acetone-Butanol-Ethanol supply chain planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    17. Jan Frederick Unnewehr & Hans-Peter Waldl & Thomas Pahlke & Iván Herráez & Anke Weidlich, 2020. "Reducing Operational Costs of Offshore HVDC Energy Export Systems Through Optimized Maintenance," Energies, MDPI, vol. 13(5), pages 1-20, March.
    18. Christopher Jung & Dirk Schindler, 2023. "Reasons for the Recent Onshore Wind Capacity Factor Increase," Energies, MDPI, vol. 16(14), pages 1-17, July.
    19. Danial Esmaeili Aliabadi & Tiago Pinto, 2025. "Modeling Electricity Markets and Energy Systems: Challenges and Opportunities," Energies, MDPI, vol. 18(2), pages 1-4, January.
    20. Hdidouan, Daniel & Staffell, Iain, 2017. "The impact of climate change on the levelised cost of wind energy," Renewable Energy, Elsevier, vol. 101(C), pages 575-592.

    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:gam:jeners:v:18:y:2025:i:6:p:1497-:d:1614646. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.