BENOPT

Model family for investigating future transformation scenarios for the energetic use of biomass in the transport, power, heat, and selected material use sectors. Two model variants are currently in operation: BENOPT-EU aims on extending the model to cover the European region. BENOPT-DE focuses on modelling Germany as a whole. You can find out more about the two versions via the links below. 


BENOPT-EU
BENOPT-DE

Unique selling propositions

  • Target region: Germany in Europe (DE NUTS1 & expansion to the EU level)
  • Land Management: RE, Natural Sink, Bioenergy, etc.
  • Regional views on imports and exports of resources and products between regions/countries
  • Maximizing the greenhouse gas abatement or cost minimization + Pareto analyses
  • Stoachastic Modeling
    ⇒ less reliant on scenarios
  • Target region: Germany as a whole
  • Scope is adapted to address German politics on a national level
  • Biomass and Bioenergy: High sectoral, technological, CDR and biomass potential/ product details
  • Comprehensive scenario portfolio integrated
  • Fast model runtime 
    ⇒ Quick response to inquiries; Potential is given to integrate further sectoral or technological details
Contacts:

Danial Esmaeili Aliabadi
Matthias Jordan
Mohammad Sadr
Sandra Gutjahr
Ágnes Csilla T. Szabó
Isabella Kreller

Alumni:

Markus Millinger
Ali Forootani
Frazer Musonda
Katrina Chan

The BioENergy OPTimization model (BENOPT) has been developed to optimize the competition between various bioenergy technology options. BENOPT is a perfect foresight optimization model designed to optimally allocate dispatchable renewable energy carriers across different sectors. Depending on the model version it aims to achieve two main objectives: maximizing the greenhouse gas (GHG) abatement or cost minimization while meeting specific GHG targets. Additionally, it enables Pareto analyses to be performed by combining these objective functions.

BENOPT encompasses multiple sectors, including transport (road passenger, road goods, rail, shipping, and aviation), power and heat (industry, household, and commercial), and chemical industries. It also includes relevant areas of the non-energy sectors such as forestry, agriculture, soil management, and wetland management to effectively evaluate LULUCF targets for GHG reduction (BENOPT-EU). The model operates yearly, except for residual load demand and surplus power usage, which can be analyzed hourly. BENOPT integrates detailed input-output, CAPEX, and OPEX data for feedstocks, conversion, and supply. This integration allows for comprehensive cost analyses and, when combined with relevant emission factors, thorough GHG analyses.

BENOPT was/is used in the following projects, and in each case, adapted and further developed:

MoBioInd (optimization: detailed industrial prozess heat)

BioCas (optimization: governance and cascade use of biomass)

BioNET (optimization: negative emission technologies)

Milestones 2030 (simulation: power, heat, fuels)

BEPASO (optimization: power, heat, fuels, chemicals)

BioPlanW (optimization: heat)

BKSQuote (optimization: fuels)

TATBio (optimization: power, heat, fuels)

BEniVer (optimization: biofuels and electrofuels)

AGRI-TRANSFORM (optimization: all sectors, including food)

SmartWirbelschicht, KonditorGas (optimization: incl. advanced technologies in heat)

SoBio, BIOSTRAT, Symobio 2.0 (optimization: power, heat, fuels)

SoBio ll (optimization: bioeconomy)

Man0EUvRE (optimization, integrated view, EU)

News and Updates 

Biomass use in the different sectors

  • 26.09.2025: Frazer Musonda's PhD dissertation defense at Leipzig University.

PhD Defense

  • 10.12.2024: Winning the UFZ Research Award 2024 for their achievements in realizing sustainable biomass use for climate neutrality in Germany.

The REWG Team

  • July 2023 - The first paper regarding the new graphical user interface of the BENOPT model has been published.

Publications:

Sadr, M., Esmaeili Aliabadi, D., Jordan, M., Wollnik, R., Thrän, D. (2026): Unleashing the combined potential of bio-based carbon dioxide removal in Germany’s path to net zero from the bioenergy system perspective, iScience 29 (8), art. 116852 10.1016/j.isci.2026.116852

Gutjahr, S., Thrän, D., Esmaeili Aliabadi, D. (2026): Tango of renewables in the triangle of uncertainty: A German case study, Adv. Appl. Energy 22, art. 100281 10.1016/j.adapen.2026.100281

Cyfka, A., Jordan, M., Vollmers, J., Thrän, D. (2026): The future role of agroforestry and Agri-PV in the German energy system - An analysis with the BENOPTex model. Energy Conv. Manag.-X 10.1016/j.ecmx.2026.101614

Esmaeili Aliabadi, D., Wulff, N., Lehneis, R., Sadr, M., Gutjahr, S., Reutter, F.J., Jordan, M., Lehmann, P., Thrän, D. (2025): Climate change may impair the transition to a fully renewable energy system: A German case study. Energy 338, art. 138684 10.1016/j.energy.2025.138684

Wulff, N., Esmaeili Aliabadi, D., Samuel, H., Pregger, T., Özcan, D., Gils, H.C., Kronshage, S., Ruiz, E.S.A., Grimme, W., Horst, J., Jochem, P. (2025): Energy system implications of demand scenarios and supply strategies for renewable transportation fuels. Energy Strateg. Rev. 58, art. 101606: 10.1016/j.esr.2024.101606

Sadr, M., Esmaeili Aliabadi, D., Jordan, M., Thrän, D. (2024): A bottom-up regional potential assessment of bioenergy with carbon capture and storage in Germany. Environ. Res. Lett. 10.1088/1748-9326/ad7edd

Jordan, M., Meisel, K., Dotzauer, M., Schindler, H., Schröder, J., Cyffka, K.-F., Dögnitz, N., Naumann, K., Schmid, C., Lenz, V., Daniel-Gromke, J., Costa de Paiva, G., Esmaeili Aliabadi, D., Szarka, N., Thrän, D. (2024): Do current energy policies in Germany promote the use of biomass in areas where it is particularly beneficial to the system? Analysing short- and long-term energy scenarios. Energy Sustain. Soc. 14 , art. 32 10.1186/s13705-024-00464-1

Sadr, M., Esmaeili Aliabadi, D., Avşar, B., Thrän, D. (2024): Assessing the impact of seasonality on bioenergy production from energy crops in Germany, considering just-in-time philosophy. Biofuels Bioprod. Biorefining https://doi.org/10.1002/bbb.2602

Musonda, F., Millinger, M., & Thrän, D. (2024): Modelling assessment of resource competition for renewable basic chemicals and the effect of recycling. GCB Bioenergy, 16, e13133. https://doi.org/10.1111/gcbb.13133

Esmaeili Aliabadi, D., Chan, K., Wulff, N., Meisel, K., Jordan, M., Österle, I., Pregger, T., Thrän, D. (2023): Future renewable energy targets in the EU: Impacts on the German transport, Transportation Research Part D: Transport and Environment, 124, 103963: https://doi.org/10.1016/j.trd.2023.103963

Jordan, M., Meisel, K., Dotzauer, M., Schröder, J., Cyffka, K.-F., Dögnitz, N., Schmid, C., Lenz, V., Naumann, K., Daniel-Gromke, J., Costa de Paiva, G., Schindler, H., Esmaeili Aliabadi, D., Szarka, N., Thrän, D. (2023): The controversial role of energy crops in the future German energy system: The trade offs of a phase-out and allocation priorities of the remaining biomass residues. Energy Reports, 10, 3848 - 3858: https://doi.org/10.1016/j.egyr.2023.10.055

Esmaeili Aliabadi, D., Manske, D., Seeger, L., Lehneis, R., Thrän, D. (2023). Integrating knowledge acquisition, visualization, and dissemination in energy system models: BENOPTex study. Energies 16 (13), art. 5113: https://doi.org/10.3390/en16135113

Millinger, M., Tafarte, P., Jordan, M., Musonda, F., Chan, K., Meisel, K., & Aliabadi, D. E. (2022). A model for cost-and greenhouse gas optimal material and energy allocation of biomass and hydrogen. SoftwareX, 20, 101264: https://doi.org/10.1016/j.softx.2022.101264

Jordan, M., Millinger, M., & Thrän, D. (2022). Benopt-Heat: An economic optimization model to identify robust bioenergy technologies for the German heat transition. SoftwareX, 18, 101032: https://doi.org/10.1016/j.softx.2022.101032

Lauer, M., Dotzauer, M., Millinger, M., Oehmichen, K., Jordan, M., Kalcher, J., ... & Thraen, D. (2022). The Crucial Role of Bioenergy in a Climate‐Neutral Energy System in Germany. Chemical Engineering & Technology: https://doi.org/10.1002/ceat.202100263

Mutlu, Ö., Jordan, M., Zeng, T., & Lenz, V. (2022). Competitive Options for Bio‐Syngas in High‐Temperature Heat Demand Sectors: Projections until 2050. Chemical Engineering & Technology: https://doi.org/10.1002/ceat.202200217

Aliabadi, D. E., Chan, K., Jordan, M., Millinger, M., & Thrän, D. (2022, April). Abandoning the Residual Load Duration Curve and Overcoming the Computational Challenge. In 2022 Open Source Modelling and Simulation of Energy Systems (OSMSES) (pp. 1-6). IEEE: http://doi.org/10.1109/OSMSES54027.2022.9769166

Musonda, F., Millinger, M., Thrän, D., (2021): Optimal biomass allocation to the German bioeconomy based on conflicting economic and environmental objectives. J. Clean Prod. 309, art. 127465: http://dx.doi.org/10.1016/j.jclepro.2021.127465

Jordan, M., Hopfe, C., Millinger, M., Rode, J., Thrän, D., (2021) Incorporating consumer choice into an optimization model for the German heat sector: Effects on projected bioenergy use. J. Clean Prod. 295, art. 126319:  http://dx.doi.org/10.1016/j.jclepro.2021.126319

Millinger, M., Tafarte, P., Jordan, M., Hahn, A., Meisel, K., Thrän, D. (2021): Electrofuels from excess renewable electricity at high variable renewable shares: cost, greenhouse gas abatement, carbon use and competition. Sustainable Energy & Fuels 5 (3): 828-843: http://dx.doi.org/10.1039/D0SE01067

Meisel, K., Millinger, M., Naumann, K., Müller-Langer, F., Majer, S., Thrän, D., (2020): Future renewable fuel mixes in transport in Germany under RED II and climate protection targets. Energies 13 (7), art. 1712: http://dx.doi.org/10.3390/en13071712

Musonda, F., Millinger, M., Thrän, D., (2020): Greenhouse gas abatement potentials and economics of selected biochemicals in Germany. Sustainability 12 (6), art. 2230: http://dx.doi.org/10.3390/su12062230

Jordan, M., Millinger, M., Thrän, D., (2020): Robust bioenergy technologies for the German heat transition: A novel approach combining optimization modeling with Sobol’ sensitivity analysis. Appl. Energy 262 , art. 114534: http://dx.doi.org/10.1016/j.apenergy.2020.114534

Jordan, M., Lenz, V., Millinger, M., Oehmichen, K., Thrän, D., (2019): Future competitive bioenergy technologies in the German heat sector: Findings from an economic optimization approach. Energy 189 , art. 116194: https://doi.org/10.1016/j.energy.2019.116194

Millinger, M., Meisel, K., Thrän, D., (2019): Greenhouse gas abatement optimal deployment of biofuels from crops in Germany. Transport. Res. Part D-Transport. Environ. 69 , 265 - 275: https://doi.org/10.1016/j.trd.2019.02.005. Open source model available here: https://doi.org/10.5281/zenodo.2812986

Millinger, M., (2018): Systems assessment of biofuels : modelling of future cost and greenhouse gas abatement competitiveness between biofuels for transport on the case of Germany. Dissertation, Universität Leipzig, Wirtschaftswissenschaftliche Fakultät. PhD Dissertation 3/2018. Helmholtz-Zentrum für Umweltforschung - UFZ, Leipzig, XVII, 92 pp.

Millinger, M., Meisel, K., Budzinski, M., Thrän, D., (2018): Relative greenhouse gas abatement cost competitiveness of biofuels in Germany. Energies 11 (3), art. 615: https://doi.org/10.3390/en11030615. Open source model available here: https://doi.org/10.5281/zenodo.2810903

Millinger, M., Thrän, D., (2018): Biomass price developments inhibit biofuel investments and research in Germany: The crucial future role of high yields. J. Clean Prod. 172 , 1654 - 1663

Millinger, M., Ponitka, J., Arendt, O., Thrän, D., (2017): Competitiveness of advanced and conventional biofuels: Results from least-cost modelling of biofuel competition in Germany. Energy Policy 107 , 394 - 402

Thrän, D., Arendt, O., Banse, M., Braun, J., Fritsche, U., Gärtner, S., Hennenberg, K.J., Hünneke, K., Millinger, M., Ponitka, J., Rettenmaier, N., Schaldach, R., Schüngel, J., Wern, B., Wolf, V., (2017): Strategy elements for a sustainable bioenergy policy based on scenarios and systems modeling: Germany as example. Chem. Eng. Technol. 40 (2), 211 - 226

Thrän, D., Schaldach, R., Millinger, M., Wolf, V., Arendt, O., Ponitka, J., Gärtner, S., Rettenmaier, N., Hennenberg, K., Schüngel, J., (2016): The MILESTONES modeling framework: An integrated analysis of national bioenergy strategies and their global environmental impacts. Environ. Modell. Softw. 86 , 14 - 29