Bioenergy is a crucial element of the future energy system with range of applications in the electricity, heat and transport sectors. One major challenge for the analysis and optimisation of the bioenergy system is the degree of diversity and complexity compared to wind or solar energy. A coherent data base needs to encompass the different entities such as bioresources, conversation process and process chains. Thus Bio-Energy Technology database (BET.db) was developed by merging various existing datasets into a SQLite database. The resulting BET.db provides consistent sets for 141 biogenic raw materials as well as energy carriers, 259 conversation technologies and 134 supply concepts for energy provision . BET.db was developed as part of a non-public research project for system optimal biomass allocation (SoBio). We have valiate the usability of BET.db by connecting the Bioenergy Optimisation Model (BENOPT). For this use case we can ensure a transparent and reproducible data source for such modeling tasks.

{"references": ["V. Lenz, M. Jordan, Technical and economic data of renewable heat supply systems for different heat sub-sectors.: Supplementary material, 2019. https://data.mendeley.com/datasets/v2c93n28rj/2", "K. Meisel, M. Millinger, K. Naumann, F. M\u00fcller-Langer, S. Majer, D. Thr\u00e4n, Future Renewable Fuel Mixes in Transport in Germany under RED II and Climate Protection Targets, Energies 13 (7) (2020) 1712. https://doi.org/10.3390/en13071712", "M. Lauer, M. Dotzauer, M. Millinger, K. Oehmichen, M. Jordan, J. Kalcher, S. Majer, D. Thraen, The Crucial Role of Bioenergy in a Climate\u2010Neutral Energy System in Germany, Chem Eng & Technol 90 (1) (2022) 68. https://doi.org/10.1002/ceat.202100263"]}

The primary data comes mainly from three existing datasets for which the references are given here. The database contains an integrated referencing system. Each individual data point is thus traceable, regardless of whether it comes from the primary sources mentioned above or was researched elsewhere.