Electricity, heat, and gas sector data for modeling the german system F Kunz, M Kendziorski, WP Schill, J Weibezahn, J Zepter, ... DIW Data Documentation, 2017 | 53 | 2017 |
Reference data set: Electricity, heat, and gas sector data for modeling the german system F Kunz, J Weibezahn, P Hauser, S Heidari, WP Schill, B Felten, ... Zenodo, 2017 | 20 | 2017 |
Predicting PV areas in aerial images with deep learning M Zech, J Ranalli 2020 47th IEEE Photovoltaic Specialists Conference (PVSC), 0767-0774, 2020 | 19 | 2020 |
Wicked facets of the German energy transition–examples from the electricity, heating, transport, and industry sectors J Biehl, L Missbach, F Riedel, R Stemmle, J Jüchter, J Weber, J Kucknat, ... International Journal of Sustainable Energy 42 (1), 1128-1181, 2023 | 5 | 2023 |
A physically interpretable data-driven surrogate model for wake steering BAM Sengers, M Zech, P Jacobs, G Steinfeld, M Kühn Wind Energy Science 7 (4), 1455-1470, 2022 | 4 | 2022 |
Untersuchung von Handhabungsfehlern bei der Montage und Installation von PV Modulen C Olschok, M Pfeifer, M Zech, M Schmid, M Zehner, G Becker Proc. 27th Symposium Photovoltaische Solarenergie (OTTI, Bad Staffelstein …, 2012 | 3 | 2012 |
Detecting pipeline pathways in Landsat 5 satellite images with deep learning J Dasenbrock, A Pluta, M Zech, W Medjroubi Energies 14 (18), 5642, 2021 | 2 | 2021 |
Generalizability of Neural Network-based Identification of PV in Aerial Images J Ranalli, M Zech 2023 IEEE 50th Photovoltaic Specialists Conference (PVSC), 1-7, 2023 | 1 | 2023 |
A physically interpretable statistical wake steering model B Sengers, M Zech, P Jacobs, G Steinfeld, M Kühn Wind Energy Science Discussions 2021, 1-23, 2021 | 1 | 2021 |
End-to-end learning of representative PV capacity factors from aggregated PV feed-ins M Zech, L von Bremen Applied Energy 361, 122923, 2024 | | 2024 |
Spatio-temporal relationship of short-term renewable energy forecast errors M Zech, M Schroedter-Homscheidt, L von Bremen EMS2023, 2023 | | 2023 |
Data-driven mean-variability optimization of PV portfolios with automatic differentiation M Zech, L von Bremen ICLR 2023, tackling climate change with machine learning, 2023 | | 2023 |
Interpretation of clearness day-ahead forecast errors using novel cloud classification M Zech, L von Bremen DACH2022, 2021 | | 2021 |
Understanding the relationship between clouds and surface downward radiation forecast errors with Unsupervised Deep Learning M Zech, L von Bremen EMS2021, 2021 | | 2021 |
Interaction between atmospheric model resolution and energy system model topology M Zech, O Raventós, O Lünsdorf, L von Bremen EMS2021, 2021 | | 2021 |