Thomas Zipperle
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Thomas Zipperle has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
Christopher Scheubel
1 shared publication- Clara Luisa Orthofer
Chair of Energy Economy and Application Technology, Department of Electrical and Computer Engineering, Technical University of Munich, 80333 Munich, Germany
1 shared publication - Peter Tzscheutschler
School of Engineering and Design, Technical University of Munich, Munich, Germany
1 shared publication
Latest Publications
- Open Access
d2ix: A Model Input-Data Management and Analysis Tool for MESSAGEix
Bottom-up integrated assessment models, like MESSAGEix, depend on the description of the capabilities and limitations of technological, economical and ecological parameters, and their development over long-time horizons. Even small models of a few nodes, technologies and model years require input-data sets involving several hundred thousand data points. Such data sets quickly become incomprehensible, which makes error detection, collaborative working and the interpretation of results challenging, especially for non-self-created models. In response to the resulting need for manageable, comprehensible, and traceable representation of input-data, we developed a Python-based spreadsheet interface (d2ix) that enables presentation and editing of model input-data in a concise form. By increasing accessibility and transparency of the model input-data, d2ix reduces barriers to entry for new modellers and simplifies collaborative working. This paper describes the methodology and introduces the open-source Python-package d2ix. The package is available under the Apache License, Version 2.0 on GitHub.
Open Accessd2ix: A Model Input-Data Management and Analysis Tool for MESSAGEix
Bottom-up integrated assessment models, like MESSAGEix, depend on the description of the capabilities and limitations of technological, economical and ecological parameters, and their development over long-time horizons. Even small models of a few nodes, technologies and model years require input-data sets involving several hundred thousand data points. Such data sets quickly become incomprehensible, which makes error detection, collaborative working and the interpretation of results challenging, especially for non-self-created models. In response to the resulting need for manageable, comprehensible, and traceable representation of input-data, we developed a Python-based spreadsheet interface (d2ix) that enables presentation and editing of model input-data in a concise form. By increasing accessibility and transparency of the model input-data, d2ix reduces barriers to entry for new modellers and simplifies collaborative working. This paper describes the methodology and introduces the open-source Python-package d2ix. The package is available under the Apache License, Version 2.0 on GitHub.
- 1 August 2017
- Published by Elsevier in Renewable Energy
- Vol. 108, 52-63
Modeling of industrial-scale hybrid renewable energy systems (HRES) – The profitability of decentralized supply for industry
- 1 August 2017
- Published by Elsevier in Renewable Energy
- Vol. 108, 52-63
Modeling of industrial-scale hybrid renewable energy systems (HRES) – The profitability of decentralized supply for industry