Estimation of Marginal CO2 Emission Factors in Germany 2017
Lohmann, Kai; Huber, Julian; Weinhardt, Christof
Abstract (englisch):
This data set covers total load, hourly generation and electric efficiency of power plants >100MW in Germany 2017. Based on this data, the four jupyter-notebooks derive average carbon dioxide emissions factors for each hour and marginal emission factors for twenty load levels. The third script contains a case study for scheduling battery electric vehicles based on short-term forecasts of marginal emission factors.
| Zugehörige Institution(en) am KIT | Fakultät für Wirtschaftswissenschaften – Institut für Informationswirtschaft und -management (IISM) |
| Publikationstyp | Forschungsdaten |
| Publikationsdatum | 10.12.2019 |
| Erstellungsdatum | 10.12.2019 |
| Identifikator | DOI: 10.5445/IR/1000100740 KITopen-ID: 1000100740 |
| Lizenz | Creative Commons Namensnennung – Nicht kommerziell – Weitergabe unter gleichen Bedingungen 4.0 International |
| Liesmich | This data set covers total load, hourly generation and electric efficiency of power plants >100MW in Germany 2017. Based on this data, the four jupyter-notebooks derive average carbon dioxide emissions factors for each hour and marginal emission factors for twenty load levels. The third script contains a case study for scheduling battery electric vehicles based on short-term forecasts of marginal emission factors. |
| Art der Forschungsdaten | Dataset |