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A high-resolution hydro power time-series model for energy systems analysis: Validated with Chinese hydro reservoirs

Liu, H.; Andresen, G. B.; Brown, T. 1; Greiner, M.
1 Institut für Automation und angewandte Informatik (IAI), Karlsruher Institut für Technologie (KIT)

We expand the renewable technology model palette and present a validated high resolution hydro power time series model for energy systems analysis. Among the weather-based renewables, hydroelectricity shows unique storage-like flexibility, which is particularly important given the high variability of wind and solar power. Often limited by data availability or computational performance, a high resolution, globally applicable and validated hydro power time series model has not been available. For a demonstration, we focus on 41 Chinese reservoir- based hydro stations as a demo, determine their upstream basin areas, estimate their inflow based on gridded surface runoff data and validate their daily inflow time series in terms of both flow volume and potential power generation. Furthermore, we showcase an application of these time series with hydro cascades in energy system long term investment planning. Our method's novelty lies in:
- it is based on highly resolved spatial-temporal datasets;
- both data and algorithms used here are globally applicable;
- it includes a hydro cascade model that can be integrated into energy system simulations.

Verlagsausgabe §
DOI: 10.5445/IR/1000096238
Veröffentlicht am 19.08.2019
DOI: 10.1016/j.mex.2019.05.024
Zitationen: 5
Zitationen: 6
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2019
Sprache Englisch
Identifikator ISSN: 2215-0161
KITopen-ID: 1000096238
HGF-Programm 37.06.01 (POF III, LK 01) Networks and Storage Integration
Erschienen in MethodsX
Verlag Elsevier
Band 6
Seiten 1370-1378
Schlagwörter Hydro power, Reanalysis, Energy systems, China
Nachgewiesen in Dimensions
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