Excerpts from the report: “BeyondTMY - Meteorological data sets for CSP/STE performance simulations”

Kristian Pagh Nielsen (1) , Frank Vignola (2) , Lourdes Ramírez (3) , Philippe Blanc (4) , Richard Meyer (5) , Manuel Blanco (6)

1 DMI - Danish Meteorological Institute
2 University of Oregon
3 CIEMAT - Centro de Investigaciones Energéticas Medioambientales y Tecnológicas [Madrid]
4 O.I.E. - Centre Observation, Impacts, Énergie
5 Suntrace GmbH
6 The Cyprus Institute

In order to facilitate comprehensive economic modeling of CSP/STE power plants realistic long-term meteorological datasets with temporal resolution down to 1 minute is a main premise. Currently available standard datasets do not fulfil this premise. The datasets also need to combine the high quality of well-maintained ground-based irradiance measurements and the global coverage of satellite-derived data. Even with the best available data it is necessary to account for the uncertainty in this and the sampling uncertainty from finite time-series to enable the optimal statistical characterization. It is a general challenge that satellite-derived data lack the required temporal resolution, and also often does not cover periods with major volcanic eruptions. Here we see prospects in synthetically generated realistic datasets, although research and development work is required on how to optimally produce and quality assure these.

Mots clés: Direct Normal Irradiance; Solar Power

Domaines: Sciences de l'ingénieur [physics]; Energétique

Kristian Pagh Nielsen, Frank Vignola, Lourdes Ramírez, Philippe Blanc, Richard Meyer, et al.. Excerpts from the report: “BeyondTMY - Meteorological data sets for CSP/STE performance simulations”. AIP Conference Proceedings, 2017, SOLARPACES 2016: International Conference on Concentrating Solar Power and Chemical Energy Systems, 1850 (1), pp.140017. ⟨10.1063/1.4984525⟩. ⟨hal-01553457⟩