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Volume 16, issue 10 | Copyright

Special issue: HD(CP)2 Observational Prototype Experiment (AMT/ACP...

Atmos. Chem. Phys., 16, 6365-6379, 2016
https://doi.org/10.5194/acp-16-6365-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 25 May 2016

Research article | 25 May 2016

Local short-term variability in solar irradiance

Gerald M. Lohmann1, Adam H. Monahan2, and Detlev Heinemann1 Gerald M. Lohmann et al.
  • 1Energy Meteorology Group, Institute of Physics, Oldenburg University, Oldenburg, Germany
  • 2School of Earth and Ocean Sciences, University of Victoria, Victoria, BC, Canada

Abstract. Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers of photovoltaic (PV) power systems. Using 1Hz data recorded by as many as 99 pyranometers during the HD(CP)2 Observational Prototype Experiment (HOPE), we analyze field variability of clear-sky index k* (i.e., irradiance normalized to clear-sky conditions) and sub-minute k* increments (i.e., changes over specified intervals of time) for distances between tens of meters and about 10km. By means of a simple classification scheme based on k* statistics, we identify overcast, clear, and mixed sky conditions, and demonstrate that the last of these is the most potentially problematic in terms of short-term PV power fluctuations. Under mixed conditions, the probability of relatively strong k* increments of ±0.5 is approximately twice as high compared to increment statistics computed without conditioning by sky type. Additionally, spatial autocorrelation structures of k* increment fields differ considerably between sky types. While the profiles for overcast and clear skies mostly resemble the predictions of a simple model published by Hoff and Perez (2012), this is not the case for mixed conditions. As a proxy for the smoothing effects of distributed PV, we finally show that spatial averaging mitigates variability in k* less effectively than variability in k* increments, for a spatial sensor density of 2km−2.

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Increasing numbers of photovoltaic (PV) power systems call for the characterization of irradiance variability with very high spatiotemporal resolution. We use 1 Hz irradiance data recorded by as many as 99 pyranometers and show mixed sky conditions to differ substantially from clear and overcast skies. For example, the probabilities of strong fluctuations and their respective spatial autocorrelation structures are appreciably distinct under mixed conditions.
Increasing numbers of photovoltaic (PV) power systems call for the characterization of...
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