Local short-term variability in solar irradiance

Abstract

Abstract. Characterizing spatiotemporal irradiance variability is important for the successful grid integration of increasing numbers of photovoltaic (PV) power systems. Using 1 Hz 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 10 km. 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 2 km −2 .

The HD(CP)<sup>2</sup> Observational Prototype Experiment (HOPE) – an overview

“…They specifically calculated single-point statistics and two-point correlation coefficients for clear, overcast, and mixed skies. The statistics for clear and overcast skies show similar behaviour as in previously published work; see Lohmann et al (2016) for references. In order to account for conditions for a distributed PV system, they defined so-called irradiance increments as changes in transmissivities over specified intervals of time and showed that the magnitude of increments is more strongly reduced by spatial averaging than that of the fluctuations.…”

“…Broken clouds cause the largest deviations in the 10 × 10 km 2 domain, reaching about 30 W m −2 for 3-hourly and 80 W m −2 for 1-second-resolution observations. Also based on the horizontally high-resolved measurements of the irradiance from the PYR performed by TRO-POS, Lohmann et al (2016) analysed the statistics of spatiotemporal irradiance fluctuations with a strong applicationoriented focus on photovoltaic power systems. They specifically calculated single-point statistics and two-point correlation coefficients for clear, overcast, and mixed skies.…”

Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

“…The spatial decorrelation of the time series of SEVIRI pixels for its solar and infrared channels was studied for different cloud amounts as a function of distance ( 200 km) at different locations over Europe (Slobodda et al, 2015). In the most recent study, Lohmann et al (2016) used the Hoff and Perez (2012) model of spatial correlation using a range of cloud speeds from 2 to 10 m s −1 , and demonstrated that the Hoff and Perez (2012) model is not able to capture the correlation structure for mixed sky conditions. In our study, the spatial correlation of transmittance variations decays faster than linear at small distances as is indicated by the exponent (b) in Eq.…”

“…This unique data set can provide insights into the small-scale variability of global radiation due to various cloud types, and possibly enable the development of parameterizations of the unresolved spatiotemporal variability in the radiation field. Using this data set, Lohmann et al (2016) explored the fluctuations of the clear-sky index (i.e., the ratio of instantaneous global radiation to the radiation on the Earth with a cloud-free atmosphere) on clear, overcast, and mixed sky conditions with a simple increment statistics to study the smoothing effects of distributed photovoltaic power production.…”

Effects of temporal averaging on short-term irradiance variability under mixed sky conditions

“…If the standard deviation of k * exceeds a fixed threshold (taken to be 0.18, based on the 25 results of Lohmann et al, 2016), we classify the corresponding 900 s block as mixed, and retain it for our analyses.…”