Predicted and in situ performance of a solar air collector incorporating a translucent granular aerogel cover

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 ElsevierThere is an opportunity to improve the efficiency of flat plate solar air collectors by replacing their conventional glass covers with lightweight polycarbonate panels filled with high performance aerogel insulation. The in situ performance of a 5.4m2 solar air collector containing granular aerogel is simulated and tested. The collector is incorporated into the external insulation of a mechanically ventilated end terrace house, recently refurbished in London, UK. During the 7 day test period, peak outlet temperatures up to 45 °C are observed. Resultant supply and internal air temperatures peak at 25–30 and 21–22 °C respectively. Peak efficiencies of 22–36% are calculated based on the proposed design across a range of cover types. Measured outlet temperatures are validated to within 5% of their predicted values. Estimated outputs range from 118 to 166 kWh/m2/year for collectors with different thickness granular aerogel covers, compared to 110 kWh/m2/year for a single glazed collector, 140 k h/m2/year for a double glazed collector and 202 kWh/m2/year for a collector incorporating high performance monolithic aerogel. Payback periods of 9–16 years are calculated across all cover types. An efficiency up to 60% and a payback period as low as 4.5 years is possible with an optimised collector incorporating a 10 mm thick granular aerogel cover.This work is supported by the EPSRC, Brunel University, Buro Happold Ltd. and the Technology Strategy Board

Cloud cover effect of clear-sky index distributions and differences between human and automatic cloud observations

The statistics of clear-sky index can be used to determine solar irradiance when the theoretical clear sky irradiance and the cloud cover are known. In this paper, observations of hourly clear-sky index for the years of 2010--2013 at 63 locations in the UK are analysed for over 1 million data hours. The aggregated distribution of clear-sky index is bimodal, with strong contributions from mostly-cloudy and mostly-clear hours, as well as a lower number of intermediate hours. The clear-sky index exhibits a distribution of values for each cloud cover bin, measured in eighths of the sky covered (oktas), and also depends on solar elevation angle. Cloud cover is measured either by a human observer or automatically with a cloud ceilometer. Irradiation (time-integrated irradiance) values corresponding to human observations of "cloudless" skies (0 oktas) tend to agree better with theoretical clear-sky values, which are calculated with a radiative transfer model, than irradiation values corresponding to automated observations of 0 oktas. It is apparent that the cloud ceilometers incorrectly categorise more non-cloudless hours as cloudless than human observers do. This leads to notable differences in the distributions of clear-sky index for each okta class, and between human and automated observations. Two probability density functions---the Burr (type III) for mostly-clear situations, and generalised gamma for mostly-cloudy situations---are suggested as analytical fits for each cloud coverage, observation type, and solar elevation angle bin. For human observations of overcast skies (8 oktas) where solar elevation angle exceeds 10°, there is no significant difference between the observed clear-sky indices and the generalised gamma distribution fits

A synthetic, spatially decorrelating solar irradiance generator and application to a LV grid model with high PV penetration

Residential photovoltaic (PV) technology is expected to have mass global deployment. With widespread PV in the electricity distribution grids, the variable nature of the solar resource must be understood to facilitate reliable operation. This research demonstrates that synthetic, 1-min resolution irradiance time series that vary on a spatial dimension can be generated based on the following inputs: mean hourly meteorological observations of okta, wind speed, cloud height and atmospheric pressure. The synthetic time series temporally validate against observed 1-min irradiance data for four locations—Cambourne, UK; Lerwick, UK; San Diego, CA USA; and Oahu, HI USA—when analysing 4 metrics of variability indices, ramp-rate size, irradiance magnitude frequency and clear-sky index frequency. Each metric is calculated for the modelled and observed data at each location and CDF profile correlation compared as well as applying the Kolmogorov-Smirnov (K–S) test with 99% confidence limits. CDF correlation coefficients of each metric are all above R⩾0.908, and a minimum of 90.96% of daily irradiance time series passed the K–S test. A spatial validation was performed comparing the model outputs to real observation data. The spatial correlation coefficient regression with site separation was successfully recreated with MAPE = 0.865%, RMSE = 0.01 and R=0.955. The spatial instantaneous correlation was shown to behave anisotropically when using fixed cloud direction, with different correlation in along and cross wind directions. Cloud cover states of 40–60% showed the most spatial decorrelation while 0% and 100% had the least. The model outputs are applied to a distribution grid impact model using the IEEE-8500 node test feeder. PV scenarios of 25%,50%, and 75% uptake were modelled across a 1.5×1.5 km grid. The magnitude and frequency of severe tap changing events are found to be significantly higher when using a single irradiance time series for all PV systems versus individually assigning spatially decorrelating time series

The UK solar energy resource and the impact of climate change

AbstractSolar energy use in the UK is increasing dramatically, providing both heat energy and generation of electricity. This trend is expected to continue due to solar technologies becoming cheaper and more readily available along with low carbon government legislation such as the Renewable Heat Incentive (RHI) and Feed in Tariffs (FiTs) supporting solar energy deployment. However, the effects of climate change on the solar resource remain largely unstudied. Climate change affects cloud cover characteristics and consequently directly affects the performance of solar energy technologies.This paper investigates the UK solar irradiation resource for both the present and future climates.The present solar irradiation level was assessed through the conversion of 30 years of observed historical monthly average sunshine duration data. The method and results are validated by comparing the converted solar irradiation levels to actual solar irradiance measurements at weather stations with significant historical records of solar irradiance data.The impact of climate change is investigated across different regions of the UK by using the UKCP09 probabilistic climate change projections.We find that the current average UK annual solar resource is 101.2 Wm−2, ranging from 128.4 Wm−2 in the south of England to 71.8 Wm−2 in the northwest of Scotland. It seems likely that climate change will increase the average resource in the south of the UK, while marginally decreasing it in the Northwest. The overall effect is a mean increase of the UK solar resource, however it will have greater seasonal variability and discrepancies between geographical regions will be reinforced