Thesis (M.S.)--Naval Postgraduate School, 1977. / Includes bibliographical references (leaves 88-90).

No description available.

Thesis (Ph.D.) -- McMaster University, 2002. / Includes bibliographical references (leaves 145-157). Also available via World Wide Web.

This thesis presents the outcome of investigations undertaken in the field of terrestrial spectral solar irradiance characterisation and its impact on photovoltaics. Spectral irradiance has not previously been widely researched in the context of photovoltaic applications. Long-term, natural environment spectral irradiance observations are practically non-existent with availability very limited in terms of covered period, temporal resolution and site location. The work presented concentrates on four major aspects of spectral irradiance: spectroradiometer calibration spectral irradiance calibration transfer standards natural spectral irradiance variability and its impact on photovoltaic device efficiency impact of reference sensor spectral mismatch on accuracy of reference irradiance measurements.

Yes / The variation of solar irradiance is one of the natural forcing mechanisms of the terrestrial climate. Hence, the time-dependent solar irradiance is an important input parameter for climate modelling. The solar surface magnetic field is a powerful proxy for solar irradiance reconstruction. The analyses of data obtained with the Michelson Doppler Imager (MDI) on board the SOHO mission are therefore useful for the identification of solar surface magnetic features to be used in solar irradiance reconstruction models. However, there is still a need for automated technologies that would enable the identification of solar activity features from large databases. To achieve this we present a series of enhanced segmentation algorithms developed to detect and calculate the area coverages of specific magnetic features from MDI intensitygrams and magnetograms. These algorithms are part of the Automated Solar Activity Prediction (ASAP) tool. The segmentation algorithms allow us to identify the areas on the solar disk covered by magnetic elements inside and outside boundaries of active regions. Depending on their contrast properties, magnetic features within an active region boundary are classified as sunspot umbra and penumbra, or faculae. Outside an active region boundary magnetic elements are identified as network. We present the detailed steps involved in the segmentation process and provide the area coverages of the segmented MDI intensitygrams and magnetograms. The feature segmentation was carried out on daily intensitygrams and magnetograms from April 21, 1996 to April 11, 2011. This offers an exciting opportunity to undertake further investigations that benefit from solar features segmentations, such as solar irradiance reconstruction, which we plan to investigate in the future.

Solar photovoltaic (PV) resources are a key enabling technology in the global energy transition towards a more sustainable future. However, PV generation is highly variable due to the dynamic shading caused by clouds. To mitigate the effects of PV variability on electrical grid stability, grid operators rely on solar forecasts to proactively dispatch grid assets and balance supply and demand. To gain insights into the nature of solar variability, which is key for effective solar forecasting, this thesis presents a statistical assessment of high resolution spectral and broadband solar irradiance in Ottawa, Canada. The statistical assessment investigates the first- and second-order spectral and temporal dependencies of irradiance time series within the context of stationarity. The temporal structures indicate that solar irradiance processes are at best weakly stationary, and the implications for forecasting are discussed. The results of the statistical assessment are leveraged to develop several deterministic machine learning solar forecasting models (LSTM, XGBoost, and 1D-CNN). These models are implemented and compared in terms of computational complexity and prediction accuracy. It was found that under all sky conditions, the inclusion of spectral irradiance data improved forecasting performance compared to only using broadband irradiance. A ramp regime classification algorithm is then described, which enables the training and testing specialized ramp regime forecasting sub-models. These specialized sub-models were found to yield even greater forecasting accuracy within their respective ramp regimes, compared with the all-sky models. Further optimization and ensembling of the presented solar forecasting models is recommended for future work.

The description of a novel device to measure the spectral direct normal irradiance is presented. The solar spectral irradiance meter (SSIM) was designed at the University of Ottawa as a cost-effective alternative to a prohibitively expensive field spectroradiometer (FSR). The latter measures highly-varying and location-dependent solar spectrum, which is essential for accurate characterization of a concentrating photovoltaic system’s performance. The SSIM measures solar spectral irradiance in several narrow wavelength bands with a combination of photodiodes with integrated interference filters. This device performs spectral measurements at a fraction of the cost of a FSR, but additional post-processing is required to deduce the solar spectrum. The model was developed to take the SSIM’s inputs and reconstruct the solar spectrum in 280–4000 nm range. It resolves major atmospheric processes, such as air mass changes, Rayleigh scattering, aerosol extinction, ozone and water vapour absorptions. The SSIM was installed at the University of Ottawa’s CPV testing facility in September, 2013. The device gathered six months of data from October, 2013 to March, 2014. The mean difference between the SSIM and the Eppley pyrheliometer was within ±1.5% for cloudless periods in October, 2013. However, interference filter degradation and condensation negatively affected the performance of the SSIM. Future design changes will improve the longterm reliability of the next generation SSIMs.

Measurement uncertainty is an indication of the quality of a given measurement and ultimately translates into the confidence with which a decision can be made. In the context of PV, measurement uncertainties propagate into energy yield uncertainty, which in turn culminates into financial risk associated with an investment. This risk increases the cost of a PV installation. The aim of this thesis is to contribute towards the reduction of PV related measurement uncertainties. This is done in two ways. One is via developing and utilising more comprehensive methodologies for uncertainty propagation of complex measurands. The other is via more detailed estimates of the uncertainty contributors. In particular, the areas addressed in this thesis are the uncertainty estimation of the temperature coefficient measurements of modules; the uncertainty estimation of energy rating and module performance ratio measurements; and the uncertainties due to spectral effects on measurements performed with a flash solar simulator. The reported deviation in measurements of the temperature coefficients of P_MAX of modules is in the order of ±10% to ±15%. This is larger than the difference in the temperature coefficients of modules of the same type. The first step to improving the deviation between measurements is to estimate the uncertainty in a robust way. It was identified that there was no accepted approach of doing this. These measurements are strongly correlated, which complicates the uncertainty estimates. For the sake of simplicity, previously correlations have been avoided and conservative estimates used instead. In this work, uncertainties in both temperature and power and their correlations are estimated and propagated into the overall temperature coefficient uncertainty. Furthermore, temperature coefficients were calculated via weighing the measurements with their associated uncertainties. This was done for five different measurement setups that represent the majority of setups used worldwide. The approach was validated with measurement intercomparison of two modules measured on all systems. The approach reduced the overall uncertainty by half compared to the previous conservative estimates. It was demonstrated that uncertainties as low as 3% are achievable. The improved uncertainty estimates enabled the identification of a systematic effect due to a class B spectrum. This work culminated in the lowest reported measurement deviation of ±3.2% for module P_MAXtemperature coefficient measurements that was within the stated measurement uncertainties. The clear benefit of accounting for correlations was extended to measurements at different irradiance conditions and into the calculation of module performance ratio and energy rating. This was done via defining all the correlations between measurements and then propagating them with Monte Carlo simulations. The simulations are done with samples of a multivariate normal distribution with a variance-covariance matrix that corresponds to the estimated measurement correlations. It is demonstrated that both the energy rating and module performance ratio uncertainties strongly depend on the correlation estimates and that they cannot be conservatively overestimated. The module performance ratio uncertainty can be significantly lower than the measurement uncertainty at STC. This is because of the additional knowledge encoded into the selection of the underlying model used for calculating the energy rating. Therefore, the significance of the choice of model in the upcoming standard has been highlighted. It was confirmed that both bilinear interpolation and the proposed climatic datasets could be used for energy rating, but there are some areas that may need further investigation. An alternative way of improving uncertainty estimates and in turn reducing the associated uncertainty is via a more detailed characterisation of the uncertainty sources. A key uncertainty source is due to spectral effects in flash solar simulators. To better quantify this source, a complementary device was built to monitor the spectrum. The device is based on a matrix of photodiodes with commercially available interference filters situated on top and custom designed data acquisition electronics. This device is used in conjunction with the spectroradiometer to estimate the effects of flash-variation on the spectrum, the spectral temporal stability of the flash and spectral uniformity of the simulator and the attenuation masks used for altering the irradiance levels. It was demonstrated that the spectrum changes significantly during the flash and between flashes. While this effect is partially corrected for via the monitoring cell, it introduces additional uncertainty for non c-Si modules. This uncertainty is minimised by changes in the operational procedures. The spectral non-uniformity of the attenuation masks was shown to be significant, i.e. as large as 4%, in the NIR, prompting further investigation of the additional uncertainty for non c-Si modules. In this work, the methodology of estimating and propagating correlations in PV related measurements and the benefits of doing so are demonstrated. It is also highlighted that the uncertainty due to spectral effects goes beyond the uncertainty of spectroradiometer measurements. Finally, it is shown how they can be estimated with a complementary spectral monitor.

L’irradiance spectrale solaire (SSI) dans la bande ultraviolette est un paramètre-clé pour la spécification de la moyenne et la haute atmosphère terrestre. Elle est requise dans de nombreuses applications en météorologie de l’espace, et aussi pour l’étude du climat. Or les observations souffrent de plusieurs défauts : manque de couverture spectrale et temporelle permanente, dégradation des capteurs, désaccords entre les instruments, etc. Plusieurs modèles de reconstruction de la SSI ont été développés pour pallier à ces difficultés. Chacun souffre de défauts, et la reconstruction du spectre en-dessous de 120nm est un réel défi. C’est dans ce contexte que nous avons développé un modèle empirique, qui recourt au champ magnétique photosphérique pour reconstruire les variations du spectre solaire. Ce modèle décompose les magnétogrammes solaires en différentes structures qui sont classées à partir de leur aire (et non sur la base de leur intensité, comme dans la plupart des autres modèles). La signature spectrale de ces structures est déduite des observations, et non pas imposée par des modèles de l’atmosphère solaire. La qualité de la reconstruction s’avère être comparable à celle d’autres modèles. Parmi les principaux résultats, relevons que deux classes seulement de structures solaires suffisent à reproduire correctement la variabilité spectrale solaire. En outre, seule une faible résolution radiale suffit pour reproduire les variations de centre-bord. Enfin, nous montrons que l’amélioration apportée par la décomposition du modèle en deux constantes de temps peut être attribuée à l’effet des raies optiquement minces. / The spectrally-resolved radiative output of the Sun (SSI) in the UV band, i.e. at wavelengths below 300 nm, is a key quantity for specifying the state of the middle and upper terrestrial atmosphere. This quantity is required in numerous space weather applications, and also for climate studies. Unfortunately, SSI observations suffer from several problems : they have numerous spectral and temporal gaps, instruments are prone to degradation and often disagree, etc. This has stimulated the development of various types of SSI models. Proxy-based models suffer from lack of the physical interpretation and are as good as the proxies are. Semi-empirical models do not perform well below 300 nm, where the local thermodynamic equilibrium approximation does not hold anymore. We have developed an empirical model, which assumes that variations in the SSI are driven by solar surface magnetic flux. This model proceeds by segmenting solar magnetograms into different structures. In contrast to existing models, these features are classified by their area (and not their intensity), and their spectral signatures are derived from the observations (and not from models). The quality of the reconstruction is comparable to that of other models. More importantly, we find that two classes only of solar features are required to properly reproduce the spectral variability. Furthermore, we find that a coarse radial resolution suffices to account for geometrical line-of-sight effects. Finally, we show how the performance of the model on different time-scales is related to the optical thickness of the emission lines.

The present work proposes methods to calculate street-level exposures to solar radiation. The methods comprise a combination of different software algorithms, online databases and real-time standard measurements of solar radiation. Firstly, the use of the free access image database “Google Street View” to reconstruct urban geometries is illustrated. Google Street View represents an enormous source of information readily available for its general use in the field of urban atmospheric studies. With the aid of existing software packages, it was possible to reconstruct urban geometries as projected fisheye images of the canyon upper-hemispheric view, and to model total-shortwave solar irradiance within an urban canyon. The models allowed the calculation of relative street-canyon irradiance as a fraction of that received under a full-sky view, depending on the visibility of the solar disc and the reduced sky view factor. The combined use of the ideal models with real-time data allows for the calculation of street-canyon irradiance under any cloud conditions. Validation of these techniques was obtained by comparing the calculations against in situ measurements of irradiance from a local street canyon. The existing software, however, does not allow the calculation of spectral irradiance, required for inferring, for example, the biological effects of solar radiation. The use of spectral radiative transfer software was explored to provide spectral irradiance, but commonly available models do not include the effects of horizon obstructions. The approach presented here followed the same general guidelines used to calculate total-shortwave irradiance. The spectral models required a spectral partitioning of global irradiance into direct and diffuse components, allowing the independent analysis of horizon obstruction effects on these components at each wavelength. To partition global irradiance, two equations were developed for the calculation of the diffuse-to-global irradiance ratio (DGR) under cloudless conditions: one based on simplified radiative transfer theory, and an empirical fit for local conditions. Afterwards, the effects of horizon obstructions were evaluated in combination with real-time measurements of unobstructed global spectral irradiance. A set of simulated obstructions were used to validate the models. Finally, it was observed that neglecting the anisotropic distribution of the diffuse component of solar radiation in these simple models could produce large uncertainties in some situations. A practical solution for including the anisotropy of diffuse radiation was proposed, requiring images from an unobstructed digital sky camera. The combination of tools described here will allow calculation of total and spectral global irradiance upon a flat horizontal surface whatever the local field of view. This is possible at any geographical location were the urban geometries can be described, either by manually obtaining digital photographs, or through the Google Street View database, and where there is a reasonably local standard measurement of radiation.