Solar irradiance

Summary

Solar irradiance is the power per unit area (surface power density) received from the Sun in the form of electromagnetic radiation in the wavelength range of the measuring instrument. Solar irradiance is measured in watts per square metre (W/m2) in SI units. Solar irradiance is often integrated over a given time period in order to report the radiant energy emitted into the surrounding environment (joule per square metre, J/m2) during that time period. This integrated solar irradiance is called solar irradiation, solar exposure, solar insolation, or insolation. Irradiance may be measured in space or at the Earth's surface after atmospheric absorption and scattering. Irradiance in space is a function of distance from the Sun, the solar cycle, and cross-cycle changes. Irradiance on the Earth's surface additionally depends on the tilt of the measuring surface, the height of the Sun above the horizon, and atmospheric conditions. Solar irradiance affects plant metabolism and animal be

Official source

https://en.wikipedia.org/wiki/Solar_irradiance

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Prediction of Photocurrent in Bifacial Photovoltaic Systems

Arttu Matias Tuomiranta

Motivated by the shift of the photovoltaic (PV) industry towards bifacial solar modules, desert markets, and ever narrower profit margins, this thesis study is aimed at improving the estimation accuracy of the output of bifacial PV systems that are potentially exposed to soiling. The scope is limited to the estimation of photocurrent, the performance parameter that is the most strongly affected by bifaciality and soiling. The thesis consists of three parts with the following topics: ground surface reflectance, module soiling, and bifacial effective irradiance. As for the first topic, the thesis aims at providing tools for surface reflectance estimation in any use case. The model evaluation results that are based on a global database of reflectance measurements can be used to choose a reflectance model that is appropriate for the surface type of interest. On a global average, the results show that data-driven estimation reduces the mean absolute error of reflectance estimates by 20-40% compared to the literature values. The proposed geographically generalised parametrisations of reflectance models can be used to produce temporally variable reflectance estimates if measuring campaigns for local model calibration cannot be implemented. If they can, the thesis provides detailed guidelines for their optimal timing. The choice of the reflectance model can result in deviations of up to 2.5% in the energy yield estimated for a bifacial PV system. In the second part of the thesis, a new physical model for forecasting soiling losses is proposed. The model incorporates new methods e.g., to simulate dust deposition on tilted surfaces, to physically capture the impact of relative humidity on dust accumulation, and to estimate the hemispherical transmittance of dust for diffuse light sources. The model can be used based on the public data products of numerical weather prediction models without the need for soiling measurements. The model is validated against its alternatives and measurements made at a field experiment in the United Arab Emirates. The impact of the soiling loss model on yield estimation is found to be lower than that of the reflectance model, plus minus 1% at maximum considering usual weekly or biweekly cleaning intervals. Finally, the third part of the thesis proposes a new model for simulating the photocurrent of each solar cell of a bifacial PV power plant using a computationally efficient method. It comprises a new algorithmic design that makes it possible to make all the detailed geometric calculations once and move to the temporal domain only to estimate irradiance. The most important novelty of the proposed model is that it estimates the photocurrent contributions as a distribution of the different light sources. The model is validated against the measurements made in France and Italy. The results of the validation show that the model's current estimates are more accurate than those of the widely used "unlimited sheds" approach. The most important reasons for the better performance are the new model's capability to estimate the spatial variability of effective irradiance on the array surface and that of ground-incident irradiance around the system. As per the impact assessment, the new model was found to overestimate yield and underestimate electricity cost by 1% on average. The "unlimited sheds" approach, in turn, resulted in more variable bias. In the case of large arrays, the approach was found to overestimate yield by 4%.

EPFL2020

Evaluation of photosynthetic competency in time and space is critical for better estimates and models of oceanic primary productivity. This is especially true for areas where the lack of iron (Fe) limits phytoplankton productivity, such as the Southern Ocean. Assessment of photosynthetic competency on large scales remains challenging, but phytoplankton chlorophyll a fluorescence (ChlF) is a signal that holds promise in this respect as it is affected by, and consequently provides information about, the photosynthetic efficiency of the organism. A second process affecting the ChlF signal is heat dissipation of absorbed light energy, referred to as non-photochemical quenching (NPQ). NPQ is triggered when excess energy is absorbed, i.e. when more light is absorbed than can be used directly for photosynthetic carbon fixation. The effect of NPQ on the ChlF signal complicates its interpretation in terms of photosynthetic efficiency, and therefore most approaches relating ChlF parameters to photosynthetic efficiency seek to minimize the influence of NPQ by working under conditions of sub-saturating irradiance. Here, we propose that NPQ itself holds potential as an easily acquired optical signal indicative of phytoplankton physiological state with respect to Fe limitation. We present data from a research voyage to the Subantarctic Zone south of Australia. Incubation experiments confirmed that resident phytoplankton were Fe-limited, as the maximum quantum yield of primary photochemistry, F-v/F-m, measured with a fast repetition rate fluorometer (FRRf), increased significantly with Fe addition. The NPQ "capacity" of the phytoplankton also showed sensitivity to Fe addition, decreasing with increased Fe availability, confirming previous work. The fortuitous presence of a remnant warm-core eddy in the vicinity of the study area allowed comparison of fluorescence behaviour between two distinct water masses, with the colder water showing significantly lower F-v/F-m than the warmer eddy waters, suggesting a difference in Fe limitation status between the two water masses. Again, NPQ capacity measured with the FRRf mirrored the behaviour observed in F-v/F-m, decreasing as F-v/F-m increased in the warmer water mass. We also analysed the diel quenching of underway fluorescence measured with a standard fluorometer, such as is frequently used to monitor ambient chlorophyll a concentrations, and found a significant difference in behaviour between the two water masses. This difference was quantified by defining an NPQ parameter akin to the Stern-Volmer parameterization of NPQ, exploiting the fluorescence quenching induced by diel fluctuations in incident irradiance. We propose that monitoring of this novel NPQ parameter may enable assessment of phytoplankton physiological status (related to Fe availability) based on measurements made with standard fluorometers, as ubiquitously used on moorings, ships, floats and gliders.

2020

BIOPHYSICAL CONTROLS ON EVAPOTRANSPIRATION: NUMERICAL MODELS AND EXPERIMENTAL OBSERVATIONS

Federico Croci

Water and food are basics of human life, unfortunately climate changes and water pollution have reduced the amount of water available for human uses. In this context the study of the hydrologic cycle is becoming of growing importance in order to optimize the anthropogenic exploitation of water resource. Evapotranspiration is the term used to describe the part of the water cycle which removes liquid water from an area with vegetation into the atmosphere by the processes of both transpiration and evaporation. Evapotranspiration is an important part of the hydrologic cycle because it represents a considerable percentage of water losses in watersheds. This process is also one of the main consumers of solar energy at the Earth's surface. The estimation of evapotranspiration it is of great importance for agriculture and water resources management, for example, by knowing the rate of water loss from a region, farmers will be better placed to efficiently manage the irrigation strategies. The rate of evapotranspiration at any location on the Earth's surface is controlled by several factors such as energy availability, humidity gradient, wind speed immediately above the surface, water availability, type of vegetation, stomatal resistance and soil characteristics. The problem of estimating evapotranspiration has been widely studied. During the past several decades, different approaches have been proposed and many formulas are available in the literature to fulfill this task. The complexity of the phenomena and its great variability all over the world make difficult to find a universal and robust method for the evapotranspiration prediction and estimation. Evapotranspiration can be obtained by many estimation methods. Some of these methods need many weather parameters as inputs while others need fewer. Factors such as data availability, the intended use, and the time scale required by the problem must be considered when choosing the evapotranspiration calculation technique. The Penman-Monteith equation was derived from the classic Penman equation adding to the terms already considered in the Penman formulation (aerodynamic resistance and energy balance) the canopy resistance. This approach requires many meteorological data, such as maximum and minimum air temperatures, relative humidity, solar radiation, and wind speed. If some of these data are not available, alternative techniques have been developed to overcome this drawback. However, this estimations of meteorological data affect the quality of the result, alternatively, in such cases other simpler methods may be used. The Penman-Monteitu equation is assumed to be the most reliable because is based on physical principles and because it considers all the climatic factors, which affect evapotranspiration.

2013