Investigation of quantum dot luminescent solar concentrator single, double and triple structures: A ray tracing simulation study

Quantum dot based luminescent solar concentrators (QDLSCs) are a special class of transparent photovoltaics (TPV), especially suited for building integrated photovoltaics (BIPV). Photons are absorbed by luminescent species in a waveguide and emitted at a red-shifted wavelength. Due to total internal reflection, these photons are absorbed by the solar cells attached to the sides. Successful deployment requires high conversion efficiency and high transparency, which are contradictory requirements. We have performed Monte-Carlo ray tracing simulations to investigate single, double, and triple QDLSCs and have assessed their optical and electrical performance. To this end, eight different semiconductor quantum dot materials have been used with various absorption and emission properties, and Stokes’ shift. Device efficiency is analyzed for different average visible transmission (AVT) values, thus considering the human photopic response. The range of luminescent quantum efficiencies (30%–70%) leads to maximum efficiency of 2% for a single QDLSC, 2.4% for a double, and 2.7% for a triple structure, at high transparency and good color rendering index. Further improvements are possible towards 5% at high transparency with near-unity quantum efficiencies

Організаційний капітал: сучасний стан та вплив на соціально-економічний розвиток і якість життя населення регіонів України

На основі розрахунку інтегральних індексів дано оцінку організаційного капіталу регіонів України. Проведено групування регіонів за рівнем розвитку організаційного капіталу. Здійснена оцінка впливу організаційного капіталу на соціально-економічний розвиток та якість життя населення регіонів, яка виявила досить високий рівень цього впливу.Estimation of organizational capital of regions of Ukraine on the basis of computation of integral indexes of organizational capital of regions is carried out. The groupment of regions of Ukraine after the level of development of organizational capital is conducted. Estimation of influencing of organizational capital on socio-economic development and life standards for people of regions is carried out, and it exposes the enough high level of this influencing

Estimation of most optimal azimuthal angles for maximum PV solar efficiency using multivariate adaptive regression splines (MARS)

The aim of this study was to build a regression model of solar irradiation in the Kulluk region of Turkey by using the multivariate adaptive regression splines (MARS) technique. Using the well-known data mining algorithm, MARS, this study has explored a convenient prediction model for continuous response variables, i.e., average daily energy production from the given system (Ed), average monthly energy production from given system (Em), average daily sum of global irradiation per square meter (Hd) and average annual sum of global irradiation per square meter (Hm). Four continuous estimators are included to estimate Ed, Em, Hd and Hm: Estimated losses due to temperature and low irradiance (ESLOTEM), estimated loss due to angular reflection effect (ESLOANGREF), combined photovoltaic system loss (COMPVLOSS) and rated power of the photovoltaic system (PPVS). Four prediction models as constructed by implementing the MARS algorithm, have been obtained by applying the smallest generalized cross-validation (GCV) criterion where the means of penalty are defined as 1 and the backward pruning method for the package 'earth' of R software is used. As a result, it can be suggested that the procedure of the MARS algorithm, which achieves the greatest predictive accuracy of 100% or nearly 100%, permits researchers to obtain some remarkable hints for ascertaining predictors that affect solar irradiation parameters. The coefficient of determination denoted as R2 was estimated at the highest predictive accuracy to be nearly 1 for Ed, Em, Hd and Hm while the GCV values were found to be 0.000009, 0.018908, 0.000013 and 0.019021, respectively. The estimated results indicate that four MARS models with the first degree interaction effect have the best predictive performances for verification with the lowest GCV value

Estimation of most optimal azimuthal angles for maximum PV solar efficiency using multivariate adaptive regression splines (MARS)

The aim of this study was to build a regression model of solar irradiation in the Kulluk region of Turkey by using the multivariate adaptive regression splines (MARS) technique. Using the well-known data mining algorithm, MARS, this study has explored a convenient prediction model for continuous response variables, i.e., average daily energy production from the given system (Ed), average monthly energy production from given system (Em), average daily sum of global irradiation per square meter (Hd) and average annual sum of global irradiation per square meter (Hm). Four continuous estimators are included to estimate Ed, Em, Hd and Hm: Estimated losses due to temperature and low irradiance (ESLOTEM), estimated loss due to angular reflection effect (ESLOANGREF), combined photovoltaic system loss (COMPVLOSS) and rated power of the photovoltaic system (PPVS). Four prediction models as constructed by implementing the MARS algorithm, have been obtained by applying the smallest generalized cross-validation (GCV) criterion where the means of penalty are defined as 1 and the backward pruning method for the package "earth" of R software is used. As a result, it can be suggested that the procedure of the MARS algorithm, which achieves the greatest predictive accuracy of 100% or nearly 100%, permits researchers to obtain some remarkable hints for ascertaining predictors that affect solar irradiation parameters. The coefficient of determination denoted as R2 was estimated at the highest predictive accuracy to be nearly 1 for Ed, Em, Hd and Hm while the GCV values were found to be 0.000009, 0.018908, 0.000013 and 0.019021, respectively. The estimated results indicate that four MARS models with the first degree interaction effect have the best predictive performances for verification with the lowest GCV value

Analytical models for growth by metal organic vapor phase epitaxy. I.Isothermal models

For a proper description of growth by metal organic vapour phase epitaxy the three-dimensional Navier-Stokes partial differential equations need to be solved which govern the following series of processes: (i) transport by diffusion and flow through the gas phase, (ii) reactions which take place in this gas phase, (iii) reactions which take place at the surface. The authors are at first interested in the medium- and higher-temperature regions, which cover the growth determined by diffusion through the gas phase (medium temperature) and the growth that is determined by the desorption of growth species (higher temperature). Using a number of well justified assumptions one can reduce the problem to a two-dimensional one. For the diffusion-limited region (i.e. medium-temperature region) the effect of different flow profiles (plug flow, parabolic flow, linear increasing velocity and combination of plug and linear profile) on the growth rate has been studied under isothermal conditions. It was found that all profiles yield the same growth rate within a few per cent, so that it suffices to use the simple plug flow profile in growth rate calculations. It is also shown that axial diffusion is an important effect only at the end of long reactors. Finally a model is derived in which surface reaction kinetics is combined with the diffusion-limited model for the isothermal case

Переклад у концепції національної літератури Івана Франка

Abstract: This paper presents a working model to estimate the solar photovoltaic potential using high- resolution LiDAR data and Geographic Information Systems. This bottom-up approach method has been selected to arrive at the potential as this gives a better estimate than a top-down approach. The novelty of the study lies in estimating the potential at high resolution and classifying the rooftop as suitable or not for solar photovoltaic installations based on factors like irradiation, slope and orientation. The city of Apeldoorn in the Netherlands has been selected as the study area. The model was able to successfully locate suitable sites for photovoltaic installations at rooftop level. In addition, the area feasible for the installations and the potential power output has also been calculated. We conclude that the city has a potential of 319 MWp capacity, which would yield 283.9 GWh/yr in relation to the 304 GWh/yr consumption from residential buildings in the area