scholarly journals Evaluation of Optimal Occasional Tilt on Photovoltaic Power Plant Energy Efficiency and Land Use Requirements, Iran

2021 ◽  
Vol 13 (18) ◽  
pp. 10213
Author(s):  
Amirhossein Fathi ◽  
Masoomeh Bararzadeh Ledari ◽  
Yadollah Saboohi
Keyword(s):  
Power Plant ◽  
Solar Radiation ◽  
Solar Energy ◽  
Orientation Angle ◽  
Optimum Operating ◽  
Time Interval ◽  
Time Intervals ◽  
Optimum Time ◽  
Equal Time ◽  
Geographical Regions

The paper studies the optimum panel horizontal orientation angle toward the Sun and the optimum time interval of the panel’s movement. The optimum time intervals or panel movement can change the rate of input energy to the panel surface in Iran. For this purpose, a neural network has been trained to estimate the intensity of solar radiation in Iran. After model validation, the intensity of solar radiation has been estimated by selecting adequate geographical regions. Based on the intensity of sunlight, Iran has been divided into ten regions. In these regions, 40 cities have been randomly selected to study the effect of the panel’s angle variations within appropriate time intervals, as well as equal time intervals. The results show that the choice of the mounting system with the possibility of five angles’ implementation can increase the amount of solar energy between 3.9% and 7.4%. Compared to this number of angles at the equal time intervals, the amount of incoming solar energy has increased by 3% to 7%. In the first and second cases, the area of the power plant increases by about 12% to 24% compared to the yearly optimum tilt angle. Moreover, the amount of radiation incoming to the panel with the optimum operating angle is in alignment with the results of PVsyst software.

scholarly journals Improving the Efficiency of Solar Power Plants

2020 ◽  
Vol 30 (3) ◽  
pp. 480-497
Author(s):  
Dmitriy S. Strebkov ◽  
Yuriy Kh. Shogenov ◽  
Nikolay Yu. Bobovnikov
Keyword(s):  
Power Plant ◽  
Solar Radiation ◽  
Solar Energy ◽  
Power Plants ◽  
Solar Power ◽  
Horizontal Surface ◽  
Solar Power Plant ◽  
Utilization Factor ◽  
Working Surface ◽  
Solar Power Plants

Introduction. An urgent scientific problem is to increase the efficiency of using solar energy in solar power plants (SES). The purpose of the article is to study methods for increasing the efficiency of solar power plants. Materials and Methods. Solar power plants based on modules with a two-sided working surface are considered. Most modern solar power plants use solar modules. The reflection of solar radiation from the earth’s surface provides an increase in the production of electrical energy by 20% compared with modules with a working surface on one side. It is possible to increase the efficiency of using solar energy by increasing the annual production of electric energy through the creation of equal conditions for the use of solar energy by the front and back surfaces of bilateral solar modules. Results. The article presents a solar power plant on a horizontal surface with a vertical arrangement of bilateral solar modules, a solar power station with a deviation of bilateral solar modules from a vertical position, and a solar power plant on the southern slope of the hill with an angle β of the slope to the horizon. The formulas for calculating the sizes of the solar energy reflectors in the meridian direction, the width of the solar energy reflectors, and the angle of inclination of the solar modules to the horizontal surface are given. The results of computer simulation of the parameters of a solar power plant operating in the vicinity of Luxor (Egypt) are presented. Discussion and Conclusion. It is shown that the power generation within the power range of 1 kW takes a peak value for vertically oriented two-sided solar modules with horizontal reflectors of sunlight at the installed capacity utilization factor of 0.45. At the same time, when the solar radiation becomes parallel to the plane of vertical solar modules, there is a decrease in the output of electricity. The proposed design allows equalizing and increasing the output of electricity during the maximum period of solar radiation. Vertically oriented modules are reliable and easy to use while saving space between modules.

Estimation of Methods of Calculation of Values of Total Solar Radiation for Different Time Intervals

2021 ◽  
pp. 89-98
Author(s):  
Yuri Y. Tkachenko ◽  
Vladimir V. Latun ◽  
Valeriy I. Denisov
Keyword(s):  
Solar Radiation ◽  
Calculated Data ◽  
Time Interval ◽  
Total Solar Radiation ◽  
Total Radiation ◽  
Calculation Methods ◽  
Time Intervals ◽  
High Dust Content ◽  
Former Ussr ◽  
Small Cloud

The article presents the results of evaluation of a number of methods for calculating total, scattered and direct radiation. The methods were tested on actinometric data of eight stations of the former USSR, located in different climatic and latitudinal zones, in order to clarify the spatial boundaries of their application and the time interval for which it is possible to carry out calculations with an error of not more than 10 %. It is established that the accuracy of calculations is influenced by the location of the station in relation to the seas and lakes. In addition, a number of methods do not take into account the tier and shape of the cloud, so at the same amount of cloud observed different amounts of total radiation, which in turn leads to errors in the calculation of the amounts of radiation. For stations with high atmospheric transparency and low air humidity, the calculation methods provide understated data compared to full-scale ones. For stations with high dust content of the surface layer of the atmosphere, the calculated data are overstated. For marine and lake stations, overestimation of the calculated data is caused by increased humidity throughout the year and as a result, even with a small cloud cover, incoming solar radiation is significantly weakened by water vapor. The considered calculation methods can be used to calculate monthly amounts of total radiation with an accuracy of 10-12 %. Calculation for shorter time intervals leads to an increase in calculation errors. Using the method of calculating the total radiation components gives an error in the calculation of monthly amounts from 10 to 30 %, depending on the latitude. Performing calculations using this method for time intervals less than a month leads to a sharp increase in the size of errors.

Interval between sequential glufosinate applications influences weed control in cotton

2020 ◽  
Vol 34 (4) ◽  
pp. 528-533 ◽  
Author(s):  
Taylor M. Randell ◽  
Lavesta C. Hand ◽  
Jenna C. Vance ◽  
A. Stanley Culpepper
Keyword(s):  
Palmer Amaranth ◽  
Time Interval ◽  
Cotton Yield ◽  
Time Intervals ◽  
Optimum Time ◽  
Variable Control ◽  
Control Research ◽  
Annual Grasses ◽  
Production Areas ◽  
Large Crabgrass

AbstractDicamba and 2,4-D systems control many problematic weeds; however, drift to susceptible crops can be a concern in diverse production areas. Glufosinate-based systems are an alternative, but current recommended rates of glufosinate can result in variable control. Research was conducted in 2017 and 2018 to investigate the optimum time interval between sequential glufosinate applications and determine if the addition of glyphosate with glufosinate is beneficial for controlling Palmer amaranth and annual grasses in cotton. The interval between sequential applications (1, 3, 5, 7, 10, or 14 d or no second spray) was the whole plot and herbicide option (glufosinate or glufosinate plus glyphosate) was the subplot. Combined over herbicides, Palmer amaranth 15- to 20-cm tall (at four locations) was controlled 98% to 99% with sequential intervals of 1 to 7 d compared with 70% to 88% with intervals of 10 or 14 d. Lowest biomass weight and population densities were noted with 1- to 7-d intervals. Large crabgrass 15- to 20-cm tall (at five locations) was controlled 93% to 98% with glufosinate applications 3- to 7-d apart as compared with 76% to 81% with applications 10- to 14-d apart. Lowest biomass weights were observed with 1- to 7-d intervals. When glufosinate controlled grass less than 93%, adding glyphosate was beneficial. Neither interval between sequential applications nor herbicide option influenced cotton yield. Shorter time intervals between sequential application and including glyphosate can improve the effectiveness of a glufosinate-based system in managing Palmer amaranth and large crabgrass.

scholarly journals Optimum time interval and frequency of glyphosate application for weed control in plantain (Musa sp.)

1969 ◽  
Vol 72 (2) ◽  
pp. 297-300
Author(s):  
Lii-Chyuan Liu ◽  
José Rodríguez-García
Keyword(s):  
Weed Control ◽  
Field Trial ◽  
Musa Acuminata ◽  
Time Interval ◽  
Time Intervals ◽  
Optimum Time ◽  
Yield Data ◽  
Musa Sp ◽  
Reduced Time

A field trial was conducted at the Corozal Substation, to determine the effect of two time intervals (6 and 12 weeks) and four frequencies (once, twice, three and four times) of glyphosate application on weed control, phytotoxicity and yield of plantain (Musa acuminata x M. balbisiana AAB) throughout a planting cycle. The effectiveness of glyphosate at 1% increased with reduced time interval and increased frequency of application. Plantain injury was more pronounced with increased time interval and increased number of applications. The maximum yields in terms of number and weight of fruits were obtained with three applications at a 6-week interval from planting onward. The lowest number and weight of fruits were obtained in the non-weeded check. On the basis of weed control, phytotoxicity and yield data, optimum time interval and frequency of glyphosate application during a planting-to-harvest cycle was three applications of glyphosate at 1% every 6 weeks.

METABOLIC STUDIES WITH 131I-LABELED THYROXINE. II.

1963 ◽  
Vol 44 (3) ◽  
pp. 475-480 ◽  
Author(s):  
R. Grinberg
Keyword(s):  
Spinal Cord ◽  
Central Nervous System ◽  
Nervous System ◽  
Optic Nerve ◽  
Pituitary Gland ◽  
Time Interval ◽  
Time Intervals ◽  
Pituitary Glands ◽  
The Central Nervous System ◽  
Tentative Explanation

ABSTRACT Radiologically thyroidectomized female Swiss mice were injected intraperitoneally with 131I-labeled thyroxine (T4*), and were studied at time intervals of 30 minutes and 4, 28, 48 and 72 hours after injection, 10 mice for each time interval. The organs of the central nervous system and the pituitary glands were chromatographed, and likewise serum from the same animal. The chromatographic studies revealed a compound with the same mobility as 131I-labeled triiodothyronine in the organs of the CNS and in the pituitary gland, but this compound was not present in the serum. In most of the chromatographic studies, the peaks for I, T4 and T3 coincided with those for the standards. In several instances, however, such an exact coincidence was lacking. A tentative explanation for the presence of T3* in the pituitary gland following the injection of T4* is a deiodinating system in the pituitary gland or else the capacity of the pituitary gland to concentrate T3* formed in other organs. The presence of T3* is apparently a characteristic of most of the CNS (brain, midbrain, medulla and spinal cord); but in the case of the optic nerve, the compound is not present under the conditions of this study.

scholarly journals Detrended Multiple Cross-Correlation Coefficient applied to solar radiation, air temperature and relative humidity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Andrea de Almeida Brito ◽  
Heráclio Alves de Araújo ◽  
Gilney Figueira Zebende
Keyword(s):  
Relative Humidity ◽  
Solar Radiation ◽  
Solar Energy ◽  
Correlation Coefficient ◽  
Air Temperature ◽  
Cross Correlation ◽  
Global Solar Radiation ◽  
Meteorological Variables ◽  
Hourly Data ◽  
Cross Correlations

AbstractDue to the importance of generating energy sustainably, with the Sun being a large solar power plant for the Earth, we study the cross-correlations between the main meteorological variables (global solar radiation, air temperature, and relative air humidity) from a global cross-correlation perspective to efficiently capture solar energy. This is done initially between pairs of these variables, with the Detrended Cross-Correlation Coefficient, ρDCCA, and subsequently with the recently developed Multiple Detrended Cross-Correlation Coefficient, $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2. We use the hourly data from three meteorological stations of the Brazilian Institute of Meteorology located in the state of Bahia (Brazil). Initially, with the original data, we set up a color map for each variable to show the time dynamics. After, ρDCCA was calculated, thus obtaining a positive value between the global solar radiation and air temperature, and a negative value between the global solar radiation and air relative humidity, for all time scales. Finally, for the first time, was applied $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}$$DMCx2 to analyze cross-correlations between three meteorological variables at the same time. On taking the global radiation as the dependent variable, and assuming that $${\boldsymbol{DM}}{{\boldsymbol{C}}}_{{\bf{x}}}^{{\bf{2}}}={\bf{1}}$$DMCx2=1 (which varies from 0 to 1) is the ideal value for the capture of solar energy, our analysis finds some patterns (differences) involving these meteorological stations with a high intensity of annual solar radiation.

scholarly journals Neural Network Approach for Global Solar Irradiance Prediction at Extremely Short-Time-Intervals Using Particle Swarm Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1213
Author(s):  
Ahmed Aljanad ◽  
Nadia M. L. Tan ◽  
Vassilios G. Agelidis ◽  
Hussain Shareef
Keyword(s):  
Neural Networks ◽  
Particle Swarm Optimization ◽  
Solar Irradiance ◽  
Particle Swarm ◽  
Time Interval ◽  
Time Intervals ◽  
Swarm Optimization ◽  
Backpropagation Neural Networks ◽  
Proposed Model ◽  
Short Time

Hourly global solar irradiance (GSR) data are required for sizing, planning, and modeling of solar photovoltaic farms. However, operating and controlling such farms exposed to varying environmental conditions, such as fast passing clouds, necessitates GSR data to be available for very short time intervals. Classical backpropagation neural networks do not perform satisfactorily when predicting parameters within short intervals. This paper proposes a hybrid backpropagation neural networks based on particle swarm optimization. The particle swarm algorithm is used as an optimization algorithm within the backpropagation neural networks to optimize the number of hidden layers and neurons used and its learning rate. The proposed model can be used as a reliable model in predicting changes in the solar irradiance during short time interval in tropical regions such as Malaysia and other regions. Actual global solar irradiance data of 5-s and 1-min intervals, recorded by weather stations, are applied to train and test the proposed algorithm. Moreover, to ensure the adaptability and robustness of the proposed technique, two different cases are evaluated using 1-day and 3-days profiles, for two different time intervals of 1-min and 5-s each. A set of statistical error indices have been introduced to evaluate the performance of the proposed algorithm. From the results obtained, the 3-days profile’s performance evaluation of the BPNN-PSO are 1.7078 of RMSE, 0.7537 of MAE, 0.0292 of MSE, and 31.4348 of MAPE (%), at 5-s time interval, where the obtained results of 1-min interval are 0.6566 of RMSE, 0.2754 of MAE, 0.0043 of MSE, and 1.4732 of MAPE (%). The results revealed that proposed model outperformed the standalone backpropagation neural networks method in predicting global solar irradiance values for extremely short-time intervals. In addition to that, the proposed model exhibited high level of predictability compared to other existing models.

Real-World Experience with Artificial Intelligence-Based Triage in Transferred Large Vessel Occlusion Stroke Patients

2021 ◽  
pp. 1-6
Author(s):  
Jacob R. Morey ◽  
Xiangnan Zhang ◽  
Kurt A. Yaeger ◽  
Emily Fiano ◽  
Naoum Fares Marayati ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Clinical Outcomes ◽  
Warning System ◽  
Large Vessel ◽  
Time Interval ◽  
Large Vessel Occlusion ◽  
Time Intervals ◽  
Vessel Occlusion ◽  
Left Behind ◽  
Stroke Center

<b><i>Background and Purpose:</i></b> Randomized controlled trials have demonstrated the importance of time to endovascular therapy (EVT) in clinical outcomes in large vessel occlusion (LVO) acute ischemic stroke. Delays to treatment are particularly prevalent when patients require a transfer from hospitals without EVT capability onsite. A computer-aided triage system, Viz LVO, has the potential to streamline workflows. This platform includes an image viewer, a communication system, and an artificial intelligence (AI) algorithm that automatically identifies suspected LVO strokes on CTA imaging and rapidly triggers alerts. We hypothesize that the Viz application will decrease time-to-treatment, leading to improved clinical outcomes. <b><i>Methods:</i></b> A retrospective analysis of a prospectively maintained database was assessed for patients who presented to a stroke center currently utilizing Viz LVO and underwent EVT following transfer for LVO stroke between July 2018 and March 2020. Time intervals and clinical outcomes were compared for 55 patients divided into pre- and post-Viz cohorts. <b><i>Results:</i></b> The median initial door-to-neuroendovascular team (NT) notification time interval was significantly faster (25.0 min [IQR = 12.0] vs. 40.0 min [IQR = 61.0]; <i>p</i> = 0.01) with less variation (<i>p</i> &#x3c; 0.05) following Viz LVO implementation. The median initial door-to-skin puncture time interval was 25 min shorter in the post-Viz cohort, although this was not statistically significant (<i>p</i> = 0.15). <b><i>Conclusions:</i></b> Preliminary results have shown that Viz LVO implementation is associated with earlier, more consistent NT notification times. This application can serve as an early warning system and a failsafe to ensure that no LVO is left behind.

scholarly journals Optimal Perturbations of an Oceanic Vortex Lens

Fluids ◽  
2018 ◽  
Vol 3 (3) ◽  
pp. 63 ◽  
Author(s):  
Thomas Meunier ◽  
Claire Ménesguen ◽  
Xavier Carton ◽  
Sylvie Le Gentil ◽  
Richard Schopp
Keyword(s):  
Normal Mode ◽  
Growth Rates ◽  
Time Interval ◽  
Time Intervals ◽  
Horizontal Structure ◽  
Azimuthal Wave ◽  
Wave Numbers ◽  
Non Linear ◽  
Long Time ◽  
Short Time

The stability properties of a vortex lens are studied in the quasi geostrophic (QG) framework using the generalized stability theory. Optimal perturbations are obtained using a tangent linear QG model and its adjoint. Their fine-scale spatial structures are studied in details. Growth rates of optimal perturbations are shown to be extremely sensitive to the time interval of optimization: The most unstable perturbations are found for time intervals of about 3 days, while the growth rates continuously decrease towards the most unstable normal mode, which is reached after about 170 days. The horizontal structure of the optimal perturbations consists of an intense counter-shear spiralling. It is also extremely sensitive to time interval: for short time intervals, the optimal perturbations are made of a broad spectrum of high azimuthal wave numbers. As the time interval increases, only low azimuthal wave numbers are found. The vertical structures of optimal perturbations exhibit strong layering associated with high vertical wave numbers whatever the time interval. However, the latter parameter plays an important role in the width of the vertical spectrum of the perturbation: short time interval perturbations have a narrow vertical spectrum while long time interval perturbations show a broad range of vertical scales. Optimal perturbations were set as initial perturbations of the vortex lens in a fully non linear QG model. It appears that for short time intervals, the perturbations decay after an initial transient growth, while for longer time intervals, the optimal perturbation keeps on growing, quickly leading to a non-linear regime or exciting lower azimuthal modes, consistent with normal mode instability. Very long time intervals simply behave like the most unstable normal mode. The possible impact of optimal perturbations on layering is also discussed.

Sign in / Sign up

Export Citation Format

Share Document