Establishing a typical solar radiation year time series for the application of building integrated photovoltaic systems in Taiwan

2010 ◽  
Author(s):  
Kuo-Tsang Huang ◽  
Wen-Sheng Ou
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Photovoltaic Systems ◽  
Building Integrated Photovoltaic

scholarly journals Sizing stand-alone photovoltaic systems

2006 ◽  
Vol 2006 ◽  
pp. 1-8 ◽  
Author(s):  
A. Balouktsis ◽  
T. D. Karapantsios ◽  
A. Antoniadis ◽  
D. Paschaloudis ◽  
A. Bezergiannidou ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Actual Data ◽  
Photovoltaic Systems ◽  
Statistical Parameters ◽  
Radiation Data ◽  
Daily Average ◽  
Load Demand ◽  
Stochastic Time Series ◽  
Stochastic Time

A method of sizing stand-alone photovoltaic systems regarding the reliability to satisfy the load demand, economy of components, and discharge depth exploited by the batteries is presented in this work. Solar radiation data simulated by an appropriate stochastic time series model, and not actual measurements, are used in the sizing procedure. This offers two distinct advantages: (a) sizing can be performed even for locations where no actual data exist, (b) the influence of the variation of the statistical parameters of solar radiation in sizing can be examined. The method has been applied and tested for several representative locations all over Greece for which monthly daily average values of solar radiation are given byELOT(Hellenic Organization of Standardization).

scholarly journals The effects of daily meteorological perturbation on pregnancy outcome: follow-up of a cohort of young women undergoing IVF treatment

2019 ◽  
Vol 18 (1) ◽  
Author(s):  
Mingpeng Zhao ◽  
Haoyang Zhang ◽  
Tarah H. B. Waters ◽  
Jacqueline Pui Wah Chung ◽  
Tin Chiu Li ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Time Series Analysis ◽  
Subgroup Analysis ◽  
Seasonal Variations ◽  
Multiple Logistic Regression Analysis ◽  
Human Reproduction ◽  
Mixed Effect ◽  
Series Analysis ◽  
Patient Consent

Abstract Background Human reproduction follows a seasonal pattern with respect to spontaneous conception, a phenomenon wherein the effect of meteorological fluctuations might not be unique. However, the effect of seasonal variations on patients who underwent in vitro fertilization (IVF) treatment is unclear. We aimed to evaluate the effects of meteorological variation on the pregnancy rate in a cohort undergoing IVF treatment by performing multivariable analyses. Methods We conducted a cohort study in a sub-tropical region with prominent seasonal variations (2005–2016). Women aged < 35 years who were treated with a long ovarian stimulation protocol and underwent fresh embryo transfer (ER) were included. Data on gonadotropin administration (CYCL), oocyte retrieval (OR), ER, and pregnancy outcomes were prospectively recorded. For each patient, the daily average of meteorological data (temperature, humidity, sunlight duration, solar radiation) was recorded from the date of CYCL to ER. Multiple logistic regression analysis adjusted for age, fertilization method, year of the cycle, gonadotropin dose, and transferred embryo grade was performed to determine the relationship between the meteorological parameters and clinical pregnancy. Patients with one successful cycle and one failed cycle were subtracted for a case-control subgroup analysis through mixed effect logistics regressions. Time-series analysis of data in the epidemic level was conducted using the distributed lag linear and non-linear models (DLNMs). Results There were 1029 fresh cycles in 860 women (mean age 31.9 ± 2.0 years). Higher mean temperature from CYCL to OR (adjusted odds ratio [aOR] 1.04; 95% confidence interval [CI] 1.01–1.07, P = 0.01) increased the odds of pregnancy, while OR to ER did not show any statistical significance. Compared to that in winter, the odds of becoming pregnant were higher during higher temperature seasons, summer and autumn (aOR 1.47, 95%CI 0.97–2.23, P = 0.07 (marginally significant) and aOR 1.73, 95%CI 1.12–2.68, P = 0.02, respectively). Humidity, sunlight duration, and solar radiation had no effect on the outcome. The subgroup analysis confirmed this finding. The time-series analysis revealed a positive association between temperature and relative risk for pregnancy. Conclusions In IVF treatment, the ambient temperature variation alters the pregnancy rates; this aspect must be considered when obtaining patient consent for assisted conception.

Dynamic Modeling of Solar Radiation Disturbances Based on a Biomimetic Cloud Shading Model

2018 ◽  
Vol 140 (2) ◽  
Author(s):  
Jesús García ◽  
Iván Portnoy ◽  
Ricardo Vasquez Padilla ◽  
Marco E. Sanjuan
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Control Strategies ◽  
Ground Level ◽  
Direct Solar Radiation ◽  
Complex Phenomenon ◽  
Two Dimensional ◽  
Multi Objective Optimization ◽  
Tuning Parameters ◽  
Radiation Time

Variation in direct solar radiation is one of the main disturbances that any solar system must handle to maintain efficiency at acceptable levels. As known, solar radiation profiles change due to earth's movements. Even though this change is not manipulable, its behavior is predictable. However, at ground level, direct solar radiation mainly varies due to the effect of clouds, which is a complex phenomenon not easily predictable. In this paper, dynamic solar radiation time series in a two-dimensional (2D) spatial domain are obtained using a biomimetic cloud-shading model. The model is tuned and compared against available measurement time series. The procedure uses an objective function based on statistical indexes that allow extracting the most important characteristics of an actual set of curves. Then, a multi-objective optimization algorithm finds the tuning parameters of the model that better fit data. The results showed that it is possible to obtain responses similar to real direct solar radiation transients using the biomimetic model, which is useful for other studies such as testing control strategies in solar thermal plants.

Application of transparent dye-sensitized solar cells to building integrated photovoltaic systems

2011 ◽  
Vol 46 (10) ◽  
pp. 1899-1904 ◽  
Author(s):  
Sanghoon Yoon ◽  
Sehyun Tak ◽  
Jinsoo Kim ◽  
Yongseok Jun ◽  
Kisuk Kang ◽  
...  
Keyword(s):  
Solar Cells ◽  
Dye Sensitized Solar Cells ◽  
Photovoltaic Systems ◽  
Dye Sensitized ◽  
Building Integrated Photovoltaic ◽  
Sensitized Solar Cells

scholarly journals A New Method for Fusion of Measured and Model-derived Solar Radiation Time-series

2014 ◽  
Vol 48 ◽  
pp. 1617-1626 ◽  
Author(s):  
Theresa Mieslinger ◽  
Felix Ament ◽  
Kaushal Chhatbar ◽  
Richard Meyer
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
New Method ◽  
Radiation Time

scholarly journals Compatibility of different measurement techniques. Long-term global solar radiation observations at Izaña Observatory

2016 ◽  
Author(s):  
Rosa Delia García ◽  
Emilio Cuevas ◽  
Omaira Elena García ◽  
Ramon Ramón ◽  
Pedro Miguel Romero-Campos ◽  
...  
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Sunshine Duration ◽  
Measurement Techniques ◽  
Temporal Stability ◽  
Global Solar Radiation ◽  
Surface Radiation ◽  
Multifilter Rotating Shadowband Radiometer ◽  
High Consistency

Abstract. A 1-year intercomparison of classical and modern radiation and sunshine duration instruments has been performed at Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain) starting on July 17, 2014. We compare global solar radiation (GSR) records measured with a CM-21 pyranometer Kipp &amp; Zonen, taken in the framework of the Baseline Surface Radiation Network, with those measured with a Multifilter Rotating Shadowband Radiometer (MFRSR), and a bimetallic pyranometer (PYR), and GSR estimated from sunshine duration performed by a Campbell-Stokes sunshine recorder (CS) and a Kipp &amp; Zonen sunshine duration sensor (CSD). Given the GSR BSRN records are subject of strict quality controls (based on principles of physical limits and comparison with the LibRadtran model), they have been used as reference in the intercomparison study. We obtain an overall root mean square error (RMSE) of ~0.9 MJm2 (4 %) for GSR PYR and GSR MFRSR, 1.9 MJm2 (7 %) and 1.2 MJm2 (5 %) for GSR CS and GSR CSD, respectively. Factors such as temperature, fraction of the clear sky, relative humidity and the solar zenith angle have shown to moderately affect the GSR observations. As application of the methodology developed in this work, we have re-evaluated the GSR time series between 1977 and 1991 obtained with two PYRs at IZO. By comparing with coincident GSR estimates from SD observations, we probe the high consistency of those measurements and their temporal stability. These results demonstrate that 1) the continuous-basis intercomparison of different GSR techniques offers important diagnostics for identifying inconsistencies between GSR data records, and 2) the GSR measurements performed with classical and more simple instruments are consistent with more modern techniques and, thus, valid to recover GSR time series and complete worldwide distributed GSR data. The intercomparison and quality assessment of these different techniques have allowed to obtain a complete and consistent long-term global solar radiation series (1977–2015) at Izaña.

scholarly journals Forecasting and Modelling of Solar Radiation for Photovoltaic (PV) Systems

2021 ◽  
Author(s):  
Ines Sansa ◽  
Najiba Mrabet Bellaaj
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Cloud Cover ◽  
Moving Average ◽  
Arma Model ◽  
Weather Conditions ◽  
Pv Systems ◽  
Auto Regressive ◽  
Micro Grid ◽  
One Year

Solar radiation is characterized by its fluctuation because it depends to different factors such as the day hour, the speed wind, the cloud cover and some other weather conditions. Certainly, this fluctuation can affect the PV power production and then its integration on the electrical micro grid. An accurate forecasting of solar radiation is so important to avoid these problems. In this chapter, the solar radiation is treated as time series and it is predicted using the Auto Regressive and Moving Average (ARMA) model. Based on the solar radiation forecasting results, the photovoltaic (PV) power is then forecasted. The choice of ARMA model has been carried out in order to exploit its own strength. This model is characterized by its flexibility and its ability to extract the useful statistical properties, for time series predictions, it is among the most used models. In this work, ARMA model is used to forecast the solar radiation one year in advance considering the weekly radiation averages. Simulation results have proven the effectiveness of ARMA model to forecast the small solar radiation fluctuations.

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