scholarly journals A model of very short-term solar irradiance forecasting based on low-cost sky images

2017 ◽  
Author(s):  
Yiyang Ai ◽  
Yonggang Peng ◽  
Wei Wei
Keyword(s):  
Solar Irradiance ◽  
Low Cost ◽  
Short Term

scholarly journals Stellar activity, differential rotation, and exoplanets

2010 ◽  
Vol 6 (S273) ◽  
pp. 89-95 ◽  
Author(s):  
A. F. Lanza
Keyword(s):  
Time Series ◽  
Differential Rotation ◽  
Solar Irradiance ◽  
Giant Planet ◽  
Total Solar Irradiance ◽  
Short Term ◽  
Stellar Activity ◽  
Transiting Planets ◽  
Spot Model ◽  
Spot Activity

AbstractThe photospheric spot activity of some of the stars with transiting planets discovered by the CoRoT space experiment is reviewed. Their out-of-transit light modulations are fitted by a spot model previously tested with the total solar irradiance variations. This approach allows us to study the longitude distribution of the spotted area and its variations versus time during the five months of a typical CoRoT time series. The migration of the spots in longitude provides a lower limit for the surface differential rotation, while the variation of the total spotted area can be used to search for short-term cycles akin the solar Rieger cycles. The possible impact of a close-in giant planet on stellar activity is also discussed.

scholarly journals An On-Line Low-Cost Irradiance Monitoring Network with Sub-Second Sampling Adapted to Small-Scale PV Systems

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3405 ◽  
Author(s):  
Manuel Espinosa-Gavira ◽  
Agustín Agüera-Pérez ◽  
Juan González de la Rosa ◽  
José Palomares-Salas ◽  
José Sierra-Fernández
Keyword(s):  
Sensor Networks ◽  
Low Cost ◽  
Monitoring Network ◽  
Absolute Error ◽  
Small Scale ◽  
Photovoltaic Systems ◽  
Real Time Control ◽  
Short Term ◽  
Time Control ◽  
Cloud Motion

Very short-term solar forecasts are gaining interest for their application on real-time control of photovoltaic systems. These forecasts are intimately related to the cloud motion that produce variations of the irradiance field on scales of seconds and meters, thus particularly impacting in small photovoltaic systems. Very short-term forecast models must be supported by updated information of the local irradiance field, and solar sensor networks are positioning as the more direct way to obtain these data. The development of solar sensor networks adapted to small-scale systems as microgrids is subject to specific requirements: high updating frequency, high density of measurement points and low investment. This paper proposes a wireless sensor network able to provide snapshots of the irradiance field with an updating frequency of 2 Hz. The network comprised 16 motes regularly distributed over an area of 15 m × 15 m (4 motes × 4 motes, minimum intersensor distance of 5 m). The irradiance values were estimated from illuminance measurements acquired by lux-meters in the network motes. The estimated irradiances were validated with measurements of a secondary standard pyranometer obtaining a mean absolute error of 24.4 W/m 2 and a standard deviation of 36.1 W/m 2 . The network was able to capture the cloud motion and the main features of the irradiance field even with the reduced dimensions of the monitoring area. These results and the low-cost of the measurement devices indicate that this concept of solar sensor networks would be appropriate not only for photovoltaic plants in the range of MW, but also for smaller systems such as the ones installed in microgrids.

scholarly journals Prediction of Solar Irradiance Based on Artificial Neural Networks

Inventions ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 45 ◽  
Author(s):  
Waleed I. Hameed ◽  
Baha A. Sawadi ◽  
Safa J. Al-Kamil ◽  
Mohammed S. Al-Radhi ◽  
Yasir I. A. Al-Yasir ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Solar Irradiance ◽  
Open Circuit Voltage ◽  
Low Cost ◽  
Short Circuit ◽  
Short Circuit Current ◽  
Open Circuit ◽  
Pv Module ◽  
Artificial Neural

Prediction of solar irradiance plays an essential role in many energy systems. The objective of this paper is to present a low-cost solar irradiance meter based on artificial neural networks (ANN). A photovoltaic (PV) mathematical model of 50 watts and 36 cells was used to extract the short-circuit current and the open-circuit voltage of the PV module. The obtained data was used to train the ANN to predict solar irradiance for horizontal surfaces. The strategy was to measure the open-circuit voltage and the short-circuit current of the PV module and then feed it to the ANN as inputs to get the irradiance. The experimental and simulation results showed that the proposed method could be utilized to achieve the value of solar irradiance with acceptable approximation. As a result, this method presents a low-cost instrument that can be used instead of an expensive pyranometer.

scholarly journals Short-Term Forecasting of Surface Solar Irradiance Based on Meteosat-SEVIRI Data Using a Nighttime Cloud Index

2015 ◽  
Vol 7 (7) ◽  
pp. 9070-9090 ◽  
Author(s):  
Annette Hammer ◽  
Jan Kühnert ◽  
Kailash Weinreich ◽  
Elke Lorenz
Keyword(s):  
Solar Irradiance ◽  
Short Term ◽  
Short Term Forecasting

scholarly journals Forecasting of solar irradiance and ramp events with all-sky imagers

2021 ◽  
Author(s):  
Stavros-Andreas Logothetis ◽  
Vasileios Salamalikis ◽  
Stefan Wilbert ◽  
Jan Remund ◽  
Luis Zarzalejo ◽  
...  
Keyword(s):  
Solar Irradiance ◽  
Large Scale ◽  
Forecast Error ◽  
Forecast Accuracy ◽  
Short Term ◽  
Event Prediction ◽  
High Penetration ◽  
Spanish Research ◽  
Short Term Forecasting ◽  
Solar Resource

<p>Cloud cameras (all sky imagers/ASIs) can be used for short-term (next 20 min) forecasts of solar irradiance. For this reason, several experimental and operational solutions emerged in the last decade with different approaches in terms of instrument types and forecast algorithms. Moreover, few commercial and semi-prototype systems are already available or being investigated. So far, the uncertainty of the predictions cannot be fully compared, as previously published tests were carried out during different periods and at different locations. In this study, the results from a benchmark exercise are presented in order to qualify the current ASI-based short-term forecasting solutions and examine their accuracy. This first comparative measurement campaign carried out as part of the IEA PVPS Task 16 (https://iea-pvps.org/research-tasks/solar-resource-for-high-penetration-and-large-scale-applications/). A 3-month observation campaign (from August to December 2019) took place at Plataforma Solar de Almeria of the Spanish research center CIEMAT including five different ASI systems and a network of high-quality measurements of solar irradiance and other atmospheric parameters. Forecasted time-series of global horizontal irradiance are compared with ground-based measurements and two persistence models to identify strengths and weaknesses of each approach and define best practices of ASI-based forecasts. The statistical analysis is divided into seven cloud classes to interpret the different cloud type effect on ASIs forecast accuracy. For every cloud cluster, at least three ASIs outperform persistence models, in terms of forecast error, highlighting their performance capabilities. The feasibility of ASIs on ramp event detection is also investigated, applying different approaches of ramp event prediction. The revealed findings are promising in terms of overall performance of ASIs as well as their forecasting capabilities in ramp detection.  </p>

scholarly journals Short-Term Debt and Financial Performance of Small and Medium Scale Enterprises in Buganda Region, Uganda

2020 ◽  
Vol 9 (4) ◽  
pp. 58-69
Author(s):  
Henry Mugisha ◽  
Job Omagwa ◽  
James Kilika
Keyword(s):  
Financial Performance ◽  
Small And Medium Enterprises ◽  
Low Cost ◽  
Linear Regression Analysis ◽  
Sampling Technique ◽  
Primary Data ◽  
Short Term ◽  
Cross Sectional ◽  
Capital Shortage ◽  
Qualitative Approaches

Short-term debt is regarded as an important source of financing for Small and Medium-sized enterprises (SMEs). This is because it can be easily accessed and useful during times of emergent working capital shortage. However, short-term debt is the least researched among the components of capital structure, which explains why its contribution to the financial performance of small and medium-sized businesses still lacks empirical validation especially in the Ugandan context. This paper sought to determine the effect of short-term debt on financial performance of Small and Medium Enterprises in Uganda. The study adopted a descriptive cross-sectional research design to collect and analyse the data. Stratified random sampling technique was used to select SMEs while purposive sampling technique was used to select one key respondent from each of the sampled 453 SMEs in Uganda. Primary data was collected using survey questionnaire. Data was analysed using descriptive statistics and simple linear regression analysis. The findings indicted that short-term debt had a negative and significant effect on financial performance of SMEs as measured by return on assets. The study provides empirical evidence to support the propositions in the extant literature that short-term debt significantly hampers financial performance of SMEs. The study recommends that SMEs should adopt low cost operation procedures to improve profitability. This would lead to accumulated profits that can be used for investment purposes as a means of driving growth among the SMEs without resorting to borrowing. This paper suggests that further research should be conducted to establish the justification for the negative and significant effect of short-term debt on financial performance using qualitative approaches.

scholarly journals The Impact of a Short-Term Walking Intervention to Decrease Perceived Stress

2020 ◽  
Vol 34 (4) ◽  
Author(s):  
Katie J. Fischer
Keyword(s):  
Perceived Stress ◽  
Low Cost ◽  
Private University ◽  
Upper Midwest ◽  
Short Term ◽  
Post Intervention ◽  
University Employees ◽  
Walking Intervention ◽  
The Impact

This study examined a short-term, low-cost walking intervention developed and implemented at a small, private university in the upper Midwest. Results showed a significant decrease in perceived stress (pre-intervention PSQ mean = 0.41 ± 0.16 versus post-intervention PSQ mean = 0.30 ± 0.14, p <0.001), and a significant increase in daily steps (pre-intervention mean = 6,810 ± 2,544 versus post-intervention mean = 9,352 ± 2,825, p < 0.001). These results provide support for the effectiveness of a short-term walking intervention to increase daily steps and decrease perceived stress for university employees.

Comparison of short-term solar irradiance forecasting methods when weather conditions are complicated

2018 ◽  
Vol 10 (5) ◽  
pp. 053501 ◽  
Author(s):  
Yunjun Yu ◽  
Junfei Cao ◽  
Xiaofeng Wan ◽  
Fanpeng Zeng ◽  
Jianbo Xin ◽  
...  
Keyword(s):  
Solar Irradiance ◽  
Weather Conditions ◽  
Short Term ◽  
Forecasting Methods
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