Generation of synthetic 4 s utility-scale PV output time series from hourly solar irradiance data

2021 ◽  
Vol 13 (2) ◽  
pp. 026301
Author(s):  
Kanyawee Keeratimahat ◽  
Jessie Copper ◽  
Anna Bruce ◽  
Iain MacGill
Keyword(s):  
Time Series ◽  
Solar Irradiance ◽  
Irradiance Data ◽  
Output Time ◽  
Utility Scale

scholarly journals Mapping regularities in the solar irradiance data using complementary complexity measures

2020 ◽  
Author(s):  
Dragutin T. Mihailović ◽  
Aleksandar Aksentijevic ◽  
Anja Mihailović
Keyword(s):  
Time Series ◽  
Solar Irradiance ◽  
Irradiation Time ◽  
Temporal Structure ◽  
Solar Irradiation ◽  
La Réunion ◽  
Periodic Patterns ◽  
Complexity Measures ◽  
Irradiance Data ◽  
First Time

AbstractSolar irradiance represents one of the principal phenomena of interest in geophysics and recent research, especially which concerned with renewable energy, suggests that the complexity of solar irradiance time series offers important insights into the dynamics of different geophysical systems. We examined the complexity of the daily cumulative global horizontal irradiance (kWh/m2; dGHI in further text) recorded by satellite for 32 stations on the island of La Réunion over a 35-month period (2004–2006) using Kolmogorov complexity (KC) and a recently introduced measure—Aksentijevic–Gibson complexity (AG) which is capable of quantifying the complexity of both long and short strings. Previous examinations of physical data suggest that AG could represent a useful addition to the geophysical analysis toolkit. Our results demonstrate for the first time that running KC is capable of capturing periodic patterns in data and that AG is sensitive to both global/long-scale spatial and temporal structure and local/short-range complexity fluctuations. Importantly, we report a putative weekly periodicity which might be related to environmental factors and human activity. In conclusion, we suggest that AG could represent a useful tool in the study of solar irradiation time series but also with other types of geophysical data.

scholarly journals A physical downscaling algorithm for the generation of high-resolution spatiotemporal solar irradiance data

Solar Energy ◽  
2021 ◽  
Vol 216 ◽  
pp. 508-517
Author(s):  
Grant Buster ◽  
Michael Rossol ◽  
Galen Maclaurin ◽  
Yu Xie ◽  
Manajit Sengupta
Keyword(s):  
High Resolution ◽  
Solar Irradiance ◽  
Irradiance Data

scholarly journals GMM-HMM-based Medium- and Long-term Multi-Wind Farm Correlated Power Output Time Series Generation Method

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Yufei Li ◽  
Bo Hu ◽  
Tao Niu ◽  
Shengpu Gao ◽  
Jiahao Yan ◽  
...  
Keyword(s):  
Time Series ◽  
Power Output ◽  
Wind Farm ◽  
Output Time

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.

Data Fusion of Total Solar Irradiance Composite Time Series Using 40 years of Satellite Measurements: First Results 

2021 ◽  
Author(s):  
Jean-Philippe Montillet ◽  
Wolfgang Finsterle ◽  
Werner Schmutz ◽  
Margit Haberreiter ◽  
Rok Sikonja
Keyword(s):  
Time Series ◽  
Data Fusion ◽  
Solar Irradiance ◽  
Total Solar Irradiance ◽  
Maunder Minimum ◽  
The Sun ◽  
Climate Reconstructions ◽  
The Earth ◽  
First Results ◽  
The Difference

<p><span>Since the late 70’s, successive satellite missions have been monitoring the sun’s activity, recording total solar irradiance observations. These measurements are important to estimate the Earth’s energy imbalance, </span><span>i.e. the difference of energy absorbed and emitted by our planet. Climate modelers need the solar forcing time series in their models in order to study the influence of the Sun on the Earth’s climate. With this amount of TSI data, solar irradiance reconstruction models  can be better validated which can also improve studies looking at past climate reconstructions (e.g., Maunder minimum). V</span><span>arious algorithms have been proposed in the last decade to merge the various TSI measurements over the 40 years of recording period. We have developed a new statistical algorithm based on data fusion.  The stochastic noise processes of the measurements are modeled via a dual kernel including white and coloured noise.  We show our first results and compare it with previous releases (PMOD,ACRIM, ... ). </span></p>

A Solar Irradiance Data Acquisition System Based on Labview

2015 ◽  
Vol 719-720 ◽  
pp. 596-599
Author(s):  
Xin Wen Duan ◽  
Yue Zhang
Keyword(s):  
Virtual Instrument ◽  
Solar Irradiance ◽  
Energy Resource ◽  
Data Acquisition System ◽  
Simulation Software ◽  
Acquisition System ◽  
External Temperature ◽  
Irradiance Data ◽  
Instrument Technology ◽  
Software And Hardware

The application of virtual instrument technology to design solar irradiance acquisition system, an ideal combination of software and hardware, is aimed at collecting, storing and analyzing data of external temperature and solar irradiance.The data proves helpful in assessing whether the solar energy resource deserves to be developded economically.The system is reliable and has been verified by simulation software proteus.

scholarly journals Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis

2019 ◽  
Author(s):  
Jaqueline Lekscha ◽  
Reik V. Donner
Keyword(s):  
Time Series ◽  
Network Analysis ◽  
Nonlinear Filtering ◽  
Ice Cores ◽  
Second Step ◽  
Different Types ◽  
Output Time ◽  
Input Time ◽  
Past Climate Variability ◽  
Input Time Series

Abstract. Analysing palaeoclimate proxy time series using windowed recurrence network analysis (wRNA) has been shown to provide valuable information on past climate variability. In turn, it has also been found that the robustness of the obtained results differs among proxies from different palaeoclimate archives. To systematically test the suitability of wRNA for studying different types of palaeoclimate proxy time series, we use the framework of forward proxy modelling. For this, we create artificial input time series with different properties and, in a first step, compare the time series properties of the input and the model output time series. In a second step, we compare the areawise significant anomalies detected using wRNA. For proxies from tree and lake archives, we find that significant anomalies present in the input time series are sometimes missed in the input time series after the nonlinear filtering by the corresponding models. For proxies from speleothems, we observe falsely identified significant anomalies that are not present in the input time series. Finally, for proxies from ice cores, the wRNA results show the best correspondence with those for the input data. Our results contribute to improve the interpretation of windowed recurrence network analysis results obtained from real-world palaeoclimate time series.

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