Review of solar irradiance forecasting methods and a proposition for small-scale insular grids
read more
Citations
WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data.
Integrating Machine Learning Algorithms for Predicting Solar Power Generation
Predicción de nubes a corto plazo para una planta solar a partir de datos históricos
Hybrid Black-box Solar Analytics and their Privacy Implications
A Low-cost System for High-frequency Solar Imagery and Power Data Acquisition
References
Time series analysis, forecasting and control
A Description of the Advanced Research WRF Version 3
Related Papers (5)
Frequently Asked Questions (17)
Q2. What are the future works in "Review of solar irradiance forecasting methods and a proposition for small-scale insular grids" ?
For small-scale insular grids A summary of the literature on solar irradiance forecasting models illustrated by Figure 1 and Figure 2 gives indications for future work. However, a further consideration in choosing among forecasting models is efficiency. The authors suggest to use the mesoscale model WRF. At higher frequency, the data is more dominated by short-term patterns which can be picked up by persistence or ANN.
Q3. What are some examples of statistical methods used in time series forecasting?
Seasonality analysis, Box-Jenkins or Auto Regressive Integrated Moving Average (ARIMA), Multiple Regressions and Exponential Smoothing are examples of statistical methods, whilst AI paradigms include fuzzy inference systems, genetic algorithm, neural networks, machine learning etc.Statistical methods have been used successfully in time series forecasting for several decades.
Q4. What are the main types of models used for irradiance forecasting?
They include time series models, satellite data based models, sky images based models, ANN models, wavelet analysis based models, etc. NWP models are based on historical data and the reproduction of physical information.
Q5. What are the main sources of information used for the determination of local solar irradiance?
Satellites and ground-based sky images, have been used for the determination and forecasting of local solar irradiance conditions.
Q6. What are the main features of the NWP models?
They allow the correction of systematic deviations in dependence on different meteorological parameters and for modeling of the irradiance if it is not provided as output parameter of an NWP model.
Q7. What is the role of MM5 and WRF in the forecasting of solar energy?
In addition, the capability of MM5 and WRF to integrate local measurements, for example, aerosols, may also contribute to improving forecast accuracy.
Q8. What are the key variables needed to run a forecast?
The key variables needed are the three-dimensional fields of wind, temperature, and humidity and the two-dimensional field of surface pressure.
Q9. What is the purpose of Kalman filters?
Kalman filters are designed to efficiently extract a signal from noisy data and are therefore expected to show a more robust performance if only limited training data are available, which is the case if the training is performed on the basis of individual stations.
Q10. What is the way to determine the irradiance of clouds?
Satellites and ground-based sky images with their high temporal and spatial resolution offer the potential to derive the required information on cloud motion.
Q11. How is the resolution of the driving global model increased?
To achieve the intended high spatial resolution in a mesoscale model with reasonable computing time, the resolution of the driving global model is increased stepwise with internal nesting.
Q12. What are the main factors that influence the irradiance of clouds at surface level?
Besides the deterministic daily and annual patterns of irradiance, clouds cover as well as cloud optical depth have the strongest influence on solar irradiance at surface level.
Q13. What is the advantage of using a hybrid model for forecasting sequences of total solar ?
Cao and Cao in [45] and [11] developed a hybrid model for forecasting sequences of total daily solar irradiance, which combines ANN with wavelet analysis.
Q14. What was the suitable realization of their approach?
Pelland et al. [44] found that the most suitable realization of their approach was a set of Kalman filter equations established separately for each forecast horizon and modeling the bias in dependence on the forecasted irradiance.
Q15. Why are GFS data used to initialize MM5 or WRF?
GFS data of NOAA are used to initialize MM5 or WRF for operational applications, because, in contrast to ECMWF data, they are available for free.
Q16. What are the main uses of the forecasts?
These forecasts are used by utility companies, transmission system operators, energy service providers, energy traders, and independent power producers in their scheduling, dispatching and regulation of power.
Q17. What is the fit to the residual series?
The introduction of a resonating model introduced for the power market by Lucheroni [20] plus the judicious intermittent use of a proxy for curvature allows for a much superior fit to this residual series.