Preliminary assessment of two spatio-temporal forecasting technics for hourly satellite-derived irradiance in a complex meteorological context

André, Maïna; Perez, Richard; Soubdhan, Ted; Schlemmer, James; Calif, Rudy; Monjoly, Stéphanie

doi:10.1016/j.solener.2018.11.010

Cited by 24 publications

(13 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We also have to note that Lorenz et al compared forecasts against ground measurements while here, we compare forecasts against satellite-retrieved irradiances. Nevertheless, it has been shown that satellite data are an acceptable, if not in many cases preferable, ground measurement proxy to both train and test forecast models [40][41][42][43][44]. Figure 10b plots the RMSE of our PV power forecast against the RMSE of the persistence, while Table 3 reports the accuracy of day-ahead forecasts of single plants' generation in different countries.…”

Section: Forecast Resultsmentioning

confidence: 99%

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

et al. 2020

Self Cite

View full text Add to dashboard Cite

One of the major problem of photovoltaic grid integration is limiting the solar-induced imbalances since these can undermine the security and stability of the electrical system. Improving the forecast accuracy of photovoltaic generation is becoming essential to allow a massive solar penetration. In particular, improving the forecast accuracy of large solar farms’ generation is important both for the producers/traders to minimize the imbalance costs and for the transmission system operators to ensure stability. In this article, we provide a benchmark for the day-ahead forecast accuracy of utility scale photovoltaic (PV) plants in 1325 locations spanning the country of Italy. We then use these benchmarked forecasts and real energy prices to compute the economic value of the forecast accuracy and accuracy improvement in the context of the Italian energy market’s regulatory framework. Through this study, we further point out several important criticisms of the Italian “single pricing” system that brings paradoxical and counterproductive effects regarding the need to reduce the imbalance volumes. Finally, we propose a new market-pricing rule and innovative actions to overcome the undesired effects of the current dispatching regulations.

show abstract

Section: Forecast Resultsmentioning

confidence: 99%

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…We also have to note that Lorenz et al compared forecasts against ground measurements while here, we compare forecasts against satellite-retrieved irradiances. Nevertheless, it has been shown that satellite data are an acceptable, if not in many case preferable ground measurement proxy to both train and test forecast models [40,41,42,43,44,45]. in four EU locations [39] (the dashed line is the fit of the accuracy of the outperforming forecasts) (a); RMSE of the PV power forecast vs RMSE of persistence (b).…”

Section: Forecast Resultsmentioning

confidence: 99%

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

Pierro¹,

Moser²,

Perez³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

One of the major problem of photovoltaic grid integration is limiting the solar-induced imbalances since these can undermine the security and stability of the electrical system. Improving the forecast accuracy of photovoltaic generation is becoming essential to allow a massive solar penetration. In particular, improving the forecast accuracy of large solar farms generation is important both for the producers/traders to minimize the imbalance costs and for the Transmission System Operators to insure stability. In this article, we provide a benchmark for the day-ahead forecast accuracy of utility scale PV plants in 1325 locations spanning the country of Italy. We then use these benchmarked forecasts and real energy prices to compute the economic value of forecast accuracy and accuracy improvement in the context of the Italian energy market regulatory framework. Through this study, we further point out some several important criticisms of the Italian “single pricing” system that brings to paradoxical and counterproductive effects regarding the need to reduce the imbalance volumes. Finally, we propose a new market-pricing rule and innovative actions to overcome these undesired effects of the current dispatching regulations.

show abstract

“…A classification of daily irradiance profiles was performed. Often, in the literature, in solar area, the k-means method is used [13,27,36]. Recently, the Fuzzy C-means clustering is used for the implementation of demand side management measures [42] or to classify global horizontal irradiance [28].…”

Section: Methods Of Insolation Conditions Classificationmentioning

confidence: 99%

“…Some works in the literature demonstrate the solar forecasting performance using a combination of neural network (NN) model and other techniques: neural network mixed with wavelet [7], neural network mixed with neighboring meteorological sensors [8], and multiple parameters neural network model [9]. Reference models based on the family of ARMA (autoregressive moving average) and STARMA (spatiotemporal autoregressive moving average) also show a relevant predictive performance of solar radiation for short time horizons (e.g., [10][11][12][13][14]). In [15], a combination of autoregressive (AR) and neural network (NN) models is presented taking advantage of the unique strength of AR and NN models in linear and nonlinear modeling.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, for the first time in the literature, we present the forecasting performance of a model as a function of two horizon strategies on the modeling process and as a function of daily clearness index classification. For the solar radiation classification, several methods are proposed in the literature based on unsupervised clustering methods such as k-means [13,25], Ward's method [26], best information criterion [27] or, recently, Fuzzy c-means method [28]. Fuzzy c-means method was used here.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Forecast Horizon and Solar Variability Influences on the Performances of Multiscale Hybrid Forecast Model

et al. 2019

Self Cite

View full text Add to dashboard Cite

The tropical insular region is characterized by a large diversity of microclimates and land/sea contrasts, creating a challenging solar forecasting. Therefore, it is necessary to develop and use performant and robustness forecasting techniques. This paper examines the predictive performance of a novel solar forecasting approach, the multiscale hybrid forecast model (MHFM), as a function of several parameters. The MHFM model is a technique recently used for irradiance forecasting based on a hybrid autoregressive (AR) and neural network (NN) model combined with multiscale decomposition methods. This technique presents a relevant performance for 1 h ahead global horizontal irradiance forecast. The goal of this work is to highlight the strength and limits of this model by assessing the influence of different parameters from a metric error analysis. This study illustrates modeling process performance as a function of daily insolation conditions and testifies the influence of learning data and test data time scales. Several forecast horizon strategies and their influence on the MHFM performance were investigated. With the best strategy, a rRMSE value from 4.43 % to 10.24 % was obtained for forecast horizons from 5 min to 6 h. The analysis of intra-day solar resource variability showed that the best performance of MHFM was obtained for clear sky days with a rRMSE of 2.91 % and worst for cloudy sky days with a rRMSE of 6.73 % . These works constitute an additional analysis in agreement with the literature about influence of daily insolation conditions and horizons time scales on modeling process.

show abstract

Preliminary assessment of two spatio-temporal forecasting technics for hourly satellite-derived irradiance in a complex meteorological context

Cited by 24 publications

References 47 publications

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study

Forecast Horizon and Solar Variability Influences on the Performances of Multiscale Hybrid Forecast Model

Contact Info

Product

Resources

About