A combination of supervised dimensionality reduction and learning methods to forecast solar radiation

Machine learning is routinely used to forecast solar radiation from inputs, which are forecasts of meteorological variables provided by numerical weather prediction (NWP) models, on a spatially distributed grid. However, the number of features resulting from these grids is usually large, especially if several vertical levels are included. Principal Components Analysis (PCA) is one of the simplest and most widely-used methods to extract features and reduce dimensionality in renewable energy forecasting, although this method has some limitations. First, it performs a global linear analysis, and second it is an unsupervised method. Locality Preserving Projection (LPP) overcomes the locality problem, and recently the Linear Optimal Low-Rank (LOL) method has extended Linear Discriminant Analysis (LDA) to be applicable when the number of features is larger than the number of samples. Supervised Nonnegative Matrix Factorization (SNMF) also achieves this goal extending the Nonnegative Matrix Factorization (NMF) framework to integrate the logistic regression loss function. In this article we try to overcome all these issues together by proposing a Supervised Local Maximum Variance Preserving (SLMVP) method, a supervised non-linear method for feature extraction and dimensionality reduction. PCA, LPP, LOL, SNMF and SLMVP have been compared on Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) radiation data at two different Iberian locations: Seville and Lisbon. Results show that for both kinds of radiation (GHI and DNI) and the two locations, SLMVP produces smaller MAE errors than PCA, LPP, LOL, and SNMF, around 4.92% better for Seville and 3.12% for Lisbon. It has also been shown that, although SLMVP, PCA, and LPP benefit from using a non-linear regression method (Gradient Boosting in this work), this benefit is larger for PCA and LPP because SMLVP is able to perform non-linear transformations of inputs.This work has been made possible by projects funded by Agencia Estatal de Investigación (PID2019-107455RB-C22 / AEI / 10.13039/501100011033). This work was also supported by the Comunidad de Madrid Excellence Program and Comunidad de Madrid-Universidad Politécnica de Madrid young investigators initiative

SOWISP—A retrospective high spatial and temporal resolution database of the installed wind and solar PV power in Spain

The proposal of new energy systems based on renewable energies requires thorough research in order to derive technically reliable and economically sustainable systems. One of the key inputs of such research is constituted by reliable databases of renewable resources. Despite the great effort of the scientific community in recent years, most current databases are far from optimal. Although some databases are based on real data, they lack adequate spatial resolution and/or temporal coverage. Other databases are obtained by estimating renewable energy potential from meteorological reanalysis; however, these estimates are subject to high uncertainty. One of the main problems when building these renewable resource databases is the lack of actual values of installed capacity. In this study we present the SOlar and Wind Installed Spanish Power (SOWISP) database. SOWISP provides the actual installed capacity of wind and photovoltaic solar energy in each Spanish town, with a monthly resolution, and covering the period of 2015–2020. SOWISP has been developed and validated based on a careful and thorough compilation of different public databases. It covers the need for a publicly available database with sufficient spatial and temporal resolution suitable for the analysis of energy systems. Moreover, SOWISP, along with other freely available datasets, supports many modern applications. In addition, a Python package (available on GitHub) was developed for managing this databaseSpanish GovernmentJunta de Andalucia PID2019-107455RB-C21/AEI/92 10.13039/501100011033European CommissionUE-Junta de Andalucia PID2019-107455RB-C22/AEI/10.13039/501100011033 TEP-220 PAIDI2020-DOC_0111

Optimal management of wind and solar energy resources

This paper presents a portfolio-based approach to the harvesting of renewable energy (RE) resources. Our examined problem setting considers the possibility of distributing the total available capacity across an array of heterogeneous RE generation technologies (wind and solar power production units) being dispersed over a large geographical area. We formulate the capacity allocation process as a bi-objective optimization problem, in which the decision maker seeks to increase the mean productivity of the entire array while having control on the variability of the aggregate energy supply. Using large-scale optimization techniques, we are able to calculate - to an arbitrary degree of accuracy - the complete set of Pareto-optimal configurations of power plants, which attain the maximum possible energy delivery for a given level of power supply risk. Experimental results from a reference geographical region show that wind and solar resources are largely complementary. We demonstrate how this feature could help energy policy makers to improve the overall reliability of future RE generation in a properly designed risk management framework

Benchmarking of different approaches to forecast solar irradiance

Ponencia presentada en: 24th European Photovoltaic Solar Energy Conference and Exhibition celebrada del 21-25 de septiembre de 2009 en Hamburgo.Power generation from photovoltaic systems is highly variable due to its dependence on meteorological conditions. An efficient use of this fluctuating energy source requires reliable forecast information for management and operation strategies. Due to the strong increase of solar power generation the prediction of solar yields becomes more and more important. As a consequence, in the last years various research organisations and companies have developed different methods to forecast irradiance as a basis for respective power forecasts. For the end-users of these forecasts it is important that standardized methodology is used when presenting results on the accuracy of a prediction model in order to get a clear idea on the advantages of a specific approach. In this paper we introduce a benchmarking procedure to asses the accuracy of irradiance forecasts and compare different approaches of forecasting. The evaluation shows a strong dependence of the forecast accuracy on the climatic conditions. For Central European stations the relative rmse ranges from 40 % to 60 %, for Spanish stations relative rmse values are in the range of 20 % to 35 %

Evolutionary-based prediction interval estimation by blending solar radiation forecasting models using meteorological weather types

Recent research has shown that the integration or blending of different forecasting models is able to improve the predictions of solar radiation. However, most works perform model blending to improve point forecasts, but the integration of forecasting models to improve probabilistic forecasting has not received much attention. In this work the estimation of prediction intervals for the integration of four Global Horizontal Irradiance (GHI) forecasting models (Smart Persistence, WRF-solar, CIADcast, and Satellite) is addressed. Several short-term forecasting horizons, up to one hour ahead, have been analyzed. Within this context, one of the aims of the article is to study whether knowledge about the synoptic weather conditions, which are related to the stability of weather, might help to reduce the uncertainty represented by prediction intervals. In order to deal with this issue, information about which weather type is present at the time of prediction, has been used by the blending model. Four weather types have been considered. A multi-objective variant of the Lower Upper Bound Estimation approach has been used in this work for prediction interval estimation and compared with two baseline methods: Quantile Regression (QR) and Gradient Boosting (GBR). An exhaustive experimental validation has been carried out, using data registered at Seville in the Southern Iberian Peninsula. Results show that, in general, using weather type information reduces uncertainty of prediction intervals, according to all performance metrics used. More specifically, and with respect to one of the metrics (the ratio between interval coverage and width), for high-coverage (0.90, 0.95) prediction intervals, using weather type enhances the ratio of the multi-objective approach by 2%¿. Also, comparing the multi-objective approach versus the two baselines for high-coverage intervals, the improvement is 11%¿% over QR and 10%¿% over GBR. Improvements for low-coverage intervals (0.85) are smaller.The authors are supported by projects funded by Agencia Estatal de Investigación, Spain (PID2019-107455RB-C21 and PID2019-107455RB-C22/AEI/10.13039/501100011033). Also supported by Spanish Ministry of Economy and Competitiveness, project ENE2014-56126-C2-1-R and ENE2014-56126-C2-2-R (http://prosol.uc3m.es). The University of Jaén team is also supported by FEDER, Spain funds and by the Junta de Andalucía, Spain (Research group TEP-220

Exclusive fish oil lipid emulsion rescue strategy improves cholestasis in neonates on partially fish oil-based lipid emulsion: a pilot study

Resolution of parenteral nutrition-associated liver disease has been identified in infants receiving SMOFlipid™ or a 100% fish oil lipid emulsion (FOLE). However, the effect of FOLE is unknown when the previous emulsion received is a mixed lipid emulsion containing fish oil. This observational pilot study reports data regarding the use of Omegaven™ after the diagnosis of cholestasis while receiving SMOFlipid™. We conducted a retrospective review of medical charts of neonates in which a partially fish oil-based lipid emulsion was replaced by a fish oil lipid emulsion at 1 g/kg/day due to cholestasis. Thirty-eight infants (92.1% preterm, being 44.7% born below 28 weeks’ gestation), received FOLE. Birth weight was 1390 (743.0; 2298) grams. The age that cholestasis diagnosed was 15.0 (10.0; 24.8) days. The fish oil emulsion was administered for 38.5 (11.2; 51.8) days. In 73.7% (28/38) of the neonates, the cholestasis was resolved. In 34.2% (13/38), resolution happened before FOLE discontinuation. In addition, in the rest of the neonates (15) in whom cholestasis resolved, resolution occurred after FOLE discontinuation. Nine of the neonates died. In conclusion, the use of a 100% fish oil-based emulsion in neonates afflicted with cholestasis developed while on a partially fish oil-based emulsion is associated with a bilirubin decreas

Central pain augmentation in fibromyalgia during subjectively-matched mechanical stimulation

The precise pathophysiology of fibromyalgia, a syndrome characterized by, among other symptoms, chronic widespread pain, remains to be elucidated (Abeles et al., 2007). The fact that, when subjected to the same amount of stimulation, patients show enhanced brain responses as compared to controls provides evidence of central pain augmentation in this syndrome. We aimed to characterize brain response differences when stimulation is adjusted to elicit similar subjective levels of pain in both groups

Evaluación de los recursos solares utilizando entornos SIG: el problema de la resolución del Modelo Digital del Terreno

Ponencia presentada en: XXIX Jornadas Científicas de la AME y el VII Encuentro Hispano Luso de Meteorología celebrado en Pamplona, del 24 al 26 de abril de 2006

Efectos diferenciales de la citoquina IL-6 después del estrés social agudo: resultados preliminares

Objetivo: evaluar el efecto diferencial del estrés social agudo sobre la interleucina 6 salival mediante la prueba conductual Trier Social Stress Test (tsst). Método: participaron diecisiete estudiantes universitarios, normotensos, a quienes se registró la presión arterial media en tres momentos: 10 minutos antes, pre y post tsst. También se recolectó una muestra de IL-6 salival pre-post tsst. Resultados: hubo un incremento en la presión arterial media sólo cuando se presentó el tsst (p0.05). El análisis de IL-6 reveló que 53 % de la muestra incrementó su concentración de IL-6 (p<0.001) mientras que 47 % de los participantes decrementó su nivel de IL-6 (p<0.01), existiendo una diferencia estadísticamente significativa post-tsst entre ambos subgrupos (p<0.05). Limitaciones: se recomienda establecer parámetros normativos de la IL-6 salival. Principales hallazgos: los datos preliminares que presentamos sugieren que el estrés social agudo incrementa la presión arterial, pero que este efecto induce una expresión diferencial de IL-6 en todos los participantes, en aquellos con una concentración baja de IL-6 se incrementa después del estrés agudo, mientras que aquellos con un nivel alto de IL-6 previo, la prueba tiende a disminuirla

Evaluación de los recursos solares en el sur de la Península utilizando el modelo MM5

Ponencia presentada en: XXIX Jornadas Científicas de la AME y el VII Encuentro Hispano Luso de Meteorología celebrado en Pamplona, del 24 al 26 de abril de 2006