Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series.

Statistical models for short-term wind power ramp forecasting

La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

Effect of short-term fasting prior to slaughter on welfare and meat quality or rainbow trout (Oncorhynchus mykiss)

El manejo pre-sacrificio es de vital importancia en acuicultura, ya que afecta tanto a las reacciones fisiológicas como a los procesos bioquímicos post mortem, y por tanto al bienestar y a la calidad del producto. El ayuno pre-sacrificio se lleva a cabo de forma habitual en acuicultura, ya que permite el vaciado del aparato digestivo de restos de alimento y heces, reduciendo de esta manera la carga bacteriana en el intestino y la dispersión de enzimas digestivos y potenciales patógenos a la carne. Sin embargo, la duración óptima de este ayuno sin que el pez sufra un estrés innecesario no está clara. Además, se sabe muy poco sobre la mejor hora del día para realizar el sacrificio, lo que a su vez está regido por los ritmos diarios de los parámetros fisiológicos de estrés. Finalmente, se sabe que la temperatura del agua juega un papel muy importante en la fisiología del estrés pero no se ha determinado su efecto en combinación con el ayuno. Además, las actuales recomendaciones en relación a la duración óptima del ayuno previo al sacrificio en peces no suelen considerar la temperatura del agua y se basan únicamente en días y no en grados día (ºC d). Se determinó el efecto del ayuno previo al sacrificio (1, 2 y 3 días, equivalente a 11,1-68,0 grados día) y la hora de sacrificio (08h00, 14h00 y 20h00) en trucha arco iris (Oncorhynchus mykiss) de tamaño comercial en cuatro pruebas usando diferentes temperaturas de agua (Prueba 1: 11,8 ºC; Prueba 2: 19,2 ºC; Prueba 3: 11,1 ºC; y Prueba 4: 22,7 ºC). Se midieron indicadores biométricos, hematológicos, metabólicos y de calidad de la carne. En cada prueba, los valores de los animales ayunados (n=90) se compararon con 90 animales control mantenidos bajo condiciones similares pero nos ayunados. Los resultados sugieren que el ayuno tuvo un efecto significativo sobre los indicadores biométricos. El coeficiente de condición en los animales ayunados fue menor que en los controles después de 2 días de ayuno. El vaciado del aparato digestivo se produjo durante las primeras 24 h de ayuno, encontrándose pequeñas cantidades de alimento después de 48 h. Por otra parte, este vaciado fue más rápido cuando las temperaturas fueron más altas. El peso del hígado de los animales ayunados fue menor y las diferencias entre truchas ayunadas y controles fueron más evidentes a medida que el vaciado del aparato digestivo fue más rápido. El efecto del ayuno hasta 3 días en los indicadores hematológicos no fue significativo. Los niveles de cortisol en plasma resultaron ser altos tanto en truchas ayunadas como en las alimentadas en todas las pruebas realizadas. La concentración media de glucosa varió entre pruebas pero mostró una tendencia a disminuir en animales ayunados a medida que el ayuno progresaba. En cualquier caso, parece que la temperatura del agua jugó un papel muy importante, ya que se encontraron concentraciones más altas durante los días 2 y 3 de ayuno en animales mantenidos a temperaturas más bajas previamente al sacrificio. Los altos niveles de lactato obtenidos en sangre parecen sugerir episodios de intensa actividad muscular pero no se pudo encontrar relación con el ayuno. De la misma manera, el nivel de hematocrito no mostró efecto alguno del ayuno y los leucocitos tendieron a ser más altos cuando los animales estaban menos estresados y cuando su condición corporal fue mayor. Finalmente, la disminución del peso del hígado (índice hepatosomático) en la Prueba 3 no se vio acompañada de una reducción del glucógeno hepático, lo que sugiere que las truchas emplearon una estrategia diferente para mantener constantes los niveles de glucosa durante el periodo de ayuno en esa prueba. En relación a la hora de sacrificio, se obtuvieron niveles más bajos de cortisol a las 20h00, lo que indica que las truchas estaban menos estresadas y que el manejo pre-sacrificio podría resultar menos estresante por la noche. Los niveles de hematocrito fueron también más bajos a las 20h00 pero solo con temperaturas más bajas, sugiriendo que las altas temperaturas incrementan el metabolismo. Ni el ayuno ni la hora de sacrificio tuvieron un efecto significativo sobre la evolución de la calidad de la carne durante los 3 días de almacenamiento. Por el contrario, el tiempo de almacenamiento sí que parece tener un efecto claro sobre los parámetros de calidad del producto final. Los niveles más bajos de pH se alcanzaron a las 24-48 h post mortem, con una lata variabilidad entre duraciones del ayuno (1, 2 y 3 días) en animales sacrificados a las 20h00, aunque no se pudo distinguir ningún patrón común. Por otra parte, la mayor rigidez asociada al rigor mortis se produjo a las 24 h del sacrificio. La capacidad de retención de agua se mostró muy estable durante el período de almacenamiento y parece ser independiente de los cambios en el pH. El parámetro L* de color se incrementó a medida que avanzaba el período de almacenamiento de la carne, mientras que los valores a* y b* no variaron en gran medida. En conclusión, basándose en los resultados hematológicos, el sacrificio a última hora del día parece tener un efecto menos negativo en el bienestar. De manera general, nuestros resultados sugieren que la trucha arco iris puede soportar un período de ayuno previo al sacrificio de hasta 3 días o 68 ºC d sin que su bienestar se vea seriamente comprometido. Es probable que con temperaturas más bajas las truchas pudieran ser ayunadas durante más tiempo sin ningún efecto negativo sobre su bienestar. En cualquier caso, se necesitan más estudios para determinar la relación entre la temperatura del agua y la duración óptima del ayuno en términos de pérdida de peso vivo y la disminución de los niveles de glucosa en sangre y otros indicadores metabólicos. SUMMARY Pre-slaughter handling in fish is important because it affects both physiological reactions and post mortem biochemical processes, and thus welfare and product quality. Pre-slaughter fasting is regularly carried out in aquaculture, as it empties the viscera of food and faeces, thus reducing the intestinal bacteria load and the spread of gut enzymes and potential pathogens to the flesh. However, it is unclear how long rainbow trout can be fasted before suffering unnecessary stress. In addition, very little is known about the best time of the day to slaughter fish, which may in turn be dictated by diurnal rhythms in physiological stress parameters. Water temperature is also known to play a very important role in stress physiology in fish but the combined effect with fasting is unclear. Current recommendations regarding the optimal duration of pre-slaughter fasting do not normally consider water temperature and are only based on days, not degree days (ºC d). The effects of short-term fasting prior to slaughter (1, 2 and 3 days, between 11.1 and 68.0 ºC days) and hour of slaughter (08h00, 14h00 and 20h00) were determined in commercial-sized rainbow trout (Oncorhynchus mykiss) over four trials at different water temperatures (TRIAL 1, 11.8 ºC; TRIAL 2, 19.2 ºC; TRIAL 3, 11.1 ºC; and TRIAL 4, 22.7 ºC). We measured biometric, haematological, metabolic and product quality indicators. In each trial, the values of fasted fish (n=90) were compared with 90 control fish kept under similar conditions but not fasted. Results show that fasting affected biometric indicators. The coefficient of condition in fasted trout was lower than controls 2 days after food deprivation. Gut emptying occurred within the first 24 h after the cessation of feeding, with small traces of digesta after 48 h. Gut emptying was faster at higher water temperatures. Liver weight decreased in food deprived fish and differences between fasted and fed trout were more evident when gut clearance was faster. The overall effect of fasting for up to three days on haematological indicators was small. Plasma cortisol levels were high in both fasted and fed fish in all trials. Plasma glucose response to fasting varied among trials, but it tended to be lower in fasted fish as the days of fasting increased. In any case, it seems that water temperature played a more important role, with higher concentrations at lower temperatures on days 2 and 3 after the cessation of feeding. Plasma lactate levels indicate moments of high muscular activity and were also high, but no variation related to fasting could be found. Haematocrit did not show any significant effect of fasting, but leucocytes tended to be higher when trout were less stressed and when their body condition was higher. Finally, the loss of liver weight was not accompanied by a decrease in liver glycogen (only measured in TRIAL 3), suggesting that a different strategy to maintain plasma glucose levels was used. Regarding the hour of slaughter, lower cortisol levels were found at 20h00, suggesting that trout were less stressed later in the day and that pre-slaughter handling may be less stressful at night. Haematocrit levels were also lower at 20h00 but only at lower temperatures, indicating that higher temperatures increase metabolism. Neither fasting nor the hour of slaughter had a significant effect on the evolution of meat quality during 3 days of storage. In contrast, storage time seemed to have a more important effect on meat quality parameters. The lowest pH was reached 24-48 h post mortem, with a higher variability among fasting durations at 20h00, although no clear pattern could be discerned. Maximum stiffening from rigor mortis occurred after 24 h. The water holding capacity was very stable throughout storage and seemed to be independent of pH changes. Meat lightness (L*) slightly increased during storage and a* and b*-values were relatively stable. In conclusion, based on the haematological results, slaughtering at night may have less of a negative effect on welfare than at other times of the day. Overall, our results suggest that rainbow trout can cope well with fasting up to three days or 68 ºC d prior to slaughter and that their welfare is therefore not seriously compromised. At low water temperatures, trout could probably be fasted for longer periods without negative effects on welfare but more research is needed to determine the relationship between water temperature and days of fasting in terms of loss of live weight and the decrease in plasma glucose and other metabolic indicators.

Mixed models for short-run forecasting of electricity prices: Application for the Spanish market

Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every profit maximization strategy. In this article a new and very easy method to compute accurate forecasts for electricity prices using mixed models is proposed. The main idea is to develop an efficient tool for one-step-ahead forecasting in the future, combining several prediction methods for which forecasting performance has been checked and compared for a span of several years. Also as a novelty, the 24 hourly time series has been modelled separately, instead of the complete time series of the prices. This allows one to take advantage of the homogeneity of these 24 time series. The purpose of this paper is to select the model that leads to smaller prediction errors and to obtain the appropriate length of time to use for forecasting. These results have been obtained by means of a computational experiment. A mixed model which combines the advantages of the two new models discussed is proposed. Some numerical results for the Spanish market are shown, but this new methodology can be applied to other electricity markets as well

Improving photovoltaics grid integration through short time forecasting and self-consumption

The uncertainty associated to the forecast of photovoltaic generation is a major drawback for the widespread introduction of this technology into electricity grids. This uncertainty is a challenge in the design and operation of electrical systems that include photovoltaic generation. Demand-Side Management (DSM) techniques are widely used to modify energy consumption. If local photovoltaic generation is available, DSM techniques can use generation forecast to schedule the local consumption. On the other hand, local storage systems can be used to separate electricity availability from instantaneous generation; therefore, the effects of forecast error in the electrical system are reduced. The effects of uncertainty associated to the forecast of photovoltaic generation in a residential electrical system equipped with DSM techniques and a local storage system are analyzed in this paper. The study has been performed in a solar house that is able to displace a residential user?s load pattern, manage local storage and estimate forecasts of electricity generation. A series of real experiments and simulations have carried out on the house. The results of this experiments show that the use of Demand Side Management (DSM) and local storage reduces to 2% the uncertainty on the energy exchanged with the grid. In the case that the photovoltaic system would operate as a pure electricity generator feeding all generated electricity into grid, the uncertainty would raise to around 40%.

Short-term effects of four tillage practices on soil physical properties, soil water potential, and maize yield

The area cultivated using conservation tillage has recently increased in central Spain. However, soil compaction and water retention with conservation tillage still remains a genuine concern for landowners in this region be- cause of its potential effect on the crop growth and yield. The aim of this research is to determine the short- term influences of four tillage treatments on soil physical properties. In the experiment, bulk density, cone index, soil water potential, soil temperature and maize (Zea mays L.) productivity have been measured. A field experiment was established in spring of 2013 on a loamy soil. The experiment compared four tillage methods (zero tillage, ZT; reservoir tillage, RT; minimum tillage, MT; and conventional tillage, CT). Soil bulk density and soil cone index were measured during maize growing season and at harvesting time. Furthermore, the soil water potential was monitored by using a wireless sensors network with sensors at 20 and 40 cm depths. Also, soil temperatures were registered at depths of 5 and 12 cm. Results indicated that there were significant differ- ences between soil bulk density and cone index of ZT method and those of RT, MT, and CT, during the growing season; although, this difference was not significant at the time of harvesting in some soil layers. Overall, in most soil layers, tillage practice affected bulk density and cone index in the order: ZT N RT N MT N CT. Regardless oftheentireobservationperiod,results exhibited that soils under ZT and RT treatments usually resulted in higher water potential and lower soil temperature than the other two treatments at both soil depths. In addition, clear differences in maize grain yield were observed between ZT and CT treatments, with a grain yield (up to 15.4%) increase with the CT treatment. On the other hand, no significant differences among (RT, MT, and CT) on maizeyieldwerefound.Inconclusion,the impact of soil compaction increase and soil temperature decrease,pro- duced by ZT treatment is a potential reason for maize yield reduction in this tillage method. We found that RT could be certainly a viable option for farmers incentral Spain,particularly when switching to conservation tillage from conventional tillage. This technique showed a moderate and positive effect on soil physical properties and increased maize yields compared to ZT and MT, and provides an opportunity to stabilize maize yields compared to CT.

A dynamic factor model for mid-term forecasting of wind power generation

The main objective of this paper is the development and application of multivariate time series models for forecasting aggregated wind power production in a country or region. Nowadays, in Spain, Denmark or Germany there is an increasing penetration of this kind of renewable energy, somehow to reduce energy dependence on the exterior, but always linked with the increaseand uncertainty affecting the prices of fossil fuels. The disposal of accurate predictions of wind power generation is a crucial task both for the System Operator as well as for all the agents of the Market. However, the vast majority of works rarely onsider forecasting horizons longer than 48 hours, although they are of interest for the system planning and operation. In this paper we use Dynamic Factor Analysis, adapting and modifying it conveniently, to reach our aim: the computation of accurate forecasts for the aggregated wind power production in a country for a forecasting horizon as long as possible, particularly up to 60 days (2 months). We illustrate this methodology and the results obtained for real data in the leading country in wind power production: Denmark

Evolution of extreme temperature events in short term climate projection for Iberian Peninsula

Extreme events of maximum and minimum temperatures are a main hazard for agricultural production in Iberian Peninsula. For this purpose, in this study we analyze projections of their evolution that could be valid for the next decade, represented in this study by the 30-year period 2004-2034 (target period). For this purpose two kinds of data were used in this study: 1) observations from the station network of AEMET (Spanish National Meteorological Agency) for five Spanish locations, and 2) simulated data at a resolution of 50 50 km horizontal grid derived from the outputs of twelve Regional Climate Models (RCMs) taken from project ENSEMBLES (van der Linden and Mitchell, 2009), with a bias correction (Dosio and Paruolo, 2011; Dosio et al., 2012) regarding the observational dataset Spain02 (Herrera et al., 2012). To validate the simulated climate, the available period of observations was compared to a baseline period (1964-1994) of simulated climate for all locations. Then, to analyze the changes for the present/very next future, probability of extreme temperature events for 2004-2034 were compared to that of the baseline period. Although only minor changes are expected, small variations in variability may have a significant impact in crop performance.

Short-term response of the Ca cycle of a montane forest in Ecuador to low experimental CaCl2 additions

The tropical montane forests of the E Andean cordillera in Ecuador receive episodic Sahara- dust inputs particularly increasing Ca deposition. We added CaCl2 to isolate the effect of Ca deposition by Sahara dust to tropical montane forest from the simultaneously occurring pH effect. We examined components of the Ca cycle at four control plots and four plots with added Ca (2 × 5 kg ha?1 Ca annually as CaCl2) in a random arrangement. Between August 2007 and December 2009 (four applications of Ca), we determined Ca concentrations and fluxes in litter leachate, mineral soil solution (0.15 and 0.30 m depths), throughfall, and fine litterfall and Al con- centrations and speciation in soil solutions. After 1 y of Ca addition, we assessed fine-root bio- mass, leaf area, and tree growth. Only < 3% of the applied Ca leached below the acid organic layer (pH 3.5?4.8). The added CaCl2 did not change electrical conductivity in the root zone after 2 y. In the second year of fertilization, Ca retention in the canopy of the Ca treatment tended to decrease relative to the control. After 2 y, 21% of the applied Ca was recycled to soil with throughfall and litterfall. One year after the first Ca addition, fine-root biomass had decreased significantly. Decreasing fine-root biomass might be attributed to a direct or an indirect beneficial effect of Ca on the soil decomposer community. Because of almost complete association of Al with dissolved organic matter and high free Ca2+ : Al3+ activity ratios in solution of all plots, Al toxicity was unlikely. We conclude that the added Ca was retained in the system and had benefi- cial effects on some plants.

Operational short term health impact assessment of air pollution modelling system over Europe

The last decade, scientific studies have indicated an association between air pollution to which people are exposed and wide range of adverse health outcomes. We have developed a tool which is based on a model (MM5-CMAQ) running over Europe with 50 km spatial resolution, based on EMEP annual emissions, to produce a short-term forecast of the impact on health. In order to estimate the mortality change (forecasted for the next 24 hours) we have chosen a log-linear (Poisson) regression form to estimate the concentration-response function. The parameters involved in the C-R function have been estimated based on epidemiological studies, which have been published. Finally, we have derived the relationship between concentration change and mortality change from the C-R function which is the final health impact function.