Pre-Feasibility Study of Hybrid Wind Power-H-2 System Connected to Electrical Grid

The growth of wind power as an electric energy source is profitable from an environmental point of view and improves the energetic independence of countries with little fossil fuel resources. However, the wind resource randomness poses a great challenge in the management of electric grids. This study raises the possibility of using hydrogen as a mean to damp the variability of the wind resource. Thus, it is proposed the use of all the energy produced by a typical wind farm for hydrogen generation, that will in turn be used after for suitable generation of electric energy according to the operation rules in a liberalized electric market.

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.

A wavelet-based approach for large wind power ramp characterisation

A wavelet-based approach for large wind power ramp characterisation

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

Detecting and characterising ramp events in wind power time series

In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain

A review on the recent history of wind power ramp forecasting.

Forecasting large and fast variations of wind power (the so called ramps) helps achieve the integration of large amounts of wind energy. This paper presents a survey on wind power ramp forecasting, reflecting the increasing interest on this topic observed since 2007. Three main aspects were identified from the literature: wind power ramp definition, ramp underlying meteorological causes and experi-ences in predicting ramps. In this framework, we additionally outline a number of recommendations and potential lines of research.

Identifying wind power ramp causes from multivariate datasets: a methodological proposal and its application to reanalysis data.

Forecasting abrupt variations in wind power generation (the so-called ramps) helps achieve large scale wind power integration. One of the main issues to be confronted when addressing wind power ramp forecasting is the way in which relevant information is identified from large datasets to optimally feed forecasting models. To this end, an innovative methodology oriented to systematically relate multivariate datasets to ramp events is presented. The methodology comprises two stages: the identification of relevant features in the data and the assessment of the dependence between these features and ramp occurrence. As a test case, the proposed methodology was employed to explore the relationships between atmospheric dynamics at the global/synoptic scales and ramp events experienced in two wind farms located in Spain. The achieved results suggested different connection degrees between these atmospheric scales and ramp occurrence. For one of the wind farms, it was found that ramp events could be partly explained from regional circulations and zonal pressure gradients. To perform a comprehensive analysis of ramp underlying causes, the proposed methodology could be applied to datasets related to other stages of the wind-topower conversion chain.

Hybrid wind-diesel power plant valuation and optimization using real option theory and dynamic programming

El sistema de energía eólica-diesel híbrido tiene un gran potencial en la prestación de suministro de energía a comunidades remotas. En comparación con los sistemas tradicionales de diesel, las plantas de energía híbridas ofrecen grandes ventajas tales como el suministro de capacidad de energía extra para "microgrids", reducción de los contaminantes y emisiones de gases de efecto invernadero, y la cobertura del riesgo de aumento inesperado del precio del combustible. El principal objetivo de la presente tesis es proporcionar nuevos conocimientos para la evaluación y optimización de los sistemas de energía híbrido eólico-diesel considerando las incertidumbres. Dado que la energía eólica es una variable estocástica, ésta no puede ser controlada ni predecirse con exactitud. La naturaleza incierta del viento como fuente de energía produce serios problemas tanto para la operación como para la evaluación del valor del sistema de energía eólica-diesel híbrido. Por un lado, la regulación de la potencia inyectada desde las turbinas de viento es una difícil tarea cuando opera el sistema híbrido. Por otro lado, el bene.cio económico de un sistema eólico-diesel híbrido se logra directamente a través de la energía entregada a la red de alimentación de la energía eólica. Consecuentemente, la incertidumbre de los recursos eólicos incrementa la dificultad de estimar los beneficios globales en la etapa de planificación. La principal preocupación del modelo tradicional determinista es no tener en cuenta la incertidumbre futura a la hora de tomar la decisión de operación. Con lo cual, no se prevé las acciones operativas flexibles en respuesta a los escenarios futuros. El análisis del rendimiento y simulación por ordenador en el Proyecto Eólico San Cristóbal demuestra que la incertidumbre sobre la energía eólica, las estrategias de control, almacenamiento de energía, y la curva de potencia de aerogeneradores tienen un impacto significativo sobre el rendimiento del sistema. En la presente tesis, se analiza la relación entre la teoría de valoración de opciones y el proceso de toma de decisiones. La opción real se desarrolla con un modelo y se presenta a través de ejemplos prácticos para evaluar el valor de los sistemas de energía eólica-diesel híbridos. Los resultados muestran que las opciones operacionales pueden aportar un valor adicional para el sistema de energía híbrida, cuando esta flexibilidad operativa se utiliza correctamente. Este marco se puede aplicar en la optimización de la operación a corto plazo teniendo en cuenta la naturaleza dependiente de la trayectoria de la política óptima de despacho, dadas las plausibles futuras realizaciones de la producción de energía eólica. En comparación con los métodos de valoración y optimización existentes, el resultado del caso de estudio numérico muestra que la política de operación resultante del modelo de optimización propuesto presenta una notable actuación en la reducción del con- sumo total de combustible del sistema eólico-diesel. Con el .n de tomar decisiones óptimas, los operadores de plantas de energía y los gestores de éstas no deben centrarse sólo en el resultado directo de cada acción operativa, tampoco deberían tomar decisiones deterministas. La forma correcta es gestionar dinámicamente el sistema de energía teniendo en cuenta el valor futuro condicionado en cada opción frente a la incertidumbre. ABSTRACT Hybrid wind-diesel power systems have a great potential in providing energy supply to remote communities. Compared with the traditional diesel systems, hybrid power plants are providing many advantages such as providing extra energy capacity to the micro-grid, reducing pollution and greenhouse-gas emissions, and hedging the risk of unexpected fuel price increases. This dissertation aims at providing novel insights for assessing and optimizing hybrid wind-diesel power systems considering the related uncertainties. Since wind power can neither be controlled nor accurately predicted, the energy harvested from a wind turbine may be considered a stochastic variable. This uncertain nature of wind energy source results in serious problems for both the operation and value assessment of the hybrid wind-diesel power system. On the one hand, regulating the uncertain power injected from wind turbines is a difficult task when operating the hybrid system. On the other hand, the economic profit of a hybrid wind-diesel system is achieved directly through the energy delivered to the power grid from the wind energy. Therefore, the uncertainty of wind resources has increased the difficulty in estimating the total benefits in the planning stage. The main concern of the traditional deterministic model is that it does not consider the future uncertainty when making the dispatch decision. Thus, it does not provide flexible operational actions in response to the uncertain future scenarios. Performance analysis and computer simulation on the San Cristobal Wind Project demonstrate that the wind power uncertainty, control strategies, energy storage, and the wind turbine power curve have a significant impact on the performance of the system. In this dissertation, the relationship between option pricing theory and decision making process is discussed. A real option model is developed and presented through practical examples for assessing the value of hybrid wind-diesel power systems. Results show that operational options can provide additional value to the hybrid power system when this operational flexibility is correctly utilized. This framework can be applied in optimizing short term dispatch decisions considering the path-dependent nature of the optimal dispatch policy, given the plausible future realizations of the wind power production. Comparing with the existing valuation and optimization methods, result from numerical example shows that the dispatch policy resulting from the proposed optimization model exhibits a remarkable performance in minimizing the total fuel consumption of the wind-diesel system. In order to make optimal decisions, power plant operators and managers should not just focus on the direct outcome of each operational action; neither should they make deterministic decisions. The correct way is to dynamically manage the power system by taking into consideration the conditional future value in each option in response to the uncertainty.

Wind pumps for irrigating greenhouse crops

Agriculture is a major consumer of energy in many countries of the world. Only a few of these countries are self-sufficient in conventional energy sources, which are also exhaustible. Fortunately, there are other sources of energy, such as wind, which has experienced recent developments in the area of wind power generation. From irrigation projects to power supply in remote farms, wind power generation can play a vital role. A simple methodology for technical evaluation of windmills for irrigation water pumping has been developed in this study to determine the feasibility per unit amount of water supplied and the levels of daily irrigation demand satisfied by windmill irrigation system at various levels of risk (probability of failure). For this purpose, a series of three hourly wind-speed data over a period of 38 years at Ciego de Ávila, Cuba, were analyzed to compute the diurnal wind pump discharge at varying levels of risk. The sizes of reservoirs required to modulate fluctuating discharge and to satisfy the levels of irrigation demand, on function of crop development dates, cultivated area and water elevation height, were computed by cumulative deficit water budgeting. An example is given illustrating the use of the methodology on tomato crop Licopersicon esculentum Mill) under greenhouse.

Urban wind energy: empirical optimization of high-rise building roof shape for the wind energy exploitation

El programa Europeo HORIZON2020 en Futuras Ciudades Inteligentes establece como objetivo que el 20% de la energía eléctrica sea generada a partir de fuentes renovables. Este objetivo implica la necesidad de potenciar la generación de energía eólica en todos los ámbitos. La energía eólica reduce drásticamente las emisiones de gases de efecto invernadero y evita los riesgos geo-políticos asociados al suministro e infraestructuras energéticas, así como la dependencia energética de otras regiones. Además, la generación de energía distribuida (generación en el punto de consumo) presenta significativas ventajas en términos de elevada eficiencia energética y estimulación de la economía. El sector de la edificación representa el 40% del consumo energético total de la Unión Europea. La reducción del consumo energético en este área es, por tanto, una prioridad de acuerdo con los objetivos "20-20-20" en eficiencia energética. La Directiva 2010/31/EU del Parlamento Europeo y del Consejo de 19 de mayo de 2010 sobre el comportamiento energético de edificaciones contempla la instalación de sistemas de suministro energético a partir de fuentes renovables en las edificaciones de nuevo diseño. Actualmente existe una escasez de conocimiento científico y tecnológico acerca de la geometría óptima de las edificaciones para la explotación de la energía eólica en entornos urbanos. El campo tecnológico de estudio de la presente Tesis Doctoral es la generación de energía eólica en entornos urbanos. Específicamente, la optimization de la geometría de las cubiertas de edificaciones desde el punto de vista de la explotación del recurso energético eólico. Debido a que el flujo del viento alrededor de las edificaciones es exhaustivamente investigado en esta Tesis empleando herramientas de simulación numérica, la mecánica de fluidos computacional (CFD en inglés) y la aerodinámica de edificaciones son los campos científicos de estudio. El objetivo central de esta Tesis Doctoral es obtener una geometría de altas prestaciones (u óptima) para la explotación de la energía eólica en cubiertas de edificaciones de gran altura. Este objetivo es alcanzado mediante un análisis exhaustivo de la influencia de la forma de la cubierta del edificio en el flujo del viento desde el punto de vista de la explotación energética del recurso eólico empleando herramientas de simulación numérica (CFD). Adicionalmente, la geometría de la edificación convencional (edificio prismático) es estudiada, y el posicionamiento adecuado para los diferentes tipos de aerogeneradores es propuesto. La compatibilidad entre el aprovechamiento de las energías solar fotovoltaica y eólica también es analizado en este tipo de edificaciones. La investigación prosigue con la optimización de la geometría de la cubierta. La metodología con la que se obtiene la geometría óptima consta de las siguientes etapas: - Verificación de los resultados de las geometrías previamente estudiadas en la literatura. Las geometrías básicas que se someten a examen son: cubierta plana, a dos aguas, inclinada, abovedada y esférica. - Análisis de la influencia de la forma de las aristas de la cubierta sobre el flujo del viento. Esta tarea se lleva a cabo mediante la comparación de los resultados obtenidos para la arista convencional (esquina sencilla) con un parapeto, un voladizo y una esquina curva. - Análisis del acoplamiento entre la cubierta y los cerramientos verticales (paredes) mediante la comparación entre diferentes variaciones de una cubierta esférica en una edificación de gran altura: cubierta esférica estudiada en la literatura, cubierta esférica integrada geométricamente con las paredes (planta cuadrada en el suelo) y una cubierta esférica acoplada a una pared cilindrica. El comportamiento del flujo sobre la cubierta es estudiado también considerando la posibilidad de la variación en la dirección del viento incidente. - Análisis del efecto de las proporciones geométricas del edificio sobre el flujo en la cubierta. - Análisis del efecto de la presencia de edificaciones circundantes sobre el flujo del viento en la cubierta del edificio objetivo. Las contribuciones de la presente Tesis Doctoral pueden resumirse en: - Se demuestra que los modelos de turbulencia RANS obtienen mejores resultados para la simulación del viento alrededor de edificaciones empleando los coeficientes propuestos por Crespo y los propuestos por Bechmann y Sórensen que empleando los coeficientes estándar. - Se demuestra que la estimación de la energía cinética turbulenta del flujo empleando modelos de turbulencia RANS puede ser validada manteniendo el enfoque en la cubierta de la edificación. - Se presenta una nueva modificación del modelo de turbulencia Durbin k — e que reproduce mejor la distancia de recirculación del flujo de acuerdo con los resultados experimentales. - Se demuestra una relación lineal entre la distancia de recirculación en una cubierta plana y el factor constante involucrado en el cálculo de la escala de tiempo de la velocidad turbulenta. Este resultado puede ser empleado por la comunidad científica para la mejora del modelado de la turbulencia en diversas herramientas computacionales (OpenFOAM, Fluent, CFX, etc.). - La compatibilidad entre las energías solar fotovoltaica y eólica en cubiertas de edificaciones es analizada. Se demuestra que la presencia de los módulos solares provoca un descenso en la intensidad de turbulencia. - Se demuestran conflictos en el cambio de escala entre simulaciones de edificaciones a escala real y simulaciones de modelos a escala reducida (túnel de viento). Se demuestra que para respetar las limitaciones de similitud (número de Reynolds) son necesarias mediciones en edificaciones a escala real o experimentos en túneles de viento empleando agua como fluido, especialmente cuando se trata con geometrías complejas, como es el caso de los módulos solares. - Se determina el posicionamiento más adecuado para los diferentes tipos de aerogeneradores tomando en consideración la velocidad e intensidad de turbulencia del flujo. El posicionamiento de aerogeneradores es investigado en las geometrías de cubierta más habituales (plana, a dos aguas, inclinada, abovedada y esférica). - Las formas de aristas más habituales (esquina, parapeto, voladizo y curva) son analizadas, así como su efecto sobre el flujo del viento en la cubierta de un edificio de gran altura desde el punto de vista del aprovechamiento eólico. - Se propone una geometría óptima (o de altas prestaciones) para el aprovechamiento de la energía eólica urbana. Esta optimización incluye: verificación de las geometrías estudiadas en el estado del arte, análisis de la influencia de las aristas de la cubierta en el flujo del viento, estudio del acoplamiento entre la cubierta y las paredes, análisis de sensibilidad del grosor de la cubierta, exploración de la influencia de las proporciones geométricas de la cubierta y el edificio, e investigación del efecto de las edificaciones circundantes (considerando diferentes alturas de los alrededores) sobre el flujo del viento en la cubierta del edificio objetivo. Las investigaciones comprenden el análisis de la velocidad, la energía cinética turbulenta y la intensidad de turbulencia en todos los casos. ABSTRACT The HORIZON2020 European program in Future Smart Cities aims to have 20% of electricity produced by renewable sources. This goal implies the necessity to enhance the wind energy generation, both with large and small wind turbines. Wind energy drastically reduces carbon emissions and avoids geo-political risks associated with supply and infrastructure constraints, as well as energy dependence from other regions. Additionally, distributed energy generation (generation at the consumption site) offers significant benefits in terms of high energy efficiency and stimulation of the economy. The buildings sector represents 40% of the European Union total energy consumption. Reducing energy consumption in this area is therefore a priority under the "20-20-20" objectives on energy efficiency. The Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings aims to consider the installation of renewable energy supply systems in new designed buildings. Nowadays, there is a lack of knowledge about the optimum building shape for urban wind energy exploitation. The technological field of study of the present Thesis is the wind energy generation in urban environments. Specifically, the improvement of the building-roof shape with a focus on the wind energy resource exploitation. Since the wind flow around buildings is exhaustively investigated in this Thesis using numerical simulation tools, both computational fluid dynamics (CFD) and building aerodynamics are the scientific fields of study. The main objective of this Thesis is to obtain an improved (or optimum) shape of a high-rise building for the wind energy exploitation on the roof. To achieve this objective, an analysis of the influence of the building shape on the behaviour of the wind flow on the roof from the point of view of the wind energy exploitation is carried out using numerical simulation tools (CFD). Additionally, the conventional building shape (prismatic) is analysed, and the adequate positions for different kinds of wind turbines are proposed. The compatibility of both photovoltaic-solar and wind energies is also analysed for this kind of buildings. The investigation continues with the buildingroof optimization. The methodology for obtaining the optimum high-rise building roof shape involves the following stages: - Verification of the results of previous building-roof shapes studied in the literature. The basic shapes that are compared are: flat, pitched, shed, vaulted and spheric. - Analysis of the influence of the roof-edge shape on the wind flow. This task is carried out by comparing the results obtained for the conventional edge shape (simple corner) with a railing, a cantilever and a curved edge. - Analysis of the roof-wall coupling by testing different variations of a spherical roof on a high-rise building: spherical roof studied in the litera ture, spherical roof geometrically integrated with the walls (squared-plant) and spherical roof with a cylindrical wall. The flow behaviour on the roof according to the variation of the incident wind direction is commented. - Analysis of the effect of the building aspect ratio on the flow. - Analysis of the surrounding buildings effect on the wind flow on the target building roof. The contributions of the present Thesis can be summarized as follows: - It is demonstrated that RANS turbulence models obtain better results for the wind flow around buildings using the coefficients proposed by Crespo and those proposed by Bechmann and S0rensen than by using the standard ones. - It is demonstrated that RANS turbulence models can be validated for turbulent kinetic energy focusing on building roofs. - A new modification of the Durbin k — e turbulence model is proposed in order to obtain a better agreement of the recirculation distance between CFD simulations and experimental results. - A linear relationship between the recirculation distance on a flat roof and the constant factor involved in the calculation of the turbulence velocity time scale is demonstrated. This discovery can be used by the research community in order to improve the turbulence modeling in different solvers (OpenFOAM, Fluent, CFX, etc.). - The compatibility of both photovoltaic-solar and wind energies on building roofs is demonstrated. A decrease of turbulence intensity due to the presence of the solar panels is demonstrated. - Scaling issues are demonstrated between full-scale buildings and windtunnel reduced-scale models. The necessity of respecting the similitude constraints is demonstrated. Either full-scale measurements or wind-tunnel experiments using water as a medium are needed in order to accurately reproduce the wind flow around buildings, specially when dealing with complex shapes (as solar panels, etc.). - The most adequate position (most adequate roof region) for the different kinds of wind turbines is highlighted attending to both velocity and turbulence intensity. The wind turbine positioning was investigated for the most habitual kind of building-roof shapes (flat, pitched, shed, vaulted and spherical). - The most habitual roof-edge shapes (simple edge, railing, cantilever and curved) were investigated, and their effect on the wind flow on a highrise building roof were analysed from the point of view of the wind energy exploitation. - An optimum building-roof shape is proposed for the urban wind energy exploitation. Such optimization includes: state-of-the-art roof shapes test, analysis of the influence of the roof-edge shape on the wind flow, study of the roof-wall coupling, sensitivity analysis of the roof width, exploration of the aspect ratio of the building-roof shape and investigation of the effect of the neighbouring buildings (considering different surrounding heights) on the wind now on the target building roof. The investigations comprise analysis of velocity, turbulent kinetic energy and turbulence intensity for all the cases.

Wind pumps for irrigating greenhouse crops: comparison in different socio-economical frameworks

Wind power can play an interesting role in irrigation projects in different areas. A methodology can determine the feasibility of the technology and the levels of daily irrigation demand satisfied by windmills at different levels of risk, using tomato (Lycopersicon esculentum Mill) as greenhouse crop. The present work compared the feasibility of the technology and the critical factors involved in three different countries: Cuba, Spain and Pakistan. The study considered as factors the wind speed level, the energy cost, the tomato prices, the reliability and distance to the electrical grid, and the crop development dates, determining the economic feasibility for each combination of factors in each country.

MultiPARTES: Multicore Virtualization for Mixed-Criticality Systems

Modern embedded applications typically integrate a multitude of functionalities with potentially different criticality levels into a single system. Without appropriate preconditions, the integration of mixed-criticality subsystems can lead to a significant and potentially unacceptable increase of engineering and certification costs. A promising solution is to incorporate mechanisms that establish multiple partitions with strict temporal and spatial separation between the individual partitions. In this approach, subsystems with different levels of criticality can be placed in different partitions and can be verified and validated in isolation. The MultiPARTES FP7 project aims at supporting mixed- criticality integration for embedded systems based on virtualization techniques for heterogeneous multicore processors. A major outcome of the project is the MultiPARTES XtratuM, an open source hypervisor designed as a generic virtualization layer for heterogeneous multicore. MultiPARTES evaluates the developed technology through selected use cases from the offshore wind power, space, visual surveillance, and automotive domains. The impact of MultiPARTES on the targeted domains will be also discussed. In a number of ongoing research initiatives (e.g., RECOMP, ARAMIS, MultiPARTES, CERTAINTY) mixed-criticality integration is considered in multicore processors. Key challenges are the combination of software virtualization and hardware segregation and the extension of partitioning mechanisms to jointly address significant non-functional requirements (e.g., time, energy and power budgets, adaptivity, reliability, safety, security, volume, weight, etc.) along with development and certification methodology.

Deviation of Cup and Propeller Anemometer Calibration Results with Air Density

The effect of air density variations on the calibration constants of several models of anemometers has been analyzed. The analysis was based on a series of calibrations between March 2003 and February 2011. Results indicate a linear behavior of both calibration constants with the air density. The effect of changes in air density on the measured wind speed by an anemometer was also studied. The results suggest that there can be an important deviation of the measured wind speed with changes in air density from the one at which the anemometer was calibrated, and therefore the need to take this effect into account when calculating wind power estimations.

Electricity price forecasting accounting for renewable energies: optimal combined forecasts

Electricity price forecasting is an interesting problem for all the agents involved in electricity market operation. For instance, every profit maximisation strategy is based on the computation of accurate one-day-ahead forecasts, which is why electricity price forecasting has been a growing field of research in recent years. In addition, the increasing concern about environmental issues has led to a high penetration of renewable energies, particularly wind. In some European countries such as Spain, Germany and Denmark, renewable energy is having a deep impact on the local power markets. In this paper, we propose an optimal model from the perspective of forecasting accuracy, and it consists of a combination of several univariate and multivariate time series methods that account for the amount of energy produced with clean energies, particularly wind and hydro, which are the most relevant renewable energy sources in the Iberian Market. This market is used to illustrate the proposed methodology, as it is one of those markets in which wind power production is more relevant in terms of its percentage of the total demand, but of course our method can be applied to any other liberalised power market. As far as our contribution is concerned, first, the methodology proposed by García-Martos et al(2007 and 2012) is generalised twofold: we allow the incorporation of wind power production and hydro reservoirs, and we do not impose the restriction of using the same model for 24h. A computational experiment and a Design of Experiments (DOE) are performed for this purpose. Then, for those hours in which there are two or more models without statistically significant differences in terms of their forecasting accuracy, a combination of forecasts is proposed by weighting the best models(according to the DOE) and minimising the Mean Absolute Percentage Error (MAPE). The MAPE is the most popular accuracy metric for comparing electricity price forecasting models. We construct the combi nation of forecasts by solving several nonlinear optimisation problems that allow computation of the optimal weights for building the combination of forecasts. The results are obtained by a large computational experiment that entails calculating out-of-sample forecasts for every hour in every day in the period from January 2007 to Decem ber 2009. In addition, to reinforce the value of our methodology, we compare our results with those that appear in recent published works in the field. This comparison shows the superiority of our methodology in terms of forecasting accuracy.