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.

Adapting micro-economy of energy corporations to macroeconomy policies aiming at a sustainable economy

Esta Tesis surgió ante la intensidad y verosimilitud de varias señales o “warnings” asociadas a políticas dirigidas a reducir el peso del petróleo en el sector energético, tanto por razones económicas, como geopolíticas, como ambientales. Como tal Tesis se consolidó al ir incorporando elementos novedosos pero esenciales en el mundo petrolífero, particularmente las “tecnologías habilitantes”, tanto de incidencia directa, como el “fracking” como indirecta, del cual es un gran ejemplo el Vehículo Eléctrico (puro). La Tesis se definió y estructuró para elaborar una serie de indagaciones y disquisiciones, que comportaran un conjunto de conclusiones que fueran útiles para las corporaciones energéticas. También para la comprensión de la propia evolución del sector y de sus prestaciones técnicas y económicas, de cara a dar el servicio que los usuarios finales piden. Dentro de las tareas analíticas y reflexivas de la Tesis, se acuñaron ciertos términos conceptuales para explicar más certeramente la realidad del sector, y tal es el caso del “Investment burden”, que pondera la inversión específica (€/W) requerida por una instalación, con la duración del período de construcción y los riesgos tanto tangibles como regulatorios. Junto a ello la Tesis propone una herramienta de estudio y prognosis, denominada “Market integrated energy efficiency”, especialmente aplicable a dicotomías. Tal es el caso del coche térmico, versus coche eléctrico. El objetivo es optimizar una determinada actividad energética, o la productividad total del sector. Esta Tesis propone varias innovaciones, que se pueden agrupar en dos niveles: el primero dentro del campo de la Energía, y el segundo dentro del campo de las corporaciones, y de manera especial de las corporaciones del sector hidrocarburos. A nivel corporativo, la adaptación a la nueva realidad será función directa de la capacidad de cada corporación para desarrollar y/o comprar las tecnologías que permitan mantener o aumentar cuota de mercado. Las conclusiones de la Tesis apuntan a tres opciones principalmente para un replanteamiento corporativo: - Diversificación energética - Desplazamiento geográfico - Beneficiándose de posibles nuevos nichos tecnológicos, como son: • En upstream: Recuperación estimulada de petróleo mediante uso de energías renovables • En downstream: Aditivos orientados a reducir emisiones • En gestión del cambio: Almacenamiento energético con fines operativos Algunas políticas energéticas siguen la tendencia de crecimiento cero de algunos países de la OCDE. No obstante, la realidad mundial es muy diferente a la de esos países. Por ejemplo, según diversas estimaciones (basadas en bancos de datos solventes, referenciados en la Tesis) el número de vehículos aumentará desde aproximadamente mil millones en la actualidad hasta el doble en 2035; mientras que la producción de petróleo sólo aumentará de 95 a 145 millones de barriles al día. Un aumento del 50% frente a un aumento del 100%. Esto generará un curioso desajuste, que se empezará a sentir en unos pocos años. Las empresas y corporaciones del sector hidrocarburos pueden perder el monopolio que atesoran actualmente en el sector transporte frente a todas las demás fuentes energéticas. Esa pérdida puede quedar compensada por una mejor gestión de todas sus capacidades y una participación más integrada en el mundo de la energía, buscando sinergias donde hasta ahora no había sino distanciamiento. Los productos petrolíferos pueden alimentar cualquier tipo de maquina térmica, como las turbinas Brayton, o alimentar reformadores para la producción masiva de H2 para su posterior uso en pilas combustible. El almacenamiento de productos derivados del petróleo no es ningún reto ni plantea problema alguno; y sin embargo este almacenamiento es la llave para resolver muchos problemas. Es posible que el comercio de petróleo se haga menos volátil debido a los efectos asociados al almacenamiento; pero lo que es seguro es que la eficiencia energética de los usos de ese petróleo será más elevada. La Tesis partía de ciertas amenazas sobre el futuro del petróleo, pero tras el análisis realizado se puede vislumbrar un futuro prometedor en la fusión de políticas medioambientales coercitivas y las nuevas tecnologías emergentes del actual portafolio de oportunidades técnicas. ABSTRACT This Thesis rises from the force and the credibility of a number of warning signs linked to policies aimed at reducing the role of petroleum in the energy industry due to economical, geopolitical and environmental drives. As such Thesis, it grew up based on aggregating new but essentials elements into the petroleum sector. This is the case of “enabling technologies” that have a direct impact on the petroleum industry (such as fracking), or an indirect but deep impact (such as the full electrical vehicle). The Thesis was defined and structured in such a way that could convey useful conclusions for energy corporations through a series of inquiries and treatises. In addition to this, the Thesis also aims at understating la evolution of the energy industry and its capabilities both technical and economical, towards delivering the services required by end users. Within the analytical task performed in the Thesis, new terms were coined. They depict concepts that aid at explaining the facts of the energy industry. This is the case for “Investment burden”, it weights the specific capital investment (€/W) required to build a facility with the time that takes to build it, as well as other tangible risks as those posed by regulation. In addition to this, the Thesis puts forward an application designed for reviewing and predicting: the so called “Market integrated energy efficiency”, especially well-suited for dichotomies, very appealing for the case of the thermal car versus the electric car. The aim is to optimize energy related activity; or even the overall productivity of the system. The innovations proposed in this Thesis can be classified in two tiers. Tier one, within the energy sector; and tier two, related to Energy Corporation in general, but with oil and gas corporations at heart. From a corporate level, the adaptation to new energy era will be linked with the corporation capability to develop or acquire those technologies that will yield to retaining or enhancing market share. The Thesis highlights three options for corporate evolution: - diversification within Energy - geographic displacement - profiting new technologies relevant to important niches of work for the future, as: o Upstream: enhanced oil recovery using renewable energy sources (for upstream companies in the petroleum business) o Downstream: additives for reducing combustion emissions o Management of Change: operational energy storage Some energy policies tend to follow the zero-growth of some OECD countries, but the real thing could be very different. For instance, and according to estimates the number of vehicles in use will grow from 1 billion to more than double this figure 2035; but oil production will only grow from 95 million barrel/day to 145 (a 50% rise of versus an intensification of over a 100%). Hydrocarbon Corporation can lose the monopoly they currently hold over the supply of energy to transportation. This lose can be mitigated through an enhanced used of their capabilities and a higher degree of integration in the world of energy, exploring for synergies in those places were gaps were present. Petroleum products can be used to feed any type of thermal machine, as Brayton turbines, or steam reformers to produce H2 to be exploited in fuel cells. Storing petroleum products does not present any problem, but very many problems can be solved with them. Petroleum trading will likely be less volatile because of the smoothing effects of distributed storage, and indeed the efficiency in petroleum consumption will be much higher. The Thesis kicked off with a menace on the future of petroleum. However, at the end of the analysis, a bright future can be foreseen in the merging between highly demanding environmental policies and the relevant technologies of the currently emerging technical portfolio.

Production of biodiesel from animal fat using supercritical ethanol

Biodiesel is currently produced from a catalytic transesterification reaction of various types of edible and non-edible oil with methanol. The use of waste animal tallow instead of edible oils opens a route to recycle this waste. This material has the advantage of lower costs but the problem of high content of free fatty acids, becoming necessary a pre-esterification reaction that increases the cost of the catalytic process. The production of biodiesel using supercritical alcohols is appropriate for materials with high acidity and water content, therefore the use of this process with animal fat is a promising alternative. Ethanol has been used because it can be produced from biomass via fermentation resulting in a complete renewable biodiesel, instead of methanol that derives from fossil feedstocks. Two different processes have been studied: first, the direct transesterification of animal fat using supercritical ethanol and second a two-step process where the first step is a hydrolysis of the animal fat and the second step is the esterification of the resulting fatty acids. The temperature, the molar ratio ethanol:fat and the time have been modified in the different reactions to study the effect in the final conversion and the degradation of the unsaturated fatty acid esters, main inconvenient of these high temperature and pressure processes.

Modelling and Simulation of Moored Devices for Ocean Currents Energy Harnessing

The main objective of this paper is the presentation of modelling solutions off loating devices that can be used for harnessing energy from ocean currents. It has been structured into three main parts. First, the growing current interest in marine renewable energy in general, and in extracting energy from currents in particular, is presented, showing the large number of solutions that are emerging and some of the most significant types. GESMEY generator is presented in second section. It is based on a new concept that has been patented by the Universidad Politécnica de Madrid and which is currently being developed through a collaborative agreement with the SOERMAR Foundation. The main feature of this generator is that on operation is fully submerged, and no other facilities are required to move to floating state for maintenance, which greatly increases its performance. Third part of the article is devoted to present the modelling and simulation challenges that arise in the development of devices for harnessing the energy of marine currents, along with some solutions which have been adopted within the frame of the GESMEY Project, making particular emphasis on the dynamics of the generator and its control

Development of a grid connected micro wind generator. A practical activity for the course on electric generation with wind energy

This paper describes a practical activity, part of the renewable energy course where the students have to build their own complete wind generation system, including blades, PM-generator, power electronics and control. After connecting the system to the electric grid the system has been tested during real wind scenarios. The paper will describe the electric part of the work surface-mounted permanent magnet machine design criteria as well as the power electronics part for the power control and the grid connection. A Kalman filter is used for the voltage phase estimation and current commands obtained in order to control active and reactive power. The connection to the grid has been done and active and reactive power has been measured in the system.

Análisis técnico-económico de acceso al mercado alemán EPEX SPOT

Acciona Energía dispone en Alemania de 150 MW de potencia instalada. Todos ellos de energía eólica, en un total de doce parques eólicos situados en la sur del país. El proyecto tiene por objeto comparar las distintas modalidades de venta de energía procedente de fuentes renovables que ofrece el estado alemán para la cartera de activos de Acciona Energía, llegando a una conclusión final de cuál de ellas es la más aconsejable. Para ello se ha realizado un estudio del funcionamiento y normas del mercado Epex Spot de la electricidad y de la legislación alemana correspondiente a la materia, así como un seguimiento exhaustivo de producción y otras variables de los parques eólicos para su análisis. Los cálculos y las estimaciones realizados llevaron a la conclusión, que la mejor opción era la venta directa en el mercado Epex Spot, para lo que primero habría que darse de alta como agente en dicho mercado. Aunque esta opción asuma mayores riesgos también ofrecería un aumento considerable de ingresos. ABSTRACT Acciona Energía has 150 MW of power capacity in Germany, all of them wind energy in a total of twelve installations, located in the south of the country. The main goal of the project is to compare the different ways to sell the energy which became from renewable source that German state offers for Acciona’s asset portfolio, finding the most advisable conclusion. To do so a study of standards and rules of Epex Spot electricity market and German law related to this topic has been made. In addition of an exhaustive monitoring of energy production and others wind farms variables has been analyzed. The reckoning and estimations saw the conclusion that the best option was the direct sell in Epex Spot market, in order to do that the first of all is to register as market agent. Despite this options assume bigger risks, it provide a substantial increase in income

Methodology to assess EU Biofuel Policies: The CAPRI Approach

This report is based on the outcome of a study carried out by the European Commission's Joint Research Centre - Institute for Prospective Technological Studies (JRC-IPTS, Spain) in cooperation with EuroCARE (Bonn, Germany). The report provides a detailed description of the methodology developed to assess the implications of the European Renewable Energy Directive on the agricultural sector, with an explicit focus on regional effects of biofuel targets in the EU. For the analysis, the spatial agricultural sector model CAPRI has been extended to include a global representation of biofuel markets (with endogenous supply, demand and trade flows for biofuels and biofuel feedstocks) while keeping the focus on regional impacts in the EU. The model is capable to simulate the impacts of EU biofuel policies on food production and prices, the potential use of by-products in the feed chain, the increasing pressure on marginal and idle land and the share of imported biofuels (self-sufficiency indicators). CAPRI is now able to jointly assess biofuel and agricultural policies, including policy instruments defined at the Member State level. The CAPRI biofuel module allows for a detailed analysis of most relevant biofuel support instruments like consumer tax exemptions, quota obligations, import tariffs and other trade measures. Additionally, the model allows for analysing scenarios regarding technical progress in 2nd generation technologies for biofuels.

Impacts of the EU Biofuel Target on Agricultural Markets and Land Use - A Comparative Modelling Assessment

The Renewable Energy Directive (2009/28/EC) requires that 20% of the EU's energy needs should come from renewable sources by 2020, and includes a target for the transport sector of 10% from biofuels. This report analyses and discusses the global impacts of this biofuel target on agricultural production, markets and land use, as simulated by three agricultural sector models, AGLINK-COSIMO, ESIM and CAPRI. The impacts identified include higher EU production of ethanol and biodiesel, and of the crops used to produce them, as well as more imports of both biofuels. Trade flows of biofuel feedstocks also change to reflect greater EU demand, including a significant increase in vegetable oil imports. However, as the extra demand is small in world market terms, the impact on world market prices is limited. With the EU biofuel target, global use of land for crop cultivation is higher by 5.2 million hectares. About one quarter is area within the EU, some of which would otherwise have left agriculture.

Testing a GIS-based methodology for optimal location of Pumped Storage power plants in Norway

Europe needs to restructure its energy system. The aim to decrease the reliance on fossil fuels to a higher dependence on renewable energy has now been imposed by The European Commission. In order to achieve this goal there is a great interest in Norway to become "The Green Battery of Europe". In the pursuit of this goal a GIS-tool was created to investigate the pump storage potential in Norway. The tool searches for possible connections between existing reservoirs and dams with the criteria selected by the user. The aim of this thesis was to test the tool and see if the results suggested were plausible, develop a cost calculation method for the PSH lines, and make suggestions for further development of the tool. During the process the tool presented many non-feasible pumped storage hydropower (PSH) connections. The area of Telemark was chosen for the more detailed study. The results were discussed and some improvements were suggested for further development of the tool. Also a sensitivity test was done to see which of the parameters set by the user are the most relevant for the PSH connection suggestion. From a range of the most promising PSH plants suggested by the tool, the one between Songavatn and Totak was chosen for a case study, where there already exists a power plant between both reservoirs. A new Pumped Storage Plant was designed with a power production of 1200 MW. There are still many topics open to discussion, such as how to deal with environmental restrictions, or how to deal with inflows and outflows of the reservoirs from the existing power plants. Consequently the GIS-tool can be a very useful tool to establish the best possible connections between existing reservoirs and dams, but it still needs a deep study and the creation of new parameters for the user.

Wind intermittency and CO2 reductions: the case of the spanish power system

Renewable energy sources are believed to reduce drastically greenhouse gas emissions that would otherwise be generated from fossil fuels used to generate electricity. This implies that a unit of renewable energy will replace a unit of fossil-fuel, with its CO2 emissions, on an equivalent basis (with no other effects on the grid). But, the fuel economy and emissions in the existing power systems are not proportional with the electricity production of intermittent sources due to cycling of the fossil fuel plants that make up the balance of the grid (i.e. changing the power output makes thermal units to operate less efficiently). This study focuses in the interactions between wind generation and thermal plants cycling, by establishing the levels of extra fuel use caused by decreased efficiencies of fossil back-up for wind electricity in Spain. We analyze the production of all thermal plants in 2011, studying different scenarios where wind penetration causes major deviations in programming, while we define a procedure for quantifying the carbon reductions by using emission factors and efficiency curves from the existing installations. The objectives are to discuss the real contributions of renewable energies to the environmental targets as well as suggest alternatives that would improve the reliability of future power systems.

The cup anemometer, a fundamental meteorological instrument for the wind energy industry

The cup anemometer has been used widely by the wind energy industry since its early beginning, covering two fundamental aspects: wind mill performance control and wind energy production forecast. Furthermore, despite modern technological advances such as LIDAR and SODAR, the cup anemometer remains clearly the most used instrument by the wind energy industry. Together with the major advantages of this instrument (precision, robustness), some issues must be taken into account by scientists and researchers when using it. Overspeeding, interaction with stream wakes due to allocation on masts and wind- mills, loss of performance due to wear and tear, change of performance due to different climatic conditions, checking of the maintenance status and recalibration, etc. In the present work a review of the research campaigns carried out at the IDR/UPM Institute to analyze cup anemometer performance is included. Several aspects of this instrument are examined: the calibration process, the loss of performances due to aging and wear and tear, the effect of changes of air density, the rotor aerodynamics, and the harmonic terms contained in the anemometer output signal and their possible relation to the anemometer performances.

New method for analytical photovoltaic parameters identification: meeting manufacturer’s datasheet for different ambient conditions

At present, photovoltaic energy is one of the most important renewable energy sources. The demand for solar panels has been continuously growing, both in the industrial electric sector and in the private sector. In both cases the analysis of the solar panel efficiency is extremely important in order to maximize the energy production. In order to have a more efficient photovoltaic system, the most accurate understanding of this system is required. However, in most of the cases the only information available in this matter is reduced, the experimental testing of the photovoltaic device being out of consideration, normally for budget reasons. Several methods, normally based on an equivalent circuit model, have been developed to extract the I-V curve of a photovoltaic device from the small amount of data provided by the manufacturer. The aim of this paper is to present a fast, easy, and accurate analytical method, developed to calculate the equivalent circuit parameters of a solar panel from the only data that manufacturers usually provide. The calculated circuit accurately reproduces the solar panel behavior, that is, the I-V curve. This fact being extremely important for practical reasons such as selecting the best solar panel in the market for a particular purpose, or maximize the energy extraction with MPPT (Maximum Peak Power Tracking) methods.

Evaluación del dispositivo Raspberry Pi como elemento de despliegue de servicios en el marco de las Smart Grids

La tendencia actual de las redes de telecomunicaciones conduce a pensar en un futuro basado en el concepto emergente de las Smart Cities¸ que tienen como objetivo el desarrollo urbano basado en un modelo de sostenibilidad que responda a las necesidades crecientes de las ciudades. Dentro de las Smart Cities podemos incluir el concepto de Smart Grid, el cual está referido a sistemas de administración y producción de energía eficientes, que permitan un sistema energético sostenible, y que den cabida a las fuentes de energía renovables. Sistemas de este tipo se muestran a los usuarios como un conjunto de servicios con los que interactuar sin ser tan sólo un mero cliente, sino un agente más del entorno energético. Por otro lado, los sistemas de software distribuidos son cada vez más comunes en una infraestructura de telecomunicaciones cada vez más extensa y con más capacidades. Dentro de este ámbito tecnológico, las arquitecturas orientadas a servicios han crecido exponencialmente sobre todo en el sector empresarial. Con sistemas basados en estas arquitecturas, se pueden ofrecer a empresas y usuarios sistemas software basados en el concepto de servicio. Con la progresión del hardware actual, la miniaturización de los equipos es cada vez mayor, sin renunciar por ello a la potencia que podemos encontrar en sistemas de mayor tamaño. Un ejemplo es el dispositivo Raspberry Pi, que contiene un ordenador plenamente funcional contenido en el tamaño de una cajetilla de tabaco, y con un coste muy reducido. En este proyecto se pretenden aunar los tres conceptos expuestos. De esta forma, se busca utilizar el dispositivo Raspberry Pi como elemento de despliegue integrado en una arquitectura de Smart Grid orientada a servicios. En los trabajos realizados se ha utilizado la propuesta definida por el proyecto de I+D europeo e-GOTHAM, con cuya infraestructura se ha tenido ocasión de realizar diferentes pruebas de las descritas en esta memoria. Aunque esta arquitectura está orientada a la creación de una Smart Grid, lo experimentado en este PFG podría encajar en otro tipo de aplicaciones. Dentro del estudio sobre las soluciones software actuales, se ha trabajado en la evaluación de la posibilidad de instalar un Enterprise Service Bus en el Raspberry Pi y en la optimización de la citada instalación. Una vez conseguida una instalación operativa, se ha desarrollado un controlador de un dispositivo físico (sensor/actuador), denominado Dispositivo Lógico, a modo de prueba de la viabilidad del uso del Raspberry Pi para actuar como elemento en el que instalar aplicaciones en entornos de Smart Grid o Smart Home. El éxito logrado con esta experimentación refuerza la idea de considerar al Raspberry Pi, como un importante elemento a tener en cuenta para el despliegue de servicios de Smart Cities o incluso en otros ámbitos tecnológicos. ABSTRACT. The current trend of telecommunication networks lead to think in a future based on the emerging concept of Smart Cities, whose objective is to ensure the urban development based on a sustainable model to respond the new necessities of the cities. Within the Smart cites we can include the concept of Smart Grid, which is based on management systems and efficient energy production, allowing a sustainable energy producing system, and that includes renewable energy sources. Systems of this type are shown to users as a set of services that allow users to interact with the system not only as a single customer, but also as other energy environment agent. Furthermore, distributed software systems are increasingly common in a telecommunications infrastructure more extensive and with more capabilities. Within this area of technology, service-oriented architectures have grown exponentially especially in the business sector. With systems based on these architectures, can be offered to businesses and users software systems based on the concept of service. With the progression of the actual hardware, the miniaturization of computers is increasing, without sacrificing the power of larger systems. An example is the Raspberry Pi, which contains a fully functional computer contained in the size of a pack of cigarettes, and with a very low cost. This PFG (Proyecto Fin de Grado) tries to combine the three concepts presented. Thus, it is intended to use the Raspberry Pi device as a deployment element integrated into a service oriented Smart Grid architecture. In this PFG, the one proposed in the European R&D e-GOTHAM project has been observed. In addition several tests described herein have been carried out using the infrastructure of that project. Although this architecture is oriented to the creation of a Smart Grid, the experiences reported in this document could fit into other applications. Within the study on current software solutions, it have been working on assessing the possibility of installing an Enterprise Service Bus in the Raspberry Pi and optimizing that facility. Having achieved an operating installation, it has been developed a driver for a physical device (sensor / actuator), called logical device, for testing the feasibility of using the Raspberry Pi to act as an element in which to install applications in Smart Grid and Smart Home Environments. The success of this experiment reinforces the idea of considering the Raspberry Pi as an important element to take into account in the deployment of Smart Cities services or even in other technological fields.

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

Predicción espacio-temporal de la irradiancia solar global a corto plazo en España mediante geoestadística y redes neuronales artificiales

El enriquecimiento del conocimiento sobre la Irradiancia Solar (IS) a nivel de superficie terrestre, así como su predicción, cobran gran interés para las Energías Renovables (ER) - Energía Solar (ES)-, y para distintas aplicaciones industriales o ecológicas. En el ámbito de las ER, el uso óptimo de la ES implica contar con datos de la IS en superficie que ayuden tanto, en la selección de emplazamientos para instalaciones de ES, como en su etapa de diseño (dimensionar la producción) y, finalmente, en su explotación. En este último caso, la observación y la predicción es útil para el mercado energético, la planificación y gestión de la energía (generadoras y operadoras del sistema eléctrico), especialmente en los nuevos contextos de las redes inteligentes de transporte. A pesar de la importancia estratégica de contar con datos de la IS, especialmente los observados por sensores de IS en superficie (los que mejor captan esta variable), estos no siempre están disponibles para los lugares de interés ni con la resolución espacial y temporal deseada. Esta limitación se une a la necesidad de disponer de predicciones a corto plazo de la IS que ayuden a la planificación y gestión de la energía. Se ha indagado y caracterizado las Redes de Estaciones Meteorológicas (REM) existentes en España que publican en internet sus observaciones, focalizando en la IS. Se han identificado 24 REM (16 gubernamentales y 8 redes voluntarios) que aglutinan 3492 estaciones, convirtiéndose éstas en las fuentes de datos meteorológicos utilizados en la tesis. Se han investigado cinco técnicas de estimación espacial de la IS en intervalos de 15 minutos para el territorio peninsular (3 técnicas geoestadísticas, una determinística y el método HelioSat2 basado en imágenes satelitales) con distintas configuraciones espaciales. Cuando el área de estudio tiene una adecuada densidad de observaciones, el mejor método identificado para estimar la IS es el Kriging con Regresión usando variables auxiliares -una de ellas la IS estimada a partir de imágenes satelitales-. De este modo es posible estimar espacialmente la IS más allá de los 25 km identificados en la bibliografía. En caso contrario, se corrobora la idoneidad de utilizar estimaciones a partir de sensores remotos cuando la densidad de observaciones no es adecuada. Se ha experimentado con el modelado de Redes Neuronales Artificiales (RNA) para la predicción a corto plazo de la IS utilizando observaciones próximas (componentes espaciales) en sus entradas y, los resultados son prometedores. Así los niveles de errores disminuyen bajo las siguientes condiciones: (1) cuando el horizonte temporal de predicción es inferior o igual a 3 horas, las estaciones vecinas que se incluyen en el modelo deben encentrarse a una distancia máxima aproximada de 55 km. Esto permite concluir que las RNA son capaces de aprender cómo afectan las condiciones meteorológicas vecinas a la predicción de la IS. ABSTRACT ABSTRACT The enrichment of knowledge about the Solar Irradiance (SI) at Earth's surface and its prediction, have a high interest for Renewable Energy (RE) - Solar Energy (SE) - and for various industrial and environmental applications. In the field of the RE, the optimal use of the SE involves having SI surface to help in the selection of sites for facilities ES, in the design stage (sizing energy production), and finally on their production. In the latter case, the observation and prediction is useful for the market, planning and management of the energy (generators and electrical system operators), especially in new contexts of smart transport networks (smartgrid). Despite the strategic importance of SI data, especially those observed by sensors of SI at surface (the ones that best measure this environmental variable), these are not always available to the sights and the spatial and temporal resolution desired. This limitation is bound to the need for short-term predictions of the SI to help planning and energy management. It has been investigated and characterized existing Networks of Weather Stations (NWS) in Spain that share its observations online, focusing on SI. 24 NWS have been identified (16 government and 8 volunteer networks) that implies 3492 stations, turning it into the sources of meteorological data used in the thesis. We have investigated five technical of spatial estimation of SI in 15 minutes to the mainland (3 geostatistical techniques and HelioSat2 a deterministic method based on satellite images) with different spatial configurations. When the study area has an adequate density of observations we identified the best method to estimate the SI is the regression kriging with auxiliary variables (one of them is the SI estimated from satellite images. Thus it is possible to spatially estimate the SI beyond the 25 km identified in the literature. Otherwise, when the density of observations is inadequate the appropriateness is using the estimates values from remote sensing. It has been experimented with Artificial Neural Networks (ANN) modeling for predicting the short-term future of the SI using observations from neighbor’s weather stations (spatial components) in their inputs, and the results are promising. The error levels decrease under the following conditions: (1) when the prediction horizon is less or equal than 3 hours the best models are the ones that include data from the neighboring stations (at a maximum distance of 55 km). It is concluded that the ANN is able to learn how weather conditions affect neighboring prediction of IS at such Spatio-temporal horizons.