Seasonal Dynamic Factor Analysis and Bootstrap Inference: Application to Electricity Market Forecasting

In this work, we propose the Seasonal Dynamic Factor Analysis (SeaDFA), an extension of Nonstationary Dynamic Factor Analysis, through which one can deal with dimensionality reduction in vectors of time series in such a way that both common and specific components are extracted. Furthermore, common factors are able to capture not only regular dynamics (stationary or not) but also seasonal ones, by means of the common factors following a multiplicative seasonal VARIMA(p, d, q) × (P, D, Q)s model. Additionally, a bootstrap procedure that does not need a backward representation of the model is proposed to be able to make inference for all the parameters in the model. A bootstrap scheme developed for forecasting includes uncertainty due to parameter estimation, allowing enhanced coverage of forecasting intervals. A challenging application is provided. The new proposed model and a bootstrap scheme are applied to an innovative subject in electricity markets: the computation of long-term point forecasts and prediction intervals of electricity prices. Several appendices with technical details, an illustrative example, and an additional table are available online as Supplementary Materials.

The first renewable forward market mechanisms in the Iberian Electricity Market

A description of the first renewable forward market mechanisms in the Iberian Electricity Market is provided. A contract for difference mechanism is available in Spain since March 2011between the last resort suppliers and the special regime (renewables and cogeneration) settling the price differences between the equilibrium price of the forward regulated auctions for the last resort supply and the spot price of the corresponding delivery period. Regulated auctions of baseload futures of the Portuguese zone in which the Portuguese last resort supplier sells the special regime production exist since December 2011. The experience gained from renewables auctions in Latin America could be used in the Iberian Electricity market, complementing these first market mechanisms. Introduction of renewable auctions at least for the most mature technologies (i.e. wind) in Spain and Portugal providing a fair price for the renewable generation will be of utmost importance in the short term to diminish the tariff deficit caused by the massive deployment of the feed-in-tariff scheme. Liquidity in the forward markets will also increase as a result of the entry of renewable generation companies intending to maximize their profits due to gradual suppression of feed in tariff schemes.

Unit Commitment and Electricity Prices Forecasting for Market Strategy Preparation in Interconnected Systems

In this paper we present a solution for building a better strategy to take part in external electricity markets. For an optimal strategy development, both the internal system costs as well as the future values of the series of electricity prices in external markets need to be known. But in practice, the real problems that must be faced are that both future electricity prices and costs are unknown. Thus, the first ones must be modeled and forecasted and the costs must be calculated. Our methodology for building an optimal strategy consists of three steps: The first step is modeling and forecasting market prices in external systems. The second step is the cost calculation on internal system taking into account the expected prices in the first step. The third step is based on the results of the previous steps, and consists of preparing the bids for external markets. The main goal is to reduce consumers' costs unlike many others that are oriented to increase GenCo's profits.

Analysis of the Iberian electricity forward market hedging efficiency

An assessment of the hedging performance in the Iberian Forward Electricity Market is performed. Aggregated data from the Portuguese and Spanish clearing houses for energy derivatives are considered. The hedging performance is measured through the ratio of the final open interest of a month derivatives contract divided by its accumulated cleared volume. The base load futures in the Iberian energy derivatives exchange show the lowest ratios due to good liquidity. The peak futures show bigger ratios as their reduced liquidity is produced by auctions fixed by Portuguese regulation. The base load swaps settled in the clearing house located in Spain show initially large values due to low registered volumes, as this clearing house is mainly used for short maturity (daily and weekly swaps). This hedging ratio can be a powerful oversight tool for energy regulators when accessing to all the derivatives transactions as envisaged by European regulation.

Propuestas regulatorias para el diseño de un mercado ibérico a plazo eficiente de la energía = Regulatory proposals for the development of an efficient iberian energy forward market

El mercado ibérico de futuros de energía eléctrica gestionado por OMIP (“Operador do Mercado Ibérico de Energia, Pólo Português”, con sede en Lisboa), también conocido como el mercado ibérico de derivados de energía, comenzó a funcionar el 3 de julio de 2006. Se analiza la eficiencia de este mercado organizado, por lo que se estudia la precisión con la que sus precios de futuros predicen el precio de contado. En dicho mercado coexisten dos modos de negociación: el mercado continuo (modo por defecto) y la contratación mediante subasta. En la negociación en continuo, las órdenes anónimas de compra y de venta interactúan de manera inmediata e individual con órdenes contrarias, dando lugar a operaciones con un número indeterminado de precios para cada contrato. En la negociación a través de subasta, un precio único de equilibrio maximiza el volumen negociado, liquidándose todas las operaciones a ese precio. Adicionalmente, los miembros negociadores de OMIP pueden liquidar operaciones “Over-The-Counter” (OTC) a través de la cámara de compensación de OMIP (OMIClear). Las cinco mayores empresas españolas de distribución de energía eléctrica tenían la obligación de comprar electricidad hasta julio de 2009 en subastas en OMIP, para cubrir parte de sus suministros regulados. De igual manera, el suministrador de último recurso portugués mantuvo tal obligación hasta julio de 2010. Los precios de equilibrio de esas subastas no han resultado óptimos a efectos retributivos de tales suministros regulados dado que dichos precios tienden a situarse ligeramente sesgados al alza. La prima de riesgo ex-post, definida como la diferencia entre los precios a plazo y de contado en el periodo de entrega, se emplea para medir su eficiencia de precio. El mercado de contado, gestionado por OMIE (“Operador de Mercado Ibérico de la Energía”, conocido tradicionalmente como “OMEL”), tiene su sede en Madrid. Durante los dos primeros años del mercado de futuros, la prima de riesgo media tiende a resultar positiva, al igual que en otros mercados europeos de energía eléctrica y gas natural. En ese periodo, la prima de riesgo ex-post tiende a ser negativa en los mercados de petróleo y carbón. Los mercados de energía tienden a mostrar niveles limitados de eficiencia de mercado. La eficiencia de precio del mercado de futuros aumenta con el desarrollo de otros mecanismos coexistentes dentro del mercado ibérico de electricidad (conocido como “MIBEL”) –es decir, el mercado dominante OTC, las subastas de centrales virtuales de generación conocidas en España como Emisiones Primarias de Energía, y las subastas para cubrir parte de los suministros de último recurso conocidas en España como subastas CESUR– y con una mayor integración de los mercados regionales europeos de energía eléctrica. Se construye un modelo de regresión para analizar la evolución de los volúmenes negociados en el mercado continuo durante sus cuatro primeros años como una función de doce indicadores potenciales de liquidez. Los únicos indicadores significativos son los volúmenes negociados en las subastas obligatorias gestionadas por OMIP, los volúmenes negociados en el mercado OTC y los volúmenes OTC compensados por OMIClear. El número de creadores de mercado, la incorporación de agentes financieros y compañías de generación pertenecientes a grupos integrados con suministradores de último recurso, y los volúmenes OTC compensados por OMIClear muestran una fuerte correlación con los volúmenes negociados en el mercado continuo. La liquidez de OMIP está aún lejos de los niveles alcanzados por los mercados europeos más maduros (localizados en los países nórdicos (Nasdaq OMX Commodities) y Alemania (EEX)). El operador de mercado y su cámara de compensación podrían desarrollar acciones eficientes de marketing para atraer nuevos agentes activos en el mercado de contado (p.ej. industrias consumidoras intensivas de energía, suministradores, pequeños productores, compañías energéticas internacionales y empresas de energías renovables) y agentes financieros, captar volúmenes del opaco OTC, y mejorar el funcionamiento de los productos existentes aún no líquidos. Resultaría de gran utilidad para tales acciones un diálogo activo con todos los agentes (participantes en el mercado, operador de mercado de contado, y autoridades supervisoras). Durante sus primeros cinco años y medio, el mercado continuo presenta un crecimento de liquidez estable. Se mide el desempeño de sus funciones de cobertura mediante la ratio de posición neta obtenida al dividir la posición abierta final de un contrato de derivados mensual entre su volumen acumulado en la cámara de compensación. Los futuros carga base muestran la ratio más baja debido a su buena liquidez. Los futuros carga punta muestran una mayor ratio al producirse su menor liquidez a través de contadas subastas fijadas por regulación portuguesa. Las permutas carga base liquidadas en la cámara de compensación ubicada en Madrid –MEFF Power, activa desde el 21 de marzo de 2011– muestran inicialmente valores altos debido a bajos volúmenes registrados, dado que esta cámara se emplea principalmente para vencimientos pequeños (diario y semanal). Dicha ratio puede ser una poderosa herramienta de supervisión para los reguladores energéticos cuando accedan a todas las transacciones de derivados en virtud del Reglamento Europeo sobre Integridad y Transparencia de los Mercados de Energía (“REMIT”), en vigor desde el 28 de diciembre de 2011. La prima de riesgo ex-post tiende a ser positiva en todos los mecanismos (futuros en OMIP, mercado OTC y subastas CESUR) y disminuye debido a la curvas de aprendizaje y al efecto, desde el año 2011, del precio fijo para la retribución de la generación con carbón autóctono. Se realiza una comparativa con los costes a plazo de generación con gas natural (diferencial “clean spark spread”) obtenido como la diferencia entre el precio del futuro eléctrico y el coste a plazo de generación con ciclo combinado internalizando los costes de emisión de CO2. Los futuros eléctricos tienen una elevada correlación con los precios de gas europeos. Los diferenciales de contratos con vencimiento inmediato tienden a ser positivos. Los mayores diferenciales se dan para los contratos mensuales, seguidos de los trimestrales y anuales. Los generadores eléctricos con gas pueden maximizar beneficios con contratos de menor vencimiento. Los informes de monitorización por el operador de mercado que proporcionan transparencia post-operacional, el acceso a datos OTC por el regulador energético, y la valoración del riesgo regulatorio pueden contribuir a ganancias de eficiencia. Estas recomendaciones son también válidas para un potencial mercado ibérico de futuros de gas, una vez que el hub ibérico de gas –actualmente en fase de diseño, con reuniones mensuales de los agentes desde enero de 2013 en el grupo de trabajo liderado por el regulador energético español– esté operativo. El hub ibérico de gas proporcionará transparencia al atraer más agentes y mejorar la competencia, incrementando su eficiencia, dado que en el mercado OTC actual no se revela precio alguno de gas. ABSTRACT The Iberian Power Futures Market, managed by OMIP (“Operador do Mercado Ibérico de Energia, Pólo Português”, located in Lisbon), also known as the Iberian Energy Derivatives Market, started operations on 3 July 2006. The market efficiency, regarding how well the future price predicts the spot price, is analysed for this energy derivatives exchange. There are two trading modes coexisting within OMIP: the continuous market (default mode) and the call auction. In the continuous trading, anonymous buy and sell orders interact immediately and individually with opposite side orders, generating trades with an undetermined number of prices for each contract. In the call auction trading, a single price auction maximizes the traded volume, being all trades settled at the same price (equilibrium price). Additionally, OMIP trading members may settle Over-the-Counter (OTC) trades through OMIP clearing house (OMIClear). The five largest Spanish distribution companies have been obliged to purchase in auctions managed by OMIP until July 2009, in order to partly cover their portfolios of end users’ regulated supplies. Likewise, the Portuguese last resort supplier kept that obligation until July 2010. The auction equilibrium prices are not optimal for remuneration purposes of regulated supplies as such prices seem to be slightly upward biased. The ex-post forward risk premium, defined as the difference between the forward and spot prices in the delivery period, is used to measure its price efficiency. The spot market, managed by OMIE (Market Operator of the Iberian Energy Market, Spanish Pool, known traditionally as “OMEL”), is located in Madrid. During the first two years of the futures market, the average forward risk premium tends to be positive, as it occurs with other European power and natural gas markets. In that period, the ex-post forward risk premium tends to be negative in oil and coal markets. Energy markets tend to show limited levels of market efficiency. The price efficiency of the Iberian Power Futures Market improves with the market development of all the coexistent forward contracting mechanisms within the Iberian Electricity Market (known as “MIBEL”) – namely, the dominant OTC market, the Virtual Power Plant Auctions known in Spain as Energy Primary Emissions, and the auctions catering for part of the last resort supplies known in Spain as CESUR auctions – and with further integration of European Regional Electricity Markets. A regression model tracking the evolution of the traded volumes in the continuous market during its first four years is built as a function of twelve potential liquidity drivers. The only significant drivers are the traded volumes in OMIP compulsory auctions, the traded volumes in the OTC market, and the OTC cleared volumes by OMIClear. The amount of market makers, the enrolment of financial members and generation companies belonging to the integrated group of last resort suppliers, and the OTC cleared volume by OMIClear show strong correlation with the traded volumes in the continuous market. OMIP liquidity is still far from the levels reached by the most mature European markets (located in the Nordic countries (Nasdaq OMX Commodities) and Germany (EEX)). The market operator and its clearing house could develop efficient marketing actions to attract new entrants active in the spot market (e.g. energy intensive industries, suppliers, small producers, international energy companies and renewable generation companies) and financial agents as well as volumes from the opaque OTC market, and to improve the performance of existing illiquid products. An active dialogue with all the stakeholders (market participants, spot market operator, and supervisory authorities) will help to implement such actions. During its firs five and a half years, the continuous market shows steady liquidity growth. The hedging performance is measured through a net position ratio obtained from the final open interest of a month derivatives contract divided by its accumulated cleared volume. The base load futures in the Iberian energy derivatives exchange show the lowest ratios due to good liquidity. The peak futures show bigger ratios as their reduced liquidity is produced by auctions fixed by Portuguese regulation. The base load swaps settled in the clearing house located in Spain – MEFF Power, operating since 21 March 2011, with a new denomination (BME Clearing) since 9 September 2013 – show initially large values due to low registered volumes, as this clearing house is mainly used for short maturity (daily and weekly swaps). The net position ratio can be a powerful oversight tool for energy regulators when accessing to all the derivatives transactions as envisaged by European regulation on Energy Market Integrity and Transparency (“REMIT”), in force since 28 December 2011. The ex-post forward risk premium tends to be positive in all existing mechanisms (OMIP futures, OTC market and CESUR auctions) and diminishes due to the learning curve and the effect – since year 2011 – of the fixed price retributing the indigenous coal fired generation. Comparison with the forward generation costs from natural gas (“clean spark spread”) – obtained as the difference between the power futures price and the forward generation cost with a gas fired combined cycle plant taking into account the CO2 emission rates – is also performed. The power futures are strongly correlated with European gas prices. The clean spark spreads built with prompt contracts tend to be positive. The biggest clean spark spreads are for the month contract, followed by the quarter contract and then by the year contract. Therefore, gas fired generation companies can maximize profits trading with contracts of shorter maturity. Market monitoring reports by the market operator providing post-trade transparency, OTC data access by the energy regulator, and assessment of the regulatory risk can contribute to efficiency gains. The same recommendations are also valid for a potential Iberian gas futures market, once an Iberian gas hub – currently in a design phase, with monthly meetings amongst the stakeholders in a Working Group led by the Spanish energy regulatory authority since January 2013 – is operating. The Iberian gas hub would bring transparency attracting more shippers and improving competition and thus its efficiency, as no gas price is currently disclosed in the existing OTC market.

Explanation of changes in real estate stock market

The aim of this study is to explain the changes in the real estate prices as well as in the real estate stock market prices, using some macro-economic explanatory variables, such as the gross domestic product (GDP), the real interest rate and the unemployment rate. Several regressions have been carried out in order to express some types of incremental and absolute deflated real estate lock market indexes in terms of the macro-economic variables. The analyses are applied to the Swedish economy. The period under study is 1984-1994. Time series on monthly data are used. i.e. the number of data-points is 132. If time leads/lags are introduced in the e regressions, significant improvements in the already high correlations are achieved. The signs of the coefficients for IR, UE and GDP are all what one would expect to see from an economic point of view: those for GDP are all positive, those for both IR and UE are negative. All the regressions have high R2 values. Both markets anticipate change in the unemployment rate by 6 to 9 months, which seems reasonable because such change can be forecast quite reliably. But, on the contrary, there is no reason why they should anticipate by 3-6 months changes in the interest rate that can hardly be reliably forecast so far in advance.

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.

Climate variability effects on field crops in Iberian Peninsula. Predictability

La presente Tesis constituye un avance en el conocimiento de los efectos de la variabilidad climática en los cultivos en la Península Ibérica (PI). Es bien conocido que la temperatura del océano, particularmente de la región tropical, es una de las variables más convenientes para ser utilizado como predictor climático. Los océanos son considerados como la principal fuente de almacenamiento de calor del planeta debido a la alta capacidad calorífica del agua. Cuando se libera esta energía, altera los regímenes globales de circulación atmosférica por mecanismos de teleconexión. Estos cambios en la circulación general de la atmósfera afectan a la temperatura, precipitación, humedad, viento, etc., a escala regional, los cuales afectan al crecimiento, desarrollo y rendimiento de los cultivos. Para el caso de Europa, esto implica que la variabilidad atmosférica en una región específica se asocia con la variabilidad de otras regiones adyacentes y/o remotas, como consecuencia Europa está siendo afectada por los patrones de circulaciones globales, que a su vez, se ven afectados por patrones oceánicos. El objetivo general de esta tesis es analizar la variabilidad del rendimiento de los cultivos y su relación con la variabilidad climática y teleconexiones, así como evaluar su predictibilidad. Además, esta Tesis tiene como objetivo establecer una metodología para estudiar la predictibilidad de las anomalías del rendimiento de los cultivos. El análisis se centra en trigo y maíz como referencia para otros cultivos de la PI, cultivos de invierno en secano y cultivos de verano en regadío respectivamente. Experimentos de simulación de cultivos utilizando una metodología en cadena de modelos (clima + cultivos) son diseñados para evaluar los impactos de los patrones de variabilidad climática en el rendimiento y su predictibilidad. La presente Tesis se estructura en dos partes: La primera se centra en el análisis de la variabilidad del clima y la segunda es una aplicación de predicción cuantitativa de cosechas. La primera parte está dividida en 3 capítulos y la segundo en un capitulo cubriendo los objetivos específicos del presente trabajo de investigación. Parte I. Análisis de variabilidad climática El primer capítulo muestra un análisis de la variabilidad del rendimiento potencial en una localidad como indicador bioclimático de las teleconexiones de El Niño con Europa, mostrando su importancia en la mejora de predictibilidad tanto en clima como en agricultura. Además, se presenta la metodología elegida para relacionar el rendimiento con las variables atmosféricas y oceánicas. El rendimiento de los cultivos es parcialmente determinado por la variabilidad climática atmosférica, que a su vez depende de los cambios en la temperatura de la superficie del mar (TSM). El Niño es el principal modo de variabilidad interanual de la TSM, y sus efectos se extienden en todo el mundo. Sin embargo, la predictibilidad de estos impactos es controversial, especialmente aquellos asociados con la variabilidad climática Europea, que se ha encontrado que es no estacionaria y no lineal. Este estudio mostró cómo el rendimiento potencial de los cultivos obtenidos a partir de datos de reanálisis y modelos de cultivos sirve como un índice alternativo y más eficaz de las teleconexiones de El Niño, ya que integra las no linealidades entre las variables climáticas en una única serie temporal. Las relaciones entre El Niño y las anomalías de rendimiento de los cultivos son más significativas que las contribuciones individuales de cada una de las variables atmosféricas utilizadas como entrada en el modelo de cultivo. Además, la no estacionariedad entre El Niño y la variabilidad climática europea se detectan con mayor claridad cuando se analiza la variabilidad de los rendimiento de los cultivos. La comprensión de esta relación permite una cierta predictibilidad hasta un año antes de la cosecha del cultivo. Esta predictibilidad no es constante, sino que depende tanto la modulación de la alta y baja frecuencia. En el segundo capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de verano en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de maíz en la PI para todo el siglo veinte, usando un modelo de cultivo calibrado en 5 localidades españolas y datos climáticos de reanálisis para obtener series temporales largas de rendimiento potencial. Este estudio evalúa el uso de datos de reanálisis para obtener series de rendimiento de cultivos que dependen solo del clima, y utilizar estos rendimientos para analizar la influencia de los patrones oceánicos y atmosféricos. Los resultados muestran una gran fiabilidad de los datos de reanálisis. La distribución espacial asociada a la primera componente principal de la variabilidad del rendimiento muestra un comportamiento similar en todos los lugares estudiados de la PI. Se observa una alta correlación lineal entre el índice de El Niño y el rendimiento, pero no es estacionaria en el tiempo. Sin embargo, la relación entre la temperatura del aire y el rendimiento se mantiene constante a lo largo del tiempo, siendo los meses de mayor influencia durante el período de llenado del grano. En cuanto a los patrones atmosféricos, el patrón Escandinavia presentó una influencia significativa en el rendimiento en PI. En el tercer capítulo se identifica los patrones oceánicos y atmosféricos de variabilidad climática que afectan a los cultivos de invierno en la PI. Además, se presentan hipótesis acerca del mecanismo eco-fisiológico a través del cual el cultivo responde. Este estudio se centra en el análisis de la variabilidad del rendimiento de trigo en secano del Noreste (NE) de la PI. La variabilidad climática es el principal motor de los cambios en el crecimiento, desarrollo y rendimiento de los cultivos, especialmente en los sistemas de producción en secano. En la PI, los rendimientos de trigo son fuertemente dependientes de la cantidad de precipitación estacional y la distribución temporal de las mismas durante el periodo de crecimiento del cultivo. La principal fuente de variabilidad interanual de la precipitación en la PI es la Oscilación del Atlántico Norte (NAO), que se ha relacionado, en parte, con los cambios en la temperatura de la superficie del mar en el Pacífico Tropical (El Niño) y el Atlántico Tropical (TNA). La existencia de cierta predictibilidad nos ha animado a analizar la posible predicción de los rendimientos de trigo en la PI utilizando anomalías de TSM como predictor. Para ello, se ha utilizado un modelo de cultivo (calibrado en dos localidades del NE de la PI) y datos climáticos de reanálisis para obtener series temporales largas de rendimiento de trigo alcanzable y relacionar su variabilidad con anomalías de la TSM. Los resultados muestran que El Niño y la TNA influyen en el desarrollo y rendimiento del trigo en el NE de la PI, y estos impactos depende del estado concurrente de la NAO. Aunque la relación cultivo-TSM no es igual durante todo el periodo analizado, se puede explicar por un mecanismo eco-fisiológico estacionario. Durante la segunda mitad del siglo veinte, el calentamiento (enfriamiento) en la superficie del Atlántico tropical se asocia a una fase negativa (positiva) de la NAO, que ejerce una influencia positiva (negativa) en la temperatura mínima y precipitación durante el invierno y, por lo tanto, aumenta (disminuye) el rendimiento de trigo en la PI. En relación con El Niño, la correlación más alta se observó en el período 1981 -2001. En estas décadas, los altos (bajos) rendimientos se asocian con una transición El Niño - La Niña (La Niña - El Niño) o con eventos de El Niño (La Niña) que están finalizando. Para estos eventos, el patrón atmosférica asociada se asemeja a la NAO, que también influye directamente en la temperatura máxima y precipitación experimentadas por el cultivo durante la floración y llenado de grano. Los co- efectos de los dos patrones de teleconexión oceánicos ayudan a aumentar (disminuir) la precipitación y a disminuir (aumentar) la temperatura máxima en PI, por lo tanto el rendimiento de trigo aumenta (disminuye). Parte II. Predicción de cultivos. En el último capítulo se analiza los beneficios potenciales del uso de predicciones climáticas estacionales (por ejemplo de precipitación) en las predicciones de rendimientos de trigo y maíz, y explora métodos para aplicar dichos pronósticos climáticos en modelos de cultivo. Las predicciones climáticas estacionales tienen un gran potencial en las predicciones de cultivos, contribuyendo de esta manera a una mayor eficiencia de la gestión agrícola, seguridad alimentaria y de subsistencia. Los pronósticos climáticos se expresan en diferentes formas, sin embargo todos ellos son probabilísticos. Para ello, se evalúan y aplican dos métodos para desagregar las predicciones climáticas estacionales en datos diarios: 1) un generador climático estocástico condicionado (predictWTD) y 2) un simple re-muestreador basado en las probabilidades del pronóstico (FResampler1). Los dos métodos se evaluaron en un caso de estudio en el que se analizaron los impactos de tres escenarios de predicciones de precipitación estacional (predicción seco, medio y lluvioso) en el rendimiento de trigo en secano, sobre las necesidades de riego y rendimiento de maíz en la PI. Además, se estimó el margen bruto y los riesgos de la producción asociada con las predicciones de precipitación estacional extremas (seca y lluviosa). Los métodos predWTD y FResampler1 usados para desagregar los pronósticos de precipitación estacional en datos diarios, que serán usados como inputs en los modelos de cultivos, proporcionan una predicción comparable. Por lo tanto, ambos métodos parecen opciones factibles/viables para la vinculación de los pronósticos estacionales con modelos de simulación de cultivos para establecer predicciones de rendimiento o las necesidades de riego en el caso de maíz. El análisis del impacto en el margen bruto de los precios del grano de los dos cultivos (trigo y maíz) y el coste de riego (maíz) sugieren que la combinación de los precios de mercado previstos y la predicción climática estacional pueden ser una buena herramienta en la toma de decisiones de los agricultores, especialmente en predicciones secas y/o localidades con baja precipitación anual. Estos métodos permiten cuantificar los beneficios y riesgos de los agricultores ante una predicción climática estacional en la PI. Por lo tanto, seríamos capaces de establecer sistemas de alerta temprana y diseñar estrategias de adaptación del manejo del cultivo para aprovechar las condiciones favorables o reducir los efectos de condiciones adversas. La utilidad potencial de esta Tesis es la aplicación de las relaciones encontradas para predicción de cosechas de la próxima campaña agrícola. Una correcta predicción de los rendimientos podría ayudar a los agricultores a planear con antelación sus prácticas agronómicas y todos los demás aspectos relacionados con el manejo de los cultivos. Esta metodología se puede utilizar también para la predicción de las tendencias futuras de la variabilidad del rendimiento en la PI. Tanto los sectores públicos (mejora de la planificación agrícola) como privados (agricultores, compañías de seguros agrarios) pueden beneficiarse de esta mejora en la predicción de cosechas. ABSTRACT The present thesis constitutes a step forward in advancing of knowledge of the effects of climate variability on crops in the Iberian Peninsula (IP). It is well known that ocean temperature, particularly the tropical ocean, is one of the most convenient variables to be used as climate predictor. Oceans are considered as the principal heat storage of the planet due to the high heat capacity of water. When this energy is released, it alters the global atmospheric circulation regimes by teleconnection1 mechanisms. These changes in the general circulation of the atmosphere affect the regional temperature, precipitation, moisture, wind, etc., and those influence crop growth, development and yield. For the case of Europe, this implies that the atmospheric variability in a specific region is associated with the variability of others adjacent and/or remote regions as a consequence of Europe being affected by global circulations patterns which, in turn, are affected by oceanic patterns. The general objective of this Thesis is to analyze the variability of crop yields at climate time scales and its relation to the climate variability and teleconnections, as well as to evaluate their predictability. Moreover, this Thesis aims to establish a methodology to study the predictability of crop yield anomalies. The analysis focuses on wheat and maize as a reference crops for other field crops in the IP, for winter rainfed crops and summer irrigated crops respectively. Crop simulation experiments using a model chain methodology (climate + crop) are designed to evaluate the impacts of climate variability patterns on yield and its predictability. The present Thesis is structured in two parts. The first part is focused on the climate variability analyses, and the second part is an application of the quantitative crop forecasting for years that fulfill specific conditions identified in the first part. This Thesis is divided into 4 chapters, covering the specific objectives of the present research work. Part I. Climate variability analyses The first chapter shows an analysis of potential yield variability in one location, as a bioclimatic indicator of the El Niño teleconnections with Europe, putting forward its importance for improving predictability in both climate and agriculture. It also presents the chosen methodology to relate yield with atmospheric and oceanic variables. Crop yield is partially determined by atmospheric climate variability, which in turn depends on changes in the sea surface temperature (SST). El Niño is the leading mode of SST interannual variability, and its impacts extend worldwide. Nevertheless, the predictability of these impacts is controversial, especially those associated with European climate variability, which have been found to be non-stationary and non-linear. The study showed how potential2 crop yield obtained from reanalysis data and crop models serves as an alternative and more effective index of El Niño teleconnections because it integrates the nonlinearities between the climate variables in a unique time series. The relationships between El Niño and crop yield anomalies are more significant than the individual contributions of each of the atmospheric variables used as input in the crop model. Additionally, the non-stationarities between El Niño and European climate variability are more clearly detected when analyzing crop-yield variability. The understanding of this relationship allows for some predictability up to one year before the crop is harvested. This predictability is not constant, but depends on both high and low frequency modulation. The second chapter identifies the oceanic and atmospheric patterns of climate variability affecting summer cropping systems in the IP. Moreover, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of simulated crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The third chapter identifies the oceanic and atmospheric patterns of climate variability affecting winter cropping systems in the IP. Also, hypotheses about the eco-physiological mechanism behind crop response are presented. It is focused on an analysis of rainfed wheat yield variability in IP. Climate variability is the main driver of changes in crop growth, development and yield, especially for rainfed production systems. In IP, wheat yields are strongly dependent on seasonal rainfall amount and temporal distribution of rainfall during the growing season. The major source of precipitation interannual variability in IP is the North Atlantic Oscillation (NAO) which has been related in part with changes in the Tropical Pacific (El Niño) and Atlantic (TNA) sea surface temperature (SST). The existence of some predictability has encouraged us to analyze the possible predictability of the wheat yield in the IP using SSTs anomalies as predictor. For this purpose, a crop model with a site specific calibration for the Northeast of IP and reanalysis climate datasets have been used to obtain long time series of attainable wheat yield and relate their variability with SST anomalies. The results show that El Niño and TNA influence rainfed wheat development and yield in IP and these impacts depend on the concurrent state of the NAO. Although crop-SST relationships do not equally hold on during the whole analyzed period, they can be explained by an understood and stationary ecophysiological mechanism. During the second half of the twenty century, the positive (negative) TNA index is associated to a negative (positive) phase of NAO, which exerts a positive (negative) influence on minimum temperatures (Tmin) and precipitation (Prec) during winter and, thus, yield increases (decreases) in IP. In relation to El Niño, the highest correlation takes place in the period 1981-2001. For these decades, high (low) yields are associated with an El Niño to La Niña (La Niña to El Niño) transitions or to El Niño events finishing. For these events, the regional associated atmospheric pattern resembles the NAO, which also influences directly on the maximum temperatures (Tmax) and precipitation experienced by the crop during flowering and grain filling. The co-effects of the two teleconnection patterns help to increase (decrease) the rainfall and decrease (increase) Tmax in IP, thus on increase (decrease) wheat yield. Part II. Crop forecasting The last chapter analyses the potential benefits for wheat and maize yields prediction from using seasonal climate forecasts (precipitation), and explores methods to apply such a climate forecast to crop models. Seasonal climate prediction has significant potential to contribute to the efficiency of agricultural management, and to food and livelihood security. Climate forecasts come in different forms, but probabilistic. For this purpose, two methods were evaluated and applied for disaggregating seasonal climate forecast into daily weather realizations: 1) a conditioned stochastic weather generator (predictWTD) and 2) a simple forecast probability resampler (FResampler1). The two methods were evaluated in a case study where the impacts of three scenarios of seasonal rainfall forecasts on rainfed wheat yield, on irrigation requirements and yields of maize in IP were analyzed. In addition, we estimated the economic margins and production risks associated with extreme scenarios of seasonal rainfall forecasts (dry and wet). The predWTD and FResampler1 methods used for disaggregating seasonal rainfall forecast into daily data needed by the crop simulation models provided comparable predictability. Therefore both methods seem feasible options for linking seasonal forecasts with crop simulation models for establishing yield forecasts or irrigation water requirements. The analysis of the impact on gross margin of grain prices for both crops and maize irrigation costs suggests the combination of market prices expected and the seasonal climate forecast can be a good tool in farmer’s decision-making, especially on dry forecast and/or in locations with low annual precipitation. These methodologies would allow quantifying the benefits and risks of a seasonal weather forecast to farmers in IP. Therefore, we would be able to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. The potential usefulness of this Thesis is to apply the relationships found to crop forecasting on the next cropping season, suggesting opportunity time windows for the prediction. The methodology can be used as well for the prediction of future trends of IP yield variability. Both public (improvement of agricultural planning) and private (decision support to farmers, insurance companies) sectors may benefit from such an improvement of crop forecasting.

Wind turbine wakes for wind energy

During recent years, wind energy has moved from an emerging technology to a nearly competitive technology. This fact, coupled with an increasing global focus on environmental concern and a political desire of a certain level of diversification in the energy supply, ensures wind energy an important role in the future electricity market. For this challenge to be met in a cost-efficient way, a substantial part of new wind turbine installations is foreseen to be erected in big onshore or offshore wind farms. This fact makes the production, loading and reliability of turbines operating under such conditions of particular interest.

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

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.

El papel de la hidroelectricidad en el contexto de las energías renovables en España

En el artículo se discute el papel de la energía hidroeléctrica en el marco del sistema eléctrico español, donde existe una elevada penetración de energías no gestionables con una tendencia clara a aumentar en los próximos años. El desarrollo de nuevas centrales hidroeléctricas se basará probablemente en centrales reversibles. La energía hidroeléctrica es una tecnología madura y eficiente para el almacenamiento de energía a gran escala y contribuye por tanto de manera decisiva a la integración de fuentes renovables no gestionables. Los beneficios obtenidos con la operación punta-valle pueden ser insuficientes para compensar el coste de una nueva central. Sin embargo, los ingresos obtenidos pueden incrementarse sustancialmente mediante su participación en los servicios de ajuste del sistema. Ello requeriría un diseño apropiado del mercado eléctrico. La contribución de las centrales hidráulicas reversibles al balance producción-consumo puede extenderse a las horas valle utilizando, bien bombeo en velocidad variable o bien una configuración de cortocircuito hidráulico. La necesidad de mitigar los efectos hidrológicos aguas abajo de las centrales hidroeléctricas puede introducir algunas restricciones en la operación que limitaría de algún modo los servicios descritos más arriba. Sin embargo, cabe esperar que los efectos ambientales provocados por las centrales hidráulicas reversibles sean significativamente menores. In this paper the role of hydropower in electric power systems is discussed, in the framework of the Spanish system, where a high penetration of intermittent power sources exists, showing a clear trend to increase in next years. The development of new hydro power facilities will be likely based on pumped storage hydro power plants. Hydropower is a mature and efficient technology for large-scale energy storage and therefore represents a key contribution for the integration of intermittent power sources, such as wind or photovoltaic. The benefits obtained from load shifting may be insufficient to compensate the costs of a new plant. However, the obtained revenues can significantly increase through its contribution to providing ancillary services. This would require an appropriate design of the electricity market. The contribution of pumped storage hydro power plants to balancing services can be extended to off-peak hours, using either variable speed pumping or the hydraulic shortcircuit configuration. The need to mitigate hydrological effects downstream of hydro plants may introduce some operational constraints which could limit to some extent the services described above. However environmental effects caused by pumped storage hydro power plants are expected to be significantly smaller.

In-field assessment of batteries and PV modules in a large photovoltaic rural electrification programme

Assuring the sustainability of quality in photovoltaic rural electrification programmes involves enhancing the reliability of the components of solar home systems as well as the characterization of the overall programme cost structure. Batteries and photovoltaic modules have a great impact on both the reliability and the cost assessment, the battery being the weakest component of the solar home system and consequently the most expensive element of the programme. The photovoltaic module, despite being the most reliable component, has a significant impact cost-wise on the initial investment, even at current market prices. This paper focuses on the in-field testing of both batteries and photovoltaic modules working under real operating conditions within a sample of 41 solar home systems belonging to a large photovoltaic rural electrification programme with more than 13,000 installed photovoltaic systems. Different reliability parameters such as lifetime have been evaluated, taking into account different factors, for example energy consumption rates, or the manufacturing quality of batteries. A degradation model has been proposed relating both loss of capacity and time of operation. The user e solar home system binomial is also analysed in order to understand the meaning of battery lifetime in rural electrification.

Cost-free feed-in tariffs for renewable energy deployment in Spain

Feed-in-tariff (FIT) schemes have been widely employed to promote renewable energy deployment. While FITs may be perceived by consumers as an extra cost, renewable energies cause a noticeable price reduction in wholesale electricity markets. We analyse both effects for the case of the Spanish electricity market during 2010. In particular, we examine the level of FITs that makes savings and extra costs to be similar on an hourly basis. Results are obtained for a wide range of renewable generation scenarios. It is found that FITs with null extra costs for consumers are in the range of 50–80 €/MWh. Some of the side-effects of a high penetration of renewable energy in the market are analysed in detail and discussed.

Forecasting Electricity Prices and their volatilities using Unobserved Components.

The liberalization of electricity markets more than ten years ago in the vast majority of developed countries has introduced the need of modelling and forecasting electricity prices and volatilities, both in the short and long term. Thus, there is a need of providing methodology that is able to deal with the most important features of electricity price series, which are well known for presenting not only structure in conditional mean but also time-varying conditional variances. In this work we propose a new model, which allows to extract conditionally heteroskedastic common factors from the vector of electricity prices. These common factors are jointly estimated as well as their relationship with the original vector of series, and the dynamics affecting both their conditional mean and variance. The estimation of the model is carried out under the state-space formulation. The new model proposed is applied to extract seasonal common dynamic factors as well as common volatility factors for electricity prices and the estimation results are used to forecast electricity prices and their volatilities in the Spanish zone of the Iberian Market. Several simplified/alternative models are also considered as benchmarks to illustrate that the proposed approach is superior to all of them in terms of explanatory and predictive power.