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.

Sistema eléctrico y de control de potencia de un túnel aerodinámico = Design of the power distribution and control system for a wind tunnel facility

Este proyecto trata de diseñar el sistema eléctrico y de control de potencia de una maqueta del túnel aerodinámico ACLA-16 de la Universidad Politécnica de Madrid (UPM). Dicha maqueta se utiliza para estudiar el efecto de la capa límite atmosférica, debido a su importancia en el impacto sobre estructuras civiles. Primero se desarrolla una parte teórica sobre qué son los túneles aerodinámicos, las aplicaciones que tienen y conceptos básicos acerca de la capa límite atmosférica. Luego se analiza el diseño geométrico de la maqueta del túnel y se detallan los elementos que debe tener el sistema eléctrico. Además, se realiza una simulación por ordenador con un programa de CFD (Fluent) para comparar los resultados experimentales reales con los resultados numéricos de la simulación para comprobar si se pueden extraer resultados aceptables por ordenador y así ahorrar costes y tiempo en el estudio de ensayos.

Sistema eléctrico y de control de potencia de un túnel aerodinámico = Design of the power distribution and control system for a wind tunnel facility

El proyecto está basado en el estudio de la planta de potencia de un túnel aerodinámico. Para ello se ha realizado una breve introducción definiendo qué es un túnel aerodinámico, cuál es su propósito, qué tipos hay, etc. Posteriormente se ha escogido un tipo concreto de túnel entre todas las posibilidades y se ha procedido a su estudio. Se ha definido una forma y unas dimensiones y tras calcular las pérdidas de carga, se ha seleccionado la planta de potencia necesaria para compensar dichas pérdidas, dimensionándose también las conexiones de esta desde la acometida de potencia eléctrica. Por último se han dimensionado las conexiones correspondientes a la iluminación y los servicios que competen al túnel aerodinámico.

Sistema eléctrico y de control de potencia de un tunel aerodinámico = Design of the power distributation and control system for a wind tunnel facility

La utilización de túneles aerodinámicos en ingeniería civil está cada vez más demandada debido al actual desarrollo urbanístico, esto es, la necesidad de edificios cada vez más altos en los que concentrar mayor cantidad de población, puentes y estructuras que faciliten el paso de medios de transporte alternativos, la importancia de los aspectos artísticos en la construcción (además de los funcionales), etc. Son muchos los factores que pueden hacer necesario el ensayo de alguna de esas estructuras en un túnel aerodinámico, y no existe un criterio universal a la hora de decidir si conviene o no hacerlo.

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

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.

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.

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 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

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.

Design and Optimization of Power Delivery and Distribution Systems Using Evolutionary Computation Techniques

Nowadays computing platforms consist of a very large number of components that require to be supplied with diferent voltage levels and power requirements. Even a very small platform, like a handheld computer, may contain more than twenty diferent loads and voltage regulators. The power delivery designers of these systems are required to provide, in a very short time, the right power architecture that optimizes the performance, meets electrical specifications plus cost and size targets. The appropriate selection of the architecture and converters directly defines the performance of a given solution. Therefore, the designer needs to be able to evaluate a significant number of options in order to know with good certainty whether the selected solutions meet the size, energy eficiency and cost targets. The design dificulties of selecting the right solution arise due to the wide range of power conversion products provided by diferent manufacturers. These products range from discrete components (to build converters) to complete power conversion modules that employ diferent manufacturing technologies. Consequently, in most cases it is not possible to analyze all the alternatives (combinations of power architectures and converters) that can be built. The designer has to select a limited number of converters in order to simplify the analysis. In this thesis, in order to overcome the mentioned dificulties, a new design methodology for power supply systems is proposed. This methodology integrates evolutionary computation techniques in order to make possible analyzing a large number of possibilities. This exhaustive analysis helps the designer to quickly define a set of feasible solutions and select the best trade-off in performance according to each application. The proposed approach consists of two key steps, one for the automatic generation of architectures and other for the optimized selection of components. In this thesis are detailed the implementation of these two steps. The usefulness of the methodology is corroborated by contrasting the results using real problems and experiments designed to test the limits of the algorithms.

Offshore Wind Farms: Foundations and influence on the Littoral Processes

Offshore wind farms are beginning to form part of coastal and marine landscapes located in dynamic surroundings. An integral management model must therefore be applied to achieve not only technical and economic viability of the project but also respect for the environment. Amongst other aspects, the latter calls for an analysis of the possible impact these facilities may have on littoral processes and this requires the differences between littoral processes prior and subsequent to the facility’s construction to be known. The maritime climate, the composition of the coast, lay-out distribution and characteristics of the facility’s components need to be known, particularly foundations as they are the main obstacles waves and currents meet. This article first addresses different aspects related to an offshore wind farm’s influence on the analysis of how it affects littoral dynamics and, because of their importance in this study, pays special attention to foundations. Coastal erosion due to this type of facility is then examined. The main conclusion of this article is that, whilst there are certain opinions claiming the coast is not affected by the presence of this kind of facility since the distance from location to coast and between wind turbine generators themselves is long, the impact must be analysed in each specific case, at least until experience proves otherwise and criteria are adopted in this respect.

A wavelet-based approach for large wind power ramp characterisation

A wavelet-based approach for large wind power ramp characterisation

Optimisation of a Low-Speed Wind Tunnel. Analysis and Redesign of Corner Vanes.

This paper includes the experimental study, analysis, redesign and subsequent test of the parts of a closed circuit, low speed wind tunnel which are relevant in terms of total pressure loss. The objective is to lower the energy consumption of this system for given conditions in test chamber, so as to reduce the operational costs. In order to achieve this objective, several tasks were performed as the text shows in its different parts. For these tasks, the ETSIAE wind tunnel was used, although the results of this work can be extrapolated to any wind tunnel with the same characteristics. Part II presents a theoretical previous study of the general running of a closed circuit, low speed wind tunnel, as well as the followed procedure to conduct experimental tests for obtaining the total pressure loss in its parts. Results from these tests and their analysis are included in this part. In part III, the analysis of the influence of corner 1 on the pressure loss takes place. As it is said in this part, corner 1 has great importance in the total pressure loss of the wind tunnel. Therefore, it is the first part that should be modified in order to improve the performances of the wind tunnel. During part IV, an optimised guide vane is designed in order to reduce the pressure loss in corner 1 of the wind tunnel. Software MISES is used to achieve this goal by means of selecting the optimum guide vane. In order to introduce the new guide vane in wind tunnels with affordable costs, the easily constructable criterion is kept during design. For this reason, the guide vane will consist of simple aerodynamic contours. Part V includes some possible improvements for the proposed guide vane, in order to evaluate if there is room for improvement in its design. Finally, part VI includes the tests that were conducted in the wind tunnel with the new guide vane cascade and the analysis of their results, in order to asses whether the proposed design fulfills the requirement of lowering the total pressure loss in the wind tunnel. Part VII gathers the main ideas resulting from the whole work.

Equipment and procedures for ON-SITE testing of PV plants and BIPV

Actual system performance of a PV system can differ from its expected behaviour.. This is the main reason why the performance of PV systems should be monitored, analyzed and, if needed, improved on. Some of the current testing procedures relating to the electrical behaviour of PV systems are appropriated for detecting electrical performance losses, but they are not well-suited to reveal hidden defects in the modules of PV plants and BIPV, which can lead to future losses. This paper reports on the tests and procedures used to evaluate the performance of PV systems, and especially on a novel procedure for quick on-site measurements and defect recognition caused by overheating in PV modules located in operating PV installations.