DISTRIBUTED APPROACH FOR SOLVING OPTIMAL POWER FLOW PROBLEMS IN THREE-PHASE UNBALANCED DISTRIBUTION NETWORK

The objective of this report is to study distributed (decentralized) three phase optimal power flow (OPF) problem in unbalanced power distribution networks. A full three phase representation of the distribution networks is considered to account for the highly unbalance state of the distribution networks. All distribution network’s series/shunt components, and load types/combinations had been modeled on commercial version of General Algebraic Modeling System (GAMS), the high-level modeling system for mathematical programming and optimization. The OPF problem has been successfully implemented and solved in a centralized approach and distributed approach, where the objective is to minimize the active power losses in the entire system. The study was implemented on the IEEE-37 Node Test Feeder. A detailed discussion of all problem sides and aspects starting from the basics has been provided in this study. Full simulation results have been provided at the end of the report.

Dynamic Optimization of SLA-Based Services Scaling Rules

Current advanced cloud infrastructure management solutions allow scheduling actions for dynamically changing the number of running virtual machines (VMs). This approach, however, does not guarantee that the scheduled number of VMs will properly handle the actual user generated workload, especially if the user utilization patterns will change. We propose using a dynamically generated scaling model for the VMs containing the services of the distributed applications, which is able to react to the variations in the number of application users. We answer the following question: How to dynamically decide how many services of each type are needed in order to handle a larger workload within the same time constraints? We describe a mechanism for dynamically composing the SLAs for controlling the scaling of distributed services by combining data analysis mechanisms with application benchmarking using multiple VM configurations. Based on processing of multiple application benchmarks generated data sets we discover a set of service monitoring metrics able to predict critical Service Level Agreement (SLA) parameters. By combining this set of predictor metrics with a heuristic for selecting the appropriate scaling-out paths for the services of distributed applications, we show how SLA scaling rules can be inferred and then used for controlling the runtime scale-in and scale-out of distributed services. We validate our architecture and models by performing scaling experiments with a distributed application representative for the enterprise class of information systems. We show how dynamically generated SLAs can be successfully used for controlling the management of distributed services scaling.

SLA-driven predictive orchestration for distributed cloud-based mobile services

We describe a system for performing SLA-driven management and orchestration of distributed infrastructures composed of services supporting mobile computing use cases. In particular, we focus on a Follow-Me Cloud scenario in which we consider mobile users accessing cloud-enable services. We combine a SLA-driven approach to infrastructure optimization, with forecast-based performance degradation preventive actions and pattern detection for supporting mobile cloud infrastructure management. We present our system's information model and architecture including the algorithmic support and the proposed scenarios for system evaluation.

Distributed Rate Allocation in Inter-Session Network Coding

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.

Service level agreements-driven management of distributed applications in cloud computing environments

Advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing workload conditions, such as number of connected users, application performance might suffer, leading to violations of Service Level Agreements (SLA) and possible inefficient use of hardware resources. Combining dynamic application requirements with the increased use of virtualised computing resources creates a challenging resource Management context for application and cloud-infrastructure owners. In such complex environments, business entities use SLAs as a means for specifying quantitative and qualitative requirements of services. There are several challenges in running distributed enterprise applications in cloud environments, ranging from the instantiation of service VMs in the correct order using an adequate quantity of computing resources, to adapting the number of running services in response to varying external loads, such as number of users. The application owner is interested in finding the optimum amount of computing and network resources to use for ensuring that the performance requirements of all her/his applications are met. She/he is also interested in appropriately scaling the distributed services so that application performance guarantees are maintained even under dynamic workload conditions. Similarly, the infrastructure Providers are interested in optimally provisioning the virtual resources onto the available physical infrastructure so that her/his operational costs are minimized, while maximizing the performance of tenants’ applications. Motivated by the complexities associated with the management and scaling of distributed applications, while satisfying multiple objectives (related to both consumers and providers of cloud resources), this thesis proposes a cloud resource management platform able to dynamically provision and coordinate the various lifecycle actions on both virtual and physical cloud resources using semantically enriched SLAs. The system focuses on dynamic sizing (scaling) of virtual infrastructures composed of virtual machines (VM) bounded application services. We describe several algorithms for adapting the number of VMs allocated to the distributed application in response to changing workload conditions, based on SLA-defined performance guarantees. We also present a framework for dynamic composition of scaling rules for distributed service, which used benchmark-generated application Monitoring traces. We show how these scaling rules can be combined and included into semantic SLAs for controlling allocation of services. We also provide a detailed description of the multi-objective infrastructure resource allocation problem and various approaches to satisfying this problem. We present a resource management system based on a genetic algorithm, which performs allocation of virtual resources, while considering the optimization of multiple criteria. We prove that our approach significantly outperforms reactive VM-scaling algorithms as well as heuristic-based VM-allocation approaches.

Self-organizing Routing Algorithm fo Wireless Sensors Networks (WSN) using Ant Colony Optimization (ACO) with Tinyos.

This paper describes the basic tools to work with wireless sensors. TinyOShas a componentbased architecture which enables rapid innovation and implementation while minimizing code size as required by the severe memory constraints inherent in sensor networks. TinyOS's component library includes network protocols, distributed services, sensor drivers, and data acquisition tools ? all of which can be used asia or be further refined for a custom application. TinyOS was originally developed as a research project at the University of California Berkeley, but has since grown to have an international community of developers and users. Some algorithms concerning packet routing are shown. Incar entertainment systems can be based on wireless sensors in order to obtain information from Internet, but routing protocols must be implemented in order to avoid bottleneck problems. Ant Colony algorithms are really useful in such cases, therefore they can be embedded into the sensors to perform such routing task.

Analysis of Chromatic Aberration Effects in Triple-Junction Solar Cells Using Advanced Distributed Models

The consideration of real operating conditions for the design and optimization of a multijunction solar cell receiver-concentrator assembly is indispensable. Such a requirement involves the need for suitable modeling and simulation tools in order to complement the experimental work and circumvent its well-known burdens and restrictions. Three-dimensional distributed models have been demonstrated in the past to be a powerful choice for the analysis of distributed phenomena in single- and dual-junction solar cells, as well as for the design of strategies to minimize the solar cell losses when operating under high concentrations. In this paper, we present the application of these models for the analysis of triple-junction solar cells under real operating conditions. The impact of different chromatic aberration profiles on the short-circuit current of triple-junction solar cells is analyzed in detail using the developed distributed model. Current spreading conditions the impact of a given chromatic aberration profile on the solar cell I-V curve. The focus is put on determining the role of current spreading in the connection between photocurrent profile, subcell voltage and current, and semiconductor layers sheet resistance.

PV self-consumption optimization with storage and Active DSM for the residential sector

With the rising prices of the retail electricity and the decreasing cost of the PV technology, grid parity with commercial electricity will soon become a reality in Europe. This fact, together with less attractive PV feed-in-tariffs in the near future and incentives to promote self-consumption suggest, that new operation modes for the PV Distributed Generation should be explored; differently from the traditional approach which is only based on maximizing the exported electricity to the grid. The smart metering is experiencing a growth in Europe and the United States but the possibilities of its use are still uncertain, in our system we propose their use to manage the storage and to allow the user to know their electrical power and energy balances. The ADSM has many benefits studied previously but also it has important challenges, in this paper we can observe and ADSM implementation example where we propose a solution to these challenges. In this paper we study the effects of the Active Demand-Side Management (ADSM) and storage systems in the amount of consumed local electrical energy. It has been developed on a prototype of a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead–acid batteries, controllable appliances and smart metering. We carried out simulations for long-time experiments (yearly studies) and real measures for short and mid-time experiments (daily and weekly studies). Results show the relationship between the electricity flows and the storage capacity, which is not linear and becomes an important design criterion.

Distributed collaborative processing in wireless sensor networks with application to target localization and beamforming

Abstract The proliferation of wireless sensor networks and the variety of envisioned applications associated with them has motivated the development of distributed algorithms for collaborative processing over networked systems. One of the applications that has attracted the attention of the researchers is that of target localization where the nodes of the network try to estimate the position of an unknown target that lies within its coverage area. Particularly challenging is the problem of estimating the target’s position when we use received signal strength indicator (RSSI) due to the nonlinear relationship between the measured signal and the true position of the target. Many of the existing approaches suffer either from high computational complexity (e.g., particle filters) or lack of accuracy. Further, many of the proposed solutions are centralized which make their application to a sensor network questionable. Depending on the application at hand and, from a practical perspective it could be convenient to find a balance between localization accuracy and complexity. Into this direction we approach the maximum likelihood location estimation problem by solving a suboptimal (and more tractable) problem. One of the main advantages of the proposed scheme is that it allows for a decentralized implementation using distributed processing tools (e.g., consensus and convex optimization) and therefore, it is very suitable to be implemented in real sensor networks. If further accuracy is needed an additional refinement step could be performed around the found solution. Under the assumption of independent noise among the nodes such local search can be done in a fully distributed way using a distributed version of the Gauss-Newton method based on consensus. Regardless of the underlying application or function of the sensor network it is al¬ways necessary to have a mechanism for data reporting. While some approaches use a special kind of nodes (called sink nodes) for data harvesting and forwarding to the outside world, there are however some scenarios where such an approach is impractical or even impossible to deploy. Further, such sink nodes become a bottleneck in terms of traffic flow and power consumption. To overcome these issues instead of using sink nodes for data reporting one could use collaborative beamforming techniques to forward directly the generated data to a base station or gateway to the outside world. In a dis-tributed environment like a sensor network nodes cooperate in order to form a virtual antenna array that can exploit the benefits of multi-antenna communications. In col-laborative beamforming nodes synchronize their phases in order to add constructively at the receiver. Some of the inconveniences associated with collaborative beamforming techniques is that there is no control over the radiation pattern since it is treated as a random quantity. This may cause interference to other coexisting systems and fast bat-tery depletion at the nodes. Since energy-efficiency is a major design issue we consider the development of a distributed collaborative beamforming scheme that maximizes the network lifetime while meeting some quality of service (QoS) requirement at the re¬ceiver side. Using local information about battery status and channel conditions we find distributed algorithms that converge to the optimal centralized beamformer. While in the first part we consider only battery depletion due to communications beamforming, we extend the model to account for more realistic scenarios by the introduction of an additional random energy consumption. It is shown how the new problem generalizes the original one and under which conditions it is easily solvable. By formulating the problem under the energy-efficiency perspective the network’s lifetime is significantly improved. Resumen La proliferación de las redes inalámbricas de sensores junto con la gran variedad de posi¬bles aplicaciones relacionadas, han motivado el desarrollo de herramientas y algoritmos necesarios para el procesado cooperativo en sistemas distribuidos. Una de las aplicaciones que suscitado mayor interés entre la comunidad científica es la de localization, donde el conjunto de nodos de la red intenta estimar la posición de un blanco localizado dentro de su área de cobertura. El problema de la localization es especialmente desafiante cuando se usan niveles de energía de la seal recibida (RSSI por sus siglas en inglés) como medida para la localization. El principal inconveniente reside en el hecho que el nivel de señal recibida no sigue una relación lineal con la posición del blanco. Muchas de las soluciones actuales al problema de localization usando RSSI se basan en complejos esquemas centralizados como filtros de partículas, mientas que en otras se basan en esquemas mucho más simples pero con menor precisión. Además, en muchos casos las estrategias son centralizadas lo que resulta poco prácticos para su implementación en redes de sensores. Desde un punto de vista práctico y de implementation, es conveniente, para ciertos escenarios y aplicaciones, el desarrollo de alternativas que ofrezcan un compromiso entre complejidad y precisión. En esta línea, en lugar de abordar directamente el problema de la estimación de la posición del blanco bajo el criterio de máxima verosimilitud, proponemos usar una formulación subóptima del problema más manejable analíticamente y que ofrece la ventaja de permitir en¬contrar la solución al problema de localization de una forma totalmente distribuida, convirtiéndola así en una solución atractiva dentro del contexto de redes inalámbricas de sensores. Para ello, se usan herramientas de procesado distribuido como los algorit¬mos de consenso y de optimización convexa en sistemas distribuidos. Para aplicaciones donde se requiera de un mayor grado de precisión se propone una estrategia que con¬siste en la optimización local de la función de verosimilitud entorno a la estimación inicialmente obtenida. Esta optimización se puede realizar de forma descentralizada usando una versión basada en consenso del método de Gauss-Newton siempre y cuando asumamos independencia de los ruidos de medida en los diferentes nodos. Independientemente de la aplicación subyacente de la red de sensores, es necesario tener un mecanismo que permita recopilar los datos provenientes de la red de sensores. Una forma de hacerlo es mediante el uso de uno o varios nodos especiales, llamados nodos “sumidero”, (sink en inglés) que actúen como centros recolectores de información y que estarán equipados con hardware adicional que les permita la interacción con el exterior de la red. La principal desventaja de esta estrategia es que dichos nodos se convierten en cuellos de botella en cuanto a tráfico y capacidad de cálculo. Como alter¬nativa se pueden usar técnicas cooperativas de conformación de haz (beamforming en inglés) de manera que el conjunto de la red puede verse como un único sistema virtual de múltiples antenas y, por tanto, que exploten los beneficios que ofrecen las comu¬nicaciones con múltiples antenas. Para ello, los distintos nodos de la red sincronizan sus transmisiones de manera que se produce una interferencia constructiva en el recep¬tor. No obstante, las actuales técnicas se basan en resultados promedios y asintóticos, cuando el número de nodos es muy grande. Para una configuración específica se pierde el control sobre el diagrama de radiación causando posibles interferencias sobre sis¬temas coexistentes o gastando más potencia de la requerida. La eficiencia energética es una cuestión capital en las redes inalámbricas de sensores ya que los nodos están equipados con baterías. Es por tanto muy importante preservar la batería evitando cambios innecesarios y el consecuente aumento de costes. Bajo estas consideraciones, se propone un esquema de conformación de haz que maximice el tiempo de vida útil de la red, entendiendo como tal el máximo tiempo que la red puede estar operativa garantizando unos requisitos de calidad de servicio (QoS por sus siglas en inglés) que permitan una decodificación fiable de la señal recibida en la estación base. Se proponen además algoritmos distribuidos que convergen a la solución centralizada. Inicialmente se considera que la única causa de consumo energético se debe a las comunicaciones con la estación base. Este modelo de consumo energético es modificado para tener en cuenta otras formas de consumo de energía derivadas de procesos inherentes al funcionamiento de la red como la adquisición y procesado de datos, las comunicaciones locales entre nodos, etc. Dicho consumo adicional de energía se modela como una variable aleatoria en cada nodo. Se cambia por tanto, a un escenario probabilístico que generaliza el caso determinista y se proporcionan condiciones bajo las cuales el problema se puede resolver de forma eficiente. Se demuestra que el tiempo de vida de la red mejora de forma significativa usando el criterio propuesto de eficiencia energética.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

A practical approach for outdoors distributed target localization in wireless sensor networks

Wireless sensor networks are posed as the new communication paradigm where the use of small, low-complexity, and low-power devices is preferred over costly centralized systems. The spectra of potential applications of sensor networks is very wide, ranging from monitoring, surveillance, and localization, among others. Localization is a key application in sensor networks and the use of simple, efficient, and distributed algorithms is of paramount practical importance. Combining convex optimization tools with consensus algorithms we propose a distributed localization algorithm for scenarios where received signal strength indicator readings are used. We approach the localization problem by formulating an alternative problem that uses distance estimates locally computed at each node. The formulated problem is solved by a relaxed version using semidefinite relaxation technique. Conditions under which the relaxed problem yields to the same solution as the original problem are given and a distributed consensusbased implementation of the algorithm is proposed based on an augmented Lagrangian approach and primaldual decomposition methods. Although suboptimal, the proposed approach is very suitable for its implementation in real sensor networks, i.e., it is scalable, robust against node failures and requires only local communication among neighboring nodes. Simulation results show that running an additional local search around the found solution can yield performance close to the maximum likelihood estimate.

Decentralized multi-tasks distribution in heterogeneous robot teams by means of ant colony optimization and learning automata

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-election of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested on decentralized solution where the robots themselves autonomously and in an individual manner, are responsible of selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-tasks distribution problem and we propose a solution using two different approaches by applying Ant Colony Optimization-based deterministic algorithms as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithm, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Heated fiber optic distributed temperature sensing for measuring soil volumetric heat capacity and water content: A dual probe heat-pulse approach

The first feasibility study of using dual-probe heated fiber optics with distributed temperature sensing to measure soil volumetric heat capacity and soil water content is presented. Although results using different combinations of cables demonstrate feasibility, further work is needed to gain accuracy, including a model to account for the finite dimension and the thermal influence of the probes. Implementation of the dual-probe heat-pulse (DPHP) approach for measurement of volumetric heat capacity (C) and water content (θ) with distributed temperature sensing heated fiber optic (FO) systems presents an unprecedented opportunity for environmental monitoring (e.g., simultaneous measurement at thousands of points). We applied uniform heat pulses along a FO cable and monitored the thermal response at adjacent cables. We tested the DPHP method in the laboratory using multiple FO cables at a range of spacings. The amplitude and phase shift in the heat signal with distance was found to be a function of the soil volumetric heat capacity. Estimations of C at a range of moisture contents (θ = 0.09– 0.34 m3 m−3) suggest the feasibility of measurement via responsiveness to the changes in θ, although we observed error with decreasing soil water contents (up to 26% at θ = 0.09 m3 m−3). Optimization will require further models to account for the finite radius and thermal influence of the FO cables. Although the results indicate that the method shows great promise, further study is needed to quantify the effects of soil type, cable spacing, and jacket configurations on accuracy.

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

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