Intermediate band materials for more efficient solar energy use: quantum modelling and experimental realizations

The intermediate band (IB) solar cell (Fig. 1) has been proposed [1] to increase photovoltaic efficiency by a factor above 1.5, based on the absorption of two sub-bandgap photons to promote an electron across the bandgap. To realize this principle, that can be applied also to obtain efficient photocatalysis with sunlight, we proposed in recent years several materials where a metal or heavy element, substituting for an electropositive atom in a known semiconductor that has an appropriate band gap width (around 2 eV), forms inside the gap the partially filled levels needed for this aim

Energy and power aware scheduling algorithm modeling for battery powered embedded systems

Energy management has always been recognized as a challenge in mobile systems, especially in modern OS-based mobile systems where multi-functioning are widely supported. Nowadays, it is common for a mobile system user to run multiple applications simultaneously while having a target battery lifetime in mind for a specific application. Traditional OS-level power management (PM) policies make their best effort to save energy under performance constraint, but fail to guarantee a target lifetime, leaving the painful trading off between the total performance of applications and the target lifetime to the user itself. This thesis provides a new way to deal with the problem. It is advocated that a strong energy-aware PM scheme should first guarantee a user-specified battery lifetime to a target application by restricting the average power of those less important applications, and in addition to that, maximize the total performance of applications without harming the lifetime guarantee. As a support, energy, instead of CPU or transmission bandwidth, should be globally managed as the first-class resource by the OS. As the first-stage work of a complete PM scheme, this thesis presents the energy-based fair queuing scheduling, a novel class of energy-aware scheduling algorithms which, in combination with a mechanism of battery discharge rate restricting, systematically manage energy as the first-class resource with the objective of guaranteeing a user-specified battery lifetime for a target application in OS-based mobile systems. Energy-based fair queuing is a cross-application of the traditional fair queuing in the energy management domain. It assigns a power share to each task, and manages energy by proportionally serving energy to tasks according to their assigned power shares. The proportional energy use establishes proportional share of the system power among tasks, which guarantees a minimum power for each task and thus, avoids energy starvation on any task. Energy-based fair queuing treats all tasks equally as one type and supports periodical time-sensitive tasks by allocating each of them a share of system power that is adequate to meet the highest energy demand in all periods. However, an overly conservative power share is usually required to guarantee the meeting of all time constraints. To provide more effective and flexible support for various types of time-sensitive tasks in general purpose operating systems, an extra real-time friendly mechanism is introduced to combine priority-based scheduling into the energy-based fair queuing. Since a method is available to control the maximum time one time-sensitive task can run with priority, the power control and time-constraint meeting can be flexibly traded off. A SystemC-based test-bench is designed to assess the algorithms. Simulation results show the success of the energy-based fair queuing in achieving proportional energy use, time-constraint meeting, and a proper trading off between them. La gestión de energía en los sistema móviles está considerada hoy en día como un reto fundamental, notándose, especialmente, en aquellos terminales que utilizando un sistema operativo implementan múltiples funciones. Es común en los sistemas móviles actuales ejecutar simultaneamente diferentes aplicaciones y tener, para una de ellas, un objetivo de tiempo de uso de la batería. Tradicionalmente, las políticas de gestión de consumo de potencia de los sistemas operativos hacen lo que está en sus manos para ahorrar energía y satisfacer sus requisitos de prestaciones, pero no son capaces de proporcionar un objetivo de tiempo de utilización del sistema, dejando al usuario la difícil tarea de buscar un compromiso entre prestaciones y tiempo de utilización del sistema. Esta tesis, como contribución, proporciona una nueva manera de afrontar el problema. En ella se establece que un esquema de gestión de consumo de energía debería, en primer lugar, garantizar, para una aplicación dada, un tiempo mínimo de utilización de la batería que estuviera especificado por el usuario, restringiendo la potencia media consumida por las aplicaciones que se puedan considerar menos importantes y, en segundo lugar, maximizar las prestaciones globales sin comprometer la garantía de utilización de la batería. Como soporte de lo anterior, la energía, en lugar del tiempo de CPU o el ancho de banda, debería gestionarse globalmente por el sistema operativo como recurso de primera clase. Como primera fase en el desarrollo completo de un esquema de gestión de consumo, esta tesis presenta un algoritmo de planificación de encolado equitativo (fair queueing) basado en el consumo de energía, es decir, una nueva clase de algoritmos de planificación que, en combinación con mecanismos que restrinjan la tasa de descarga de una batería, gestionen de forma sistemática la energía como recurso de primera clase, con el objetivo de garantizar, para una aplicación dada, un tiempo de uso de la batería, definido por el usuario, en sistemas móviles empotrados. El encolado equitativo de energía es una extensión al dominio de la energía del encolado equitativo tradicional. Esta clase de algoritmos asigna una reserva de potencia a cada tarea y gestiona la energía sirviéndola de manera proporcional a su reserva. Este uso proporcional de la energía garantiza que cada tarea reciba una porción de potencia y evita que haya tareas que se vean privadas de recibir energía por otras con un comportamiento más ambicioso. Esta clase de algoritmos trata a todas las tareas por igual y puede planificar tareas periódicas en tiempo real asignando a cada una de ellas una reserva de potencia que es adecuada para proporcionar la mayor de las cantidades de energía demandadas por período. Sin embargo, es posible demostrar que sólo se consigue cumplir con los requisitos impuestos por todos los plazos temporales con reservas de potencia extremadamente conservadoras. En esta tesis, para proporcionar un soporte más flexible y eficiente para diferentes tipos de tareas de tiempo real junto con el resto de tareas, se combina un mecanismo de planificación basado en prioridades con el encolado equitativo basado en energía. En esta clase de algoritmos, gracias al método introducido, que controla el tiempo que se ejecuta con prioridad una tarea de tiempo real, se puede establecer un compromiso entre el cumplimiento de los requisitos de tiempo real y el consumo de potencia. Para evaluar los algoritmos, se ha diseñado en SystemC un banco de pruebas. Los resultados muestran que el algoritmo de encolado equitativo basado en el consumo de energía consigue el balance entre el uso proporcional a la energía reservada y el cumplimiento de los requisitos de tiempo real.

Temperaturas de confort e implicaciones energéticas en viviendas climatizadas mecánicamente. Estudio en clima cálido y húmedo

Este trabajo presenta un estudio de campo sobre confort térmico basado en la concepción adaptativa, para la determinación de las temperaturas y rangos de confort térmico de sujetos habituados a espacios enfriados mecánicamente en viviendas con aire acondicionado (AA) en el clima cálido y húmedo de la ciudad de Maracaibo (Venezuela) y las consecuentes implicaciones energéticas que tiene la satisfacción de esa demanda de confortabilidad en el sector residencial de la ciudad. Para la estimación de la temperatura de confort (Tc) y el rango de temperaturas de confort se aplican diferentes metodologías de análisis estadístico, las cuales son comparadas con las respectivas calculadas con el índice PMV; se analizan también otros aspectos asociados a la confortabilidad térmica, tales como las respuestas en las diferentes escalas de valoración de la confortabilidad, las preferencias, experiencias y expectativas térmicas de los sujetos. Las implicaciones energéticas se determinan en base al consumo de la energía eléctrica residencial debido exclusivamente a la variación de la Tc, entre la obtenida inicialmente en espacios naturalmente ventilados (NV) en Maracaibo (Bravo y Gonzalez 2001a) y la determinada ahora en espacios con AA. Para ello, se utiliza una metodología que es el resultado de la modificación parcial de la propuesta por Yamtraipat et al (2006). Entre los resultados y conclusiones derivadas de este estudio se encuentra que el 57 % de las personas prefieren las mismas condiciones confortables experimentadas en los ambientes con AA y solamente un 30 % prefieren experimentar ambientes ligeramente fríos y ligeramente calientes. Mientras tanto, las estimaciones de la Tc, y el respectivo rango, varían de acuerdo a la metodología empleada. Con la convencional metodología adaptativa, la Tc se estima en 25 °C en un amplio rango de 6 °C, entre 22 °C y 28 °C; mientras que con la metodología denominada “método de los promedios de los intervalos de las sensaciones térmicas” (Gómez-Azpeitia et al, 2007), la misma Tc se estima en 24 °C, en un rango estrecho de 22,5 °C a 25,5 °C y en un rango ampliado de 21 °C a 27 °C (amplitud 6 °C), donde se encuentran las tres cuartas partes de las personas del estudio. Ambas Tc son muy próximas a la temperatura operativa optima de 24,5 °C (rango de 23 °C a 26 °C) establecida por las normas internacionales ISO 7730:1994 y ASHRAE 55:1992 para el verano en climas templados. Sin embargo, la Tc estimada con los valores de PMV resulta ser superior en 1 °C y 2 °C a la Tc estimada con la metodología adaptativa (25 °C) y con el metodo de los promedios de los intervalos (24 °C), respectivamente. Con la metodología aplicada y la muestra del estudio se estima que de haberse registrado una Tbsint igual o próxima a 28 C (equivalente a la Tc en espacios NV en Maracaibo) en todos los espacios medidos (con Tbsint entre 19 C y 29 C), el ahorro total de la energía anual seria de 1.648,1 GWh en un ano respecto al consumo de AA en el año 2007 (2.522,3 GWh en un ano), mientras que el ahorro de energía asumiendo Tbsint de 24 C y de 25 C, resultan en 651,9 GWh en un ano y 425,7 GWh en un ano, respectivamente. Esto significa respectivos consumos adiciones de energía eléctrica equivalentes al 60,4 % y 74,2 %. Finalmente, los hábitos o conductas adoptadas por las personas de este estudio, sumado a las predominantes manifestaciones de confortabilidad en ambientes enfriados mecánicamente, redundan en mayores adaptaciones a condiciones de frio y exigencias de temperaturas de confort más bajas, con su consecuente consumo energético para proveerlas. ABSTRACT This investigation presents a study on thermal comfort following the adaptive approach for the determination of the thermal comfort temperatures and ranges of subjects accustomed to mechanically refrigerated spaces in dwellings with air conditioning (AA) systems in the hot and humid weather of the city of Maracaibo (Venezuela) and the ensuing energy use implications it has on the satisfaction of such demand of comfortability in the residential sector of the city. For the estimation of the comfort temperature (Tc) and the range of comfort temperatures different statistical analysis methodologies were used, which are then compared to the respective values calculated with the PMV index, also discusses other aspects related with thermal comfortability were analyzed, such as the responses on the different scales of perception of thermal comfortability, preferences, experiences and expectations of the analyzed subjects. The energetic implications are determined through the residential energy consumption related exclusively with the variation of the Tc between the originally calculated for naturally ventilated (NV) spaces in Maracaibo (Bravo y Gonzalez 2001a) and the one calculated on the present study with AA. For this, a new methodology was developed by partially modifying the Yamtraipat et al (2006) proposal. Among the results and conclusions of this study are that 57 % of the studied subjects prefer the same comfortable conditions experienced on AA environments and only a 30 % prefer to experience slightly cooler or warmer environments. Also, estimations of the Tc and its respective range vary according to the used methodology. With the conventional adaptive methodology, the Tc is estimated in 25 °C with a wide range of 6 °C, between 22 °C and 28 °C, while using the “thermal sensation intervals averages method” (Gomez-Azpeitia et al, 2007) the Tc is estimated in 24 °C on a narrow range between 22.5 °C and 25.5 °C and a widened range of 21 °C to 27 °C (6 °C in amplitude), a range where . of the studied subjects are located. Both Tc are very close to the optimum operation temperature of 24.5 °C (with a range between 23 °C and 26 °C) established on the ISO 7730:1994 and ASHRAE 55:1992 international norms for the summer on warm climates. However, the estimated Tc with the PMV indexes results to be 1 °C and 2 °C above the Tc estimated with the adaptive methodology (25 °C) and the thermal sensation intervals averages method (24 °C), respectively. With the applied methodology and this study sample, its estimated that if a Tbsint equal or close to 28 °C (equivalent to the Tc in NV spaces in Maracaibo) was registered in all measured spaces (with Tbsint between 19 °C and 29 °C) the total yearly energy savings would be of 1.648,1 GWh in a year with respect to the AA consumption in the year 2007 (2.522.3 GWh in a year), while the energy savings assuming a Tbinst of 24 °C and 25 °C result in 651.9 GWh and 425.7 Gwh in a year, respectively. This means that the respective additional electrical energy consumption amount to 60.4 % and 74.2 %, respectively. Finally, the habits or behaviors adopted by the subjects analyzed on this study, added to the predominant manifestations of comfortability in mechanically refrigerated environments result in greater adaptations to colder conditions and lower thermal comfort temperature demands, with the consequential increase in power consumption to meet them.

A swarm intelligence approach based on coupled oscillators: an application in demand side management with photovoltaic distributed generation

Esta Tesis aborda los problemas de eficiencia de las redes eléctrica desde el punto de vista del consumo. En particular, dicha eficiencia es mejorada mediante el suavizado de la curva de consumo agregado. Este objetivo de suavizado de consumo implica dos grandes mejoras en el uso de las redes eléctricas: i) a corto plazo, un mejor uso de la infraestructura existente y ii) a largo plazo, la reducción de la infraestructura necesaria para suplir las mismas necesidades energéticas. Además, esta Tesis se enfrenta a un nuevo paradigma energético, donde la presencia de generación distribuida está muy extendida en las redes eléctricas, en particular, la generación fotovoltaica (FV). Este tipo de fuente energética afecta al funcionamiento de la red, incrementando su variabilidad. Esto implica que altas tasas de penetración de electricidad de origen fotovoltaico es perjudicial para la estabilidad de la red eléctrica. Esta Tesis trata de suavizar la curva de consumo agregado considerando esta fuente energética. Por lo tanto, no sólo se mejora la eficiencia de la red eléctrica, sino que también puede ser aumentada la penetración de electricidad de origen fotovoltaico en la red. Esta propuesta conlleva grandes beneficios en los campos económicos, social y ambiental. Las acciones que influyen en el modo en que los consumidores hacen uso de la electricidad con el objetivo producir un ahorro energético o un aumento de eficiencia son llamadas Gestión de la Demanda Eléctrica (GDE). Esta Tesis propone dos algoritmos de GDE diferentes para cumplir con el objetivo de suavizado de la curva de consumo agregado. La diferencia entre ambos algoritmos de GDE reside en el marco en el cual estos tienen lugar: el marco local y el marco de red. Dependiendo de este marco de GDE, el objetivo energético y la forma en la que se alcanza este objetivo son diferentes. En el marco local, el algoritmo de GDE sólo usa información local. Este no tiene en cuenta a otros consumidores o a la curva de consumo agregado de la red eléctrica. Aunque esta afirmación pueda diferir de la definición general de GDE, esta vuelve a tomar sentido en instalaciones locales equipadas con Recursos Energéticos Distribuidos (REDs). En este caso, la GDE está enfocada en la maximización del uso de la energía local, reduciéndose la dependencia con la red. El algoritmo de GDE propuesto mejora significativamente el auto-consumo del generador FV local. Experimentos simulados y reales muestran que el auto-consumo es una importante estrategia de gestión energética, reduciendo el transporte de electricidad y alentando al usuario a controlar su comportamiento energético. Sin embargo, a pesar de todas las ventajas del aumento de auto-consumo, éstas no contribuyen al suavizado del consumo agregado. Se han estudiado los efectos de las instalaciones locales en la red eléctrica cuando el algoritmo de GDE está enfocado en el aumento del auto-consumo. Este enfoque puede tener efectos no deseados, incrementando la variabilidad en el consumo agregado en vez de reducirlo. Este efecto se produce porque el algoritmo de GDE sólo considera variables locales en el marco local. Los resultados sugieren que se requiere una coordinación entre las instalaciones. A través de esta coordinación, el consumo debe ser modificado teniendo en cuenta otros elementos de la red y buscando el suavizado del consumo agregado. En el marco de la red, el algoritmo de GDE tiene en cuenta tanto información local como de la red eléctrica. En esta Tesis se ha desarrollado un algoritmo autoorganizado para controlar el consumo de la red eléctrica de manera distribuida. El objetivo de este algoritmo es el suavizado del consumo agregado, como en las implementaciones clásicas de GDE. El enfoque distribuido significa que la GDE se realiza desde el lado de los consumidores sin seguir órdenes directas emitidas por una entidad central. Por lo tanto, esta Tesis propone una estructura de gestión paralela en lugar de una jerárquica como en las redes eléctricas clásicas. Esto implica que se requiere un mecanismo de coordinación entre instalaciones. Esta Tesis pretende minimizar la cantidad de información necesaria para esta coordinación. Para lograr este objetivo, se han utilizado dos técnicas de coordinación colectiva: osciladores acoplados e inteligencia de enjambre. La combinación de estas técnicas para llevar a cabo la coordinación de un sistema con las características de la red eléctrica es en sí mismo un enfoque novedoso. Por lo tanto, este objetivo de coordinación no es sólo una contribución en el campo de la gestión energética, sino también en el campo de los sistemas colectivos. Los resultados muestran que el algoritmo de GDE propuesto reduce la diferencia entre máximos y mínimos de la red eléctrica en proporción a la cantidad de energía controlada por el algoritmo. Por lo tanto, conforme mayor es la cantidad de energía controlada por el algoritmo, mayor es la mejora de eficiencia en la red eléctrica. Además de las ventajas resultantes del suavizado del consumo agregado, otras ventajas surgen de la solución distribuida seguida en esta Tesis. Estas ventajas se resumen en las siguientes características del algoritmo de GDE propuesto: • Robustez: en un sistema centralizado, un fallo o rotura del nodo central provoca un mal funcionamiento de todo el sistema. La gestión de una red desde un punto de vista distribuido implica que no existe un nodo de control central. Un fallo en cualquier instalación no afecta el funcionamiento global de la red. • Privacidad de datos: el uso de una topología distribuida causa de que no hay un nodo central con información sensible de todos los consumidores. Esta Tesis va más allá y el algoritmo propuesto de GDE no utiliza información específica acerca de los comportamientos de los consumidores, siendo la coordinación entre las instalaciones completamente anónimos. • Escalabilidad: el algoritmo propuesto de GDE opera con cualquier número de instalaciones. Esto implica que se permite la incorporación de nuevas instalaciones sin afectar a su funcionamiento. • Bajo coste: el algoritmo de GDE propuesto se adapta a las redes actuales sin requisitos topológicos. Además, todas las instalaciones calculan su propia gestión con un bajo requerimiento computacional. Por lo tanto, no se requiere un nodo central con un alto poder de cómputo. • Rápido despliegue: las características de escalabilidad y bajo coste de los algoritmos de GDE propuestos permiten una implementación rápida. No se requiere una planificación compleja para el despliegue de este sistema. ABSTRACT This Thesis addresses the efficiency problems of the electrical grids from the consumption point of view. In particular, such efficiency is improved by means of the aggregated consumption smoothing. This objective of consumption smoothing entails two major improvements in the use of electrical grids: i) in the short term, a better use of the existing infrastructure and ii) in long term, the reduction of the required infrastructure to supply the same energy needs. In addition, this Thesis faces a new energy paradigm, where the presence of distributed generation is widespread over the electrical grids, in particular, the Photovoltaic (PV) generation. This kind of energy source affects to the operation of the grid by increasing its variability. This implies that a high penetration rate of photovoltaic electricity is pernicious for the electrical grid stability. This Thesis seeks to smooth the aggregated consumption considering this energy source. Therefore, not only the efficiency of the electrical grid is improved, but also the penetration of photovoltaic electricity into the grid can be increased. This proposal brings great benefits in the economic, social and environmental fields. The actions that influence the way that consumers use electricity in order to achieve energy savings or higher efficiency in energy use are called Demand-Side Management (DSM). This Thesis proposes two different DSM algorithms to meet the aggregated consumption smoothing objective. The difference between both DSM algorithms lie in the framework in which they take place: the local framework and the grid framework. Depending on the DSM framework, the energy goal and the procedure to reach this goal are different. In the local framework, the DSM algorithm only uses local information. It does not take into account other consumers or the aggregated consumption of the electrical grid. Although this statement may differ from the general definition of DSM, it makes sense in local facilities equipped with Distributed Energy Resources (DERs). In this case, the DSM is focused on the maximization of the local energy use, reducing the grid dependence. The proposed DSM algorithm significantly improves the self-consumption of the local PV generator. Simulated and real experiments show that self-consumption serves as an important energy management strategy, reducing the electricity transport and encouraging the user to control his energy behavior. However, despite all the advantages of the self-consumption increase, they do not contribute to the smooth of the aggregated consumption. The effects of the local facilities on the electrical grid are studied when the DSM algorithm is focused on self-consumption maximization. This approach may have undesirable effects, increasing the variability in the aggregated consumption instead of reducing it. This effect occurs because the algorithm only considers local variables in the local framework. The results suggest that coordination between these facilities is required. Through this coordination, the consumption should be modified by taking into account other elements of the grid and seeking for an aggregated consumption smoothing. In the grid framework, the DSM algorithm takes into account both local and grid information. This Thesis develops a self-organized algorithm to manage the consumption of an electrical grid in a distributed way. The goal of this algorithm is the aggregated consumption smoothing, as the classical DSM implementations. The distributed approach means that the DSM is performed from the consumers side without following direct commands issued by a central entity. Therefore, this Thesis proposes a parallel management structure rather than a hierarchical one as in the classical electrical grids. This implies that a coordination mechanism between facilities is required. This Thesis seeks for minimizing the amount of information necessary for this coordination. To achieve this objective, two collective coordination techniques have been used: coupled oscillators and swarm intelligence. The combination of these techniques to perform the coordination of a system with the characteristics of the electric grid is itself a novel approach. Therefore, this coordination objective is not only a contribution in the energy management field, but in the collective systems too. Results show that the proposed DSM algorithm reduces the difference between the maximums and minimums of the electrical grid proportionally to the amount of energy controlled by the system. Thus, the greater the amount of energy controlled by the algorithm, the greater the improvement of the efficiency of the electrical grid. In addition to the advantages resulting from the smoothing of the aggregated consumption, other advantages arise from the distributed approach followed in this Thesis. These advantages are summarized in the following features of the proposed DSM algorithm: • Robustness: in a centralized system, a failure or breakage of the central node causes a malfunction of the whole system. The management of a grid from a distributed point of view implies that there is not a central control node. A failure in any facility does not affect the overall operation of the grid. • Data privacy: the use of a distributed topology causes that there is not a central node with sensitive information of all consumers. This Thesis goes a step further and the proposed DSM algorithm does not use specific information about the consumer behaviors, being the coordination between facilities completely anonymous. • Scalability: the proposed DSM algorithm operates with any number of facilities. This implies that it allows the incorporation of new facilities without affecting its operation. • Low cost: the proposed DSM algorithm adapts to the current grids without any topological requirements. In addition, every facility calculates its own management with low computational requirements. Thus, a central computational node with a high computational power is not required. • Quick deployment: the scalability and low cost features of the proposed DSM algorithms allow a quick deployment. A complex schedule of the deployment of this system is not required.

Greenfield shopping center development. The integration between environmental features, building design and investment analysis at the decision making stage

The Shopping centre is a long term investment in which Greenfield development decisions are often taken based on risks analysis regarding construction costs, location, competition, market and an expected DCF. Furthermore, integration between the building design, project planning, operational costs and investment analysis is not entirely considered by the investor at the decision making stage. The absence of such information tends to produce certain negative impacts on the future running costs and annual maintenance of the building, especially on energy demand and other occupancy expenses paid by the tenants to the landlord. From the investor´s point of view, this blind spot in strategy development will possibly decrease their profit margin as changes in the occupancy expenses[ ] have a direct outcome on the profit margin. In order to try to reduce some higher operating cost components such as energy use and other utility savings as well as their CO2 emissions, quite a few income properties worldwide have some type of environmental label such as BREEAM and LEED. The drawback identified in this labelling is that usually the investments required to get an ecolabel are high and the investor finds no direct evidence that it increases market value. However there is research on certified commercial properties (especially offices) that shows better performance in terms of occupancy rate and rental cost (Warren-Myers, 2012). Additionally, Sayce (2013) says that the certification only provides a quick reference point i.e. the lack of a certificate does not indicate that a building is not sustainable or efficient. Based on the issues described above, this research compares important components of the development stages such as investments costs, concept/ strategy development as well as the current investor income and property value. The subjects for this analysis are a shopping centre designed with passive cooling/bioclimatic strategies evaluated at the decision making stage, a certified regional shopping centre and a non-certified standard regional shopping centre. Moreover, the proposal intends to provide decision makers with some tools for linking green design features to the investment analysis in order to optimize the decision making process when looking into cost savings and design quality.

Reducing the impact of EV charging on the electric grid

One of the main objectives of European Commission related to climate and energy is the well-known 20-20-20 targets to be achieved in 2020: Europe has to reduce greenhouse gas emissions of at least 20% below 1990 levels, 20% of EU energy consumption has to come from renewable resources and, finally, a 20% reduction in primary energy use compared with projected levels, has to be achieved by improving energy efficiency. In order to reach these objectives, it is necessary to reduce the overall emissions, mainly in transport (reducing CO2, NOx and other pollutants), and to increase the penetration of the intermittent renewable energy. A high deployment of battery electric (BEVs) and plug-in hybrid electric vehicles (PHEVs), with a low-cost source of energy storage, could help to achieve both targets. Hybrid electric vehicles (HEVs) use a combination of a conventional internal combustion engine (ICE) with one (or more) electric motor. There are different grades of hybridation from micro-hybrids with start-stop capability, mild hybrids (with kinetic energy recovery), medium hybrids (mild hybrids plus energy assist) and full hybrids (medium hybrids plus electric launch capability). These last types of vehicles use a typical battery capacity around 1-2 kWh. Plug in hybrid electric vehicles (PHEVs) use larger battery capacities to achieve limited electric-only driving range. These vehicles are charged by on-board electricity generation or either plugging into electric outlets. Typical battery capacity is around 10 kWh. Battery Electric Vehicles (BEVs) are only driven by electric power and their typical battery capacity is around 15-20 kWh. One type of PHEV, the Extended Range Electric Vehicle (EREV), operates as a BEV until its plug-in battery capacity is depleted; at which point its gasoline engine powers an electric generator to extend the vehicle's range. The charging of PHEVs (including EREVs) and BEVs will have different impacts to the electric grid, depending on the number of vehicles and the start time for charging. Initially, the lecture will start analyzing the electrical power requirements for charging PHEVs-BEVs in Flanders region (Belgium) under different charging scenarios. Secondly and based on an activity-based microsimulation mobility model, an efficient method to reduce this impact will be presented.

Use of the energy-release rate in a 2 scale damage analysis of a bonded joint

Stress singularities appear at the extremities of an adhesive bond. They can produce a damage mechanism that we assimilate in this Note to a crack. The energy release rate permits to characterize its evolution. But a very refined mesh would be necessary for a real structure. Using an asymptotic method based on the small thickness of the bond a limit model with a different local behaviour is suggested. It leads to an approximation of the energy release rate

Analysis and Potential of Use of Biomass Energy in Canary Islands, Spain

Biomass has always been associated with the development of the population in the Canary Islands as the first source of elemental energy that was in the archipelago and the main cause of deforestation of forests, which over the years has been replaced by forest fossil fuels. The Canary Islands store a large amount of energy in the form of biomass. This may be important on a small scale for the design of small power plants with similar fuels from agricultural activities, and these plants could supply rural areas that could have self-sufficiency energy. The problem with the Canary Islands for a boost in this achievement is to ensure the supply to the consumer centers or power plants for greater efficiency that must operate continuously, allowing them to have a resource with regularity, quality and at an acceptable cost. In the Canary Islands converge also a unique topography with a very rugged terrain that makes it greater difficult to use and significantly more expensive. In this work all these aspects are studied, giving conclusions, action paths and theoretical potentials.

Modeling the Real-Time Use of Reserves in the Joint Energy and Reserve Hourly Scheduling of a Pumped Storage Plant

This paper studies the impact that different approaches of modeling the real-time use of the secondary regulation reserves have in the joint energy and reserve hourly scheduling of a price-taker pumped-storage hydropower plant. The unexpected imbalance costs due to the error between the forecasted real-time use of the reserves and the actual value are also studied and evaluated for the different approaches. The proposed methodology is applied to a daily-cycle and closed-loop pumped-storage hydropower plant. Preliminary results show that the deviations in the water volume at the end of the day are important when the percentage of the real-time use of reserves is unknown in advance, and also that the total income in all approaches after correcting these deviations is significantly lower than the maximum theoretical income.