18 resultados para ENERGY PLANNING


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Technology transfer (TT) in the area of renewable energy (RE) throughout history has been an important tool for rural development (RD). Initially, the TT has been conceptualized as the purchase or donation of machinery from first world countries - without any consideration of staff training and contextual conditions for the adaptation of technology to the needs of the country. Various researches have revealed the existence of different approaches to planning the TT of RE, demonstrating the high complexity of projects from the social and contextual dimension. This paper addresses the conceptual evolution of the TT of RE for RD, examining its different periods considered for three criteria: historical events occurred, the role of stakeholders and changing objectives for the TT of RE for RD. For the conceptual analysis of changes the model Working With People (WWP) is used for planning and project management of high social complexity in RD. The analysis defines the existence of four historical periods in the TT of RE and synthesizes the lessons of experience from the three dimensions (ethical-social, technical-entrepreneurial, and political-contextual) of the WWP model.

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Las redes del futuro, incluyendo las redes de próxima generación, tienen entre sus objetivos de diseño el control sobre el consumo de energía y la conectividad de la red. Estos objetivos cobran especial relevancia cuando hablamos de redes con capacidades limitadas, como es el caso de las redes de sensores inalámbricos (WSN por sus siglas en inglés). Estas redes se caracterizan por estar formadas por dispositivos de baja o muy baja capacidad de proceso y por depender de baterías para su alimentación. Por tanto la optimización de la energía consumida se hace muy importante. Son muchas las propuestas que se han realizado para optimizar el consumo de energía en este tipo de redes. Quizás las más conocidas son las que se basan en la planificación coordinada de periodos de actividad e inactividad, siendo una de las formas más eficaces para extender el tiempo de vida de las baterías. La propuesta que se presenta en este trabajo se basa en el control de la conectividad mediante una aproximación probabilística. La idea subyacente es que se puede esperar que una red mantenga la conectividad si todos sus nodos tienen al menos un número determinado de vecinos. Empleando algún mecanismo que mantenga ese número, se espera que se pueda mantener la conectividad con un consumo energético menor que si se empleara una potencia de transmisión fija que garantizara una conectividad similar. Para que el mecanismo sea eficiente debe tener la menor huella posible en los dispositivos donde se vaya a emplear. Por eso se propone el uso de un sistema auto-adaptativo basado en control mediante lógica borrosa. En este trabajo se ha diseñado e implementado el sistema descrito, y se ha probado en un despliegue real confirmando que efectivamente existen configuraciones posibles que permiten mantener la conectividad ahorrando energía con respecto al uso de una potencia de transmisión fija. ABSTRACT. Among the design goals for future networks, including next generation networks, we can find the energy consumption and the connectivity. These two goals are of special relevance when dealing with constrained networks. That is the case of Wireless Sensors Networks (WSN). These networks consist of devices with low or very low processing capabilities. They also depend on batteries for their operation. Thus energy optimization becomes a very important issue. Several proposals have been made for optimizing the energy consumption in this kind of networks. Perhaps the best known are those based on the coordinated planning of active and sleep intervals. They are indeed one of the most effective ways to extend the lifetime of the batteries. The proposal presented in this work uses a probabilistic approach to control the connectivity of a network. The underlying idea is that it is highly probable that the network will have a good connectivity if all the nodes have a minimum number of neighbors. By using some mechanism to reach that number, we hope that we can preserve the connectivity with a lower energy consumption compared to the required one if a fixed transmission power is used to achieve a similar connectivity. The mechanism must have the smallest footprint possible on the devices being used in order to be efficient. Therefore a fuzzy control based self-adaptive system is proposed. This work includes the design and implementation of the described system. It also has been validated in a real scenario deployment. We have obtained results supporting that there exist configurations where it is possible to get a good connectivity saving energy when compared to the use of a fixed transmission power for a similar connectivity.

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This report analyzes the basis of hydrogen and power integration strategies, by using water electrolysis processes as a means of flexible energy storage at large scales. It is a prospective study, where the scope is to describe the characteristics of current power systems (like the generation technologies, load curves and grid constraints), and define future scenarios of hydrogen for balancing the electrical grids, considering the efficiency, economy and easiness of operations. We focus in the "Spanish case", which is a good example for planning the transition from a power system holding large reserve capacities, high penetration of renewable energies and limited interconnections, to a more sustainable energy system being capable to optimize the volumes, the regulation modes, the utilization ratios and the impacts of the installations. Thus, we explore a novel aspect of the "hydrogen economy" which is based in the potentials of existing power systems and the properties of hydrogen as energy carrier, by considering the electricity generation and demand globally and determining the optimal size and operation of the hydrogen production processes along the country; e.g. the cost production of hydrogen becomes viable for a base-load scenario with 58 TWh/year of power surplus at 0.025 V/kWh, and large number electrolyzer plants (50 MW) running in variable mode (1-12 kA/m2)