Providing 30Mbit/s to Spain’s final third. -A techno-economic assessment.

Since the Digital Agenda for Europe released the Europe2020 flagship, Member States are looking for ways of fulfilling their agreed commitments to fast and ultrafast internet deployment. However, Europe is not a homogenous reality. The economic, geographic, social and demographic features of each country make it a highly diverse region to develop best practices over Next Generation Access Networks (NGAN) deployments. There are special concerns about NGAN deployments for “the final third”, as referred to the last 25% of the country’s population who, usually, live in rural areas. This paper assesses, through a techno-economic analysis, the access cost of providing over 30 Mbps broadband for the final third of Spain`s population in municipalities, which are classified into area types, referred to as geotypes. Fixed and mobile technologies are compared in order to determine which is the most cost-effective technology for each geotype. The demographic limit for fixed networks (cable, fibre and copper) is also discussed. The assessment focuses on the supply side and the results show the access network cost only. The research completes a previous published assessment (Techno-economic analysis of next generation access networks roll-out. The case of platform competition, regulation and public policy in Spain) by including the LTE scenario. The LTE scenario is dimensioned to provide 30 Mbps (best effort) broadband, considering a network take-up of 25%. The Rocket techno-economic model is used to assess a ten-year study period deployment. Nevertheless, the deployment must start in 2014 and be completed by 2020, in order to fulfil the Digital Agenda’s goals. The feasibility of the deployment is defined as the ability to recoup the investment at the end of the study period. This ability is highly related to network take-up and, therefore, to service adoption. Network deployment in each geotype is compared with the cost of the deployment in the Urban geotype and broadband expected penetration rates for clarity and simplicity. Debating the cost-effective deployments for each geotype, while addressing the Digital Agenda’s goals regarding fast and ultrafast internet, is the main purpose of this paper. At the end of the last year, the independent Spanish regulation agency released the Spain broadband coverage report at the first half of 2013. This document claimed that 59% and 52% of Spain’s population was already covered by NGAN capable of providing 30 Mbps and 100 Mbps broadband respectively. HFC, with 47% of population coverage, and FTTH, with 14%, were considered as a 100 Mbps capable NGAN. Meanwhile VDSL, with 12% of the population covered, was the only NGAN network considered for the 30 Mbps segment. Despite not being an NGAN, the 99% population coverage of HSPA networks was also noted in the report. Since mobile operators are also required to provide 30 Mbps broadband to 90% of the population in rural areas by the end of 2020, mobile networks will play a significant role on the achievement of the 30 Mbps goal in Spain’s final third. The assessment indicates the cost of the deployment per cumulative households coverage with 4 different NGANs: FTTH, HFC, VDSL and LTE. Research shows that an investment ranging from €2,700 (VDSL) to €5,400 (HFC) million will be needed to cover the first half of the population with any fixed technology assessed. The results state that at least €3,000 million will be required to cover these areas with the least expensive technology (LTE). However, if we consider the throughput that fixed networks could provide and achievement of the Digital Agenda’s objectives, fixed network deployments are recommended for up to 90% of the population. Fibre and cable deployments could cover up to a maximum of 88% of the Spanish population cost efficiently. As there are some concerns about the service adoption, we recommend VDSL and mobile network deployments for the final third of the population. Despite LTE being able to provide the most economical roll-out, VDSL could also provide 50 Mbps from 75% to 90% of the Spanish population cost efficiently. For this population gap, facility based competition between VDSL providers and LTE providers must be encouraged. Regarding 90% to 98.5% of the Spanish population, LTE deployment is the most appropriate. Since costumers in less populated the municipalities are more sensitive to the cost of the service, we consider that a single network deployment could be most appropriate. Finally, it has become clear that it is not possible to deliver 30Mbps to the final 1.5% of the population cost-efficiently and adoption predictions are not optimistic either. As there are other broadband alternatives able to deliver up to 20 Mbps, in the authors’ opinion, it is not necessary to cover the extreme rural areas, where public financing would be required.

Instruments for analysing urban conflicts in the Global South: The case of urban transformation processes in Dakar

Physical and social transformation processes that take place in urban contexts with strong spatial growth and hardly any economic development frequently have significant adverse impacts for the affected people, which tend to be made invisible. This paper presents an analytical framework to explore different ways to approach urban transformation processes (supply side), their impacts on the set of needs of the community (demand side) and their consequences on the urban environment as a whole (context). The proposed method has been used to assess three actions related to the physical and social transformation of the largest self-made settlement in the city of Dakar, Senegal, during the 2005–2012 period. Research findings show how exogenous interests are privileged over the common good when the affected citizens are not effectively involved in decision-making processes.

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.