30,599 research outputs found

    Emerging technologies for learning (volume 2)

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    Emerging technologies for learning (volume 1)

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    Collection of 5 articles on emerging technologies and trend

    Scenarios for the development of smart grids in the UK: literature review

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    Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

    Collaborative trails in e-learning environments

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    This deliverable focuses on collaboration within groups of learners, and hence collaborative trails. We begin by reviewing the theoretical background to collaborative learning and looking at the kinds of support that computers can give to groups of learners working collaboratively, and then look more deeply at some of the issues in designing environments to support collaborative learning trails and at tools and techniques, including collaborative filtering, that can be used for analysing collaborative trails. We then review the state-of-the-art in supporting collaborative learning in three different areas – experimental academic systems, systems using mobile technology (which are also generally academic), and commercially available systems. The final part of the deliverable presents three scenarios that show where technology that supports groups working collaboratively and producing collaborative trails may be heading in the near future

    ALT-C 2010 - Conference Proceedings

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    Prosumer behaviour in emerging electricity systems

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    This dissertation investigates the interface between technology and society in the emerging electricity systems and in particular the role of the energy prosumer in the energy transition. It contributes to the understanding of the role of consumers in emerging electricity systems within the current EU energy policy context where consumer active participation is regarded as "a prerequisite for managing the energy transition successfully and in a cost-effective way". Emerging energy systems are characterized by a high level of complexity, especially for what concerns the behaviour of social actors. Social actors interact through physical and social networks by sharing information and learning from one another through social interactions. These interactions determine self-organization and emergent behaviours in energy consumption patterns and practices. I argue that the best suited tool to study emergent behaviours in energy consumption patterns and practices, and to investigate how consumers' preferences and choices lead to macro behaviours is agent based modelling. To build a sound characterization of the energy prosumer, I review the current social psychology and behavioural theories on sustainable consumption and collect evidence from EU energy prosumers surveys, studies and demand side management pilot projects. I employ these findings to inform the development of an agent based model of the electricity prosumer, Subjective Individual Model of Prosumer – SIMP, and its extended version, SIMP-N, that includes the modelling of the social network. I apply SIMP and SIMP-N models to study the emergence in consumer systems and how values and beliefs at consumer level (as defined by social psychology and behavioural theories and informed by empirical evidence) and social dynamics lead to macro behaviours. More specifically, I explore the diffusion of smart grid technologies enabled services among a population of interacting prosumers and evaluate the impact of such diffusion on individual and societal performance indicators under different policy scenarios and contextual factors. The analysis of the simulation results provides interesting insights on how different psychological characteristics, social dynamics and technological elements can strongly influence consumers' choices and overall system performance. I conclude proposing a framework for an integrated approach to modelling emerging energy systems and markets that extend the SIMP model to also include markets, distribution system operator and the electricity network
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