This work has two principal aims: a) to develop a roadmap that will help the Research Councils and others to plan their research activities in ways that will contribute to the achievement of the UK's energy policy goals; and b) to conduct a programme of research that will assess how effectively different countries conduct their energy research and development (R&D) activities in different technology areas with a view to learning lessons for the more successful execution of policy. The roadmap will consist of a top-level document which will act as a bridge between higher level energy strategies and more specific R&D plans for individual technologies. The aim is to improve the coherence of energy policy on the one hand and energy research activities on the other. The top-level document will be supplemented by web-based roadmaps for individual technology areas such as carbon capture and storage or different forms of renewable energy. Demand-side technologies, for example for transport and buildings, will also be covered. Given the interplay between technology and human behaviour, especially on the demand side, social scientists as well as scientists and engineers will be involved. The roadmaps will address both technological needs and needs for training and capacity-building. The roadmaps will be produced through interviews with policymakers and R&D funders and through a mixture of facilitated technical workshops and strategic workshops engaging a wider range of stakeholders. The first task in the research programme is to map out "systems of innovation" for different energy technologies in different countries. We intend to cover a small number of EU countries, the US and China. The mapping will cover institutions and their roles, networks and research capacity. The task will be carried out through documentary analysis and interviews in the relevant countries. We will also look at systems of innovation internationally, for example through education and training, and the activities of multinational companies. The second task will be to develop and analyse measures for the effectiveness of R&D activities in different systems of innovation. Many countries intend to achieve fundamental transitions in their energy systems, for example by moving to low-carbon technologies. We will draw on a new branch of innovation theory, "transitions theory", to develop measures of effectiveness. Finally, we will review hypotheses and findings from the analysis of the effectiveness of R&D activities with experts and draw conclusions about how the success of energy R&D programmes and their contributions to energy policy can be improved.

The UK has invested heavily in wind power in recent years, and is widely expected to build much more capacity in future. One of the driving reasons is to reduce carbon emissions, but there has been no in-depth study of how effective wind power has been, or will be, at achieving this. The simple question of 'how much carbon dioxide does a wind farm save?' has a surprisingly complex answer as it depends not just on how much power the farm produces, but on how the rest of the electricity system responds to its production. Past work by academics and government bodies has concentrated on calculating the average emissions (in grams of carbon dioxide per unit of electricity) from the entire UK power sector in various future scenarios. This project will be the first to understand the marginal emissions from wind power: the change in national emissions from adding one more or one less wind farm to the power system, the driving factors behind this, and how those factors can be used to maximise the savings. The more carbon dioxide that each turbine saves, the fewer turbines will have to be built, and the lower the cost to consumers and the UK economy. This detailed study is necessary because not all power stations respond equally to the output from wind farms. We must identify which specific power stations reduce their output when wind generation increases: high-carbon coal or lower-carbon gas? Secondly, more power stations will have to run part-loaded to cope with the weather-driven variability in wind output. We must understand how large this effect is, how great an impact it has on station efficiency and thus on national emissions. Third, large-scale investment in wind power will change the mix of other power stations that the rest of the industry chooses to build, and those stations will have different emissions at times when the wind is not blowing. Finally, to provide a holistic view of emissions we must consider the carbon emitted when power stations are built or fossil fuels are extracted from the ground using Life Cycle Assessment methodology. We will investigate these issues using a range of techniques intelligently integrated across several academic disciplines to give a complete whole-systems picture of the emissions displaced by wind, and: 1) Address fundamental problems in the emerging field of using reanalysis weather data to simulate historic wind farm outputs, allowing the output from the UK's future mix of wind farms to be quantified. 2) Produce the most detailed estimation of British power sector emissions, combining the output from every power station with their likely efficiency, derived from hourly emissions data from similar stations in the US (as these are not reported in Britain). 3) Develop statistical regression techniques to discover how these emissions vary with the level of wind output, with fuel and carbon prices, and the accuracy of the wind forecast. 4) Employ both engineering and economic models of the future electricity system to investigate how investment and operating decisions change with more wind power, and what this will mean for emissions. 5) Develop a reduced-order model of the global electricity system to replicate this analysis for other countries to ask whether the UK is well- or badly-placed to reduce emissions with wind power. Our aim is to understand the factors that affect the emissions savings from investing in wind power, so that these savings can be maximised. Energy storage, international interconnections, accurate output forecasts and a high carbon price will all help to increase the emissions savings from wind power, and we will quantify the effects of each.

National infrastructure provides essential services to a modern economy: energy, transport, digital communications, water supply, flood protection, and waste water / solid waste collection, treatment and disposal. The OECD estimates that globally US$53 trillion of infrastructure investment will be needed by 2030. The UK's National Infrastructure Plan set out over £460 billion of investment in the next decade, but is not yet known what effect that investment will have on the quality and reliability of national infrastructure services, the size of the economy, the resilience of society or its impacts upon the environment. Such a gap in knowledge exists because of the sheer complexity of infrastructure networks and their interactions with people and the environment. That means that there is too much guesswork, and too many untested assumptions in the planning, appraisal and design of infrastructure, from European energy networks to local drainage systems. Our vision is for infrastructure decisions to be guided by systems analysis. When this vision is realised, decision makers will have access to, and visualisation of, information that tells them how all infrastructure systems are performing. They will have models that help to pinpoint vulnerabilities and quantify the risks of failure. They will be able to perform 'what-if' analysis of proposed investments and explore the effects of future uncertainties, such as population growth, new technologies and climate change. The UK Infrastructure Transitions Research Consortium (ITRC) is a consortium of seven UK universities, led by the University of Oxford, which has developed unique capability in infrastructure systems analysis, modelling and decision making. Thanks to an EPSRC Programme Grant (2011-2015) the ITRC has developed and demonstrated the world's first family of national infrastructure system models (NISMOD) for analysis and long-term planning of interdependent infrastructure systems. The research is already being used by utility companies, engineering consultants, the Institution of Civil Engineers and many parts of the UK government, to analyse risks and inform billions of pounds worth of better infrastructure decisions. Infrastructure UK is now using NISMOD to analyse the National Infrastructure Plan. The aim of MISTRAL is to develop and demonstrate a highly integrated analytics capability to inform strategic infrastructure decision making across scales, from local to global. MISTRAL will thereby radically extend infrastructure systems analysis capability: - Downscale: from ITRC's pioneering representation of national networks to the UK's 25.7 million households and 5.2 million businesses, representing the infrastructure services they demand and the multi-scale networks through which these services are delivered. - Upscale: from the national perspective to incorporate global interconnections via telecommunications, transport and energy networks. - Across-scale: to other national settings outside the UK, where infrastructure needs are greatest and where systems analysis represents a huge business opportunity for UK engineering firms. These research challenges urgently need to be tackled because infrastructure systems are interconnected across scales and prolific technological innovation is now occurring that will exploit, or may threaten, that interconnectedness. MISTRAL will push the frontiers of system research in order to quantify these opportunities and risks, providing the evidence needed to plan, invest in and design modern, sustainable and resilient infrastructure services. Five years ago, proposing theory, methodology and network models that stretched from the household to the globe, and from the UK to different national contexts would not have been credible. Now the opportunity for multi-scale modelling is coming into sight, and ITRC, perhaps uniquely, has the capacity and ambition to take on that challenge in the MISTRAL programme.