To meet the 2020 renewable energy target the UK is going to need biomass, and lots of it. DECC has an aspiration for an additional 20-38TWh of biomass electricity by 2020 and this will require around 12-23 million dry tonnes of biomass. This is a huge quantity of material, the vast majority of which would be imported as pellets from Canada and the USA and burnt in converted coal fired power plants. Other imported feedstocks for liquid fuels might include Brazilian ethanol from sugar cane and oils from palm oil in Southeast Asia. The UK is not alone in wanting to use more biomass. The Netherlands, Belgium, Denmark, and Sweden all expect to use more, and estimates of future EU demand for wood pellets alone, for example, range from 23-80 million tonnes. One single coal power station in the UK is looking to source up to 10 million tonnes of biomass each year. If the UK wants biomass power on a large scale it is clear that the power generators will need to become major players in the transatlantic wood pellet trade. Against this background of increased demand, there remains significant uncertainty on whether the use of biomass for energy is environmentally sustainable. Any type of managed land use can incur a carbon 'debt' - a net loss of carbon or other greenhouse gases to the atmosphere that contributes to global warming. Other greenhouse gases include methane and the oxides of nitrogen. But quantifying the net impact of a bioenergy crop relative to what it might replace (sometimes called the counterfactual), is less than straightforward. This has led to many claims and counter-claims from commercial interests, environmental groups and academics, on the real greenhouse gas impact of land use change to bioenergy systems, where there still remains much disagreement and controversy. The project described here is aimed at addressing this controversial issue - quantifying the real GHG balance of different land use transitions to bioenergy crops, for both UK and imported bioenergy feedstocks. We will deploy sophisticated state-of-the-art instrumentation that is able to measure GHGs very rapidly, to gain a better insight into the dynamic range of GHG emissions that can occur in such systems, including when fields are ploughed and planted and when fertilisers are added. Following data collection, we will extend our analysis by modelling a wide geographical range across the UK and for biomass feedstock sourced from other areas of the world. The models we use should work if we can utilise available datasets, globally, for weather, soils and yield data of the range of crops of interest. The GHG data in such systems are usually used to develop emissions factors that are inputted into whole life cycle assessments (LCAs) of carbon (or C equivalent) costs, but these in the past have often been unverified data. We will assess the quality of past data and from our measurement and model campaigns we can test the effectiveness of emissions factors and how they might be improved from our work, including for overseas feedstocks. Finally, in an allied project we have developed a value chain model to optimise the technology options for the UK for bioenergy, depending on how cost, GHG balance and land availability are defined. We will run this model to identify the best bioenergy chains, in terms of GHG balance, for the UK and test scenarios ('what if' questions), to determine how much imported feedstock might be sustainable in the future.

There are currently no techniques available to monitor the microstructural condition of power station steel components in-service (i.e. at elevated temperatures). This problem will become more acute as coal-fuelled power stations are being developed to operate at higher pressures and temperatures to provide greater efficiency; supercritical power stations could produce output efficiencies of 45 to 50 %, compared to subcritical power stations with efficiencies of 30 to 35 %. Operation at 620 deg C is now possible, with further temperature increases to 700 deg C planned by the year 2014. Supercritical power stations also emit up to 25 % less carbon dioxide into the environment (a one percent increase in efficiency gives a two percent drop in emissions such as carbon dioxide, and nitrogen and sulphur oxides). Currently the condition of power station components is monitored during shut down periods, when insulating lagging layers are removed and replicas from the component surface are made. These replicas are examined to determine the microstructural state (degree of degradation, e.g. through carbide population changes) and whether creep cavitation has initiated. Components are removed from service and replaced when end of predicted service life is reached or significant cavitation is detected. However, as the component condition can only be checked during a scheduled shut down period, sections are often replaced prematurely. If failure of a component occurs the economic impact is severe (an unplanned shutdown is estimated to cost approximately 1.5M per day per power station) and there is potentially significant risk to life and the environment. The proposed project is to investigate the potential of a multi-frequency electromagnetic (EM) sensor system for monitoring microstructural changes in power generation steels (e.g. boiler plate and pipe) due to high temperature exposure and creep for both in-service monitoring and evaluation during maintenance periods. The work will involve development of a sensor system for long term use at elevated temperatures, and analysis and modelling of sensor signals relative to microstructural changes in the steels.

The efficiency, safety and reliability of a wide range of engineering systems in the energy sector rely strongly on the performance of their structural components. Increasing energy efficiencies, achieved by maximising operating temperatures, will drive down CO2 emissions and is therefore essential to meet stringent legislation and the UK's and international short and long-term energy goals. Engineering components operate under adverse conditions (stress, temperature and harsh environments) causing their degradation and failure by deformation and fracture processes. Existing energy facilities are aging beyond design life and require life extension to secure short-term energy supplies. Reliable component lifetime assessment is therefore vital to ensure safe operation. New build nuclear reactors will soon be developed and future reactors designed for very high temperature operation and superior performance. Plans are also advanced for the construction of the next generation of conventional power stations with excess operating temperatures and efficiencies. Opportunities are now emerging to exploit a novel collection of innovative techniques, at micro and macro length scales, to obtain a fundamental understanding of material failure mechanisms. These will enable advanced materials and component designs with predictable in-service behaviour, which are crucial to innovation in the energy sector and the key for overcoming the outstanding challenges.Emerging experimental techniques can now reveal the processes, and quantify the extent of deformation and damage in a material as it occurs. High-energy X-ray tomography measurements will give detailed quantitative 3D volumetric insights of damage development, coalescence and failure mechanisms in the bulk of specimens at micro-length scales, during deformation under stress at temperature. In addition, complimentary non-destructive tools will be innovated for practical monitoring of large scale component degradation. At a range of length scales, a digital image correlation technique will be used to measure 3D surface strains on various geometries, and will provide evidence of the influence of defects and material inhomogeneities due to welding processes on strain fields and their evolution with time.High performance computing now facilitates advanced models to simulate material behaviour and structural components' response under various operating conditions. Experimental results will provide the basis for validated mechanistic models of material deformation and failure behaviour, which will be developed and incorporated into 3D computational models that can also include various regions of inhomogeneous material behaviour. This novel collection of advanced experimental techniques, combined with the verified computational models, will provide new powerful tools that are essential to understand and predict component failure, advance designs and optimise their operation.Initially, power plant steels will be examined. However, the methodologies developed can be extended to a wide range of materials relevant to e.g. aerospace, heat and power generation, marine and chemical technologies. The outcomes will lead to methods for component on-line monitoring, predictive multi-scale modelling of materials' initial and through-life properties and the development of accurate assessment procedures for component lifetime predictions that leads to the required plant life extension. Social and economical benefits include minimised environmental impacts, secure supplies, reduced maintenance costs and increased safety. The close collaboration with industry (including partners British/EDF Energy and E.ON) will provide an effective knowledge transfer mechanism between industry and academia, ensure industrial relevance and provide inspiration to a new generation of researchers. This fundamental, timely research is therefore valuable across industrial sectors in addition to the scientific community.

Climate change is a problem that threatens the world and is caused by the release of greenhouse gas emissions, such as Carbon Dioxide from burning fuels like gas and oil. Our dwellings in the UK consume 30% of the country's total energy demand and so that we can reduce the environmental impact of our lifestyles and create greater energy security by consuming less, the UK Government has laid out a road map of measures that will deliver a zero carbon (or as close as possible) housing stock by 2050, affecting all homes in the UK.A key step on the way to 2050 is the installation of so-called 'smart-meters', which the Government has decided will be rolled out to every house in the UK by 2030. These meters will deliver much greater information to both energy providers and householders. These meters will mean more accurate and transparent billing and should stimulate a more competitive energy market, which would benefit consumers. This greater level of information about how we use energy in and around the home can help us understand where we are wasteful and can tolerate a reduction in consumption and when and where changing our habits and/or lifestyle is not acceptable.What is not understood fully is the relationship between the householder and their preferences and tolerances to change and the sorts of pressures and constraints placed on the energy providers for energy production. Today we enjoy the luxury of having as much energy as we want on demand 24hours a day, but increased reliance on renewable sources, such as wind turbines, combined with a need to reduce our consumption as a nation is likely to mean that more flexible supply and generation systems will become more common and this will have implications for how we use energy in the home. We need to find new ways to help us understand how and where we can reduce our consumption without unacceptable impact on our lifestyles. One way to do this is by understanding how everyday practices in the home (including the use of digital media) result in the consumption of energy and how these practices may change in the future because of societal trends ( e.g. the aging population, remote working, broadband in every home) and then to see how this information can offer opportunities to develop products and services that are attractive to the householder and that have a real impact on energy consumption in the home.The challenges are both technological and sociological and so this research brings together academic experts in the fields of social science, user interface design, product design, building modelling and energy consumption, systems engineering and computer science with householders, energy providers and business to focus on the issue of using digital technology for reducing energy demand in the home. This team contends that in order to develop ways in which householders can reduce their energy consumption significantly, with relatively little effort on their part, the needs of the user must be understood in the wider context of a changing energy landscape and that this can lead to the development of new ideas that can be developed into business opportunities that benefit the UK economy.

Modern energy systems are complex technical, social and economic endeavours formed through the assembly of a broad set of elements and shaped by the actions of many multiple actors including consumers, suppliers and regulators. While some gains can be achieved by optimising parts of these systems, significant reduction in energy demand is a major challenge requiring changes in behaviour from all the actors involved. In this proposal we wish to exploit the ability of digital technologies to monitor, model and represent the operation and effects of energy demand to promote changes in these systems. This is often realised through a set of actions and measures, commonly known as demand side management (DSM). Current approaches to DSM and reduction of energy demand, however, are often viewed entirely from the consumer's perspective, concentrating mostly on the importance of behavioural changes and the role of energy displays (or smart meters ) as main drivers of these changes. This emphasises only one part of modern and increasingly complex energy systems, which actually need to be understood in their entirety to ensure that changes will have both significant and sustainable impact. Accordingly, this proposal adopts an end-to-end approach to exploit digital technology to understand the overall energy supply system (from generation to transmission, distribution and utilisation), in which devised changes are targeted at the points of maximum impact and all involved system elements are fully optimised to reap the benefits of these changes.The ultimate aim of our research is to answer how the significant potential benefits of DSM can be maximised through the provision of a unified, versatile and affordable digital infrastructure that allows us to reason across a whole energy system and supports new ways to exchange information between dynamic multiscale DSM models. The expected outcome is access to, and presentation of, not just quantitative information (e.g. the amount of modified active/reactive power demands), but also qualitative information (e.g. what are the actual load mixes and load sectors responsible for the changes in demand and what are their definite effects) to all involved stakeholders. In particular, we wish to link the use of modern digital technologies, capable of impacting the behaviour of the consumers, with the ability to optimally respond to the resulting changes in energy demand. The project team brings together researchers with a background in ubiquitous computing, complex systems modelling and user centred development to work with researcher focusing of real world energy systems and energy economics. We will adopt a user driven approach to the design and development of a series of computational models and digital technologies working closely with consumers, energy supply companies and government bodies to explore a set of exciting state-of-the-art innovations based on low-cost sensing and display technologies. The project team has strong connections with key industrial, public sector and academic groups in UK and internationally, and these will be used to ensure that the proposed research will have maximum impact. Free access to any developed system to promote change, and a publicly accessible web site will be maintained for the dissemination of the results. We intend to make any software artefacts and device designs available via open source distribution through the Horizon DE Hub. We will build upon our existing public dissemination work to emphasise issues of ethics and societal impact as important features of this work.