By 2050 it's estimated >400 GW of energy will be gathered by offshore wind across the whole North Sea. For scale, Hinkley Point C nuclear reactor is projected to produce 3.2 GW. How will this increased anthropogenic use of our coastal seas impact already stressed marine ecosystems? And how will that same production of renewable energy offset risks of extreme climate change that, left unchecked, will increase the risk of biodiversity declines. There are many complex changes to ecosystems linked to Offshore Wind Farms (OWFs) that we need to understand now, so that the extent of increasing wind energy extraction further offshore is managed in the most sustainable way. An important effect of large wind energy extraction will be to reduce the amount of energy that would normally go into local ocean currents via surface stress, altering sea state and mixing. Conversely, there will be local increases in turbulence around turbine structures and seabed scouring near fixed foundations. Any change in ocean mixing may change the timing, distribution and diversity of phytoplankton primary production, the base of the food chain for marine ecosystems, to some degree. This has knock-on-effects on the diversity, health and locations of pelagic fish that are critical prey species of commercial fish, seabirds and marine mammals. Observed changes caused by operational OWFs in the southern North Sea include local surface temperature rise and the displacement of seabirds and fishing fleets from the OWF footprint, whereas seals often appear to be feeding near turbines. All of these changes have a linked component - important prey fish species - which are likely to aggregate near structures (as seen at other offshore platforms). Seabirds and fishing fleets subsequently have less space to hunt, with potentially increased competition for fish. However, if OWFs are also de facto marine protected areas and so positively affect local primary production, they may provide good habitat for fish population growth. So, what are the cumulative effects of current OWF developments and the thousands of additional planned structures? Do the physical, biogeochemical and ecosystem changes exacerbate or mitigate those resulting from climate change? As OWFs migrate further offshore as floating structures, how can current knowledge based on shallow, coastal fixed turbines be suitably extrapolated to understand the impacts on ecosystems dependent on seasonal cycles that are typical of deeper waters? PELAgIO will address all of these questions through an interdisciplinary, multi-scale observation and modelling framework that spans physical mixing through to plankton production, on to the response of fish and whole ecosystems. We will collect fine-scale data using the latest multi-instrumented acoustic platforms set beside and away from OWFs, complemented by autonomous surface and submarine robots to capture continuous and coincident data from physics to fish, over multiple scales and seasons to fully understand what is 'different' inside an OWF and how big its footprint is. These new data will test the effects on seabirds and marine mammals to build an OWF ecosystem parameterization that accounts for changes to mixing and wind deficit impacts, and is scalable to next-generation OWFs. This bottom-up, comprehensive approach will enable true calibration and validation of 3D ocean-biogeochemical-sediment modelling systems, from the scale of turbine foundations up to the regional and even cross-shelf scales. Identified changes will be integrated into Bayesian ecosystem models that enable the cumulative effects of ecological, social and economic trade-offs of different policy approaches for OWFs to be quantifiably assessed for present day conditions, during extreme events and under climate change.

Chalk is a highly variable soft rock that covers much of Northern Europe and is widespread under the North and Baltic Seas. It poses significant problems for the designers of large foundations for port, bridge and offshore wind turbine structures that have to sustain severe environmental loading over their many decades in service. Particular difficulties are faced when employing large driven steel piles to secure the structures in place. While driven pile foundation solutions have many potential advantages, chalk is highly sensitive to pile driving and to service loading conditions, such as the repeated cyclic buffeting applied to bridge, harbour and offshore structures by storm winds and wave impacts. Current guidance regarding how to allow for difficult pile driving conditions or predict the piles' vertical and lateral response to loads is notoriously unreliable in chalk. There is also no current industrial guidance regarding the potentially positive effects of time (after driving) on pile behaviour or the generally negative impact of the cyclic loading that the structures and their piled foundations will inevitably experience. These shortfalls in knowledge are introducing great uncertainty into the assessment and design of a range of projects around the UK and Northern Europe. Particularly affected are a series of planned and existing major offshore wind farm developments. The uncertainty regarding foundation design and performance poses a threat to the economic and safe harnessing of vital renewable, low carbon, offshore energy supplies. Better design guidelines will reduce offshore wind energy costs and also help harbour and transport projects to progress and function effectively, so delivering additional benefits to both individual consumers and UK Industry. The research proposed will generate new driven pile design guidance for chalk sites through a comprehensive programme of high quality field tests, involving multiple loading scenarios, on 21 specially instrumented driven tubular steel test piles, at an onshore test site in Kent. This will form a benchmark set of results that will be complemented by comprehensive advanced drilling, sampling, in-situ testing and laboratory experiments, supported by rigorous analysis and close analysis of other case history data. The key aim is to develop design procedures that overcome, for chalk, the current shortfalls in knowledge regarding pile driving, ageing, static and cyclic response under axial and lateral loading. The main deliverable will be new guidelines for practical design that will be suitable for both onshore and offshore applications.

Many current or projected future land-based renewable energy schemes are highly dependent on very localised climatic conditions, especially in regions of complex terrain. For example, mean wind speed, which is the determining factor in assessing the viability of wind farms, varies considerably over distances no greater than the size of a typical farm. Variations in the productivity of bio-energy crops also occur on similar spatial scales. This localised climatic variation will lead to significant differences in response of the landscape in hosting land-based renewables (LBR) and without better understanding could compromise our ability to deploy LBR to maximise environmental and energy gains. Currently climate prediction models operate at much coarser scales than are required for renewable energy applications. The required downscaling of climate data is achieved using a variety of empirical techniques, the reliability of which decreases as the complexity of the terrain increases. In this project, we will use newly emerging techniques of very high resolution nested numerical modelling, taken from the field of numerical weather prediction, to develop a micro-climate model, which will be able to make climate predictions locally down to scales of less than one kilometre. We will conduct validation experiments for the new model at wind farm and bio-energy crop sites. The model will be applied to the problems of (i) predicting the effect of a wind farm on soil carbon sequestration on an upland site, thus addressing the question of carbon payback time for wind farm schemes and (ii) for predicting local yield variations of bio-energy crops. Extremely high resolution numerical modelling of the effect of wind turbines on each other and on the air-land exchanges will be undertaken using a computational fluid dynamics model (CFD). The project will provide a new tool for climate impact prediction at the local scale and will provide new insight into the detailed physical, bio-physical and geochemical processes affecting the resilience and adaptation of sensitive (often upland) environments when hosting LBR.

By 2015, the UK is expected to face an electrical power shortage of over 20GW, based on projected economic growth and projected life expectancy of a number of existing power plants. There is currently an exceptionally wide variety of new generation technologies being considered. Nuclear power generation will take a long time from build to generation; in fact, the earliest estimated time of generation from new nuclear power stations would be 2018. Renewable energy alone is not capable of generating enough electricity to fill this gap. Around 40% of the current electricity is generated by gas/oil in the UK, but the price of gas/oil faces a huge fluctuations and uncertainty. So gas/oil is not the suitable choice to fill the big electricity generation capacity gap. To meet the various requirements in electricity demand, environment, finance and performance, coal fired power generation is really in need, actually the realistic choice, for compensating the generation gap. Plans have been made for new coal-fired power stations to be built in the UK in the near future. In China, more than 70% of electricity is currently generated by Coal. New coal fired power stations bring into generation almost every month in China. In American, 335,830MW electricity is generated by coal. It is likely that coal remains a dominant fuel for electricity generation from many years to come. Coal is, no doubt, playing an important role in electrical power generation but we must make it cleaner. Supercritical coal fired plant technology is one of the leading options with improved efficiency and hence reduced CO2 emissions per unit of electrical energy generated. Indeed, power plants using supercritical generation have energy efficiency up to 46%, around 10% above current coal fired power plants. On the other hand, this technology costs less than other clean coal technologies and can be fully integrated with appropriate CO2 capture technology in a timely manner. In addition to higher energy efficiency, lower emission levels for supercritical plants are achieved by using well-proven emission control technologies. However, power plants adopting supercritical boilers face great challenges from the UK National Grid Code (NGC) compliance. The UK grid code is far more demanding than in other European countries due to the relatively small scale of the UK electricity network. The most significant issue for a supercritical steam plant is the absence of the stored energy provided by the drum of a conventional plant. As a result the plant would struggle to produce the 10% frequency response requirement in the Grid Code quickly enough Ensuring NGC compliance for supercritical boiler power generation is an important pre-requisite for gaining acceptance in the UK for this highly promising cleaner coal technology. The generation companies have already proposed the Grid Code review request to NGC for the possibility of grid code change to accept supercritical plant There is an urgent demand to conduct the whole process modelling and simulation study to get a clearer picture of the dynamic responses of the supercritical coal fired power plant and to study the feasible strategy to improve the dynamic responses. Also, it is essential to establish the university based research capacity in the UK to provide research solutions in response to the challenges arising from adopting supercritical technology in electrical power generation and also to provide the training needed for future electrical power engineers. Currently, no supercritical or ultra-supercritical boilers operate in the UK, which make it difficult for UK researchers alone to conduct the above proposed study. There are more than 400 such units worldwide, with China operating 24 of them and more to be built. So this proposal is proposed to collaborate with Chinese top universities for this challenging research.

The wind energy sector is an industry of strategic national importance, which can help secure our energy supplies, reduce our emissions and dependence on imported fossil fuels, and protect our environment. It is an industry on which our clean energy future rests. Despite the positive benefits of wind farms however, there is concern and uncertainty over the possible negative effects wind turbines may have on the environment, particularly on birds. For example, uncertainty remains over collision mortality i.e. the number of birds killed directly through collision with wind turbines. These uncertainties are far from trivial for the industry and have real consequences, potentially delaying wind farm projects and inhibiting the ability of the UK to meet its binding 2020 targets. Three projects in Round 2 of wind farm developments in the UK were delayed by over three years due in part to uncertainties over the assessment of impacts. Therefore better quantification of the uncertainty and variability associated with the estimation of impacts is required. During Environmental Impact Assessments of wind farm developments, bird collision mortality is estimated using a mathematical model which describes the interaction of a bird with a wind turbine and predicts the risks of bird collisions with turbines. There are a limited number of collision risk models in use, not only in the UK but globally. However, it is recognised by many, including industry, statutory nature conservation agencies and academics that there is much room for improvement of these models. For example, collision risk models are deterministic and rarely include variation in the input parameters such as bird density, or bird biometrics which are inherently variable, but instead use average values. Additionally, any uncertainty in these values is not expressed. Adopting a single best value for parameters may reduce complexity and increase the accessibility of results for decision-makers however it can be misleading because it ignores the range of consequences that are plausible. This project aims to i) review current models that are used to predict bird collision mortality caused by wind farm developments, ii) determine statistical methods suited to address any shortcomings of current models and then, using this information, iii) develop an updated model which incorporates variability and uncertainty. Reviewing current models and highlighting their strengths and weaknesses, as well as reviewing methods to incorporate variability and uncertainty will aid the development of a product, a collision risk model, which is fit for purpose. Development of the understanding of uncertainty in the outputs of collision risk models will be a key part of this project, and will be of direct benefit to industry, government advisors and regulators in the assessment and licensing processes for wind farm projects. The involvement of these parties will be vital in steering this project because any revision of a collision risk model has to function to better inform planning decisions for wind farm developments. To ensure that all relevant parties are involved, contribute and ultimately buy-in to the development of a new, updated model, there will be a workshop to discuss issues surrounding current practices to which developers, licensing authorities, statutory nature conservation bodies, academics and others will be invited. Also, to ensure the outputs of this project have impact and are used by the industry, the model and any documents produced will be made freely available and accessible through a dedicated webpage. Wind energy has an important role in meeting energy targets, so there is a clear need to ensure that decisions made through the planning processes use the best available information, data and models. Improved understanding of the risks of collision to birds - a key effect considered in ornithological impact assessments of wind farms - is thus vital.