The Supergen wind research consortium is a group of research centres which undertake research primarily aimed at reducing the cost of offshore wind farming. Research is undertaken to apply the WRF mesoscale NWP model to the field of offshore wind resource assessment to assess its potential as an operational tool. WRF is run in a variety of configurations for a number of locations to determine and optimise a level of performance and assess how accessible that performance might be to an end user. Three studies set out to establish a level of performance at two different sites and improve performance through optimisation of model setup and post processing techniques. WRF was found to simulate wind speed to an appreciable level by reference to similar studies, though performance was found to vary throughout the course of the model runs and depending on the location. An average correlation coefficient of 0.9 was found for the Shell Flats resource assessment at 6-hourly resolution with an RMSE of 1.7ms-1. Performance at Scroby Sands was not at as high a level as that seen for Shell Flats with an average correlation coefficient for wind speed of 0.64 with an RMSE of 2ms-1. A range of variables were simulated by the model in the Shell Flats investigation to test the flexibility of the model output. Wind direction was produced to a moderate level of accuracy at 10-minute resolution while aggregated stability statistics showed the model had a good appreciation of the frequency of cases observed. Areas of uncertainty in model performance were addressed through model optimisation techniques including the generation of two ensembles and observational nudging. Both techniques were found to add value to the model output as well as improving performance. The difference between performance observed at Shell Flats and Scroby Sands shows that while the model clearly has inherent skill it is sensitive to the environment to which it is applied. In order to maximise performance, as large a computing resource as possible is recommended with a concerted effort to optimise model setup with the aim of allowing it to perform to its best ability. There is room for improvement in the application of mesoscale NWP to the field of offshore wind resource assessment but these results confirm an inherent skill in model performance. With the addition of further validation, improvements to model setup on a case by case basis and the application of optimisation techniques, it is anticipated mesoscale NWP can perform to a level which would justify its adoption operationally by the industry. The flexibility which can be offered relating to spatial and temporal coverage as well as the range of variables which can be produced make it an attractive option to developers if performance of a consistently high level can be established.

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In the quest to reduce the release of carbon dioxide to limit the effects of global climate change, tidal-in-stream energy is being investigated as one of many possible sustainable means of generating electricity. In this scheme, turbines are placed in a tidal flow and kinetic energy is extracted. With the goal of producing maximum power, there is an ideal amount of resistance these turbines should provide; too little resistance will not a develop a sufficient pressure differential, while too much resistance will choke the flow. Tidal flow in a strait is driven by the difference in sea-level along the channel and is impeded by friction; the interplay between the driving and resistive forces determines the flow rate and thus the extractible power. The use of kinetic energy flux, previously employed as a metric for extractible power, is found to be unreliable as it does not account for the increased resistance the turbines provide in retarding the flow. The limits on extraction from a channel are dependant on the relationship between head loss and velocity. If head loss increases with the square of the velocity, a maximum of 38% of the total fluid power may be extracted; this maximum decreases to 25\% if head loss increases linearly with velocity. Using these values, the estimated power potential of BC's Inside Passage is 477MW, 13% of previous assessments. If a flow has the ability to divert through a parallel channel around the installed turbines, there are further limits on production. The magnitude of this diversion is a function of the relative resistance of impeded and diversion channels. As power extraction increases, the flow will slow from its natural rate. This reduction in velocity precipitously decreases the power density the flow, requiring additional turbine area per unit of power. As such, the infrastructure costs per watt may rise five to eight times as additional turbines are installed. This places significant economic limitations on utility-scale tidal energy production.

An accurate wind resource assessment (WRA) is crucial in energy prediction as the power is directly proportional to the wind speed cubed. This thesis analyses the discrepancy between operational assessment and WRA for a wind farm located on a moderately complex terrain in Ireland. As part of this research, a WRA was undertaken and the results were input to two wind farm design tools, WindPro and WindSim, to estimate the annual energy production. Two and a half years of data was available from a 50m met mast. The data was analysed and filtered to ascertain and limit the usage of erroneous data. The dataset was then correlated with an available online dataset utilising the Measure Correlate Predict (MCP) module in WindPro in order to estimate the long term wind resource at the site. The wind resource was then used to determine the annual energy produced at the site using both WindPro and WindSim. A loss of 8% was applied to the energy calculations for comparison with the original WRA. The results demonstrate the energy production from the original energy prediction, undertaken by a leading wind consultancy prior to construction, was overestimated by an average 10.19% over the three years of operation. The averaged wind speed at hub height in the original WRA was 8.2m/s. However, the prediction undertaken using WindPro in this study estimated an average hub height wind speed of 8.0m/s while WindSim estimated an average of 7.36m/s. These differing results had a significant contribution to the difference in Annual Energy Production (AEP). The calculated annual energy results were an overestimation of energy production by an average of 8.10% utilising WindPro, while WindSim underestimated the energy output by just 0.11%.

In the quest to reduce the release of carbon dioxide to limit the effects of global climate change, tidal-in-stream energy is being investigated as one of many possible sustainable means of generating electricity. In this scheme, turbines are placed in a tidal flow and kinetic energy is extracted. With the goal of producing maximum power, there is an ideal amount of resistance these turbines should provide; too little resistance will not a develop a sufficient pressure differential, while too much resistance will choke the flow. Tidal flow in a strait is driven by the difference in sea-level along the channel and is impeded by friction; the interplay between the driving and resistive forces determines the flow rate and thus the extractible power. The use of kinetic energy flux, previously employed as a metric for extractible power, is found to be unreliable as it does not account for the increased resistance the turbines provide in retarding the flow. The limits on extraction from a channel are dependant on the relationship between head loss and velocity. If head loss increases with the square of the velocity, a maximum of 38% of the total fluid power may be extracted; this maximum decreases to 25\% if head loss increases linearly with velocity. Using these values, the estimated power potential of BC's Inside Passage is 477MW, 13% of previous assessments. If a flow has the ability to divert through a parallel channel around the installed turbines, there are further limits on production. The magnitude of this diversion is a function of the relative resistance of impeded and diversion channels. As power extraction increases, the flow will slow from its natural rate. This reduction in velocity precipitously decreases the power density the flow, requiring additional turbine area per unit of power. As such, the infrastructure costs per watt may rise five to eight times as additional turbines are installed. This places significant economic limitations on utility-scale tidal energy production.

In the quest to reduce the release of carbon dioxide to limit the effects of global climate change, tidal-in-stream energy is being investigated as one of many possible sustainable means of generating electricity. In this scheme, turbines are placed in a tidal flow and kinetic energy is extracted. With the goal of producing maximum power, there is an ideal amount of resistance these turbines should provide; too little resistance will not a develop a sufficient pressure differential, while too much resistance will choke the flow. Tidal flow in a strait is driven by the difference in sea-level along the channel and is impeded by friction; the interplay between the driving and resistive forces determines the flow rate and thus the extractible power. The use of kinetic energy flux, previously employed as a metric for extractible power, is found to be unreliable as it does not account for the increased resistance the turbines provide in retarding the flow. The limits on extraction from a channel are dependant on the relationship between head loss and velocity. If head loss increases with the square of the velocity, a maximum of 38% of the total fluid power may be extracted; this maximum decreases to 25\% if head loss increases linearly with velocity. Using these values, the estimated power potential of BC's Inside Passage is 477MW, 13% of previous assessments. If a flow has the ability to divert through a parallel channel around the installed turbines, there are further limits on production. The magnitude of this diversion is a function of the relative resistance of impeded and diversion channels. As power extraction increases, the flow will slow from its natural rate. This reduction in velocity precipitously decreases the power density the flow, requiring additional turbine area per unit of power. As such, the infrastructure costs per watt may rise five to eight times as additional turbines are installed. This places significant economic limitations on utility-scale tidal energy production. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

In the Arctic Ocean, almost 50% of the seafloor is underlain by continental shelf. However, the geology of the pre-rift continental crust that makes up the basement of the shelf is poorly constrained because it is overlain by thick Cenozoic sedimentary cover. This study explores the available data and methods for mapping the continental bedrock geology beneath the sediments. In a GIS framework, extrapolation of geological map units to the shelf edge was guided by onshore structure and offshore bathymetry. The compilation involved identification of data sources, development of a common legend for pre-rift basement geology, building attributes tables for analysis, and extrapolating geological contacts. As a first-order assessment of mineral resource potential of the continental shelf, permissive tracts for certain mineral deposit types were also identified. The analysis includes a case study of permissive geology for magmatic Ni-Cu deposits in the Taimyr Peninsula in northern Russia.

One of the Sustainable Development Goals set in 2015 by the United Nations aims to ensure access to affordable, reliable, sustainable, and modern energy for all, increasing the global share of renewable energy to 32-35% by 2030. Moving towards this goal, the University of Trento funded the interdepartmental strategic project ERiCSol (Energie Rinnovabili e Combustibili Solari), in order to promote the research on renewable energy storage and solar fuels. The research activity presented in this thesis lies in the framework of this project, focusing on the development of new advanced simulation approaches to improve the estimation of the wind resource availability and the related power production for Italian wind farms in complex terrain. The wind farms, operated by the company AGSM S.p.A., are located in two different geographical contexts: Rivoli Veronese and Affi are at the inlet of the Adige Valley, while Casoni di Romagna and Carpinaccio Firenzuola, are on the crest of the Apennines close to the borders between the provinces of Bologna e Firenze. The analysis of data from year-long field measurements highlighted the different peculiarities of these areas. The wind farms at the mouth of the Adige Valley are influenced by a daily periodic thermally-driven circulation, characterised by a nocturnal intense down-valley wind alternating with a diurnal weaker up-valley wind, while the Apennines wind farms are primarily affected by synoptic-scale winds. Simulations, with the mesoscale Weather Research and Forecasting (WRF) model, are performed and compared with field measurements in both cases, to highlight strengths and weaknesses. The results show that the model is able to capture with good accuracy wind speed and direction in the Apennines wind farms, while larger errors arise for Rivoli Veronese and Affi wind farms, where the intensity of the nocturnal down-valley wind is generally underestimated. Considering the former case, modelled and observed yearly wind speed density distributions are compared, in order to evaluate the impact of model errors in the estimation of the wind resource at these sites. Since reliable simulations of the wind resource are also essential to ensure the security in power transmission and to prevent penalties to energy operators, an analysis of the power production is also performed, to evaluate how errors in the estimate of the resource translate into errors in the estimate of the production. Considering the wind farms at the mouth of the Adige Valley, the research work mainly focuses on the evaluation of the impact of data assimilation by means of observational nudging on model results, in order to optimize the setup for operational forecasts. Different configurations are tested and compared, varying the temporal window for the assimilation of local data.

Transition towards a low carbon economy raises concerns of loss of security of supply with high penetrations of renewable generation displacing traditional fossil fuel based generation. While wind and wave resources are increasingly forecastable, they are stochastic in nature. The tidal current resource, although variable has the advantage of being deterministic and truly predictable. With the first Crown Estate leasing round complete for wave and tidal current energy, plans are in place to install 1000 MW of tidal capacity in the Pentland Firth and Orkney waters. The aim of the work presented in this thesis is to examine the role tidal current energy can realistically play in the future electricity mix. To achieve this objective it was first necessary to develop new methodologies to capture the temporal and spatial variability of tidal current dynamics over long timescales and identify metrics relevant in a tidal energy context. These methodologies were developed for project scale resource characterisation, and provided a basis for development of a national scale dataset. The creation of project and national scale tidal datasets capture spatial and temporal variability at a level beyond previous insight, as demonstrated in case studies of three important early stage tidal current energy development sites. The provision of a robust national scale dataset enabled the development of realistic scenarios for the growth of the tidal current energy sector in UK waters. Assessing the various scenarios proposed indicates that first-generation technology solutions have the potential to generate up to 31 TWh/yr (over 8% of 2009 UK electricity demand). However, only 14 TWh/yr can be sensibly generated after incorporating realistic economic and environmental limitations proposed in this study. The preceding development of methodologies, datasets and scenarios enabled statistical analysis of the matching characteristics of future tidal energy generation potential with the present UK electricity demand and trends of electricity usage. This analysis demonstrated that the UK tidal current energy resource is much more in phase than has previously been understood, highlighting the flaws in previous studies suggesting that a combined portfolio of sites around the UK can deliver firm power. As there is negligible firm production, base-load contribution is insignificant. However, the time-series generated from this analysis identifies the role tidal current energy can play in meeting future energy demand and offer significant benefit for the operation of the electricity system as part of an integrated portfolio.

The UK has an abundant offshore wind resource with offshore wind farming set to grow rapidly over the coming years. Optimisation of energy production is of the utmost importance and accurate estimates of wind speed distributions are critical for the planning process. Synthetic aperture radar (SAR) data can provide synoptic, wide area wind field estimates at resolutions of a few kilometres and has great potential for wind resource assessment. This thesis addresses the key challenges for the operational implementation of SAR in this context; namely the accuracy of SAR wind retrievals and the ability of SAR to characterise the mean wind speed and wind power density. We consider the main stages of SAR wind retrieval; the retrieval algorithm; sources of a priori information; the optimal configuration of the retrieval system; and the challenges for and accuracy of SAR wind resource estimation. This study was conducted for the eastern Irish Sea in the UK, a region undergoing significant offshore wind energy development. A new wind retrieval algorithm was developed that implements a maximum a posterior probability (MAP) method drawn from Bayesian statistics. MAP was demonstrated to be less sensitive to input errors than the standard direction-based wind speed algorithm (DWSA) and provides a simple retrieval quality check via the error reduction ratio. Retrieval accuracy is strongly influenced by the quality of a priori information. The accuracy of two operationally viable a priori sources, mesoscale numerical weather prediction (NWP) data and WISAR image directions, was evaluated by comparison against in-situ wind observations and WERA coastal data. Results show that NWP wind speeds produce good wind speed and direction estimates with standard deviations of ¬±2 ms-1 and ±16o respectively. WISAR directions were less accurate producing standard deviations ranging from ±20o to ±29o, but were preferable when strong differences between NWP timesteps were observed. The accuracy of SAR wind retrievals was evaluated by comparison against in-situ wind observations. The MAP algorithm was found to provide modest improvements in retrieval accuracy over DWSA. Highest quality retrievals achieved using the CMOD5 forward model, producing wind speeds with a RMSE of 1.83 ms-1. Regarding the ability of SAR to estimate offshore wind resources, dataset density was found to be a controlling parameter. With 103 scenes available mean wind speeds were well characterised by comparison against in-situ observations and Wind Atlas results, while wind power density showed considerable errors. The accuracy of wind speed maps was further improved by accounting for wind direction and fetch effects upon the SAR wind distribution. A key strength of the SAR wind fields is their ability to identify the effect of mesoscale structures upon the surface wind field with atmospheric gravity waves observed in 30% of the images. These structures are shown to introduce wind speed fluctuations of up to ±2 ms-1 at scales of 5 to 10 km and may have significant implications for wind power prediction. These findings show that SAR may provide an important source of wide area wind speed observations as a complement to existing wind resource estimation techniques. SAR may be of particular use in coastal areas where complex wind fields are observed.