Studies in Electrical Machines & Wind Turbines associated with developing Reliable Power Generation

The publications listed in date order in this document are offered for the Degree of Doctor of Science in Durham University and have been selected from the author’s full publication list. The papers in this thesis constitute a continuum of original work in fundamental and applied electrical science, spanning 30 years, deployed on real industrial problems, making a significant contribution to conventional and renewable energy power generation. This is the basis of a claim of high distinction, constituting an original and substantial contribution to engineering science

Climate Adaptation Engineering and Risk-based Design and Management of Infrastructure

International audienceA changing climate may also result in more intense tropical cyclones and storms, more intense rain events and flooding, and other natural hazards. Moreover, increases in CO2 atmospheric concentrations, temperature and humidity will increase corrosion of concrete and steel structures. The chapter will describe how risk-based approaches are well suited to optimising climate adaptation strategies related to the design and maintenance of existing infrastructure. Climate adaptation strategies may include retrofitting or strengthening of existing structures, more frequent inspections, or enhanced designs. An important aspect is assessing at what point in time climate adaptation becomes economically viable. Stochastic methods are used to model infrastructure performance, effectiveness of adaptation strategies, exposure, and costs. These concepts will be illustrated with state-of-the-art research of risk-based assessment of climate adaptation strategies

Advancing probabilistic risk assessment of offshore wind turbines on monopiles

Offshore Wind Turbines (OWTs) are a unique type of engineered structure. Their design spans all engineering disciplines, ranging from structural engineering for the substructure and foundation to electrical or mechanical engineering for the generating equipment. Consequently, the different components of an OWT are commonly designed independently using codified standards. Within the OWT design process, financial cost plays an important role as a constraint on decision making, because of the competition between prospective wind farm operators and with other forms of electricity generation. However, the current, independent design process does not allow for a combined assessment of OWT system financial loss. Nor does it allow for quantification of the uncertainties (e.g., wind and wave loading, materials properties) that characterise an OWT’s operations and which may have a strong impact on decision making. This thesis proposes quantifying financial losses associated with an OWT exposed to stochastic wind and wave conditions using a probabilistic risk modelling framework, as a first step towards evaluating Offshore Wind Farm (OWF) resilience. The proposed modelling framework includes a number of novel elements, including the development of site-specific fragility functions (relationships between the likelihood of different levels of damage experienced by an OWT over a range of hazard intensities), which account for uncertainties in both structural capacity and demands. As a further element of novelty, fragility functions are implemented in a closed-form assessment of financial loss, based on a combinatorial system reliability approach, which considers both structural and non-structural components. Two important structural performance objectives (or limit states) are evaluated in this thesis: 1) the Ultimate Limit State (ULS) which assesses the collapse of an OWT due to extreme wind and wave conditions, such as those resulting from hurricanes; and 2) the Fatigue Limit State (FLS), which addresses the cumulative effects of operational loading, i.e., cracks growing over the life of the structure until they threaten its integrity. This latter limit state is assessed using a novel machine learning technique, Gaussian Process (GP) regression, to develop a computationally-efficient surrogate model that emulates the output from computationally-expensive time-domain structural analyses. The consequence of the OWT failing is evaluated by computing annualised financial losses for the full OWT system. This provides a metric which is easily communicable to project stakeholders, and can also be used to compare the relative importance of different components and design strategies. Illustrative applications at case-study sites are presented as a walk-through of the calculation steps in the proposed framework and its various components. The calculation of losses provides a foundation from which a more detailed assessment of OWT and OWF resilience could be developed

Effect of roof shape, wind direction, building height and urban configuration on the energy yield and positioning of roof mounted wind turbines

PhD ThesisThe increasing interest among architects and planners in designing environmentally friendly buildings has led to a desire to explore and integrate renewable sources of energy within the built environment. Roof mounted wind turbines is a technology that presents a high potential for integration within the built environment. However, there is a state of uncertainty regarding the viability of these wind turbines. This thesis argues that part of this uncertainty is attributed to uninformed decisions about positioning and locating urban wind turbines. This is underpinned by lack of consideration to the wind accelerating effect of different roof shapes, buildings’ heights and surrounding urban configurations. This thesis aims to investigate the effect of different roof shapes on wind acceleration and positioning of roof mounted wind turbines covering different buildings’ heights within different urban configurations under different wind directions. To achieve the aim of the thesis, the commercial Computational Fluid Dynamics (CFD) code Fluent 12.1, implementing the Realizable k-ε turbulence model, is used to simulate wind flow around different roof shapes, different buildings’ heights and different urban settings. Predictions are comparatively analysed to identify the optimum roof shape for mounting wind turbines. Simulation results indicate that the barrel vaulted roof has the highest wind accelerating effect. The barrel vaulted roof shape case was carried further to investigate the effect of building height and surrounding urban configurations on the energy yield and positioning of roof mounted wind turbines. The optimum mounting location for each of the investigated roof shapes namely: flat, domed, gabled, pyramidal, barrel vaulted and wedged roofs is identified. Results from the investigation predict a possible increase up to 56.1% in energy yield in the case of a barrel vaulted roof if an informed wind assessment above buildings’ roofs is carried out. However, changing the building height and surrounding urban configuration had an effect on choosing the optimum mounting location and the energy yield at that location.A studentship from the School of Architecture, Planning and Landscape,Newcastle University. Arab British Chamber of Commerce. Newcastle University International Postgraduate Scholarship

Aeronautical Engineering: A special bibliography, supplement 60

This bibliography lists 284 reports, articles, and other documents introduced into the NASA scientific and technical information system in July 1975

Cost allocation and risk management in renewable electricity networks

As part of the efforts to mitigate climate change, there has been rapidly increasing share of renewable power generation in the European electricity system. In the interest of bridging the gap between corporate and academic research interests, this PhD project presents a research collaboration on renewable electricity systems between Aarhus University and the energy trading company Danske Commodities.The first part of this dissertation has the perspective of a central planner exploring the optimal system design based on simplified fundamental models of the European electricity system. The aim is to determine the optimal locations and capacities of renewable generation sources while keeping the system reliable and cost-efficient. A subsequent step is to allocate the costs associated with the investments needed for the optimal electricity system of the future. I apply power flow tracing techniques for allocation of transmission system usage, cost allocation of generation capacities as well as consumption-based carbon accounting.In the second part, the perspective is changed to that of individual investors in renewable generation technologies, specifically wind turbines. I apply econometric models in the form of copulas to jointly model wind power production and power spot price. The goal is for an energy trading company to minimize the risk associated with long-term wind power purchase agreements, which, in turn, minimizes the risk of investors in these wind turbines. This provides additional incentives for similar investments and thereby increasing the share of renewable power generation in the European electricity system.Applying physical and financial models to different aspects of the European electricity system has led to insights on the differences between the two modeling perspectives. The central planning perspective is useful when exploring pragmatic solutions to the overall design of the European electricity system of the future, but provides no guidance for the individual actors in the system. In contrast, an investor in renewable generating assets focuses on a set of business goals with little regard to their impact on the overall electricity system.The link between the two perspectives is the policy makers, who regulate the electricity system. The results from system models using the central planning perspective can be used by the policy makers as guidelines to provide the right incentives for investors, and other actors in the system, such that the current European electricity system develops towards the optimal and sustainable system of the future

Evidence review of the potential wider impacts of climate change mitigation options: agriculture, forestry, land use and waste sectors

A report prepared for Scottish Government. Greenhouse gas (GHG) mitigation is a central policy objective in Scotland. The Climate Change (Scotland) Act 2009 sets an interim 42% reduction target for 2020 and an 80% target for 2050 across all sectors of society (1990 baseline). As a priority policy area, it has become vital to better understand the co-benefits and adverse impacts arising from mitigation actions on our environment, economy and society. Integrated assessment is key in prioritising environmental actions, reducing adverse impacts and enhancing positive co-effects. This report aims to summarise evidence on the wider impacts (WI) of GHG mitigation options (MO) in the Agriculture, land use, land use change and forestry sectors (ALULUCF) and those related waste management. The key findings of the review, are a summary of the wider impacts and an overview of the challenges in quantifying and monetising these impacts

Uncertainty quantification Of performance and stability of high-speed axial compressors

Geometrical uncertainties in a compressor (due to manufacturing tolerance and/or in-service degradation) often result in flow asymmetry around the annulus of a compressor that jeopardises compressor stability and performance. Usually, sensitivity of compressor stability and performance for any parametric variation is arrived at by considering all blades to have same dimension. In reality, an inherent blade-to-blade variation causes the blades to have a probability distribution. These blades can be redistributed circumferentially resulting in adjacent passage areas between different blades to be completely random and hence the performance variation. Surrogate model is preferred for quantifying the effects of parametric variation on compressor stability and performance given its quick turnaround time vis-a-vis CFD and experiments. In this thesis, uncertainties for three test cases were considered: each representative of fans on military aircraft engines, fans on civil aircraft engines and a 1-stage transonic compressor used in industrial gas turbine. This research establishes a rule of thumb to arrange blades of differing dimensions around the compressor to eke out maximum performance and stability margin. The parameters tip gap and stagger angle represent manufacturing tolerance while in-service degradation was represented by leading edge damage. For both random tip gap variation (0.15% to 0.94% span) and random leading edge damage (4% to 18% chord), the compressor performance and stability boundaries were found to be best with a zigzag pattern of blade arrangement and worst with a sinusoidal pattern of arrangement. The converse was found to be true for blades having random stagger angle variation (± 2.25% change in nominal stagger angle). The best/worst arrangement of blades with differing dimensions was ascertained using a mix of CFD and travelling salesman (TSP) analogy. The TSP analogy is handy for determining the best arrangement when two or more parameters vary simultaneously. Generalised surrogate model was developed to accurately predict the performance of compressors undergoing random tip gap and stagger angle variation. Due to its robustness, the surrogate model was combined with Monte Carlo technique to gauge the impact of parametric variation on quantities of interest (QoI). The mean absolute percentage error between CFD and surrogate models of stagger angle and tip gap (for different QoI) were found to be less than 0.14% and 1.5% respectively. This de novo analysis considers only the aerodynamic effect from geometric variations while neglecting the associated aeroelastic effects. Detailed analyses based on past experience and physical reasoning were used to validate the numerical simulations.Open Acces

Identifications of renewable energy risks and risk management review

This report describes the basis of risk analyses of renewable energy and climate change risk to renewable energy. The report gives a background on risk analysis and management in connection with climate change and renewable energy. It identifies all aspects of renewable energy risks and risks due to climate change. Contributions give precise current types of risks of renewable energy. This report’s novelty is the identification of renewable energy risks due to climate change. It is a background review report. This report concludes that even though the risks of renewable energy to the environment and/or risks of climate change to renewable energy are small compared to fossil fuels, they cannot be ignored. In addition, safeguarding renewable energy deployment is important. This can be achieved through analysing its risks, understanding energy laws and applying energy laws to renewable energy solutions throughout their lifetime. This report is a starting point and contribution to regional renewable energy development and future in-depth risk analyses of renewable energy by combining multidisciplinary fields.fi=vertaisarvioimaton|en=nonPeerReviewed