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Cyber-physical attacks are the most significant threat facing the utilisation and development of the various smart grid technologies. Among these attacks, false data injection attacks (FDIAs) represent a major category, with a wide variety of types and effects. There has been extensive reporting on FDIAs recently. Several detection algorithms have been developed over the past few years to address this threat. In Chapter 2, this thesis starts by providing a deep analysis of the literature on these algorithms. The concluding remarks of this chapter present the main criteria that should be considered in developing future detection algorithms for FDIAs in different systems of smart grids. Following that, this dissertation proposes FDIA detection algorithms in the major systems in smart grids that are the most susceptible and vulnerable towards FDIAs. In wide-area monitoring systems, being able to promptly differentiate FDIA from normal grid contingencies is crucial for a grid operator to decide the correct response and reduce FDIA false alarms. In Chapter 3, two FDIA characterisation algorithms are developed to address this issue. The automatic generation control (AGC) is paramount in maintaining the stability and operation of power grids. FDIAs are particularly difficult to detect and represent a major threat to AGC systems. Chapter 4 proposes a novel spatio-temporal learning algorithm that can learn the normal dynamics of the power grid with AGC systems. It then utilises this unsupervised learned model in detecting FDIA affecting the AGC system. The utilisation of distributed generation units in power distribution systems has increased the complexity of system monitoring and operation. Numerous information and communication technologies have been adopted recently to overcome the associated challenges, but they have created wide opportunities for energy theft and other types of cyber-physical attacks. Chapter 5 utilises the developed spatio-temporal learning algorithm in Chapter 4 in detecting the various possibilities of FDIA affecting the distribution systems by evaluating the reconstruction error of each measurement sample. The proposed algorithm is data-driven, which makes it resilient against distribution systems’ uncertainties and nonlinearities. The collected results indicate a superior detection performance of the proposed detection algorithms compared to those in the literature.

Customer value propositions (VPs) can have an important role to play in corporate sustainability, as mechanisms for facilitating value delivery across economic, social, and environmental dimensions. However, there are paradoxes and tensions in the process of facilitating value delivery, giving rise to the central question that motivates this thesis: How can marketers integrate sustainability considerations into VPs, and how do they handle the inevitable tensions that arise? Three studies address this question, with an explicit focus on the sustainability elements of VPs rather than VPs themselves. The first, a conceptual study, advances a typology of the roles that sustainability elements play in VPs. It illustrates why simple distinctions between VPs and sustainable VPs lack nuance, proposing the term sustainability-oriented VPs to encompass the spectrum of possibilities. A conceptual framework identifies their antecedents, customer outcomes, and moderating factors, accompanied by ten research propositions and a suggested research agenda. This framework specifies the multi-level nature of antecedents, the need to distinguish between perceived sustainability value and perceived value outcomes, and a novel perspective of sustainability-oriented VPs as tension management exercises. The second study is informed by 40 in-depth interviews with 21 senior marketers across organizations and industries. It identifies four types on a spectrum of organizational sustainability orientations and shows how they influence the role of sustainability elements in VPs. This study also expands on the typology of sustainability element roles, adding considerations that affect customer acceptance of them. Paradox tension management practices also influence these roles. The third study takes the case of an organization operating in a high-pressure sustainability environment. It explores how tensions related to communication about sustainability elements emerge, and in so doing, answers calls for nested paradox research. It depicts a complexity of paradox relationships not evident in studies with fewer paradoxes or levels. Addressing the lack of research connecting organizational logics and sustainability tensions, this study also investigates the role of logics in the flow, management and also creation of paradoxes. The communication choices marketers make can act as paradox tension management strategies.

With the increase of environment awareness and sustainable energy demand, green and renewable energy derived from inexhaustible natural sources, such as solar and wind, has attracted much interest. Wind energy, a key participant in the green energy market, is embraced by many countries as a replacement of traditional energy. Wind power generation, for its robust system structure and economic efficiency achieved by mass production, has a lower cost in the ever-growing market than most energy production relying on other technical routes. Building wind power facilities also have certain benefits of land shielding and ecology protection, because they are mostly three-dimensional constructions that would have little impact on the local environment. Since wind turbines need to be installed in areas with unabated wind flow for maximising energy production, they are often placed on the land with high annual average wind speed and long valid wind time, such as plateaus, mountains, and coasts. However, that also means the turbines would operate in a harsher environment for a considerable length of time; thus, it is crucial to maintain their operation safety, and the study of turbine components through numerical simulation is essential to achieve a balance between cost and safety. In the past decades, the direct-drive wind turbine has been one of the most widely used wind turbines. However, in recent years, the problem of parts aging has surfaced for the earlier batch of direct-drive wind turbines – the bearing has been detected as one of the many vulnerable parts. In direct-drive wind turbine, the temperature in the shaft plays a significant role and should be considered as a design parameter. The operation of the rotating shaft, fixed axle, and bearing is governed by the presence of the lubrication and the proper alignment of the assembly, Nevertheless, as the bearing of the wind turbines fatigues due to long-term stress and strain, the friction begins to increase, and the temperature of the bearing during its operation tends to increase. The rotating shaft with a relatively high temperature would heat the lubricating fluid and result in the change of physical properties of the lubricant. This causes a positive feedback circle in which the friction between the shaft and bearing will keep increasing, and eventually the bearing breakdowns and resulting in the failure of the direct-drive wind turbine system. Hence, it is imperative that the temperature in the shaft is maintained as low as possible so as to prevent further degradation of the bearing. This thesis aims to study the heat increase in a bearing of a wind turbine by focusing primarily on the heat increase in the bearing structure. The consideration of fins to increase the surface area for heat removal is investigated in this thesis. Fin structure is a typical structure that could be attached to the original structure as minor protrusions to enhance the heat transfer from the rotating shaft to the environment. Understanding of the mechanism of the fin enhanced heat transfer in rotation structure will be obtained, and feasibility of using a fin structure to reduce the bearing temperature of the wind turbine as recorded by the maximum temperature being experienced in the assembly will be attained for design considerations. Moreover, optimisation study of fin spacing and height in the rotating motion is also carried out. Additional information on the pressure on the surface of the fins, as well as the shear stress and maximum deformation caused by the rotation of the fins are analysed.

Hybrid aircraft are a proposed intermediate step towards full electrification of aircraft. This is an important direction for the aviation industry, in order to play its part in society’s shift away from burning fossil fuels, to prevent exacerbation of their environmental impacts. The exhaust gases of a piston aero-engine have been identified as a significant source of wasted heat that could be exploited to improve the overall efficiency of the powertrain and thereby reduce fuel-burn. This thesis explores the feasibility of harvesting this wasted exhaust heat in a piston-engine, propeller-driven aircraft, from an initial high-level assessment of the possibility of the concept, through to an evaluation of whether an organic Rankine cycle (ORC) is a suitable candidate for the harvester that converts the waste heat to a useable mechanical form and finishing with a preliminary sizing analysis to estimate the required hybrid componentry mass and from that, the hybrid aircraft fuel-burn reduction. The hybrid powertrain considered features a downsized ICE, sized to provide enough power for cruise, with a traction battery providing additional power for climb and manoeuvres. A parallel powertrain topology is found to be the most efficient and lightest way to connect the harvester output back to the propeller shaft, and its required electrical componentry is given. The ICE power downsizing factor is introduced as a figure of merit and its upper limit is quantified for any potential harvesting technology characterised by efficiency and mass. The Breguet range equation is adapted for the hybrid powertrain to estimate fuel-burn during cruise. Three benchmark aircraft of varying size and power are used to determine the best use cases for this hybrid powertrain. The maximum allowable mass of the harvester for each aircraft is calculated for a reference mission of 200 km at 5000 ft. The ORC is then modelled and optimised. It is found that its efficiency can be as high as 14.27% which corresponds to a downsizing factor limit of 34.1%. It is calculated that the fuel-burn reduction of the hybrid powertrain has a theoretical upper limit of 12.7 - 14.5% (for a mass-less ORC). The estimated mass of the ORC is then computed, revealing that it falls below the previously calculated maximum allowable mass for all aircraft. However, using this mass, the estimated fuel burn falls to only as high as 4.4%. It is thus concluded that the hybrid powertrain is a feasible method of reducing aircraft fuel-burn, with discussion of further research and development steps.

Energy plays a very significant role in the operation of the economic machinery of a country. Insufficient energy supply can lead to high energy prices, which, in turn, can cause many, if not all, prices of commodities to increase. This leads to inflation and all its consequential adverse outcomes within the economy. For this reason, energy planning is an essential macroeconomic planning activity for the economic planning of the country. Like most other countries, energy planning in Australia is done through econo metric modelling. This is done using linear regression models that correlate energy demand (independent variable) to other macroeconomic factors, like gross domes tic product, as dependent variables. However, such a technique is unsuitable when complex interactions exist between variables. Motivated by the success of Artificial Neural Networks (ANN), this thesis aims to develop an ANN model as an alternative tool for energy demand forecasting in Australia. First, a set of macroeconomic variables is chosen as potential input features (independent variables) for the energy demand forecasting model. The output feature (dependent variable) is the monthly energy use of Australia. The output feature was measured in tons of oil. Several incremental models are developed and run to see the incremental effect of adding features on the accuracy of performance of the ANN models. Correlation analysis of features is also performed to see how each feature affects the output feature and how they are related. Then, to determine what structure of an ANN would provide better perfor mance, three different structures are chosen and run on different datasets. Dif ferent testing and training periods are used to establish the performance of each model. To automate the process of optimising ANN models, a genetic algorithm is designed to optimise the number of neurons in different ANNs. In doing this, the overall structures and performance of optimised ANNs for predicting energy production in the Australian context are ...

Cellulose is the most abundant polymer on earth. Its use within the bioenergy and bio-materials sector to provide raw feedstock molecules is critical to supplant petrochemical-derived resources. The alkaline carbohydrate fuel cell has recently been of growing interest as it has been shown to produce power directly from monosaccharides without further breakdown and combustion steps that introduce substantial energetic losses. The development of the direct alkaline carbohydrate fuel cell is currently in its infancy, with developments needed to refine understandings of cell geometry, charge mediation and industrial application pathways. The findings of this thesis represent contributions to these areas, demonstrating greater mechanistic understanding of these devices and new pathways forward. Mechanistic insights were gained through examining simple geometric design considerations that proved capable of significantly improving fuel cell performance. Decreasing the distance between electrodes from 20 to 6 mm increased power outputs by ~35 % and increasing the density of the nickel foam anode from 250 mg cm3 to 1000 mg cm3 increased power outputs by ~30 %. Further, indigo carmine was found to be unstable in highly alkaline solutions. Breakdown of the dye produced significant amounts of current without any carbohydrate present, calling into question the previously reported relationship between the indigo carmine concentration and power generation within an alkaline carbohydrate fuel cell. As pure carbohydrate fuels may raise ethical concerns about food security, new organic fuels were proposed and new cellulose to energy pathways examined. III A novel low-temperature hydrothermal cellulose degradation process was developed to create new cellulose-derived alternatives. The process converted over 61 % of microcrystalline cellulose to soluble aldaric acids whilst simultaneously producing value-added magnetic nanoparticles. Finally, a new novel fuelling approach was reported in which the selected fuel was reverse-engineered from the desired oxidation products. Within the fuel cell, the oxidation pathway between 5-HMF and FDCA was exploited to generate 6.5 x the power of the equivalent glucose fuel cell, whilst synthesising high-value molecules known to be useful for bioplastics. As the scale of bio-molecule production increases, this passive energy generation scheme presents an opportunity to produce significant power from an otherwise untapped chemical process, increasing the green chemical industry’s energy efficiency. Overall, this thesis entails optimisations towards enhancing energy production within the alkaline organic fuel cell and explores new novel applications which broaden the scope of these green electricity-generating devices.

The scramble for minerals, such as lithium, critical to renewable energy technologies is a feature of our race to decarbonise. At the same time, changing societal expectations are increasing pressure on companies to operate in a manner that respects human rights, including Indigenous Peoples’ rights. Situated at the nexus of these global trends, this thesis examines business and human rights (BHR) dynamics at rights-holder level in the context of extraction in South America’s ‘lithium triangle’. Examining how legal and non-legal factors translate to corporate behaviour and rights outcomes on the ground, the thesis addresses the research question: What are the key intersecting factors shaping corporate engagement with Indigenous communities and their rights in the lithium triangle? Based on extensive in-person empirical research in the region, it examines the complex dynamics between governments, companies and Indigenous communities. Empirical chapters reveal a broad range of factors influencing corporate engagement and thereby better rights outcomes. These can be distilled into four key themes: 1. Human rights pathways: state human rights commitments are transmitted to lithium triangle companies by more indirect means than traditional compliance with horizontal obligations would demonstrate. 2. Shifting dynamics: changing expectations of companies, particularly in the context of decarbonisation, has created a rapidly evolving landscape of pressure on companies from downstream customers and other actors in the lithium value chain. 3. Indigenous rights: Indigenous communities in the lithium triangle have become powerful advocates for their own rights, creating significant bottom-up influence and altering traditional corporate perceptions of risk. 4. State absence: partial absence and significant lack of capacity of the state has resulted in the effective ‘privatisation’ of certain rights, leaving companies to fill the gap. That lithium technology is potentially rights-enhancing at a global level while its extraction at local level may be rights-endangering is a juxtaposition foregrounding the need for a just transition and raising interesting questions about the realities of rights on the ground in the presence of a prevailing global economic imperative. The lithium triangle is a powerful case study highlighting the need for governments, companies and communities to work closely together to minimise negative rights impacts and maximise positive outcomes.

Photosynthesis has played a key role in the evolutionary trajectory of life on Earth. The ways in which organisms harvest sunlight have diversified over the billions of years since photosynthesis emerged in the quest for more efficient use of this energy source. The evolutionary origins of some organisms’ light harvesting apparatus, however, have remained elusive as have the causes for stark architectural changes between evolutionarily related organisms. In this thesis, I firstly provide a detailed exploration of published data describing photosynthetic efficiency through the lens of structural biology and quantum mechanics, examining observations from a range of antenna systems. After having built a framework for how an efficient photosynthetic antenna may be constructed, the rest of this thesis explores the evolutionary trajectory of the light harvesting antenna of the cryptophyte algae. Cryptophytes are a clade of secondary endosymbiotic algae which gained their photosynthetic chloroplasts from an engulfed red alga, but produced in an architecturally distinct antenna. Red algae have an antenna comprised of stacked protein rings that form an energetic funnel to the photosynthetic reaction centre which generates chemical energy from photon excitations. Cryptophytes took this energy funnel and dismantled it; complexing one of its component proteins with a peptide of unknown origin (‘cryptophyte alpha’) and packing them at high density within the chloroplast. By examining recently published cryo-electron microscopy maps of red algal antennas, I have discovered the evolutionary ancestor of the unique cryptophyte alpha subunit. Through this discovery, I reveal possible evolutionary events following secondary endosymbiosis leading to the origin of the cryptophyte light harvesting system. Finally, I examine the light harvesting antenna of a particular cryptophyte species, Hemiselmis andersenii, isolating multiple protein components and determining their crystal structures at high resolution. Through this, I discover a more complex antenna than previously thought with multiple protein components and a rich energetic structure. Some of these antenna proteins show previously unrecognised spectral properties and chromophore architecture. This structural data aids in understanding the architectural change between the red algal and cryptophyte light harvesting antennas and further diversification within the cryptophyte clade.

Photovoltaic (PV) generation is emerging as a significant technology in the global energy transition. However, while rapid urbanisation is driving increasing housing density, PV uptake in multi-occupancy housing has been limited by comparison with stand-alone housing in many jurisdictions, including in Australia, despite its world-leading 22% residential PV penetration. This thesis presents a multidisciplinary analysis of the opportunities and challenges for, and costs and benefits of, rooftop PV deployment on Australian apartment buildings. A novel geospatial analysis was used to assess the opportunity for solar on Australian apartment rooftops. Statistical and cluster-based analysis was used to characterise individual and aggregated apartment load profiles. Reviews of the academic literature and Australian regulatory arrangements, together with a series of stakeholder interviews, were undertaken to identify potential implementation arrangements for, and barriers to, deployment of apartment PV. Modelling of PV generation, energy and financial flows was used to compare outcomes for diverse buildings under different PV configurations. The size and diversity of the dataset and the variety of arrangements modelled represents a significant contribution to the literature. The thesis identifies potential PV capacity of 2.9GW – 4.0GW on Australian apartment buildings and describes significant differences between load profiles of apartments and houses. Applying PV generation to aggregated building loads is shown to increase self-sufficiency and PV self-consumption, compared to separate systems supplying common property or individual apartments, and can sometimes generate financial benefits for customers. While embedded networks can enable access to beneficial retail arrangements, behind the meter solutions may reduce regulatory complexity and cost. Optimum solutions depend on building characteristics and financial settings. Adding battery energy storage systems (BESS) can further increase self-sufficiency and decrease peak demand but the economic case is not compelling with current capital costs. Barriers including building stock diversity, demographic factors and knowledge issues, as well as specific Australian regulatory arrangements concerning governance of apartment buildings, regulation of the energy market, and electricity tariff policies, impact on the options available to apartment residents to act co-operatively in accessing renewable energy. This research identifies possible emerging business models and policy approaches to support increased apartment PV deployment.