In the last century, markets, technical configurations, existing power relations, and prevailing ideologies in industrialised countries have co-evolved in ways that promote fossil-fuel-based systems. Relatedly, the literature on sustainability transitions (STs) has gained significance in the last twenty years, primarily because of increased interest by those who are concern with enabling shifts towards low-carbon sources of energy. This research examines the kinds of changes which take place in fossil fuel path-dependent systems in response to the pressure imposed by the advent of greener alternatives. Understanding how fossil-fuelled path-dependent systems respond to such demands enables us to identify counter-strategies, which may help accelerate sustainability transitions.

Using a combination of the multi-level perspective on socio-technical transitions and institutional theory, the thesis presents case studies centred on South Africa’s coal-fired electricity regime, which is entrenched in a system known as the minerals-energy complex (MEC). The case studies examine how the coal-fired electricity regime tried to maintain stability in the face of pressure to decarbonise by diversifying to include more renewables-based and gas-fired electricity generation, each of which is considered as a niche.

The findings from the case studies are organised into three articles. The first paper presents a case study on the establishment of the MEC and shows how it became a highly path-dependent system, posing a formidable obstacle and challenge for new entrants. The second paper investigates the contestation between the dominant regime incumbent, Eskom, versus the nascent renewable energy programme. This paper demonstrates an evolving strategy of regime resistance in response to several gains achieved by the renewables niche over time. The third paper examines the emergence of a gas-to-power niche against a backdrop of interactions between electricity and liquid fuel regimes. This paper shows the highly dynamic changes that take place in a regime as it tries to maintain stability.

The overall findings demonstrate that the electricity regime evolved from highly stable to having features of a fractured regime, or what could be understood to be a form of destabilisation. The thesis contributes to the ST field by suggesting several ways in which regime stability and change could be better understood. These include enhanced theorising of regime resistance through analysis of the regime’s multi-dimensional selection environment and mobilising endogenous institutional concepts through various modes of change (drift, layering, conversion and displacement) into the theory. Policy recommendations suggest a fractured regime requires a temporally sensitive displacement policy mix. This is one in which varying stages of regime stability are recognised and potentially exploited by corresponding niche strategies.

This paper describes a novel contactless power transfer (CPT) system with geometrically improved H-shape ferromagnetic cores and electromagnetically prospective modelling analysis methods for wireless power transmitting (WPT) applications of electric vehicles (EVs). A CPT prototype, using optimized H-shaped magnetic couplers and series-to-series (SS) compensation, is proposed to address and ensure the maximization of system efficiency, power transfer ratings, and air gaps of coupling coils. By focusing on the main factors such as various system operating frequencies, different geometric designs of coils, changeable inductive coupling distances, electromagnetic field performances and actual phase angle deviations when the inductive coupling system tends to be stable with its waveforms, this small-sized H-shape CPT system has been analytically considered and modelled in a finite-element method (FEM) environment, resulting in a maximum system efficiency of 59.5%, a coil transmitting efficiency of 83.8% and a maximum power output of 42.81 kW on the load end when the resonant coupling of CPT system tends to occur within a range of calculated resonant frequencies, with an air gap of 10 mm. Moreover, the system efficiency and coil transmitting efficiency can reach 47.75% and 77.22%, respectively, and the highest RMS real power to load can achieve 31.95 kW with an air gap of 20 mm. Besides, with an air gap of 30mm, this H-shape CPT system is measured to output 20.39-kW RMS power, along with the maximum system efficiency and coil efficiency of 41.78% and 63.23%, respectively. Furthermore, the improvements of flux linkage, magnetic flux density regarding the actual electromagnetic performance produced and the issues on the calculated natural resonant frequencies have been studied by result analysis and comparison of electromagnetic field parameters generated. In addition, the current limitations and further design considerations have been discussed in this paper.

Scientists, investors and policy makers have become aware of the importance of providing near accurate spatial estimates of renewable energies. This is why current studies show improvements in methodologies to provide more precise energy predictions. Wind energy is tied to weather patterns, which are irregular, especially in climates with erratic weather patterns. This can lead to errors in the predicted potentials. Therefore, recurrent neural networks (RNN) are exploited for enhanced wind-farm power output prediction. A model involving a combination of RNN regularization methods using dropout and long short-term memory (LSTM) is presented. In this model, the regularization scheme modifies and adapts to the stochastic nature of wind and is optimised for the wind farm power output (WFPO) prediction. This algorithm implements a dropout method to suit non-deterministic wind speed by applying LSTM to prevent RNN from overfitting. A demonstration for accuracy using the proposed method is performed on a 14-turbines wind farm. The model out performs the ARIMA model with up to 80% accuracy.

This paper presents a frequency domain based methodology using Chebyshev polynomials of the first kind, the methodology can be used to make an analysis of time-varying linear systems in the transient state. The method takes advantages of the operational properties available to most orthogonal series expression, i.e. integration, differentiation, product and coefficient matrices. The approach may be seen as an extension of phasor analysis commonly used for the analysis of linear time-invariant electric networks to periodic networks. A high order time-varying system is presented and it is analyzed via the proposed methodology.

Battery Electric Energy Storage Systems (BESS) are increasingly entering electric distribution networks. Distribution system operators, suppliers, vendors and policy makers lack a common framework in terms of guidelines and recommended practices on the way BESS should be integrated into the distribution networks. The objective of WG C6.30 entitled "The Impact of Battery Energy Storage Systems on Distribution Networks" is to complement and update earlier work on Electric Energy Storage Systems. The TB produced focuses on:

> Planning and design considerations for BESS in distribution systems;
> Operational considerations for BESS in distribution systems;
> Use-cases and business cases for BESS in distribution systems;
> Standards and Grid Codes for BESS in distribution systems;
> Practical international experiences with BESS in distribution systems.

Research stations in the Antarctic have their own electrical generation facilities and are not interconnected to any grid. Scarcity of fuel and unavailability of interconnection characterize these Antarctic energy systems as mission-critical isolated microgrids. In this work, an energy management strategy has been proposed for South African Antarctic research station SANAE IV for improving fuel efficiency. The proposed strategy consists of optimal dispatch of generation and installation of a thermal load controller for the supply side, and a novel demand response scheme for the demand side. The system was simulated using HOMER Microgrid Analysis Tool. Results showed an 8.30% decrease in fuel consumption, which corresponds to 21,876 litres of diesel annually. These savings can be achieved without major capital expenditure or difficult engineering work.

This paper presents a Virtual Power Plant (VPP) decision making approach which uses fuzzy logic and a novel “insecurity” metric, based on human psychology. The VPP approach is modelled as a multi-agent system, which aims to minimize carbon emissions and/or energy cost, using an aggregation structure similar to energy or carbon markets. The “insecurity factor” reflects the operational flexibility of micro-generators, translated to a numerical value through fuzzy logic. The system was able to create a functional internal VPP market, where the micro-generators were trading autonomously according to external price signals and taking into account their own needs and limitations, as well as short-term forecasts.

This paper presents a conceptual dual loop waste heat recovery system to reduce the disturbance of the high-transient heat sources from an internal combustion engine and investigates a dynamic model of the waste heat recovery system at supercritical condition.

Access to electricity is an important precondition to many aspects of human and
economic development. Yet, in rural sub-Saharan Africa in particular, access rates
remain very low — at an average of 17% and much lower in some cases. Rural
electrification in Kenya, the focus of this thesis, had only reached 7% in 2014. Given
the goal of universal electrification by 2030, formulated as part of Sustainable
Development Goal 7, scalable and replicable approaches that are able to support
productive and non-productive uses are required.
Mini-grids are one promising solution to this problem, alongside grid extension and
off-grid approaches such as solar home systems. However, their long-term operational
sustainability has historically been a challenge. While the academic literature to date on
sustainable energy access has largely been two-dimensional in its analysis of mini-grids
(focusing on technology and economics or financing), this thesis contributes to an
emerging body of recent contributions to the literature, which have begun to foreground
socio-cultural considerations.
Bridging the literature on collective action for common-pool resource (CPR)
management and property rights theory, a refined theoretical framework is produced for
the purpose of analysing the institutional conditions for sustainable management of rural
mini-grids. The utility of this framework and of treating electricity in a mini-grid as a
CPR is demonstrated via empirical analysis of three case studies of mini-grids in rural
Kenya and evidence from 24 expert interviews. This yields insights on nontechnological
approaches to addressing operational challenges relating to sustainable
mini-grid management, e.g. fair allocation of limited amounts of electricity to different
consumers in ways that are acceptable to the entire community. This thesis develops
contributions to the literature on sustainable CPR management and collective action,
property rights theory and energy access in developing countries. From these theoretical
and empirical insights, it explores a novel institutional structure for sustainable
management of pro-poor mini-grids in the form of a community–private property hybrid
management platform, thereby opening up opportunities for future research into the
implementation of such a platform. The thesis represents the first comprehensive
attempt to analyse the institutional aspects of pro-poor mini-grid management as well as
the first comprehensive attempt to treat electricity in a mini-grid as a CPR.

The decreasing availability of fossil fuels and their negative environmental impacts requires urgent need of developing renewable energy. The main objective of this research was to develop low-dimensional nanomaterials for harvesting solar and mechanical energy with high conversion efficiency. In particular, photoelectrochemical water splitting and photovoltaic cell applications driven by sunlight were investigated in this project. A highly efficient triboelectric nanogenerator was investigated for harvesting mechanical energy. The device was further integrated with an organic solar cell for harvesting both mechanical energy and solar energy.
My research work started with the synthesis of nanostructured materials. Electrospinning, as well as electrospray, was developed to synthesise nanofibres and hollow hemispheres. The influences of processing parameters to the morphologies and structures of the nanomaterials were systematically investigated. An electrophoretic deposition method was also developed to form good-quality nanostructured metal oxide thin films, which were applied in photoelectrochemical water splitting. The metal oxide hollow hemisphere thin films were also applied in dye-sensitised solar cells.
A transparent and flexible triboelectric nanogenerator was developed in order to harvest mechanical energy. The contact electrodes were created using metal nanowire percolation networks embedded in a polymer matrix. The correlation between the energy conversion performances and optical property of the triboelectric electrodes were comprehensively studied as a function of the areal fraction of the metal nanowires.
A flexible hybrid cell, integrating the solar cell with the triboelectric device, was designed by constructing an organic solar cell under a single-electrode triboelectric nanogenerator. The hybrid cell could convert both solar and mechanical energies into electricity independently and simultaneously. Such devices are potentially able to supply electricity day and night. Nanomaterials offer novel approaches for enhancing the efficiency of harvesting solar and mechanical energy in a hybrid device.

The inclusion of Distributed Energy Resources (DER) into the grid is a great way to maximize and increase power generation at large. However it could also result in power quality issues due to their generation being dependent on external factors such as the weather. This paper aims to investigate power quality problems and potential solutions in low-voltage networks with high penetration of DER sources. The PV-Grid system is modelled and simulated using real PV irradiance and temperature data collected from PV panels during the day time on 22 of May 2015. The I-V and P-V characteristics of the PV-array were extracted to create a realistic model of the solar panels used in this paper. A Distribution STATic COMpensator (D-STATCOM) is utilized as the grid-connected inverter to perform conversion of power, power management, and compensation of reactive power. The simulation results presented demonstrate the use of the D-STATCOM to both convert the real power to AC and contribute towards the management of system reactive power at up to 100% of its rating.

This paper presents a method of utilising the Energy Hubs concept, a whole systems approach, to optimise and control the input fuels to a given load or demand. A Raspberry Pi was used as a controller for a co-firing Combined Heat and Power (CHP) generator. The control of the two fuel inputs was validated. It was found that the methodology can minimise the desired objective effectively. In addition, the control arrangement was found to be suitable for controlling an industrial valve which regulates the fuel input to the CHP generator.

This paper discusses the AC fault ride through of two terminal modular multilevel converter (MMC) VSC based HVDC integration of combined offshore wind and wave farms. The combined offshore wind and wave farms are modelled as a controllable three phase voltage source connected to a 600MVA, 460kV/370kV transformer. A 31- level MMC has been selected because of acceptable harmonic attributes. Two 300kV DC submarine cables with length of 100km have been employed in this study. A voltage source has been connected in series with an inductive resistive circuit to give a short circuit ratio of 3.5. This paper finally presents a comparative simulation analysis of hysteresis based and PI based DC voltage controller for fault ride through (FRT) capability. The analysis showed that the PI method resulted in smaller overshoots and dips. A high switching frequency PWM based electromagnetic transient (EMT) model in MATLAB/Simulink was developed for the analysis.

Multiple energy carrier systems stem from the need to evolve traditional electricity, gas and other energy systems to more efficient, integrated energy systems. An approach is presented, for controlling multiple energy carriers, including electricity (AC or DC), heat, natural gas and hydrogen, with the objective to minimise the overall cost and/or emissions, while adhering to technical and commercial constraints, such as network limits and market contracts. The technique of multi-agent systems (MAS) was used. The benefits of this approach are discussed and include a reduction of more than 50% in the balancing costs of a potential deviation. An implementation of this methodology is also presented. In order to validate the operation of the developed system, a number of experiments were performed using both software and hardware. The results validated the efficient operation of the developed system, proving its ability to optimise the operation of multiple energy carrier inputs within the context of an energy hub, using a hierarchical multi-agent system control structure.

South Africa’s coal-dominated electricity sector, a key feature of the country’s minerals-energy complex, is in crisis and subject to change. This offers potential opportunities for decarbonisation. Despite positive examples of decarbonisation in South Africa’s electricity sector, such as a procurement programme for renewable energy, there are structural path dependencies linked to coal-fired generation and security of supply. Decarbonisation goes far beyond what is technologically or even economically feasible, to encompass a complexity of political, social and economic factors. Meanwhile, decision-making in electricity is highly politicised and lack of transparency and power struggles in the policy sphere pose key challenges. Such power struggles are reflected in national debates over which technologies should be prioritised and the institutional arrangements that should facilitate them.

Planned Communities (PCs) present a unique opportunity for deployment of intelligent control of demand-side distributed energy resources (DER) and storage, which may be organized in Microgrids (MGs). MGs require balancing for maintaining safe and resilient operation. This paper discusses the implications of using MG concepts for planning and control of energy systems within PCs. A novel tool is presented, based on decision trees (DTs), with two potential applications: (i) planning of energy storage systems within such MGs and (ii) controlling energy resources for energy balancing within a PC MG. The energy storage planning and energy balancing methodology is validated through sensitivity case studies, demonstrating its effectiveness. A test implementation is presented, utilizing distributed controller hardware to execute the energy balancing algorithm in real-time.

Creating a diverse and flexible energy system to ensure security of supply is at the heart of UK energy policy. However, despite the apparent interest in the idea of securing supply in this way and the term ‘diversity’ becoming more frequently used in this context in government White Papers, policy discourse and the academic literature relatively little attention has been given to exploring what diversity means, how it can be measured, what contribution it can make to different policy objectives and the specific implications for the UK electricity system. Furthermore CCS technologies which are becoming increasingly important to decarbonisation of the power sector in order to meet legally binding greenhouse gas targets set out in the Climate Change Act which raises the question, what are the potential impacts of these technologies on the diversity of the future UK electricity system?

To answer this question a mixed methodology of quantitative energy-economic modelling (using MARKAL), scenario analysis and diversity analysis is combined with qualitative semi-structured stakeholder interviews. Data analysis is carried out in two parts. The first assesses the diversity (with a specific focus on the effect of different input assumptions on CCS technologies) of the scenarios generated using Stirling’s Diversity Heuristic and creates a set of ‘diversity profiles’ which map changes in diversity across each scenario. The second part uses stakeholder perspectives to inform the quantification of diversity across the same set of scenarios providing evidence of the impact of different stakeholder perspectives on the overall diversity of the electricity system.

Year 2010 is the significant year of offshore wind power development in China. The first national offshore wind power project is connected to the grid, and the first round of concession projects marks the strong support from central government. It is foreseeable that offshore wind power capacity in China will expand rapidly in the future, and the understanding pattern of it is crucial for analyzing the overall wind market in China and global offshore wind power development. This paper firstly provides an overview of global offshore wind power development, then in China, including historical installation, potential of resources, demonstration and concession projects, and target of development. Based on this, analysis on current policies related to offshore wind power and their implementation, current wind farm developers and turbine manufacturers of China's offshore wind industry is done. All the previous analysis generates complete evaluation of current status and some issues and trends of China offshore wind power development, based on which some policy recommendations for sustainable development of offshore wind power are made.

A number of alternative economic and economic geography theories have been developed to account for the divergence of national political economy and industrial dynamics. These include the varieties of capitalism, developmental state, neo-Schumpeterian innovation, and Gerschenkronian catching-up theories. In this thesis I shall argue that in these theories a core and often shared concept of "institutional advantage" plays a central role in explaining different economic performances across nations.

This concept is elaborated as a means of examining the causal relationships between institutional advantages and four necessary functions (market creation, capital mobilisation, process innovation and cost reduction) in the development of the photovoltaic (PV) industry of Germany, China, and South Korea. The development of these industries is examined in detail on the basis of empirical evidence in the form of archival and interview based data.

Two main conclusions are reached. Firstly, domestic market creation is not a generally necessary condition for the development of a local PV industry at a national level. China's PV industry grew fast without a sufficient domestic market unlike in Germany. However, domestic market creation is important, because the domestic PV industry, national support policy and the domestic market are interrelated. Secondly, capital mobilisation is a core function in establishing the PV industry. In the 2000s, Korea failed to establish its local PV industry despite an institutional advantage in creating domestic markets, mainly due to the fact that it had an institutional disadvantage in mobilising capital. However, Germany and China succeeded in mobilising capital in their PV sectors, governments playing a decisive role in facilitating the raising of funds in both cases.

This research contributes to a better understanding of the nature of industrial dynamics in the context of institutional configurations of a national political economy, broadening the usage of "institutional advantage" by applying this concept to comparative analysis on the national PV trajectories. Moreover, from the perspective of the social system, four necessary functions for the PV industry have been proposed and investigated.

This study develops an improved mathematical model for analyzing investment portfolios of electricity generation assets to meet long-term future demand for power. Results from such analysis will provide diversified mixes of fuels and generation technologies that achieve a balance between reduced cost and reduced risk where risk is measured by the variability of fuel costs. Fuel Diversification (FD) is important in managing the cost of electricity generation. Past studies have modeled the FD problem using the Mean-Variance (M-V) portfolio approach without explicit considerations of the load duration curve (LDC).

Most extant formulations of the M-V approach to the FD problem focus on minimizing the mean construction and other improvements, operating and maintenance costs plus a factor times the variance of the operating and maintenance costs for a representative year. Construction and other improvements are typically levelized to obtain an annuity payment over the life of the plant. In order to levelize the costs, each generating plant requires an assumed capacity factor (CF); therefore, unit costs representing technologies are evaluated in the portfolio assuming a xed load factor (LF). The M-V portfolio method as seen in the literature fails to capture a significant aspect of the underlying problem - the levelized costs change with the load factor. The upshot is that results from models that ignore the load curve are unreasonably specialized and viewed by practitioners as naive and inappropriate. This situation can be remedied by classifying loads (e.g. base, peaking, and cycling) and dedicating different technology mixes to serving the different load classes. Using this approach, the LDC is partitioned into contiguous segments. Unlike the standard M-V portfolio fix method where costs representing technologies ignore load variation, the method proposed in this research can accommodate multiple load types. Separate LFs for each load class are taken into account in balancing the mix of the available fuel/technology candidates. As a result, generating units are evaluated by how they are utilized over the load profile, and thus, the fuel mixes of generation assets are optimized for serving the varying loads.

Use of the method was demonstrated with an analysis for the state of Indiana (Gotham et al. (2009)) and the results were assessed to be much more credible than those obtained when the LDC is ignored. However, their approach treated load cutoffs for the LDC as predetermined, exogenous levels. Here, load cutoffs are endogenously chosen in an optimal manner. This formulation called the endogenous-cutoff model is used to show that optimal cutoffs are sensitive to the level of risk aversion and to observe the rate at which solutions improve as the number of endogenous cutoffs increases. This analysis will provide insight into what constitutes a good set of cutoff levels and how many cutoffs are sufficient when considering how to break up the LDC for managing FD. Analysis of this problem leads to an alternative formulation that allows the nonlinearities to be confined to a small number of variables where the cutoff s are exogenous. Instead of solving for optimal load cutoff levels, the LDC is segmented into a large number of equally spaced load cutoff levels. This equally spaced cutoff model is an approximation to the theoretical continuous-cutoff model; hence it is called the continuous model approximation.

Numerical results for the state of Indiana are presented via a series of case studies. These include analyses of the impact of the addition of carbon costs, simulating implementation of cap and trade legislation, and zero availability of nuclear power, simulating the situation where the public becomes adamantly opposed to nuclear technology. Sensitivity analyses with respect to problem data (e.g. expected technology cost and variance/covariance of technology cost) are also performed.

We consider the energy sourcing decision problem faced by industrial power consumers who must determine their long-term electricity procurement plan and need to evaluate various options to meet load requirements for their facilities including those which may involve on-site renewable generation. Other than sourcing from on-site renewable generation such as solar photovoltaic or wind, power can be purchased from spot markets or through a power purchase agreement, i.e. energy supply contract. We develop a mixed-integer linear model to make decisions that include investments in renewable generation, power purchases from spot markets, and amount sourced from supply contracts. Taking into account renewable energy certificates, the model's objective is to maximize revenue from trading renewable certificates minus the expected total costs of investing and operating on-site renewable generation, and purchasing from electricity markets. Real load data from manufacturing plants are used to illustrate a numerical case study for our model.

Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (1952). However the standard meanvariance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also present examples using real data for the state of Indiana and demonstrate the ability of the model in providing useful insights.

Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean–variance portfolio analysis pioneered by Markowitz (Markowitz, H., 1952. Portfolio selection. Journal of Finance 7(1) 77–91). However the standard mean–variance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean–variance approach, we propose a variant of the mean–variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also illustrate the approach using data for the state of Indiana and demonstrate the ability of the model in providing useful insights.

A practical mathematical programming model for the strategic fuel diversification problem is presented. The model is designed to consider the tradeoffs between the expected costs of investments in capacity, operating and maintenance costs, average fuel costs, and the variability of fuel costs. In addition, the model is designed to take the load curve into account at a high degree of resolution, while keeping the computational burden at a practical level.

The model is illustrated with a case study for Indiana's power generation system. The model reveals that an effective means of reducing the volatility of the system-level fuel costs is through the reduction of dependence on coal-fired generation with an attendant shift towards nuclear generation. Model results indicate that about a 25% reduction in the standard deviation of the generation costs can be achieved with about a 20–25% increase in average fuel costs. Scenarios that incorporate costs for carbon dioxide emissions or a moratorium on nuclear capacity additions are also presented.