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The expansion of offshore renewable energy infrastructure and the need for trans-continental shelf power transmission require the use of submarine High Voltage (HV) cables. These cables have maximum operating surface temperatures of up to 90°C and are typically buried 1-2 m beneath the seabed, within the wide range of substrates found on the continental shelf. However, the heat flow pattern and potential effects on the sedimentary environments around such anomalously high heat sources in the near surface sediments are poorly understood. Temperature measurements from a 2D laboratory experiment representing a buried submarine HV cable are presented, and the thermal regimes generated within a range of typical unconsolidated shelf sediments - coarse silt, fine sand and very coarse sand are identified. Several experiments were carried out in a large (2 x 2.5 m) tank filled with water-saturated artificial (ballotini - spherical glass beads) and natural sediments (fine marine sand) with a buried heat source and 120 thermocouples to measure the time-dependent 2D temperature distributions. The observed steady state heat flow regimes and normalised radial temperature distributions were compared with outputs from corresponding Finite Element Method (FEM) simulations. The results show that the mechanisms of heat transfer and thus temperature fields generated from submarine HV cables buried within a range of sediments are highly variable. Coarse silts with ~10-13 m2 permeability, are shown to be purely conductive with 10-60 °C radial temperature distribution within 40 cm from a 60°C above ambient source. Fine sands with ~10-11 m2 permeability, demonstrate a transition from conductive to convective heat transfer at c. 20°C above ambient with 10-55 °C asymmetric temperature rise up to 1 m above a 55°C above ambient heat source. Very coarse sands with ~10-9 m2 permeability, exhibit dominantly convective heat transfer even at very low (c. 7°C) operating heat source temperatures and with 10-18 °C significant asymmetric temperature rise of the surrounding sediments over 1 m above an 18 °C heat source. The computed controlling thermal properties demonstrate a distinct variation of thermal diffusivity and conductivity within different sediment types; sandy (fine sands) sediments are about twice more effective at diffusing heat than muddy (coarse silts) sediments. The occurrence of convection heat transfer within high permeability sediments is an important insight that are currently neglected in the existing IEC 60287 standard for current ratings estimation. Significant convection supports more efficient heat transfer leading to reduced cable temperature, increased current ratings and ampacity, decreased degradation rates of cable insulation and thus increased life span and decrease manufacturing costs of submarine cables. Also the varying sediment thermal conductivity around submarine HV cables further implies that cables buried around sandy sediments will uptake heat more rapidly than in muddy sediments, which are also not considered in the existing IEC 60287 standards. In addition, these findings are important for the surrounding near surface environments experiencing such high temperatures and may have significant implications for chemical and physical processes operating at the grain and sub-grain scale as well as biological activity at both micro-faunal and macro-faunal levels.

Environmental issues such as global warming, limited storage of fossil fuels and concerns about cost and energy efficiency are driving the development of the future smart grid. To reduce carbon emissions, it is expected that there will be a large-scale increase in the penetration of renewable generators (RGs), electric vehicles (EVs) and electrical heating systems. This will require new control approaches to ensure the balance of generation and consumption and the stability of the power grid. Energy storage can be used to support grid operations by controlling frequency and voltage, and alleviating thermal overload. This thesis makes three novel contributions to the field: optimal battery sizing; optimal dispatch of vehicle-to-grid batteries; and optimal coordination of EV batteries and RGs. Appropriate sizing of the energy storage is very important when using it to support the power system. In this thesis, an approach has been proposed to determine the capacity of a battery storage providing support during N-1 contingencies to relieve transmission line thermal overload. In addition, as the increasing use of EV is an inevitable trend in the future smart grid, the system's peak demand may increase significantly due to EV charging, causing serious overloading of some power system facilities such as transformers and cables in the grid if an effective EV battery dispatch strategy is not used. Therefore, this report presents a dispatch strategy for EV batteries based on the Analytic Hierarchy Process taking into account both vehicle users' and power system requirements and priorities, as well as the constraints of the battery system. However, using renewable power to charge EVs is the prerequisite of realizing clean transport. EVs can store the extra renewable power and feed it into the grid when needed via vehicle-to-grid operations to increase the utilization and integration of RGs in the power grid. Thus, the optimal dispatch of EVs and RGs to realize the synergy between them will be one of the key challenges. Two optimal agent-based coordinated dispatch strategies are developed in this thesis, respectively using dynamic programming and the A* search procedure (comparisons between these two algorithms are made and discussed), for the synergistic integration of EVs and RGs, so that the benefits of both EV users and power grid are maximized. Each of the proposed approaches was tested on an IEEE Reliability Test System or a modified UK generic distribution system (UKGDS) using MATLAB. The simulation results demonstrate the feasibility and efficacy of the proposed approaches.

This thesis investigates the use of a three-phase forced-commutation series capacitor (FCSC) for power factor correction in stand-alone variable-voltage variable-frequency (VVVF) systems. Two environmentally-friendly applications are chosen to represent the VVVF systems. The first application is a renewable energy resource as a direct drive wave energy conversion (WEC) buoys. The second application is the more electric aircraft (MEA). In such systems, permanent magnet PM generators are most commonly used. A generator-set generally consists of a three-phase generator connected directly to a conventional three-phase diode bridge rectifier for simplicity and cost reduction. Due to the high inherited inductance of the PM generators used in such applications, this configuration suffers from a poor power factor as a result of commutation overlap. Several controlled series compensator (CSC) topologies have been employed for decades in power systems where the voltage levels and frequency are fixed. However, in applications such as WEC and MEA, the voltage and frequency vary. Therefore, in this work, a variable switched capacitor is used in order to inject a capacitive reactance and therefore compensate the inductive reactance of the generator, which prevents power factor degradation. In a VVVF system, it is important to inject variable capacitive reactance since the inductive reactance changes with frequency variations. Five commonly used CSC circuits are compared and the FCSC is considered as the most suitable circuit topology which is able to cope with a range of frequency variations. This research mainly investigates the performance of the three-phase FCSC circuit when controlled by novel control strategy, in terms of power factor, output voltage, and output power under various load conditions, including constant and variable load. The harmonic content of the three-phase FCSC is also investigated in order to propose this topology for MEA power system. In an aerospace system, the power quality is required to meet high standards and harmonic distortion should not exceed the limited level set by aerospace industry authorities. Therefore, several types of conventional power factor corrector (PFC) are excluded from aerospace systems, due to the associated distortion levels. Preface Abstract iv In this thesis, a novel symmetrical duty cycle control (SDCC) scheme is proposed in order to qualify the three-phase FCSC converter to be employed in different ranges of frequency variation, including 1-3 Hz for wave energy and 50-500 Hz as part of aircraft frequencies. The approach is simple to implement, with no need for a sophisticated controller design. The switch duty cycle is a function of the supply frequency and this allows the FCSC circuit to cope with frequency variation. The modes of operation for both single and three-phase circuit topologies are presented. The three-phase FCSC circuit is designed and tested in the laboratory environment. The performance of the three-phase FCSC circuit when using SDCC is tested experimentally and assessed by comparison of its performance with that of the conventional three-phase diode bridge rectifier. Experimental and simulation results validate the capability of the three-phase FCSC- rectifier to improve the power factor to approximately unity in addition to increasing the output voltage and power at higher voltage and frequency values. However, only limited improvements are achieved at the lower values of the frequency spectrum.

One of the most important measures that can be employed to enhance the supply reliability and quality of electrical energy in a distribution network is feeder reconfiguration. Many studies have been conducted in this area, but only a minor proportion have considered the concept of system harmonics in feeder reconfiguration. In recent years, an increasing number of invertor/converter-based renewable generators are being connected to the distribution network, and given that these generators are harmonic sources, it is important to consider the impacts of the system harmonics in the feeder reconfiguration. Load flow analysis is used to determine a suitable network structure for specific purposes in the feeder reconfiguration problem. In this thesis, a new load flow method is proposed based on the backward/forward sweep method. This method can analyse distribution network load flow under both fundamental and harmonic conditions with distributed generators. Following this, a hybrid optimization method is proposed based on the salient features of the ant colony system and particle swarm optimization. This hybrid method has a higher searching accuracy performance for feeder reconfiguration when compared, on test system, with the ant colony system and particle swarm optimization. Finally, a 118 mid-voltage level distribution system is used to investigate the impacts of renewable generators and system harmonics. The test results verify that system harmonics will have a significant influence on feeder reconfiguration and, consequently, cannot be ignored. Furthermore, other factors including the different capacities of renewable generators, fluctuations in load demands over 24 hours, and the variable output of the renewable generators in different seasons are also investigated in the feeder reconfiguration problem.

This thesis investigates the effects of increased penetration levels of DFIG based wind turbines on rotor angle stability of power systems and how these impacts could be mitigated. The main outcome of this research is the comprehensive assessment of the stability improvements that can be achieved through a novel cost-effective control approach using existing DFIG equipments. A control strategy for both the rotor-side converter (RSC) and grid-side converter (GSC) of the DFIG is proposed to mitigate DFIGs impacts on the system stability. DFIG-GSC is utilised as a static synchronous compensator (STATCOM) to provide reactive power support during the active crowbar time when controlling of both reactive and active power is lost and a large amount of reactive power is absorbed. In addition, a supplementary power system stabiliser (PSS) is designed taking into account the influence of the crowbar system. To overcome the effects of PSS active power modulation, the PSS is designed to be implemented in the reactive power control loop of DFIG-RSC.The proposed approaches are examined on IEEE 9-bus and IEEE 39-bus systems under both small and large disturbances. The simulation results show the effectiveness and robustness of both approaches to enhance rotor angle stability. As the levels of wind penetration are increased, the benefit of such a control scheme is that the DFIG-based wind farms are able to take over the synchronous generators responsibility to support power system stability. As wind power is stochastic and fluctuates with the variation of wind speed, the proposed DFIG PSS should have the capability to damp power system oscillations effectively under non-uniform variable wind speeds across the wind farm. Therefore, the feasibility of the proposed fixed parameters PSS is evaluated using the IEEE 39-bus test system taking into account the non-uniform and variable wind speed profiles. The results confirm the robustness and stabilising effect against various operating modes and under various wind speeds.

Smart energy systems are those that incorporate the ability to collect data across the energy infrastructure and use that data to dynamically balance supply and demand and use system assets more efficiently. Making energy smarter is widely seen as a key enabler of the wider low-carbon energy transition in the UK and a major opportunity for innovation in the energy industry. This research examines processes of innovation around smart energy in the UK by focusing on three case studies of self-contained smart energy trials, or niches. Using interviews and project documentation, the research uncovers a rich account of these case studies, their origins and their outcomes. These case studies allow a deeper understanding of the evolution of smart energy within these niches, and the novel technologies, contractual arrangements, governance structures, and business models that are emerging within them. The research also explores the influence of ICT concepts and technology, as well as regulation, and incumbent energy sector actors for innovation in this area. I endeavoured to make the findings produced in this research relevant to policy makers or business strategists involved in promoting and supporting the transition to a low-carbon energy system by translating research findings into insights that can guide the management of innovation.

New energy storage devices are required to enable future technologies. With the rise of wearable consumer and medical devices, a suitable flexible and wearable means of storing electrical energy is required. Fibre-based devices present a possible method of achieving this aim. Fibres are inherently more flexible than their bulk counterparts, and as such can be employed to form the electrodes of flexible batteries and capacitors. They also present a facile possibility for incorporation into many fabrics and clothes, further boosting their potential for use in wearable devices. Electrically conducting fibres were produced from a dispersion of carbon nanomaterials in a room temperature ionic liquid. Coagulation of this dispersion was achieved through manual injection into aqueous solutions of xanthan gum. The limitations of this method are highlighted by very low ultimate tensile strengths of these fibres, in the order of 3 MPa, with high variation within all of the fibres. Fibres were also produced via scrolling of bi-component films containing poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) and poly(vinyl alcohol) (PVA). Chemical treatments were employed to impart water compatibility to these fibres, and their electrochemical, physical and electrical properties were analysed. Fibres were wet spun from two PEDOT:PSS sources, in several fibre diameters. The effect of chemical treatments on the fibres were investigated and compared. Short 5 min treatment times with dimethyl sulfoxide (DMSO) on 20 μm fibres produced from Clevios PH1000 were found to produce the best overall treatment. Up to a six-fold increase in electrical conductivity resulted, reaching 800 S cm-1, with up to 40 % increase in specific capacitance and no loss of mechanical strength (55 F g-1 and 150 MPa recorded). A wet spinning system to produce PEDOT:PSS fibres containing functionalised graphenes and carbon nanotubes, as well as birnessite nanotubes was subsequently developed. Manganese dioxide was also grown electrochemically on the outside of PEDOT:PSS fibres, with polypyrrole and PEDOT:PSS coating protection methods investigated. Electrochemical testing determined that birnessite nanotube-containing fibres presented the most viable option for energy storage device applications. Using the birnessite nanotube-containing fibre, fibre-based supercapacitors were fabricated and investigated. Specific capacitance values of 80 F g-1 were obtained, stable for over 1,000 cycles at 0.5 A g-1.

The automotive industry requires rapid advances in battery technology to fulfil the range and price criteria set by its consumer base. Lithium-ion cell chemistries are currently best-suited to this application, but are approaching their maximum practical energy density and have yet to exhibit lifespans that are equivalent to that of the vehicles that they power. Therefore, there is considerable interest in the next-generation lithium-air cell, which promises upwards of a five-fold increase in energy density over today's lithium-ion cells. However, there are many hurdles to overcome, the most important being limited cycle life. Two new organic solvents, namely adiponitrile and glutaronitrile, were investigated as possible new electrolytes for non-aqueous lithium-air cells. Both electrolytes were found to be susceptible to nucleophilic attack by the intermediate O2 radical species, resulting in rapid capacity loss upon cycling and the conversion of the discharge product, Li2O2, to LiOH. As such, these solvents have been ruled out for use in lithium-air applications. Work then focussed on the parameterisation of lithium-air cells to assist the development of a multiscale model of the lithium-air discharge mechanism that incorporates the simultaneous formation of Li2O2 in solution and as a surface layer for the first time. Numerous analytical techniques were used to obtain the oxygen concentration and diffusion coefficient of multiple electrolytes, as well as details pertaining to the cathode structure of the cell. The model was shown to predict the discharge profile of a lithium-air cell with greater accuracy than previous models at low and medium current densities, and will thus be a useful tool for the rapid screening of new electrolyte solutions and cathode structures. Finally, a new 3-electrode modification technique was developed for commercial lithium-ion pouch cells that allows potential profiles of each electrode to be obtained in-situ with no impact upon cell performance, as verified by cycling with unmodified cells and cathode/anode half-cells, and by post-mortem analysis. This technique has provided the data required to experimentally verify a parametric open circuit voltage model for lithium-ion cells that can model and predict electrode-specific decomposition mechanisms to within an accuracy of 10 mV RMSE. Ultimately, the model may be used to improve the effectiveness of a vehicular battery management system and extend the lifespan of the traction battery pack.

Due to the reforming and deregulation of electric power industry, investments in transmission equipment have drastically decreased to meet the economic needs of the competitive market. The electrical utility sector was forced to cut the costs in maintenance and operation without endangering steady supply of electrical power. With this trend, the maintenance strategy desires advanced methods for condition monitoring and assessment of in-service power transformers. Among the common condition assessment techniques, Frequency Response Analysis (FRA) is considered as an efficient off-line diagnostic technique for fault detection in transformer windings. Precise interpretation of the FRA output has proven a great challenge and attracted much effort in recent years. There is also a strong need in this research field to develop an intelligent interpretation procedure for automatic assessment of power transformer conditions. This thesis focuses on two main aspects of power transformer condition assessment: developing an accurate transformer model for the interpretation of transformer FRA responses, and establishing FRA-based novel algorithms to automatically identify transformer failure modes. Reviewing existing transformer modeling methods, this thesis explicitly introduces a simplified distributed parameter model (hybrid winding model) for FRA. The hybrid winding model has the advantage of less computational complexity and high accuracy in simulation results, even in the frequency range above 1 MHz. Analytical expressions for calculating key electrical parameters of winding models are presented. The electrical parameters of transformer windings with a complex or deformed structure are difficult to calculate using analytical formulations. Therefore, computational models based on Finite Element Method (FEM) are developed in this thesis to calculate the frequency-dependent parameters of transformer windings especially with deformed structures. These parameters are then applied to the transformer winding model for frequency response analysis. By applying the electrical parameters obtained from the FEM models, the accuracy of the hybrid winding model has been improved for cases with incipient winding faults. This methodology is implemented in simulation studies of radial winding deformation and minor axial winding movement to reveal the characteristic features of these two types of winding fault. Results show that: (1) frequency-dependent inductances and structure-dependent shunt capacitance derived from FEM models can be used in FRA analysis, (2) by using the proposed methodology, characteristics of frequency response above 1 MHz can be analyzed, (3) regarding radial winding deformation and minor axial winding movement, the changes in the electrical parameters also affect the frequency response in the high frequency range ( > 1 MHz). A Hierarchical Dimension Reduction (HDR) classifier built on FRA results is proposed in this thesis for condition assessment of power transformers. The algorithms of this classifier make advantageous use of advanced image processing technologies including image binalization and binary erosion in the first step of the procedure. This preprocessing procedure optimizes the measured FRA data by filtering the frequency sections with minor deviations which can effect the calculating results of the indices. Also in this step, FRA diagrams are re-scaled in a linear coordinate system for the convenience of calculating the indices in later step. Subsequently, based on the correlation between electrical properties and features of FRA responses, a division approach is proposed to dynamically divide the frequency range into 5 sub-bands. This division method of frequency range is more reasonable than the conventional methods of fixed frequency sub-bands and more applicable than other existing methods. Then the proposed algorithms of hybrid quantitative indices which include four indices are employed. The dimension reduction for the FRA data is processed by these algorithms in the 5 dynamic frequency sub-bands. It is the first time to establish the algorithms of the hybrid quantitative indices, which include two classical indices and two novel indices, for reducing the dimensions of the FRA data. Two new algorithms of indices, Area Ratio Index (ARI) and Angle Difference (AD), are proposed based on knowledge of FRA interpretation with respect to typical transformer failure modes. They are able to improve the classification performance in terms of the ability to identify electrical failures and the condition of residual magnetization. Based on these advantageous processes, the HDR classifier can aggregate related expertise and approved statistical indices in furtherance of automatic decision analysis on identifying transformer failure modes or conditions. The performance of this classifier has been verified by 32 sets of experimental FRA data, in which 20 sets are primarily used for determination of threshold values of the related algorithms and the rest 12 are purely used for the verification. Results of this implementation of the HDR classifier are 100% accuracy with using the 20 sets of training data and 95.83% accuracy with using the rest 12 sets.