The goal of this work is to consider the potential of using renewable energy only to power roadside units (RSUs), which not only reduces CO2 footprint but also reduces the infrastructure needed in motorway vehicular communication. The thesis begins with collation and analysis of wind and motorway traffic data for the purpose of determining the energy demand of vehicular networks as well as the energy supply obtainable from wind. This is followed by the study of a standalone RSU powered by wind energy. Small size standalone wind energy systems which have benefits of low cost, easy and large scale deployments are implemented for the low power RSUs. The concept of wind energy based rate adaptation is introduced and implemented in the RSU through which RSU can vary transmission power according to the availability of wind energy. This reduces the outage and improves the overall service quality. Traditionally rate adaptation was employed to cater for wireless channel unavailability. A queuing model for the RSU is developed and verified through simulation to evaluate the performance in terms of delay, packet loss and utilisation. Channel fading is considered and the performance of the RSU is re-evaluated in terms of the same quality of service parameters, viz. delay, packet loss and utilisation to investigate the impact of fading in the network. Next, the reliability of the RSU is redefined in the context of unavailability of sufficient wind power. The transient nature of wind energy causes the RSUs to either transmit at full data rate or not transmit at all depending on the availability of sufficient energy. Thus, a failure occurs when the wind power is less than the load. Therefore, a framework has been developed for redefining a number of reliability parameters in the context of wind powered RSUs. A detailed wind data analysis was carried out based upon the hourly wind speed obtained from the UK air information resource (AIR) database for a period of five years, to determine the energy model of the deployed micro-turbine. An energy storage device (a small battery) is connected to the micro-wind turbine for improved service quality.

This thesis describes the theory, construction and development of a direct digital control scheme for a micro-machine model of an electrical power generating system. The areas of research covered by this thesis fall into four main regions: 1. The design and development of digital transducers to reduce the noise and accuracy problems associated with analogue techniques. 2. The design and development of a fast and flexible real-time interface between the supervisory computer and the controlled system based on the use of dedicated microprocessors. 3. The development of a software real-time operating system and program suite to allow rapid implementation of a required control philosophy for the laboratory system. 4. The practical implementation of sub-optimal excitation control of the synchronous generator by state feedback techniques. The digital control scheme described has been designed as a flexible base for future work in the implementation of full excitation and governor control of the micromachine system. It is modular in concept to allow rapid application of various forms of modern control philosophy to the laboratory model system. Various support facilities of wider application have also been developed including a microprocessor to computer interface, a direct-loading cross-assembler and an on-line microprocessor debugging system. The excitation control implemented in this study involves the addition of state feedback signals to a fast-acting voltage regulator to improve the transient stability limit. The coefficients of the feedback matrix are determined by an offline parameter optimisation technique to minimise a quadratic performance index of the non-linear system model. This control is shown to effect significant improvements in the system response following the occurrence of a severe disturbance to the system.

This dissertation is, in the main, concerned with the synthesis of excitation feedback controllers designed to improve the performance of a.c. turbogenerators following a large disturbance. Solution methods and approaches for nonlinear optimisation are outlined and their application to a single-machine power system is considered. Linear search algorithms are applied to the optimisation studies of single variable excitation control. With the aid of signal-flow graph and Bode diagram techniques, a new single state variable for feedback has been made obvious. Dynamic sensitivity method has also been used to investigate the suitability of all the feedback signals under study. The theoretical excitation control laws obtained have been confirmed on a small, but realistically scaled, laboratory-model power system. Finally, multi-variable optimisation is applied to coordinated excitation and steam-flow control. Only one extra stabilising signal has been added to each of the two control loops. It has been found that substantial improvements in transient performance can be achieved by the suboptimal control laws derived, under large disturbances and different operating conditions.

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This thesis investigates ways of increasing the energy efficiency of photovoltaic power (pv) generating plants. It does so by improving models of PV plants connected to the electricity grid via space-vector-modulated three-phase inverters. Synergies of softcomputing techniques are applied to modelling the current-voltage characteristics of solar cells and to model-based control of the inverters. A novel extension of a radial-basis-function-network model is reported. The model is unique in that it incorporates a new grid-interpolation data pre-processor, which for the first time has allowed the network to be trained with real solar-cell data. Furthermore, the model provides greater accuracy compared to the industry standard model. Coordinate translation of solar-cell characteristics has been incorporated into a neurofuzzy model of solar cells. Significantly, it enables neural-network models of plants to be trained with far fewer data and with greater resilience to model imperfections than has hitherto been possible. Important applications include the modelling of new plants. Soft-computing control strategies were developed that removed the need for expert knowledge in parameter tuning: (i) a genetic algorithm for optimising the gains of the conventional PI controller; (ii) a genetic algorithm for optimising the parameters of a fuzzy logic controller; and (iii) a neural network for optimising the parameters of a fuzzy logic (ANFIs) controller. The ANFIS controller provided the best transient and steadystate behaviour. The models and control strategies were combined together to form model-based controllers that were more accurate and resilient than existing solutions. Increased power production was demonstrated of 1.5% for a plant well characterised by the conventional model, and 8.6% for a plant poorly characterised by the conventional model, with no requirement for expert knowledge. The results are believed to be important for application in developing countries because of the improved efficiencies and the ability to design and install systems without needing expensive resources.

The purpose of the present work was to investigate some properties of a propane electrode at ambient conditions. First, a search for suitable electrode was undertaken. Several ways of manufacturing porous carbon electrodes were tried and a satisfactory technique developed. The electrodes were then activated by incorporation of catalysts having known catalytic activity with hydrogen and ethylene. The potentialities of the catalysts chosen were assessed by exploratory work with a disc cell. Later, a modified cell was devised to permit measurement of concentration and volume change at constant pressure of reactants. The arrangement also allowed variation in, and measurement of, distance between electrodes. Next, detailed cell performance was investigated from physical and electrochemical measurements. Lastly, the results were discussed from the point of view of (a) mass balance or stoichiometry of reaction- from the quantity of reactants and electricity involved in the reaction (b) energy balance- from the energy input and output (c) ther-modynamics from the loss of open circuit potentials and (d) kinetics- from voltage polarisation on porous electrodes.

Emerging photovoltaic technologies, such as dye-sensitized solar cells and perovskite solar cells, offer huge potential for providing large-scale and affordable renewable energy to meet our growing power requirements. Central to the success of these technologies is the development of low cost production techniques and materials, often with control of morphological features at the nanoscale. Electrochemical anodization is one example of a technique that can meet these criteria. The aim of this PhD project is to develop ZnO nanostructures using electrochemical anodization and apply them as electron transport materials within dye-sensitized and perovskite solar cells. Aligned arrays of ZnO nanowires were produced by the anodization of zinc foil under mild reaction conditions. A systematic study of the influence of various reaction parameters on the growth of nanowires was conducted and subsequently used to optimise nanowire growth rates. Extremely high growth rates of over 3 μm min-1 were achieved, allowing high aspect ratio nanowires to be produced with lengths in excess of 100 μm. Annealing the nanowire arrays led to the production of polycrystalline ZnO nanowires with an average diameter of 160 nm and a radial slit-type pore structure along their length. Further synthetic modification of these nanowires led to the production of high surface area hierarchical structures. Direct application of the nanowire arrays in back-illuminated dye-sensitized solar cells was found to be unsuccessful due to issues with cracking. However, through the preparation of various pastes using these nanowires, it was possible to produce a range of front-illuminated dye-sensitized solar cell architectures. Whilst the anodic nanowires were found to reduce the efficiency of cells when incorporated within mesoporous ZnO films, they were found to increase the power conversion efficiencies from 1.4 % to 1.9 % when applied as light scattering layers above the mesoporous films. Furthermore, hierarchical core-shell nanostructures, derived from the anodic nanowires, were found to greatly increase the efficiency of quasi-solid state dye-sensitized solar cells with TiO2 photoanodes. Maximum power conversion efficiencies of 7.5 % were achieved through the incorporation of small quantities of these nanostructures. These are amongst the highest reported efficiencies for cells featuring ZnO and quasi-solid state cells in general. The use of ZnO nanostructures, including anodic nanowires, was compared with the use of TiO2 nanoparticles as electron transport materials within perovskite solar cells. Maximum power conversion efficiencies were 50 % lower for cells featuring ZnO rather than TiO2 mesoporous layers. Furthermore, no obvious advantage of using nanowires rather than nanoparticles could be observed. The lower performance of the cells based on ZnO was related to the detrimental thermal degradation of the perovskite material in contact with ZnO. This casts doubt over the use of ZnO nanostructures within perovskite solar cells.

Flat-rate electricity tariffs in Great Britain, which have no price variation throughout a day or a year, have been ongoing for decades to recover the cost of energy production and delivery. However, this type of electricity tariff has little incentives to encourage customers to modify their demands to suit the condition of the power supply system. Hence, it is challenged in the new smart grid environment, where demand side responses have important roles to play to encourage conventional energy efficiency and support the integration of renewable generation. In order to accommodate this new environment, the investigations of smart tariff designs and their applications in demand side response are therefore carried out from three main aspects. In a high carbon system dominated by controllable fossil generation where energy peaks typically coincide with those of networks, smart tariffs are developed by statistically tracking dynamic energy price variation tendencies and categorising real-time prices to form time-of-use patterns that capture the most significant price variations without compromising too much accuracy in total energy revenue from customers. In a low carbon system where energy peaks and network peaks may not be in synchronism at all times, additional complications will be raised when developing smart tariffs and optimal demand side response strategies. A new concept is developed in this thesis to allow shared utilization of energy storage between customers and distributed network operators to respond to conflicting energy price and network conditions. In this work, two operation models of storage share are implemented. One is fixed share between customers and network operators regardless of network conditions, and the other is dynamic share that storage capacity utilized by network operator changes with network condition. The consequential system benefit in terms of energy cost reduction and network cost saving is evaluated and converted into per unit cost reduction in the energy bill. Addition to technical solution in the form of storage, the benefit from household demand shifting, such as shifting wet appliances, in the presence of smart tariffs is evaluated. The value of household demand shifting is quantified as an equivalent storage capacity for the investigation of complementarity between technical and social interventions.

Our daily infrastructure, safety, health and comfort relies on a continuous availability of electricity. Due to the volatile nature of electricity and the limited ability of storing electrical energy, it is challenging to implement changes and improve energy efficiency, conversion effectiveness and generator size and weight. In this regard, a wide range of sufficiently high, but currently unused, energy sources are available. Harvesting unexplored waste heat or abundantly available thermal energy sources such as industrial, solar, and geothermal waste heat and abundantly available heat from friction or the human body enables local powering of electronic device, extension of battery lifetime, and even provides accumulated base load power supplies, resulting in the recovery of otherwise unused thermal energy. For this reason, solid-state thermal to electrical energy conversion utilising the pyroelectric effect provides a convenient and direct way of converting temperature fluctuations into an electrical potential difference available for discharge. In this thesis, the nature and the principles of pyroelectric energy harvesting are presented in a complete review of materials, structures and devices for thermal energy harvesting applications, followed by a detailed experimental set-up providing reproducible experimental results under constant laboratory test conditions. Introducing contactless and harmonic temperature oscillations using a radiative heating lamp allows examination of energy harvesting devices and helps to develop an geometrical optimisation approach. For radiative heating, a meshed micro- size electrode structure on polyvinylidene difluoride (PVDF) improves the pyroelectric conversion efficiency. The here presented photolithographic manufacturing technique on a flexible substrate provides new device architectures resulting in a 1050 % higher energy trade off. Further electrode modifications involve a graphene-ink based black body radiation absorber on flexible PVDF. With graphene-ink, a laminate structure introduces piezoelectric activity in response to the change in temperature. The inherent need of temperature oscillations for pyroelectric energy harvesting requires an alternating heat flow. By linking the subject fields of heat transfer in oscillating heat pipes (OHPs) for high performance cooling, together with a pyroelectric energy harvesting device, the experimental system exploits a heat induced liquid-vapour transition of a working fluid as a primary driver for a pyroelectric generator.

This thesis details the approaches which aim to automatically optimize power system security schemes. In this research, power system security scheme includes two main plans. The first plan, which is called the defence plan scheme, is about preventing cascading blackouts while the second plan, which is called the restoration plan, is about rebuilding the power system in case of failure of the first plan. Practically, the defence plan includes under-frequency load shedding and under-frequency islanding schemes. These two schemes are always considered the last stage of the defensive actions against any severe incident. It is recognized that it is not easy for any power system’s operational planner to obtain the minimum amount of load shedding or the best power system islanding formation. In the case of defence plan failure, which is always possible, a full or partial system collapse may occur. In this situation, the power system operator is urgently required to promptly restore the system. This is not an easy task, since the operator must not violate many power system security constraints. <br /> In this research, genetic algorithms and expert systems are employed, as optimization methods, to identify the best amount of load shedding and island formation for the defence plan and the shortest path to rebuild the power system for the restoration plan. In the process of designing the power system security scheme, the majority of the electromechanical power system security constraints are considered. <br /> It is well known that power system optimization problems often have a huge solution space. In this regard, many successful techniques have been used to reduce the size of the solution spaces associated with the optimization of the power system security schemes in this work. The Libyan power system is used as an industrial case study to validate the practicality of the research approaches. <br /> The results clearly show that the new methods that have been researched in this PhD work have shown great success. Using the Libyan power system, the optimized defence plan has been compared to the current defence plan. The results of this comparison have shown that the optimized defence plan outperforms the current one. Regarding the optimized restoration plan, the results present the fact that the Libyan power system can be restored in reasonable time.