The emerging trend towards the harnessing of the electrical power from solar energy has increased the research effort in power electronics applications. To achieve the required voltage level, a number of photovoltaic PV sources (cells/modules) are connected in series. The major challenge here is to deal with the partial shading problem, where the series connected PV sources are exposed to different insolation. The generated current is limited by the current of the shaded PV sources unless those sources are bypassed by diodes, in which case the total DC voltage is reduced and the shaded sources do not contribute to the generated output power. A power electronics approach can be employed to overcome the problem, by enabling both shaded and non-shaded sources to generate their maximum power, thereby and delivering the total generated power to the load. Thus no shaded PV source is bypassed or degrades the power extraction from the other PV sources. This thesis investigates the PV partial shading problem of individual PV sources which are connected in series. After the review and evaluation of existing methods to overcome this problem, the thesis employs for the first time the multilevel DC-Link inverter to deal with the problem of partial shading by using a novel control algorithm called PV permutation algorithm. The thesis also develops a simplified generalized Integration PWM (IPWM) algorithm which can be used to control higher level inverters. An improved maximum power point algorithm “voltage-hold perturbation and observation (VH-P&O)”, which overcomes the major tracking limitations, is developed from the basic P&O algorithm. Experimental systems of five and seven level DC-link inverters with a DC-DC buck converter system have been implemented. The digital processing unit eZdspTM F28335 is used to control the PV systems in real time, and Matlab-Simulink Real Time Data Exchange (RTDX) is employed to display the extracted power and to control the system parameters via a designed Graphical User Interface (GUI) window. The simulation and experimental results showed that the series connected PV sources operate at their maximum power points under partial shading conditions without affecting each other.

Proton exchange membrane (PEM) fuel cell has the potential to be one of the main energy sources in the future. However, the leading issues when operating the fuel cells are the water and the thermal managements. In this thesis, numerical studies have been developed in order to investigate the sensitivity of the PEM fuel cells performance to the thermal conductivities of the main components in PEM fuel cells, which are the membrane, the gas diffusion layer (GDL) and the catalyst layer. In addition, the effect of the thermal conductivity of these components and the metallic GDL on the temperature distribution and the water saturation was considered conducive to the improvement of the heat and water management in PEM fuel cells. On the other hand, the experimental work was completed to determine the effects of the thermal conductivity and the thermal contact resistance of the components in PEM fuel cells. The thermal conductivity of the GDL was measured in two directions, namely the in-plane and the through-plane directions taking into account the effect of the main parameters in the GDL which are the mean temperature, the compression pressure, the fibre direction, the micro porous layer (MPL) coating and polytetrafluoroethylene (PTFE) loading. Furthermore, the thermal conductivities of the membrane and the catalyst layer were measured in both directions, the in-plane and the through-plane, with considering the effect of the temperature and the Pt loading in the catalyst layer, and the effect of the water content and temperature on the membrane. This study is a comprehensive study on the thermal conductivity of PEM fuel cells and emphasized the importance of the thermal conductivity of the components in PEM fuel cells.

Small-scale wind energy is a renewable energy technology with exciting prospects in a low carbon energy future. However, in order for the technology to be fully utilized, techniques capable of predicting the wind energy resource quickly, cheaply and accurately are urgently required. Specifically, the direct measurement approaches used in the large-scale wind industry are often not financially or practically viable in the case of small-scale installations. The subject of this thesis is the development of low-cost, indirect methods for predicting the wind resource using, (i) analytical models based on boundary layer meteorology and (ii) data-driven techniques based on measure-correlate-predict (MCP). The approaches were developed and tested using long-term (11 years) wind data from meteorological stations, short-term (1 year) data from a field trial of small-scale turbines, and output from an operational forecast model. As a first step, the performance of an existing boundary layer scaling model was evaluated at 38 UK sites and found to result in large site-specific errors. Based on these findings, a revised model was developed and shown to improve prediction accuracy. However, uncertainty analysis and comparison with onsite measurements revealed average errors in the predicted wind power density of over 60% due to uncertainties in the model input parameters. Hence, it was concluded that such an approach is best applied in a scoping context to identify sites worthy of further study. To investigate the ability of low-cost, data-driven techniques to reduce these uncertainties, MCP approaches were trialled using onsite measurement periods as short as 3 months at a subset of 22 of the above UK sites. In addition to established linear approaches, non-linear Gaussian process regression and bivariate conditional probability approaches were developed. Using a 3 month measurement period, the best performing MCP approaches resulted in average errors in the predicted wind power density of 14%, compared to 26% when using the boundary layer scaling approach at the same sites. The effect of seasonal variability in the prediction errors was investigated in detail and found to be most significant at coastal sites. This variability was found to be reduced by using output from an operational forecast model in place of long-term reference wind data. This work provides a means for low-cost and rapid wind resource assessment in cases where traditional approaches are not viable.

Most of the dielectric materials developed in this thesis were relaxor dielectrics with very broad, frequency dependent peaks in relative permittivity-temperature, εr – T, plots. In some cases, plateau-like permittivity plots with very wide temperature ranges of stable permittivity varying by no more than ±15 % were obtained through compositional engineering of the relaxor base material using high levels of lattice substitution of cations of different charge and size to the host lattice. The solid solution series (1–x)Na0.5Bi0.5TiO3 – xBa0.8Ca0.2TiO3 [(1–x)NBT–xBCT] was studied initially: it showed little evidence of temperature-stable relative permittivity. However, 0.85NBT – 0.15BCT ceramics modified by BiMg0.5Ti0.5O3, [BMT], were more promising. The series, (1–x)[0.85Na0.5Bi0.5TiO3 – 0.15Ba0.8Ca0.2TiO3] – xBiMg0.5Ti0.5O3, x = 0.3, gave εr ~ 1720 ± 15 %, in the temperature range 120 to 450 ºC, and low dielectric loss tangent, tanδ ≤ 0.02, over the slightly narrower temperature range, 150 to 360 ºC. Thus an upper operating temperature > 300°C was demonstrated but without also achieving sub-zero temperature capability. Similarly, the system (1–x)[0.85Na0.5Bi0.5TiO3 – 0.15Ba0.8Ca0.2TiO3] – xLiNbO3 abbreviated [(1–x)[NBT – BCT] – xLN] gave εr ~ 2630 ± 15 % from 50 ºC to 410 ºC, and tanδ ≤ 0.02 from 120 ºC to 400 ºC, at composition x = 0.06. The incorporation of NaNbO3 [NN] in place of LiNbO3 achieved the desired sub-zero temperature capability in relative permittivity, and with an upper temperature limit slightly above 200 ºC. Examples include (1–x)[NBT – BCT] – xNN composition x = 0.3 with εr = 1400 ± 15 % from -50 to 240 °C and tanδ ≤ 0.02 from 20 ºC to 240 v ºC; for x = 0.4, εr = 1300 ± 15 % from -70 to 210 °C and tanδ ≤ 0.02 from -10 ºC to 210 ºC. In terms of the project goal of achieving a temperature range of stable permittivity combined with a low loss extending from temperatures of -55 °C (to meet the Electronic Industry Alliance military specification) up to 300 °C, the binary solid solution system (1–x)Ba0.6Sr0.4Zr0.2Ti0.8O3 – xBiMg0.5Ti0.5O3 [(1–x)BSZT – xBMT] was most promising. However there was a trade-off in that permittivity values were lower than the foregoing systems. The (1–x)BSZT – xBMT sample composition x = 0.2 gave εr ~ 500 ± 15%, in the temperature range -70 to 300 ºC and tanδ ≤ 0.02, in the range -60 to 300 ºC. This system closely matches the target temperature-range of the project, but the volumetric efficiency of a capacitor made from this dielectric would be compromised due its moderate relative permittivity values. Slightly higher values of relative permittivity were obtained for x = 0.3 in the (1–x)BSZT – xBMT series, with εr ~ 590 ± 15%, across the temperature range -60 to 340 ºC, but in this case the temperature range of low dielectric losses tanδ ≤ 0.02 was restricted to -10 to 280 ºC. Piezoelectric properties of selected samples have also been investigated in the thesis.

Proton exchange membrane fuel cells, PEMFC’s, offer a clean, flexible mode of energy generation, though efficiency improvements are required before they can become commercially viable. While platinum is currently the most commonly used cathode catalyst, a large overpotential exists for the oxygen reduction reaction, ORR, limiting the effective potential of a fuel cell to approximately 0.9 V. Efforts have been made within the literature to develop a low cost, efficient and durable alternative cathode catalyst for use within a PEMFC though at present no viable alternative has been found. However, M-Nx/C active sites, consisting of a central metal atom co-ordinated to two or four nitrogen atoms embedded within a carbon support, show great promise as possible replacements to platinum. While advances have been made in the identification of possible active sites, no study yet exists that examines the influence of each active site component on the overall activity. In this thesis the influence of each component is examined, and in doing so a highly active site is predicted. The efficacy of the model is first proven by a simultaneous computational and experimental study of the activity of both platinum and Fe/Coporphyrins, which are commonly used as precursors in the development of highly active M-Nx/C catalysts. 16 active sites are modelled using graphene and amorphous carbonlike ligands embedded with two or four nitrogen atoms and co-ordinated to either a cobalt or iron centre. The activity of each active site towards the ORR is assessed by the calculation of redox potentials, and by modelling 20 different elementary reactions which collectively form a comprehensive reduction mechanism. By direct comparison between each active site, utilising natural population, bond orbital and localised molecular orbital analysis along with electrostatic potential maps, the influence of each constituent part is quantified. Finally, it is predicted that active sites consisting of a disrupted graphene ligand, embedded with four nitrogen atoms coordinated to either an iron or cobalt centre, would demonstrate the highest activity towards the ORR, and that such an active site is responsible for the activities reported within the literature.

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