Optimisation of Smart Grid performance using centralised and distributed control techniques

A massive change is currently taking place in the manner in which power networks are operated. Traditionally, power networks consisted of large power stations which were controlled from centralised locations. The trend in modern power networks is for generated power to be produced by a diverse array of energy sources which are spread over a large geographical area. As a result, controlling these systems from a centralised controller is impractical. Thus, future power networks will be controlled by a large number of intelligent distributed controllers which must work together to coordinate their actions. The term Smart Grid is the umbrella term used to denote this combination of power systems, artificial intelligence, and communications engineering. This thesis focuses on the application of optimal control techniques to Smart Grids with a focus in particular on iterative distributed MPC. A novel convergence and stability proof for iterative distributed MPC based on the Alternating Direction Method of Multipliers is derived. Distributed and centralised MPC, and an optimised PID controllers' performance are then compared when applied to a highly interconnected, nonlinear, MIMO testbed based on a part of the Nordic power grid. Finally, a novel tuning algorithm is proposed for iterative distributed MPC which simultaneously optimises both the closed loop performance and the communication overhead associated with the desired control.

Accommodating curvature in a highly ordered functionalized metal oxide nanofiber: synthesis, characterization and multi-scale modeling of layered nanosheets

A key element in the rational design of hybrid organic-inorganic nanostructures, is control of surfactant packing and adsorption onto the inorganic phase in crystal growth and assembly. In layered single crystal nanofibers and bilayered 2D nanosheets of vanadium oxide, we show how the chemisorption of preferred densities of surfactant molecules can direct formation of ordered, curved layers. The atom-scale features of the structures are described using molecular dynamics simulations that quantify surfactant packing effects and confirm the preference for a density of 5 dodecanethiol molecules per 8 vanadium attachment sites in the synthesised structures. This assembly maintains a remarkably well ordered interlayer spacing, even when curved. The assemblies of interdigitated organic bilayers on V2O5 are shown to be sufficiently flexible to tolerate curvature while maintaining a constant interlayer distance without rupture, delamination or cleavage. The accommodation of curvature and invariant structural integrity points to a beneficial role for oxide-directed organic film packing effects in layered architectures such as stacked nanofibers and hybrid 2D nanosheet systems.

Assessing the impulse control of violent offenders using computer-based cognitive performance tasks

The topic of this thesis is impulsivity. The meaning and measurement of impulse control is explored, with a particular focus on forensic settings. Impulsivity is central to many areas of psychology; it is one of the most common diagnostic criteria of mental disorders and is fundamental to the understanding of forensic personalities. Despite this widespread importance there is little agreement as to the definition or structure of impulsivity, and its measurement is fraught with difficulty owing to a reliance on self-report methods. This research aims to address this problem by investigating the viability of using simple computerised cognitive performance tasks as complementary components of a multi-method assessment strategy for impulse control. Ultimately, the usefulness of this measurement strategy for a forensic sample is assessed. Impulsivity is found to be a multifaceted construct comprised of a constellation of distinct sub-dimensions. Computerised cognitive performance tasks are valid and reliable measures that can assess impulsivity at a neuronal level. Self-report and performance task methods assess distinct components of impulse control and, for the optimal assessment of impulse control, a multi-method battery of self-report and performance task measures is advocated. Such a battery is shown to have demonstrated utility in a forensic sample, and recommendations for forensic assessment in the Irish context are discussed.

Improved kinematic sensing for motion control applications

New compensation methods are presented that can greatly reduce the slit errors (i.e. transition location errors) and interval errors induced due to non-idealities in optical incremental encoders (square-wave). An M/T-type, constant sample-time digital tachometer (CSDT) is selected for measuring the velocity of the sensor drives. Using this data, three encoder compensation techniques (two pseudoinverse based methods and an iterative method) are presented that improve velocity measurement accuracy. The methods do not require precise knowledge of shaft velocity. During the initial learning stage of the compensation algorithm (possibly performed in-situ), slit errors/interval errors are calculated through pseudoinversebased solutions of simple approximate linear equations, which can provide fast solutions, or an iterative method that requires very little memory storage. Subsequent operation of the motion system utilizes adjusted slit positions for more accurate velocity calculation. In the theoretical analysis of the compensation of encoder errors, encoder error sources such as random electrical noise and error in estimated reference velocity are considered. Initially, the proposed learning compensation techniques are validated by implementing the algorithms in MATLAB software, showing a 95% to 99% improvement in velocity measurement. However, it is also observed that the efficiency of the algorithm decreases with the higher presence of non-repetitive random noise and/or with the errors in reference velocity calculations. The performance improvement in velocity measurement is also demonstrated experimentally using motor-drive systems, each of which includes a field-programmable gate array (FPGA) for CSDT counting/timing purposes, and a digital-signal-processor (DSP). Results from open-loop velocity measurement and closed-loop servocontrol applications, on three optical incremental square-wave encoders and two motor drives, are compiled. While implementing these algorithms experimentally on different drives (with and without a flywheel) and on encoders of different resolutions, slit error reductions of 60% to 86% are obtained (typically approximately 80%).