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.

Chemistry and synthesis of 3(2H)-furanones and 4,5-dihydro analogues: mechanistic investigations and stereochemical control

The subject matter of this thesis relates to the chemistry of the five-membered oxygen heterocycles – 3(2H)-furanones and their 4, 5-dihydro analogues. Chapter one of the thesis is a review of the relevant chemistry of the compounds: their synthesis and key transformations. In chapter two, new research on 3(2H)-furanones is outlined in two parts. The first describes an investigation into the cyclisation of α'-trialkylsilyloxyenone adducts with arenesulfenyl and selenenyl chlorides into the corresponding sulfur and selenium substituted 3(2H)-furanones without the involvement of a Lewis acid catalyst. The study, largely involving in situ NMR techniques, identified key features associated with the formation and reaction of the chlorosulfide and chloroselenide intermediates, including operation of the Thorpe-Ingold effect. The knowledge gained in this study was applied (the second part) to the synthesis of vinyl substituted furanone systems from α'-trialkylsilyloxydienones where choice of the reaction conditions and electrophilic reagent was a key feature. An important difference in the behaviour of arenesulfenyl and selenenyl halides towards conjugated dienes emerged from this work. This phase of the research concluded with a new synthesis of geiparvarin, a natural product possessing anti-tumour properties.

Modelling and predictive control techniques for building heating systems

Model predictive control (MPC) has often been referred to in literature as a potential method for more efficient control of building heating systems. Though a significant performance improvement can be achieved with an MPC strategy, the complexity introduced to the commissioning of the system is often prohibitive. Models are required which can capture the thermodynamic properties of the building with sufficient accuracy for meaningful predictions to be made. Furthermore, a large number of tuning weights may need to be determined to achieve a desired performance. For MPC to become a practicable alternative, these issues must be addressed. Acknowledging the impact of the external environment as well as the interaction of occupants on the thermal behaviour of the building, in this work, techniques have been developed for deriving building models from data in which large, unmeasured disturbances are present. A spatio-temporal filtering process was introduced to determine estimates of the disturbances from measured data, which were then incorporated with metaheuristic search techniques to derive high-order simulation models, capable of replicating the thermal dynamics of a building. While a high-order simulation model allowed for control strategies to be analysed and compared, low-order models were required for use within the MPC strategy itself. The disturbance estimation techniques were adapted for use with system-identification methods to derive such models. MPC formulations were then derived to enable a more straightforward commissioning process and implemented in a validated simulation platform. A prioritised-objective strategy was developed which allowed for the tuning parameters typically associated with an MPC cost function to be omitted from the formulation by separation of the conflicting requirements of comfort satisfaction and energy reduction within a lexicographic framework. The improved ability of the formulation to be set-up and reconfigured in faulted conditions was shown.

Identifying novel molecular mechanisms of ghrelin receptor signalling underlying neural control of food intake: interaction with stress and impulsivity

The gut-hormone, ghrelin, activates the centrally expressed growth hormone secretagogue 1a (GHS-R1a) receptor, or ghrelin receptor. The ghrelin receptor is a G-protein coupled receptor (GPCR) expressed in several brain regions, including the arcuate nucleus (Arc), lateral hypothalamus (LH), ventral tegmental area (VTA), nucleus accumbens (NAcc) and amygdala. Activation of the GHS-R1a mediates a multitude of biological activities, including release of growth hormone and food intake. The ghrelin signalling system also plays a key role in the hedonic aspects of food intake and activates the dopaminergic mesolimbic circuit involved in reward signalling. Recently, ghrelin has been shown to be involved in mediating a stress response and to mediate stress-induced food reward behaviour via its interaction with the HPA-axis at the level of the anterior pituitary. Here, we focus on the role of the GHS-R1a receptor in reward behaviour, including the motivation to eat, its anxiogenic effects, and its role in impulsive behaviour. We investigate the functional selectivity and pharmacology of GHS-R1a receptor ligands as well as crosstalk of the GHS-R1a receptor with the serotonin 2C (5-HT2C) receptor, which represent another major target in the regulation of eating behaviour, stress-sensitivity and impulse control disorders. We demonstrate, to our knowledge for the first time, the direct impact of GHS-R1a signalling on impulsive responding in a 2-choice serial reaction time task (2CSRTT) and show a role for the 5-HT2C receptor in modulating amphetamine-associated impulsive action. Finally, we investigate differential gene expression patterns in the mesocorticolimbic pathway, specifically in the NAcc and PFC, between innate low- and high-impulsive rats. Together, these findings are poised to have important implications in the development of novel treatment strategies to combat eating disorders, including obesity and binge eating disorders as well as impulse control disorders, including, substance abuse and addiction, attention deficit hyperactivity disorder (ADHD) and mood disorders.

Prevalence and control of Clostridium difficile in patients with cystic fibrosis

The aim of this thesis was to investigate the high prevalence of Clostridium difficile in patients with cystic fibrosis (CF), and to control its dissemination. To determine the carriage rate of C. difficile in CF patients, 60 patients were tested for C. difficile and its toxin. In total, 50% of patients were found to be asymptomatic carriers of C. difficile despite toxin being detected in 31.66% of patients. Ribotyping of the C. difficile isolates revealed 16 distinct ribotypes, including the hyper virulent RT078. All isolates were sensitive to both Vancomycin and Metronidazole. The effect of CF and its treatment on the gut microbiota of CF patients was assessed by 16s sequencing of the gut microbiota of 68 CF patients. When compared to a healthy control group, CF patient gut microbiota was found to be less diverse and had an increased Firmicutes to Bacteriodetes ratio. Interestingly, CF patients who were carriers of C. difficile had a less diverse gut microbiota than C. difficile negative CF patients. Multilocus sequence typing was found to be comparable to PCR-ribotyping for typing C. difficile isolates from high risk patient groups. The sequence type ST 26 is potentially associated with CF patients as all seven isolates were found in this group and this sequence type has been previously reported in CF patients in a geographically distinct study. The bacteriophage ФCD6356 was assessed as a targeted antimicrobial against C. difficile in an ex-vivo model of the human distal colon. Despite reducing viable C. difficile by 1.75 logs over 24 hours, this bacteriophage was not suitable due to its lysogenic nature. Following treatment, all surviving C. difficile were immune to reinfection due to prophage integration. However, the ФCD6356 encoded endolysin was capable of reducing viable C. difficile by 2.9 over 2 hours in vitro after being cloned and expressed in Escherichia coli.

Modelling and control of a floating oscillating water column

A novel numerical model of a Bent Backwards Duct Buoy (BBDB) Oscillating Water Column (OWC) Wave Energy Converter was created based on existing isolated numerical models of the different energy conversion systems utilised by an OWC. The novel aspect of this numerical model is that it incorporates the interdependencies of the different power conversion systems rather than modelling each system individually. This was achieved by accounting for the dynamic aerodynamic damping caused by the changing turbine rotational velocity by recalculating the turbine damping for each simulation sample and applying it via a feedback loop. The accuracy of the model was validated using experimental data collected during the Components for Ocean Renewable Energy Systems (CORES) EU FP-7 project that was tested in Galway Bay, Ireland. During the verification process, it was discovered that the model could also be applied as a valuable tool when troubleshooting device performance. A new turbine was developed and added to a full scale model after being investigated using Computational Fluid Dynamics. The energy storage capacity of the impulse turbine was investigated by modelling the turbine with both high and low inertia and applying three turbine control theories to the turbine using the full scale model. A single Maximum Power Point Tracking algorithm was applied to the low-inertia turbine, while both a fixed and dynamic control algorithm was applied to the high-inertia turbine. These results suggest that the highinertia turbine could be used as a flywheel energy storage device that could help minimize output power variation despite the low operating speed of the impulse turbine. This research identified the importance of applying dynamic turbine damping to a BBDB OWC numerical model, revealed additional value of the model as a device troubleshooting tool, and found that an impulse turbine could be applied as an energy storage system.