Models have been developed to assess the extent that wind plant can contribute to power system frequency control and stability. These are important in the context of increasing wind penetration level into power systems and because variable speed wind turbines that are now the dominant technology do not directly contribute to system inertia, but displace conventional generation plant, thus reducing the total system inertia. It is now considered likely that wind generation will have to participate in power system frequency regulation but prior to this work, little was known about the aggregate impact of extensive wind capacity in this regard, although there has been extensive prior research on the modification of individual turbine controllers to deliver inertial response in the event of rapidly falling system frequency, and droop response so as to contribute to continuous frequency service. A novel probabilistic approach has been developed to assess how the aggregate synthetic inerti al response from wind plant at a given time depends on the available wind. The calculation of collective synthetic inertial response is based on an approach to modelling wind turbulence where wind variations over a short period of time (10 seconds in this modelling) are assumed to be adequately described by a Gaussian probability distribution with a set mean wind speed and variance determined by the site turbulence intensity. This approach is then further expanded to assess the aggregate inertial response available from wind generation across the GB power system and by using a simplified lumped representation of the rest of the power system, allows the interaction between the wind plant, through its controllers, and the power system to be represented. The complete model provides a way to evaluate synthetic inertial response from wind generation under time varying wind speeds on an hourly basis and across the regions, and also as a result of turbulence and short term wind speed variation across wind farms. This research has also shown that the power output of wind turbines can also be actively controlled to provide droop response and to participate in primary frequency response. Different approaches to delivering droop response from wind plant have been investigated. The combination of droop and inertial response has been assessed for a significant frequency event and the results show that the combined approach can provide an improved performance than either droop or inertial response alone.

High power ultrasound has been used in a number of biomedical and industrial applications. In particular, such systems, when used in chemical processing, modify the course of a chemical reaction. The use of high power ultrasound induces cavitation in the load medium, which then leads to certain mechanical and chemical effects. These effects can cause damage to objects, increase local temperatures and can accelerate chemical reactions. Thus, in order to evaluate an efficient ultrasonic system and to quantify the cavitation activity, it is necessary to measure the cavitation in the reaction under the influence of a high power ultrasonic field. Conventional hydrophone techniques and sensor technologies are not suitable for this type of measurement because the sensor can be damaged and change the acoustic field in the presence of cavitation generated by the high power ultrasound. This Thesis describes the development of a non-invasive technique used to monitor acoustic cavitation activity within a reactor vessel. Both Laser Doppler Velocimetry (LDV) and broadband ultrasonic transducer approaches are considered as potential measurement techniques to measure the acoustic emission (AE) signals associated with a cavitating field. The LDV approach uses laser detection to provide information about cavitation intensity and distribution occurring within a reactor vessel. Next, finite element analysis (FEA) is used to provide a simulation platform to investigate the detection of AE sources from within the reactor vessel. This provides the necessary information to support the design of a broadband transducer appropriate for detection of cavitation generated AE. FEA is then used to design a piezoelectric ceramic composite transducer to develop a non-invasive transducer measurement system. In both approaches, a broadband integrated energy (BIE) approach is used to determine the intensity of the cavitation activity. This technique has been evaluated in different frequency ranges and at various power levels. Interestingly, the BIE in the frequency ranges of 1-5MHz was shown to be sufficient in monitoring the cavitation. Overall, the results reveal that both non-invasive techniques can be used to monitor cavitation activity. Although, neither approach provided adequate spatial resolution to accurately map the cavitation field. These techniques are most appropriate to use when the region of cavitation activity in the reactor vessel is known and the external, non-invasive technique can be targeted at this known position to provide information on the regional cavitation intensity.

Ultrasound has found application in chemical processing control using both low power, high frequency monitoring techniques and high power, low frequency process enhancement approaches. In many cases, standard ultrasonic systems are retrofitted to a process and while these produce efficiency improvements, the design of bespoke systems may offer more potential. In particular, this Thesis has considered two techniques used in the biomedical field; harmonic imaging and high intensity focused ultrasound (HIFU) and has translated these into ultrasonic transducers for use in an industrial process control system. Traditional ultrasound monitoring techniques are based on operation in the linear domain and are used to monitor chemical processes by measurement of material acoustic velocity, attenuation or based on spectral analysis. Both active and passive methods have been reported for application in this industrial sector. One issue is the presence of multiple reflections in the received ultrasonic signal which can mask the signals of interest from the load medium. This Thesis has considered a new ultrasonic monitoring approach using a combination of both linear and nonlinear spectral components. This was applied to high-throughput products and a dual frequency transducer designed and fabricated to acquire the ultrasonic backscattered signals in both the fundamental and second harmonic frequency regimes. The additional information provided by the harmonic device enabled discrimination between shampoo and conditioner products with the same density, but different molecular weights. HIFU transducer array designs are then considered for high power, low frequency chemical process enhancement applications. Typical applications of high power ultrasound use single or multiple discrete transducers to insonify a process. These are effective, but inflexible in the delivery of the ultrasonic field. The application of a HIFU array would provide control of the high power focal region in the load medium, which offer advantages to industry. Two transducer array approaches have been considered in this Thesis based on piezoelectric composite configurations. Three HIFU arrays based on the 1-3 piezocomposite have been fabricated to operate between 200-400kHz and fully characterised to evaluate their high power performance. A second transducer configuration was based on a novel 2-2 piezocomposite with a 2 layer stacked configuration. Simulation of this transducer design illustrated its potential for high power applications, although a number of fabrication issues resulted in the manufactured array not operating at full capacity. Importantly, the transducer configurations developed in this Thesis are shown to induce cavitation through the standard aluminium foil test.

Nowadays, many power electronic equipments are used in industry in seeking higher system reliability and efficiency, and more electronic or microprocessor controllers are used in power system to control AC/DC transmission lines or loads. Moreover, the importance of green energy such as wind and solar is continually growing in our societies not only due to environmental concerns but also to resolve the problem of access to electricity in rural areas. As a result, it creates power quality issues especially harmonics. In electrical power system, harmonics have a number of undesirable effects on power system equipment as well as on its operation. In order to understand the effects of these harmonics it is first necessary to analyse the penetration of these harmonics from their various sources into the network. This process of analysis is commonly known as harmonic power flow or harmonic penetration evaluation. In the thesis a review is conducted on existing harmonic power flow methods. The previous approaches require long computing time and encounter convergence problem because of poor initial value. They are only applied to small or medium power systems with a single harmonic source. A new fast hybrid method (FHM) is developed in the thesis. It is a frequency domain method which can be used to evaluate the steady state harmonic penetration with discrete harmonic frequency. It is able to solve the convergence problem, simplify the calculation procedure and achieve accurate results. In addition, the proposed method has been applied to single phase balanced large power systems (e.g. Polish 2383-bus power system) to evaluate the harmonic penetration with integrating renewable generations. The investigation also includes the effects of harmonic penetration by changing the power capacities of renewable generations. Harmonic penetration variation during a 24 hour period is also investigated by tracking the daily generation and load demand curves. The harmonic sources considered in the thesis consist of wind turbine generator (WT), photovoltaic generator (PG), electric vehicle charger (EVC) and traditional six-pulse converters.

Wind energy is an increasingly important contributor of power within the renewable energy sector. In the year to 2012, wind generation within the United Kingdom (UK) increased 40% meeting 6% of the UK's national electricity demand. The UK is committed to providing 15% of its energy from renewable resources by 2020. Currently, the UK has approximately 40% of Europe's entire wind resource with significant potential for development of both on and offshore wind. In recent years, the number of reports on defective blades contributing towards turbine failure has grown. Blade manufacturers have privately reported a recurring problem with the spar cap - a critical strengthening component - which when weakened by damage, hastens the onset of operational failure. The contents of this thesis consider composite materials used within the blade and the detection techniques appropriate for in-field implementation. Application of Guided Waves, in particular Lamb waves, suits the typical dimensions of the blade composite structure. Experiments were conducted to understand the characteristics of Lamb wave modes within glass fibre reinforced plastic (GFRP) to assess attenuation levels; modal propagation; and dispersion with respect to fibre orientation. Finite Element Analysis (FEA) was used to observe material characteristics and discern possible modes of wave propagation. To exploit the directional qualities of GFRP, directional Macro Fibre Composite (MFC) sensors were applied to a wind turbine blade providing low-profile, light-weight, durability and conformability with sufficient sensitivity to detect elastic disturbance over large areas. Parametric monitoring of GFRP samples under loading identified tensile stress from defect onset. Cross correlation and sliding-window correlation signal processing techniques on recorded data from the applied sparse array identified the onset of fibre damage using Guided wave modes. This technique was able to identify modal changes to specific defects providing the prospect for in-situ blade monitoring.

Purpose - The thesis investigates effects of automatic variation of the deficit irrigation level with the growth stage of drip irrigated maize on grain yield and crop Water Use Efficiency (WUE). It further examines the impact of water-efficient irrigation controllers on the solar Photovoltaic energy level requirements for water pumping systems. Methodology - A Wireless Sensor and Actuator Network was deployed to monitor field conditions and actuate irrigation valves according to whether the level of moisture was within the set points. A Control Treatment (CT) field was fully irrigated using constant moisture threshold levels, while an Experimental Treatment (ExT) field had the highest level of deficit irrigation at the early and later growth stages. Full irrigation was applied at the middle growth stage. Irrigation depths and grain yields were measured, while WUE and the solar energy required by the water pumping system were calculated. Findings - The findings show that 880 mm and 560 mm of water were applied to CT and ExT fields, respectively. This represents a 36% water saving and a corresponding water pumping energy saving of 36% in the ExT field. The grain yields were 0.752 kg/m2 and 0.812 kg/m2 for CT and ExT fields, respectively. This shows that, despite applying a lower amount of water, the ExT improved the grain yield by 7.4%. Furthermore, the results show an increase in WUE from 0.86 kg/m3 for the CT field to 1.45 kg/m3 for the ExT field, representing a 69% improvement. Research limitations/implications - This study focused on the maize production under Malawi's weather conditions. However, the concept would easily be replicated in other crops and in other parts of the world with two modifications: firstly, sensor calibration must be done on-site; and secondly, the specific crop coefficient pattern must be used to develop the irrigation scheduling strategy.

Wireless Heterogeneous Networking (HetNet) offers the potential to be one of the most promising approaches to meeting escalating network capacity demands cost-effectively. The main challenge facing the deployment of HetNets is provisioning backhaul connectivity for small cells and the selection is governed by availability and cost, not solely by capacity requirements. In practical deployments, the adoption of mixture of backhaul technologies is likely, creating a non-uniform capacity distribution of small cells. The challenge becomes even more demanding if the backhaul is in the form of a multi-hop network. The research therefore proposes two algorithms which ensure that users enjoy the best possible quality of experience represented in terms of connection throughput and fairness considering the issues owing to small cells backhauling. The performance of types of HetNet, the Hotspot Wireless HetNet (HWH) and Multi-hop Wireless HetNet (MWH) corresponding to direct and multi-hop backhauling of small cells is evaluated. For HWH, an algorithm - the Dynamic Backhaul Capacity Sensitive Network Selection Scheme (DyBaCS) - is developed to manage the non-uniform backhaul capacity distribution ensuring a consistently fair network bandwidth distribution whilst maintaining throughput. The performance of DyBaCS and two other commonly used network selection schemes (NSSs) is evaluated and compared. Results show that DyBaCS provides superior fairness and a user throughput performance comparable to other reported schemes. For the more complex MWH architecture, a joint Multi-hop Bandwidth Allocation (MBA) and DyBaCS algorithm is developed to manage network performance. The performance of the algorithm is compared to results obtained using the Cuckoo Search optimisation algorithm and the Fair Share bandwidth allocation scheme. Results show that the algorithm is resilient in improving cell throughput whilst maintaining high levels of fairness.

Utilising scanning lidar devices deployed in active wind farms the results presented detail the evolution of the wind speed profile in the wake of wind turbines operating in both the on and offshore environment. The results of each of the deployments are compared against a variety of wake simulation models. Focussing on the measurement of wake data at hub height, data captured from the nacelle of an offshore wind turbine detailing flow evolution behaviour across a wide range of operational wind speeds and inlet operating conditions is presented. Binned in 2m/s wind speed bins the measurements clearly show a consistent profile across the captured speed range. This profile encompasses an initial flow deficit from inlet measured on the downstream side of the rotor. For undisturbed inflow this is seen to be around 30%, slightly larger for the disturbed inflow and larger still for waked inflow. Moving downstream the measured flow values indicate a flow evolution to a maximum deficit from inlet at two rotor diameters downstream, the differences between the inflow situations are preserved through to this point. This deficit is at a maximum in the 6-8m/s wind speed bins where the Power Coefficient is at its highest. As the wind speeds increase, and the Power Coefficient decreases, the magnitude of the maximum deficit decreases. Beyond this point the flow recovers towards inlet values. None of the profiles are found to recover fully within thirteen rotor diameters of the rotor plane. The wake simulation models employed each identify different areas of strength in comparison to the lidar measurements. The Eddy-Viscosity model with a Turbulence Intensity of 6% shows the closest correlation with the results at the maximum deficit through the recovery and into the far wake. It does not attempt to model the flow behaviour in the near wake region.

Low Voltage Ride-Through (LVRT) capability is considered a critical feature that should be implemented within a Wind Energy Conversion System (WECS). The mismatch produced between the generated active power and the power delivered to the grid during any dip incidence at the Point of Common Coupling causes a dc link voltage rise, and increase in grid currents and generator speed-up. Failure to ride-through grid voltage dips would lead to converter failures within the WECS. This thesis focuses on enhancing LVRT capability of PMSG based WECS using magnetic amplifiers. LVRT techniques vary according to the turbine and utility grid variables. A survey of the state-of-art LVRT techniques highlighting the merits and demerits of each approach is carried out. A 1.5 MW wind turbine system is modelled, which includes the wind turbine, PMSG, and power converters. Also PMSG control, maximum power point extraction, and grid active and reactive power control are investigated. System performance is studied in compliance with British grid codes for active and reactive power sudden changes, frequency excursion, and grid voltage phase angle jump. The model is tested for LVRT capability under symmetrical network dips. Magnetic amplifiers have been used in various applications such as instrumentation, fault current limiting, and battery chargers. In this thesis, magnetic amplifiers are proposed as part of a LVRT capability enhancing technique. Two possible configurations are proposed; 3-phase and dc-side configurations. LVRT capability enhancement is investigated for the 1.5MW WECS using the two magnetic amplifier configurations. The 3-phase topology is able to reduce the dc link voltage rise; however, it causes an increase in the stored rotor inertia accompanied by an increase in generator speed. The dc-side magnetic amplifier topology is able to limit the dc-link voltage rise which in turn protects the power converters without affecting generator performance. In addition to simulations, a scaled prototype with the dc side magnetic amplifier configuration is used to verify the effectiveness and applicability of the proposed technique during steady state and transient behaviour under various operating conditions.

Mobile communications has become an indispensable part of our everyday lives, with increasingly more people owning a smartphone, and being given access to a plethora of wireless access technologies: WiFi, 3G, and 4G. In an environment of such diversity, where each wireless access technology has its own distinct characteristics, network selection mechanisms provide an efficient way of handling communications services by matching the services' required quality with the characteristics of a particular access technology. This thesis explores the economic aspects of intelligent network selection in the context of Digital Marketplace - a theoretical market-based framework where network operators compete in a procurement auction-based setting for the right to transport the user's requested service over their infrastructure. It investigates the suitability of a firstprice sealed-bid auction as a network selection mechanism. Since this auction-based mechanism constitutes the main trading m echanism of the Digital Marketplace, the results reported herein affect its feasibility as a market for trading wireless communications services of the future. Since it lacks extensive and rigorous economic analysis, this thesis addresses this deficiency by providing an extensive game theoretic analysis of the network selection mechanism. This thesis creates an economic model of the network selection mechanism, and is the first to characterise the equilibrium bidding behaviour for an arbitrary number of network operators participating in the Digital Marketplace. It proposes three novel numerical methods that allow for numerical derivation of the equilibrium bidding behaviour: forward shooting method (FSM), polynomial projection method (PPM), and extended FSM (EFSM). The FSM and PPM methods allow for numerically approximating equilibrium bidding behaviour for a subset of all possible bidding scenarios, while the EFSM method enables computation of the numerical solution to all bidding scenarios. Finally, since the EFSM method becomes numerically unstable for large number of network operators, a novel methodology for approximating the network selection mechanism with an auction format for which there exist many well-defined and extensively studied numerical solutions is discussed.