Performance measurement methodology for integrated services networks

With the emergence of advanced integrated services networks, the need for effective performance analysis techniques has become extremely important. Further advancements in these networks can only be possible if the practical performance issues of the existing networks are clearly understood. This thesis is concerned with the design and development of a measurement system which has been implemented on a large experimental network. The measurement system is based on dedicated traffic generators which have been designed and implemented on the Project Unison network. The Unison project is a multisite networking experiment for conducting research into the interconnection and interworking of local area network based multi-media application systems. The traffic generators were first developed for the Cambridge Ring based Unison network. Once their usefulness and effectiveness was proven, high performance traffic generators using transputer technology were built for the Cambridge Fast Ring based Unison network. The measurement system is capable of measuring the conventional performance parameters such as throughput and packet delay, and is able to characterise the operational performance of network bridging components under various loading conditions. In particular, the measurement system has been used in a 'measure and tune' fashion in order to improve the performance of a complex bridging device. Accurate measurement of packet delay in wide area networks is a recognised problem. The problem is associated with the synchronisation of the clocks between the distant machines. A chronological timestamping technique has been introduced in which the clocks are synchronised using a broadcast synchronisation technique. Rugby time clock receivers have been interfaced to each generator for the purpose of synchronisation. In order to design network applications, an accurate knowledge of the expected network performance under different loading conditions is essential. Using the measurement system, this has been achieved by examining the network characteristics at the network/user interface. Also, the generators are capable of emulating a variety of application traffic which can be injected into the network along with the traffic from real applications, thus enabling user oriented performance parameters to be evaluated in a mixed traffic environment. A number of performance measurement experiments have been conducted using the measurement system. Experimental results obtained from the Unison network serve to emphasise the power and effectiveness of the measurement methodology

Optimisation of stand-alone hydrogen-based renewable energy systems using intelligent techniques

Wind and solar irradiance are promising renewable alternatives to fossil fuels due to their availability and topological advantages for local power generation. However, their intermittent and unpredictable nature limits their integration into energy markets. Fortunately, these disadvantages can be partially overcome by using them in combination with energy storage and back-up units. However, the increased complexity of such systems relative to single energy systems makes an optimal sizing method and appropriate Power Management Strategy (PMS) research priorities. This thesis contributes to the design and integration of stand-alone hybrid renewable energy systems by proposing methodologies to optimise the sizing and operation of hydrogen-based systems. These include using intelligent techniques such as Genetic Algorithm (GA), Particle Swarm Optimisation (PSO) and Neural Networks (NNs). Three design aspects: component sizing, renewables forecasting, and operation coordination, have been investigated. The thesis includes a series of four journal articles. The first article introduced a multi-objective sizing methodology to optimise standalone, hydrogen-based systems using GA. The sizing method was developed to calculate the optimum capacities of system components that underpin appropriate compromise between investment, renewables penetration and environmental footprint. The system reliability was assessed using the Loss of Power Supply Probability (LPSP) for which a novel modification was introduced to account for load losses during transient start-up times for the back-ups. The second article investigated the factors that may influence the accuracy of NNs when applied to forecasting short-term renewable energy. That study involved two NNs: Feedforward, and Radial Basis Function in an investigation of the effect of the type, span and resolution of training data, and the length of training pattern, on shortterm wind speed prediction accuracy. The impact of forecasting error on estimating the available wind power was also evaluated for a commercially available wind turbine. The third article experimentally validated the concept of a NN-based (predictive) PMS. A lab-scale (stand-alone) hybrid energy system, which consisted of: an emulated renewable power source, battery bank, and hydrogen fuel cell coupled with metal hydride storage, satisfied the dynamic load demand. The overall power flow of the constructed system was controlled by a NN-based PMS which was implemented using MATLAB and LabVIEW software. The effects of several control parameters, which are either hardware dependent or affect the predictive algorithm, on system performance was investigated under the predictive PMS, this was benchmarked against a rulebased (non-intelligent) strategy. The fourth article investigated the potential impact of NN-based PMS on the economic and operational characteristics of such hybrid systems. That study benchmarked a rule-based PMS to its (predictive) counterpart. In addition, the effect of real-time fuel cell optimisation using PSO, when applied in the context of predictive PMS was also investigated. The comparative analysis was based on deriving the cost of energy, life cycle emissions, renewables penetration, and duty cycles of fuel cell and electrolyser units. The effects of other parameters such the LPSP level, prediction accuracy were also investigated. The developed techniques outperformed traditional approaches by drawing upon complex artificial intelligence models. The research could underpin cost-effective, reliable power supplies to remote communities as well as reducing the dependence on fossil fuels and the associated environmental footprint

Unconventional computing platforms and nature-inspired methods for solving hard optimisation problems

The search for novel hardware beyond the traditional von Neumann architecture has given rise to a modern area of unconventional computing requiring the efforts of mathematicians, physicists and engineers. Many analogue physical systems, including networks of nonlinear oscillators, lasers, condensates, and superconducting qubits, are proposed and realised to address challenging computational problems from various areas of social and physical sciences and technology. Understanding the underlying physical process by which the system finds the solutions to such problems often leads to new optimisation algorithms. This thesis focuses on studying gain-dissipative systems and nature-inspired algorithms that form a hybrid architecture that may soon rival classical hardware. Chapter 1 lays the necessary foundation and explains various interdisciplinary terms that are used throughout the dissertation. In particular, connections between the optimisation problems and spin Hamiltonians are established, their computational complexity classes are explained, and the most prominent physical platforms for spin Hamiltonian implementation are reviewed. Chapter 2 demonstrates a large variety of behaviours encapsulated in networks of polariton condensates, which are a vivid example of a gain-dissipative system we use throughout the thesis. We explain how the variations of experimentally tunable parameters allow the networks of polariton condensates to represent different oscillator models. We derive analytic expressions for the interactions between two spatially separated polariton condensates and show various synchronisation regimes for periodic chains of condensates. An odd number of condensates at the vertices of a regular polygon leads to a spontaneous formation of a giant multiply-quantised vortex at the centre of a polygon. Numerical simulations of all studied configurations of polariton condensates are performed with a mean-field approach with some theoretically proposed physical phenomena supported by the relevant experiments. Chapter 3 examines the potential of polariton graphs to find the low-energy minima of the spin Hamiltonians. By associating a spin with a condensate phase, the minima of the XY model are achieved for simple configurations of spatially-interacting polariton condensates. We argue that such implementation of gain-dissipative simulators limits their applicability to the classes of easily solvable problems since the parameters of a particular Hamiltonian depend on the node occupancies that are not known a priori. To overcome this difficulty, we propose to adjust pumping intensities and coupling strengths dynamically. We further theoretically suggest how the discrete Ising and $n$-state planar Potts models with or without external fields can be simulated using gain-dissipative platforms. The underlying operational principle originates from a combination of resonant and non-resonant pumping. Spatial anisotropy of pump and dissipation profiles enables an effective control of the sign and intensity of the coupling strength between any two neighbouring sites, which we demonstrate with a two dimensional square lattice of polariton condensates. For an accurate minimisation of discrete and continuous spin Hamiltonians, we propose a fully controllable polaritonic XY-Ising machine based on a network of geometrically isolated polariton condensates. In Chapter 4, we look at classical computing rivals and study nature-inspired methods for optimising spin Hamiltonians. Based on the operational principles of gain-dissipative machines, we develop a novel class of gain-dissipative algorithms for the optimisation of discrete and continuous problems and show its performance in comparison with traditional optimisation techniques. Besides looking at traditional heuristic methods for Ising minimisation, such as the Hopfield-Tank neural networks and parallel tempering, we consider a recent physics-inspired algorithm, namely chaotic amplitude control, and exact commercial solver, Gurobi. For a proper evaluation of physical simulators, we further discuss the importance of detecting easy instances of hard combinatorial optimisation problems. The Ising model for certain interaction matrices, that are commonly used for evaluating the performance of unconventional computing machines and assumed to be exponentially hard, is shown to be solvable in polynomial time including the Mobius ladder graphs and Mattis spin glasses. In Chapter 5 we discuss possible future applications of unconventional computing platforms including emulation of search algorithms such as PageRank, realisation of a proof-of-work protocol for blockchain technology, and reservoir computing

The WiSE Approach to Engineering Educational Environments

Developing teaching laboratories for complex applied technical fields can be expensive and carries significant risk for the sponsoring University or institution. Laboratories are typically developed as projects requiring development of sophisticated systems (including hardware, software and curriculum) delivered as a functioning whole that is: useful to staff, attractive to students and produces the required educational outcomes. All within constraints of cost, time, space and staffing

Analysis and testing of the IPB pico-hydro emulation platform with grid connection

The global context in which there is a need to reduce environmental impacts intensifies the search for new technologies for renewable sources. In addition to environmental issues, access to basic rights and social inclusion are also motivation for electricity generation, in a context including distributed generation (DG). Currently, the pico hydro power plant is an attractive application because of its resource availability; also, it is an interesting solution for a microgrid (on-grid or off-grid). On the other hand, usually, the conversion system is not "plug and play". This project presents the tests of convertion system for a "plug and play" solution, using different turbines and water wheel, permanent magnet synchronous generators (PMSG) and photovoltaic (PV) inverters. In this approach, generators can work at variable speed, having an overvoltage protection circuit. The prerequisites for device integration must be considered: power compatibility, minimum and maximum limit voltage, and the maximum current of PV inverter. The tests were done in the pico-hydro emulation platform, in the Superior School of Technology and Management (ESTiG). The low head propeller, Turgo, and Pelton turbines are tested in the emulation platform; as well as the vertical axis water wheel. The turbines were connected to the grid using SOLAX inverters (up to 1650 W) and OMNIK (up to 2300 W), presenting satisfactory results in both. The water wheel tests used five microinverters (up to 300 W), showing grid connection with three: BEON, GWL, and INVOLAR.O contexto global em que há necessidade de redução dos impactos ambientais intensifica a busca por novas tecnologias para fontes renováveis. Além das questões ambientais, o acesso a direitos básicos e inclusão social também são estímulos à geração de energia elétrica em áreas remotas, incluindo o contexto de geração distribuída (GD). Atualmente, as plantas pico-hídricas têm sua aplicação interessante pela disponibilidade do recurso primário; e interessante solução para microrredes (on-grid ou off-grid). Por outro ponto de vista, geralmente o sistema de conversão não é "plug and play". Este projeto apresenta o teste dos sistemas de conversão com uma solução "plug and play", uttilizando diferentes turbinas, geradores síncronos de ímã permanente (GSIP) e inversores fotovoltaicos. Utilizou-se a abordagem em que os geradores podem trabalhar em velocidade variável, tendo um circuito de proteção contra sobre-tensão. Devem ser considerados os pré-requisitos para integração dos componentes: compatibilidade de potência, tensões limites e corrente máxima do inversor fotovoltaico. Os testes foram feitos na plataforma de emulação de sistemas pico-hídricos na Escola Superior de Tecnologia e Gestão (ESTiG). Testaram-se turbinas para baixa queda do tipo hélice, Turgo e Pelton; e também a roda d’água de eixo vertical. A conexão das turbinas com a rede foi feita com os inversores SOLAX (até 1650 W) e OMNIK (até 2300 W), apresentando resultados satisfatórios em ambos. Com a roda d’água foram testados cinco microinversores (até 300 W), apresentando conexão com três: BEON, GWL e INVOLAR

The programmable logic controller : its prehistory, emergence and application

Programmable Logic Controllers (PLCs) are widely used devices controlling industrial machines and processes and many other diverse applications, requiring primarily, combinatorial logic and sequential control. The PLC is a hidden technology, little known by the general public and overlooked in academic historical studies of technology. The research reported in this thesis aims to address this lack of awareness. The thesis explores the development of sequential and combinatorial logic control technologies, the emergence of the PLC, its subsequent development and its industrial applications. Patents and first- hand accounts and experiences from senior industrial engineers in a number of diverse manufacturing industries have been used as the primary research sources since, as a hidden technology, academic historical accounts are sparse. This approach illustrates, through using the PLC as an example, a potential method of studying other, unrelated hidden technologies. The research has revealed the influence of geography, industrial settings and earlier engineering practices on the design, selection and application of PLC control technologies, and comments on the how these influences define specific communities of practice

A Framework for Categorization of Industrial Control System Cyber Training Environments

First responders and professionals in hazardous occupations undergo training and evaluations for the purpose of mitigating risk and damage. For example, helicopter pilots train with multiple categorized simulations that increase in complexity before flying a real aircraft. However in the industrial control cyber incident response domain, where incident response professionals help detect, respond and recover from cyber incidents, no official categorization of training environments exist. To address this gap, this thesis provides a categorization of industrial control training environments based on realism. Four levels of environments are proposed and mapped to Blooms Taxonomy. This categorization will help organizations determine which training environment best aligns with their training needs and budgets

Renewable Energy

Renewable Energy is energy generated from natural resources - such as sunlight, wind, rain, tides and geothermal heat - which are naturally replenished. In 2008, about 18% of global final energy consumption came from renewables, with 13% coming from traditional biomass, such as wood burning. Hydroelectricity was the next largest renewable source, providing 3% (15% of global electricity generation), followed by solar hot water/heating, which contributed with 1.3%. Modern technologies, such as geothermal energy, wind power, solar power, and ocean energy together provided some 0.8% of final energy consumption. The book provides a forum for dissemination and exchange of up - to - date scientific information on theoretical, generic and applied areas of knowledge. The topics deal with new devices and circuits for energy systems, photovoltaic and solar thermal, wind energy systems, tidal and wave energy, fuel cell systems, bio energy and geo-energy, sustainable energy resources and systems, energy storage systems, energy market management and economics, off-grid isolated energy systems, energy in transportation systems, energy resources for portable electronics, intelligent energy power transmission, distribution and inter - connectors, energy efficient utilization, environmental issues, energy harvesting, nanotechnology in energy, policy issues on renewable energy, building design, power electronics in energy conversion, new materials for energy resources, and RF and magnetic field energy devices

Cognitive and Autonomous Software-Defined Open Optical Networks

L'abstract è presente nell'allegato / the abstract is in the attachmen