System operational costs reduction with non-conventional reactive power sources

Wind energy installations are increasing in power systems worldwide and wind generation capacity tends to be located some distance from load centers. A conflict may arise at times of high wind generation when it becomes necessary to curtail wind energy in order to maintain conventional generators on-line for the provision of voltage control support at load centers. Using the island of Ireland as a case study and presenting commercially available reactive power support devices as possible solutions to the voltage control problems in urban areas, this paper explores the reduction in total generation costs resulting from the relaxation of the operational constraints requiring conventional generators to be kept on-line near load centers for reactive power support. The paper shows that by 2020 there will be possible savings of 87€m per annum and a reduction in wind curtailment of more than a percentage point if measures are taken to relax these constraints.

Evaporation maps for ternary non-ideal liquid mixtures

This thesis deals with the evaporation of non-ideal liquid mixtures using a multicomponent mass transfer approach. It develops the concept of evaporation maps as a convenient way of representing the dynamic composition changes of ternary mixtures during an evaporation process. Evaporation maps represent the residual composition of evaporating ternary non-ideal mixtures over the full range of composition, and are analogous to the commonly-used residue curve maps of simple distillation processes. The evaporation process initially considered in this work involves gas-phase limited evaporation from a liquid or wetted-solid surface, over which a gas flows at known conditions. Evaporation may occur into a pure inert gas, or into one pre-loaded with a known fraction of one of the ternary components. To explore multicomponent masstransfer effects, a model is developed that uses an exact solution to the Maxwell-Stefan equations for mass transfer in the gas film, with a lumped approach applied to the liquid phase. Solutions to the evaporation model take the form of trajectories in temperaturecomposition space, which are then projected onto a ternary diagram to form the map. Novel algorithms are developed for computation of pseudo-azeotropes in the evaporating mixture, and for calculation of the multicomponent wet-bulb temperature at a given liquid composition. A numerical continuation method is used to track the bifurcations which occur in the evaporation maps, where the composition of one component of the pre-loaded gas is the bifurcation parameter. The bifurcation diagrams can in principle be used to determine the required gas composition to produce a specific terminal composition in the liquid. A simple homotopy method is developed to track the locations of the various possible pseudo-azeotropes in the mixture. The stability of pseudo-azeotropes in the gas-phase limited case is examined using a linearized analysis of the governing equations. Algorithms for the calculation of separation boundaries in the evaporation maps are developed using an optimization-based method, as well as a method employing eigenvectors derived from the linearized analysis. The flexure of the wet-bulb temperature surface is explored, and it is shown how evaporation trajectories cross ridges and valleys, so that ridges and valleys of the surface do not coincide with separation boundaries. Finally, the assumption of gas-phase limited mass transfer is relaxed, by employing a model that includes diffusion in the liquid phase. A finite-volume method is used to solve the system of partial differential equations that results. The evaporation trajectories for the distributed model reduce to those of the lumped (gas-phase limited) model as the diffusivity in the liquid increases; under the same gas-phase conditions the permissible terminal compositions of the distributed and lumped models are the same.

Magnetic materials and soft-switched topologies for high-current DC-DC converters

The thesis is focused on the magnetic materials comparison and selection for high-power non-isolated dc-dc converters for industrial applications or electric, hybrid and fuel cell vehicles. The application of high-frequency bi-directional soft-switched dc-dc converters is also investigated. The thesis initially outlines the motivation for an energy-efficient transportation system with minimum environmental impact and reduced dependence on exhaustible resources. This is followed by a general overview of the power system architectures for electric, hybrid and fuel cell vehicles. The vehicle power sources and general dc-dc converter topologies are discussed. The dc-dc converter components are discussed with emphasis on recent semiconductor advances. A novel bi-directional soft-switched dc-dc converter with an auxiliary cell is introduced in this thesis. The soft-switching cell allows for the MOSFET's intrinsic body diode to operate in a half-bridge without reduced efficiency. The converter's mode-by-mode operation is analysed and closed-form expressions are presented for the average current gain of the converter. The design issues are presented and circuit limitations are discussed. Magnetic materials for the main dc-dc converter inductor are compared and contrasted. Novel magnetic material comparisons are introduced, which include the material dc bias capability and thermal conductivity. An inductor design algorithm is developed and used to compare the various magnetic materials for the application. The area-product analysis is presented for the minimum inductor size and highlights the optimum magnetic materials. Finally, the high-flux magnetic materials are experimentally compared. The practical effects of frequency, dc-bias, and converters duty-cycle effect for arbitrary shapes of flux density, air gap effects on core and winding, the winding shielding effect, and thermal configuration are investigated. The thesis results have been documented at IEEE EPE conference in 2007 and 2008, IEEE APEC in 2009 and 2010, and IEEE VPPC in 2010. A 2011 journal has been approved by IEEE Transactions on Power Electronics.

Differential and numerical models of hysteretic systems with stochastic and deterministic inputs

Many deterministic models with hysteresis have been developed in the areas of economics, finance, terrestrial hydrology and biology. These models lack any stochastic element which can often have a strong effect in these areas. In this work stochastically driven closed loop systems with hysteresis type memory are studied. This type of system is presented as a possible stochastic counterpart to deterministic models in the areas of economics, finance, terrestrial hydrology and biology. Some price dynamics models are presented as a motivation for the development of this type of model. Numerical schemes for solving this class of stochastic differential equation are developed in order to examine the prototype models presented. As a means of further testing the developed numerical schemes, numerical examination is made of the behaviour near equilibrium of coupled ordinary differential equations where the time derivative of the Preisach operator is included in one of the equations. A model of two phenotype bacteria is also presented. This model is examined to explore memory effects and related hysteresis effects in the area of biology. The memory effects found in this model are similar to that found in the non-ideal relay. This non-ideal relay type behaviour is used to model a colony of bacteria with multiple switching thresholds. This model contains a Preisach type memory with a variable Preisach weight function. Shown numerically for this multi-threshold model is a pattern formation for the distribution of the phenotypes among the available thresholds.

Design, fabrication and characterisation of components for microfluidic enzymatic biofuel cells

The concept of a biofuel cell takes inspiration from the natural capability of biological systems to catalyse the conversion of organic matter with a subsequent release of electrical energy. Enzymatic biofuel cells are intended to mimic the processes occurring in nature in a more controlled and efficient manner. Traditional fuel cells rely on the use of toxic catalysts and are often not easily miniaturizable making them unsuitable as implantable power sources. Biofuel cells however use highly selective protein catalysts and renewable fuels. As energy consumption becomes a global issue, they emerge as important tools for energy generation. The microfluidic platforms developed are intended to maximize the amount of electrical energy extracted from renewable fuels which are naturally abundant in the environment and in biological fluids. Combining microfabrication processes, chemical modification and biological surface patterning these devices are promising candidates for micro-power sources for future life science and electronic applications. This thesis considered four main aspects of a biofuel cell research. Firstly, concept of a miniature compartmentalized enzymatic biofuel cell utilizing simple fuels and operating in static conditions is verified and proves the feasibility of enzyme catalysis in energy conversion processes. Secondly, electrode and microfluidic channel study was performed through theoretical investigations of the flow and catalytic reactions which also improved understanding of the enzyme kinetics in the cell. Next, microfluidic devices were fabricated from cost-effective and disposable polymer materials, using the state-of-the-art micro-processing technologies. Integration of the individual components is difficult and multiple techniques to overcome these problems have been investigated. Electrochemical characterization of gold electrodes modified with Nanoporous Gold Structures is also performed. Finally, two strategies for enzyme patterning and encapsulation are discussed. Several protein catalysts have been effectively immobilized on the surface of commercial and microfabricated electrodes by electrochemically assisted deposition in sol-gel and poly-(o-phenylenediamine) polymer matrices and characterised with confirmed catalytic activity.

Addressing non-linear hardware limitations and extending network coverage area for power aware wireless sensor networks

Science Foundation Ireland (07/CE/11147); Irish Research Council for Science Engineering and Technology (Embark Initiative)

Investigation of factors driving the costs of operating the 2020 Irish power system with large-scale wind generation

The main goal of this work is to determine the true cost incurred by the Republic of Ireland and Northern Ireland in order to meet their EU renewable electricity targets. The primary all-island of Ireland policy goal is that 40% of electricity will come from renewable sources in 2020. From this it is expected that wind generation on the Irish electricity system will be in the region of 32-37% of total generation. This leads to issues resulting from wind energy being a non-synchronous, unpredictable and variable source of energy use on a scale never seen before for a single synchronous system. If changes are not made to traditional operational practices, the efficient running of the electricity system will be directly affected by these issues in the coming years. Using models of the electricity system for the all-island grid of Ireland, the effects of high wind energy penetration expected to be present in 2020 are examined. These models were developed using a unit commitment, economic dispatch tool called PLEXOS which allows for a detailed representation of the electricity system to be achieved down to individual generator level. These models replicate the true running of the electricity system through use of day-ahead scheduling and semi-relaxed use of these schedules that reflects the Transmission System Operator's of real time decision making on dispatch. In addition, it carefully considers other non-wind priority dispatch generation technologies that have an effect on the overall system. In the models developed, three main issues associated with wind energy integration were selected to be examined in detail to determine the sensitivity of assumptions presented in other studies. These three issues include wind energy's non-synchronous nature, its variability and spatial correlation, and its unpredictability. This leads to an examination of the effects in three areas: the need for system operation constraints required for system security; different onshore to offshore ratios of installed wind energy; and the degrees of accuracy in wind energy forecasting. Each of these areas directly impact the way in which the electricity system is run as they address each of the three issues associated with wind energy stated above, respectively. It is shown that assumptions in these three areas have a large effect on the results in terms of total generation costs, wind curtailment and generator technology type dispatch. In particular accounting for these issues has resulted in wind curtailment being predicted in much larger quantities than had been previously reported. This would have a large effect on wind energy companies because it is already a very low profit margin industry. Results from this work have shown that the relaxation of system operation constraints is crucial to the economic running of the electricity system with large improvements shown in the reduction of wind curtailment and system generation costs. There are clear benefits in having a proportion of the wind installed offshore in Ireland which would help to reduce variability of wind energy generation on the system and therefore reduce wind curtailment. With envisaged future improvements in day-ahead wind forecasting from 8% to 4% mean absolute error, there are potential reductions in wind curtailment system costs and open cycle gas turbine usage. This work illustrates the consequences of assumptions in the areas of system operation constraints, onshore/offshore installed wind capacities and accuracy in wind forecasting to better inform the true costs associated with running Ireland's changing electricity system as it continues to decarbonise into the near future. This work also proposes to illustrate, through the use of Ireland as a case study, the effects that will become ever more prevalent in other synchronous systems as they pursue a path of increasing renewable energy generation.

Impact of non-optimal grounding of the CC2420 RFIC on a 802.15.4 Tyndall sensor wireless mote

The performance of an RF output matching network is dependent on integrity of the ground connection. If this connection is compromised in anyway, additional parasitic elements may occur that can degrade performance and yield unreliable results. Traditionally, designers measure Constant Wave (CW) power to determine that the RF chain is performing optimally, the device is properly matched and by implication grounded. It is shown that there are situations where modulation quality can be compromised due to poor grounding that is not apparent using CW power measurements alone. The consequence of this is reduced throughput, range and reliability. Measurements are presented on a Tyndall Mote using a CC2420 RFIC todemonstrate how poor solder contact between the ground contacts and the ground layer of the PCB can lead tothe degradation of modulated performance. Detailed evaluation that required the development of a new measurement definition for 802.15.4 and analysis is presented to show how waveform quality is affected while the modulated output power remains within acceptable limits.

The formulation, testing and stability of 16% fat cream liqueurs

Cream liqueurs manufactured by a one-step process, where alcohol was added before homogenisation, were more stable than those processed by a two -step process which involved addition of alcohol after homogenisation. Using the one-step process, it was possible to produce creaming-stable liqueurs by using one pass through a homogeniser (27.6 MPa) equipped with "liquid whirl" valves. Test procedures to characterise cream liqueurs and to predict shelf life were studied in detail. A turbidity test proved simple, rapid and sensitive for characterising particle size and homogenisation efficiency. Prediction of age thickening/gelation in cream liqueurs during incubation at 45 °C depended on the age of the sample when incubated. Samples that gelled at 45 °C may not do so at ambient temperature. Commercial cream liqueurs were similar in gross chemical composition, and unlike experimentally produced liqueurs, these did not exhibit either age-gelation at ambient or elevated temperatures. Solutions of commercial sodium caseinates from different sources varied in their calcium sensitivity. When incorporated into cream liqueurs, caseinates influenced the rate of viscosity increase, coalescence and, possibly, gelation during incubated storage. Mild heat and alcohol treatment modified the properties of caseinate used to stabilise non-alcoholic emulsions, while the presence of alcohol in emulsions was important in preventing clustering of globules. The response to added trisodium citrate varied. In many cases, addition of the recommended level (0.18%) did not prevent gelation. Addition of small amounts of NaOH with 0.18 % trisodium citrate before homogenisation was beneficial. The stage at which citrate was added during processing was critical to the degree of viscosity increase (as opposed to gelation) in the product during 45 °C incubation. The component responsible for age-gelation was present in the milk-solids non fat portion of the cream and variations in the creams used were important in the age-gelation phenomenon Results indicated that, in addition to possibly Ca++, the micellar casein portion of serum may play a role in gelation. The role of the low molecular weight surfactants, sodium stearoyl lactylate and monodiglycerides in preventing gelation, was influenced by the presence of trisodium citrate. Clustering of fat globules and age-gelation were inhibited when 0.18 % citrate was included. Inclusion of sodium stearoyl lactylate, but not monodiglycerides, reduced the extent of viscosity increase at 45 °C in citrate containing liqueurs.

Systematic delay-driven power optimisation and power-driven delay optimisation of combinational circuits

With the proliferation of mobile wireless communication and embedded systems, the energy efficiency becomes a major design constraint. The dissipated energy is often referred as the product of power dissipation and the input-output delay. Most of electronic design automation techniques focus on optimising only one of these parameters either power or delay. Industry standard design flows integrate systematic methods of optimising either area or timing while for power consumption optimisation one often employs heuristics which are characteristic to a specific design. In this work we answer three questions in our quest to provide a systematic approach to joint power and delay Optimisation. The first question of our research is: How to build a design flow which incorporates academic and industry standard design flows for power optimisation? To address this question, we use a reference design flow provided by Synopsys and integrate in this flow academic tools and methodologies. The proposed design flow is used as a platform for analysing some novel algorithms and methodologies for optimisation in the context of digital circuits. The second question we answer is: Is possible to apply a systematic approach for power optimisation in the context of combinational digital circuits? The starting point is a selection of a suitable data structure which can easily incorporate information about delay, power, area and which then allows optimisation algorithms to be applied. In particular we address the implications of a systematic power optimisation methodologies and the potential degradation of other (often conflicting) parameters such as area or the delay of implementation. Finally, the third question which this thesis attempts to answer is: Is there a systematic approach for multi-objective optimisation of delay and power? A delay-driven power and power-driven delay optimisation is proposed in order to have balanced delay and power values. This implies that each power optimisation step is not only constrained by the decrease in power but also the increase in delay. Similarly, each delay optimisation step is not only governed with the decrease in delay but also the increase in power. The goal is to obtain multi-objective optimisation of digital circuits where the two conflicting objectives are power and delay. The logic synthesis and optimisation methodology is based on AND-Inverter Graphs (AIGs) which represent the functionality of the circuit. The switching activities and arrival times of circuit nodes are annotated onto an AND-Inverter Graph under the zero and a non-zero-delay model. We introduce then several reordering rules which are applied on the AIG nodes to minimise switching power or longest path delay of the circuit at the pre-technology mapping level. The academic Electronic Design Automation (EDA) tool ABC is used for the manipulation of AND-Inverter Graphs. We have implemented various combinatorial optimisation algorithms often used in Electronic Design Automation such as Simulated Annealing and Uniform Cost Search Algorithm. Simulated Annealing (SMA) is a probabilistic meta heuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. We used SMA to probabilistically decide between moving from one optimised solution to another such that the dynamic power is optimised under given delay constraints and the delay is optimised under given power constraints. A good approximation to the global optimum solution of energy constraint is obtained. Uniform Cost Search (UCS) is a tree search algorithm used for traversing or searching a weighted tree, tree structure, or graph. We have used Uniform Cost Search Algorithm to search within the AIG network, a specific AIG node order for the reordering rules application. After the reordering rules application, the AIG network is mapped to an AIG netlist using specific library cells. Our approach combines network re-structuring, AIG nodes reordering, dynamic power and longest path delay estimation and optimisation and finally technology mapping to an AIG netlist. A set of MCNC Benchmark circuits and large combinational circuits up to 100,000 gates have been used to validate our methodology. Comparisons for power and delay optimisation are made with the best synthesis scripts used in ABC. Reduction of 23% in power and 15% in delay with minimal overhead is achieved, compared to the best known ABC results. Also, our approach is also implemented on a number of processors with combinational and sequential components and significant savings are achieved.

Energy storage systems for wave energy converters and microgrids

The thesis initially gives an overview of the wave industry and the current state of some of the leading technologies as well as the energy storage systems that are inherently part of the power take-off mechanism. The benefits of electrical energy storage systems for wave energy converters are then outlined as well as the key parameters required from them. The options for storage systems are investigated and the reasons for examining supercapacitors and lithium-ion batteries in more detail are shown. The thesis then focusses on a particular type of offshore wave energy converter in its analysis, the backward bent duct buoy employing a Wells turbine. Variable speed strategies from the research literature which make use of the energy stored in the turbine inertia are examined for this system, and based on this analysis an appropriate scheme is selected. A supercapacitor power smoothing approach is presented in conjunction with the variable speed strategy. As long component lifetime is a requirement for offshore wave energy converters, a computer-controlled test rig has been built to validate supercapacitor lifetimes to manufacturer’s specifications. The test rig is also utilised to determine the effect of temperature on supercapacitors, and determine application lifetime. Cycle testing is carried out on individual supercapacitors at room temperature, and also at rated temperature utilising a thermal chamber and equipment programmed through the general purpose interface bus by Matlab. Application testing is carried out using time-compressed scaled-power profiles from the model to allow a comparison of lifetime degradation. Further applications of supercapacitors in offshore wave energy converters are then explored. These include start-up of the non-self-starting Wells turbine, and low-voltage ride-through examined to the limits specified in the Irish grid code for wind turbines. These applications are investigated with a more complete model of the system that includes a detailed back-to-back converter coupling a permanent magnet synchronous generator to the grid. Supercapacitors have been utilised in combination with battery systems for many applications to aid with peak power requirements and have been shown to improve the performance of these energy storage systems. The design, implementation, and construction of coupling a 5 kW h lithium-ion battery to a microgrid are described. The high voltage battery employed a continuous power rating of 10 kW and was designed for the future EV market with a controller area network interface. This build gives a general insight to some of the engineering, planning, safety, and cost requirements of implementing a high power energy storage system near or on an offshore device for interface to a microgrid or grid.

Low power predictable memory and processing architectures

Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Cost savings from relaxation of operational constraints on a power system with high wind penetration

Wind energy is predominantly a nonsynchronous generation source. Large-scale integration of wind generation with existing electricity systems, therefore, presents challenges in maintaining system frequency stability and local voltage stability. Transmission system operators have implemented system operational constraints (SOCs) in order to maintain stability with high wind generation, but imposition of these constraints results in higher operating costs. A mixed integer programming tool was used to simulate generator dispatch in order to assess the impact of various SOCs on generation costs. Interleaved day-ahead scheduling and real-time dispatch models were developed to allow accurate representation of forced outages and wind forecast errors, and were applied to the proposed Irish power system of 2020 with a wind penetration of 32%. Savings of at least 7.8% in generation costs and reductions in wind curtailment of 50% were identified when the most influential SOCs were relaxed. The results also illustrate the need to relax local SOCs together with the system-wide nonsynchronous penetration limit SOC, as savings from increasing the nonsynchronous limit beyond 70% were restricted without relaxation of local SOCs. The methodology and results allow for quantification of the costs of SOCs, allowing the optimal upgrade path for generation and transmission infrastructure to be determined.