Performance assessment of exponential Rosenbrock method for large systems of ODE

This paper studies time integration methods for large stiff systems of ordinary differential equations (ODEs) of the form u'(t) = g(u(t)). For such problems, implicit methods generally outperform explicit methods, since the time step is usually less restricted by stability constraints. Recently, however, explicit so-called exponential integrators have become popular for stiff problems due to their favourable stability properties. These methods use matrix-vector products involving exponential-like functions of the Jacobian matrix, which can be approximated using Krylov subspace methods that require only matrix-vector products with the Jacobian. In this paper, we implement exponential integrators of second, third and fourth order and demonstrate that they are competitive with well-established approaches based on the backward differentiation formulas and a preconditioned Newton-Krylov solution strategy.

Optimal distributed generation placement in radial distribution systems

Distributed generation (DG) resources are commonly used in the electric systems to obtain minimum line losses, as one of the benefits of DG, in radial distribution systems. Studies have shown the importance of appropriate selection of location and size of DGs. This paper proposes an analytical method for solving optimal distributed generation placement (ODGP) problem to minimize line losses in radial distribution systems using loss sensitivity factor (LSF) based on bus-injection to branch-current (BIBC) matrix. The proposed method is formulated and tested on 12 and 34 bus radial distribution systems. The classical grid search algorithm based on successive load flows is employed to validate the results. The main advantages of the proposed method as compared with the other conventional methods are the robustness and no need to calculate and invert large admittance or Jacobian matrices. Therefore, the simulation time and the amount of computer memory, required for processing data especially for the large systems, decreases.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

Wide area controls for transient and dynamic stability enhancement

This paper presents a study done into the effectiveness of using local acceleration measurements vs. remote angle measurements in providing stabilising control via SVCs following large disturbances. The system studied was an analogue of the Queensland-New South Wales Interconnection (QNI) and involved the control of an existing Static Var Compensators (SVC) at Sydney West. This study is placed in the context of wide area controls for large systems using aggregated models for groups of machines.

Managing growth and entry strategies across borders

Should the firm move successfully into a growth or expansion phase the owner manager will be required to increase the scale and scope of its operations. Part of this expansion will involve hiring additional employees, and increasing the overall complexity of the firm's activities. It is likely that the need for greater levels of professional management will be required to operate the firm, along with the need for enhanced planning and the introduction of systems to support the new levels of complexity. The transition from a small, owner-managed firm to a large systems-managed business will require the development of a team-based management approach with greater specialisation within the management team. Corporate governance is also likely to change as the growth cycle takes place. As it grows, the business will become more formalised in its accounting, management and other systems. The need for greater quantities of capital is likely to lead the business towards equity finance. As new equity partner are taken into the company the original owner managers may find their level of control diminished. The larger the firm becomes the more likely its management structure will become decentralised with greater separation between the owner and the firm in terms of operational and financial matters.

Making optimal and justifiable asset maintenance decisions

Maintenance decisions for large-scale asset systems are often beyond an asset manager's capacity to handle. The presence of a number of possibly conflicting decision criteria, the large number of possible maintenance policies, and the reality of budget constraints often produce complex problems, where the underlying trade-offs are not apparent to the asset manager. This paper presents the decision support tool "JOB" (Justification and Optimisation of Budgets), which has been designed to help asset managers of large systems assess, select, interpret and optimise the effects of their maintenance policies in the presence of limited budgets. This decision support capability is realized through an efficient, scalable backtracking- based algorithm for the optimisation of maintenance policies, while enabling the user to view a number of solutions near this optimum and explore tradeoffs with other decision criteria. To assist the asset manager in selecting between various policies, JOB also provides the capability of Multiple Criteria Decision Making. In this paper, the JOB tool is presented and its applicability for the maintenance of a complex power plant system.

GPU accelerated algorithms for computing matrix function vector products with applications to exponential integrators and fractional diffusion

The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.

Developing pictorial conceptual metaphors as a means of understanding and changing the Australian health system for Indigenous people

This paper describes the development of Pictorial Conceptual Metaphors, created out of a literature review on gendered Indigenous health and wellbeing that depicts the inherited effects of the ‘system’ past, present and future. The Pictorial Conceptual Metaphors are pictures that were created to tell the story of colonisation and its inherited and ongoing impacts on Indigenous people’s health and wellbeing. Aboriginal historical experiences, past, present and future are briefly overviewed in order to unpack and communicate to readers the significance and impact of these experiences on Aboriginal health, and ultimately, to bring about understanding to initiate change within the Australian health system. Systemic racism, embedded in the Australian health system, excludes and discriminates against Indigenous peoples through a lack of cultural consideration resulting in a cumulative and ongoing negative effect on Indigenous people’s health (Dudgeon et al. 2014; Fredericks 2008; Marmot 2011; Queensland Government 2012). Systemic action research identifies actions and processes in large systems such as health and education in order to bring about systemic change. Our intention to highlight the systemic changes needed in the Australian health system to improve Indigenous people’s health and wellbeing require us to understand the processes involved in bringing about systemic change. For this to occur, we needed to ‘see the system’ in order to identify the system dynamics in operation. The Pictorial Conceptual Metaphors are the first step in ‘seeing the system’; they illustrate the past and the present, and identify the preferred future for Indigenous health and wellbeing outcomes

Analysis of distrubances in large interconnected power systems

World economies increasingly demand reliable and economical power supply and distribution. To achieve this aim the majority of power systems are becoming interconnected, with several power utilities supplying the one large network. One problem that occurs in a large interconnected power system is the regular occurrence of system disturbances which can result in the creation of intra-area oscillating modes. These modes can be regarded as the transient responses of the power system to excitation, which are generally characterised as decaying sinusoids. For a power system operating ideally these transient responses would ideally would have a “ring-down” time of 10-15 seconds. Sometimes equipment failures disturb the ideal operation of power systems and oscillating modes with ring-down times greater than 15 seconds arise. The larger settling times associated with such “poorly damped” modes cause substantial power flows between generation nodes, resulting in significant physical stresses on the power distribution system. If these modes are not just poorly damped but “negatively damped”, catastrophic failures of the system can occur. To ensure system stability and security of large power systems, the potentially dangerous oscillating modes generated from disturbances (such as equipment failure) must be quickly identified. The power utility must then apply appropriate damping control strategies. In power system monitoring there exist two facets of critical interest. The first is the estimation of modal parameters for a power system in normal, stable, operation. The second is the rapid detection of any substantial changes to this normal, stable operation (because of equipment breakdown for example). Most work to date has concentrated on the first of these two facets, i.e. on modal parameter estimation. Numerous modal parameter estimation techniques have been proposed and implemented, but all have limitations [1-13]. One of the key limitations of all existing parameter estimation methods is the fact that they require very long data records to provide accurate parameter estimates. This is a particularly significant problem after a sudden detrimental change in damping. One simply cannot afford to wait long enough to collect the large amounts of data required for existing parameter estimators. Motivated by this gap in the current body of knowledge and practice, the research reported in this thesis focuses heavily on rapid detection of changes (i.e. on the second facet mentioned above). This thesis reports on a number of new algorithms which can rapidly flag whether or not there has been a detrimental change to a stable operating system. It will be seen that the new algorithms enable sudden modal changes to be detected within quite short time frames (typically about 1 minute), using data from power systems in normal operation. The new methods reported in this thesis are summarised below. The Energy Based Detector (EBD): The rationale for this method is that the modal disturbance energy is greater for lightly damped modes than it is for heavily damped modes (because the latter decay more rapidly). Sudden changes in modal energy, then, imply sudden changes in modal damping. Because the method relies on data from power systems in normal operation, the modal disturbances are random. Accordingly, the disturbance energy is modelled as a random process (with the parameters of the model being determined from the power system under consideration). A threshold is then set based on the statistical model. The energy method is very simple to implement and is computationally efficient. It is, however, only able to determine whether or not a sudden modal deterioration has occurred; it cannot identify which mode has deteriorated. For this reason the method is particularly well suited to smaller interconnected power systems that involve only a single mode. Optimal Individual Mode Detector (OIMD): As discussed in the previous paragraph, the energy detector can only determine whether or not a change has occurred; it cannot flag which mode is responsible for the deterioration. The OIMD seeks to address this shortcoming. It uses optimal detection theory to test for sudden changes in individual modes. In practice, one can have an OIMD operating for all modes within a system, so that changes in any of the modes can be detected. Like the energy detector, the OIMD is based on a statistical model and a subsequently derived threshold test. The Kalman Innovation Detector (KID): This detector is an alternative to the OIMD. Unlike the OIMD, however, it does not explicitly monitor individual modes. Rather it relies on a key property of a Kalman filter, namely that the Kalman innovation (the difference between the estimated and observed outputs) is white as long as the Kalman filter model is valid. A Kalman filter model is set to represent a particular power system. If some event in the power system (such as equipment failure) causes a sudden change to the power system, the Kalman model will no longer be valid and the innovation will no longer be white. Furthermore, if there is a detrimental system change, the innovation spectrum will display strong peaks in the spectrum at frequency locations associated with changes. Hence the innovation spectrum can be monitored to both set-off an “alarm” when a change occurs and to identify which modal frequency has given rise to the change. The threshold for alarming is based on the simple Chi-Squared PDF for a normalised white noise spectrum [14, 15]. While the method can identify the mode which has deteriorated, it does not necessarily indicate whether there has been a frequency or damping change. The PPM discussed next can monitor frequency changes and so can provide some discrimination in this regard. The Polynomial Phase Method (PPM): In [16] the cubic phase (CP) function was introduced as a tool for revealing frequency related spectral changes. This thesis extends the cubic phase function to a generalised class of polynomial phase functions which can reveal frequency related spectral changes in power systems. A statistical analysis of the technique is performed. When applied to power system analysis, the PPM can provide knowledge of sudden shifts in frequency through both the new frequency estimate and the polynomial phase coefficient information. This knowledge can be then cross-referenced with other detection methods to provide improved detection benchmarks.

An evidence-based approach to professional development planning in large state educational systems

This paper presents a systems-level approach for adjudicating the prioritization, selection, and planning of inservcie professional development (PD) for teachers. We present a step-by-step model for documenting and assessing system-wide 'bids' for professional development programs

Parallel user profiling based on folksonomy for Large Scaled Recommender Systems : an implimentation of Cascading MapReduce

The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users’ interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Del.icio.us website.

Knowledge management for enterprise systems: observations from small, medium and large organizations

Anecdotal evidence suggests that the lifecycle-wide management of Enterprise System (ES) related knowledge is critical for ES health and longevity. At a time where many ES-vendors now offering solutions to Small and Medium size organizations, this paper investigates the ability of Small and Medium size organizations to maintain a lifecycle-wide knowledge management strategy. The paper explores the alleged differences in the knowledge management practices across 27 small, medium and large organizations that had implemented a market-leading ES. Results suggest that: (1) despite similar knowledge creation efforts in all three organizational sizes, small organizations struggle with retaining, transferring and applying the knowledge. The study also reveals that, (2) the overall goodness of the knowledge management process in larger organizations remains higher than their small and medium counterparts.

Evaluating the success of large-scale, integrated information systems through the lens of IS-impact and IS-support

This study proceeds from a central interest in the importance of systematically evaluating operational large-scale integrated information systems (IS) in organisations. The study is conducted within the IS-Impact Research Track at Queensland University of Technology (QUT). The goal of the IS-Impact Track is, "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable et al, 2009). The track espouses programmatic research having the principles of incrementalism, tenacity, holism and generalisability through replication and extension research strategies. Track efforts have yielded the bicameral IS-Impact measurement model; the ‘impact’ half includes Organisational-Impact and Individual-Impact dimensions; the ‘quality’ half includes System-Quality and Information-Quality dimensions. Akin to Gregor’s (2006) analytic theory, the ISImpact model is conceptualised as a formative, multidimensional index and is defined as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (Gable et al., 2008, p: 381). The study adopts the IS-Impact model (Gable, et al., 2008) as its core theory base. Prior work within the IS-Impact track has been consciously constrained to Financial IS for their homogeneity. This study adopts a context-extension strategy (Berthon et al., 2002) with the aim "to further validate and extend the IS-Impact measurement model in a new context - i.e. a different IS - Human Resources (HR)". The overarching research question is: "How can the impacts of large-scale integrated HR applications be effectively and efficiently benchmarked?" This managerial question (Cooper & Emory, 1995) decomposes into two more specific research questions – In the new HR context: (RQ1): "Is the IS-Impact model complete?" (RQ2): "Is the ISImpact model valid as a 1st-order formative, 2nd-order formative multidimensional construct?" The study adhered to the two-phase approach of Gable et al. (2008) to hypothesise and validate a measurement model. The initial ‘exploratory phase’ employed a zero base qualitative approach to re-instantiating the IS-Impact model in the HR context. The subsequent ‘confirmatory phase’ sought to validate the resultant hypothesised measurement model against newly gathered quantitative data. The unit of analysis for the study is the application, ‘ALESCO’, an integrated large-scale HR application implemented at Queensland University of Technology (QUT), a large Australian university (with approximately 40,000 students and 5000 staff). Target respondents of both study phases were ALESCO key-user-groups: strategic users, management users, operational users and technical users, who directly use ALESCO or its outputs. An open-ended, qualitative survey was employed in the exploratory phase, with the objective of exploring the completeness and applicability of the IS-Impact model’s dimensions and measures in the new context, and to conceptualise any resultant model changes to be operationalised in the confirmatory phase. Responses from 134 ALESCO users to the main survey question, "What do you consider have been the impacts of the ALESCO (HR) system in your division/department since its implementation?" were decomposed into 425 ‘impact citations.’ Citation mapping using a deductive (top-down) content analysis approach instantiated all dimensions and measures of the IS-Impact model, evidencing its content validity in the new context. Seeking to probe additional (perhaps negative) impacts; the survey included the additional open question "In your opinion, what can be done better to improve the ALESCO (HR) system?" Responses to this question decomposed into a further 107 citations which in the main did not map to IS-Impact, but rather coalesced around the concept of IS-Support. Deductively drawing from relevant literature, and working inductively from the unmapped citations, the new ‘IS-Support’ construct, including the four formative dimensions (i) training, (ii) documentation, (iii) assistance, and (iv) authorisation (each having reflective measures), was defined as: "a measure at a point in time, of the support, the [HR] information system key-user groups receive to increase their capabilities in utilising the system." Thus, a further goal of the study became validation of the IS-Support construct, suggesting the research question (RQ3): "Is IS-Support valid as a 1st-order reflective, 2nd-order formative multidimensional construct?" With the aim of validating IS-Impact within its nomological net (identification through structural relations), as in prior work, Satisfaction was hypothesised as its immediate consequence. The IS-Support construct having derived from a question intended to probe IS-Impacts, too was hypothesised as antecedent to Satisfaction, thereby suggesting the research question (RQ4): "What is the relative contribution of IS-Impact and IS-Support to Satisfaction?" With the goal of testing the above research questions, IS-Impact, IS-Support and Satisfaction were operationalised in a quantitative survey instrument. Partial least squares (PLS) structural equation modelling employing 221 valid responses largely evidenced the validity of the commencing IS-Impact model in the HR context. ISSupport too was validated as operationalised (including 11 reflective measures of its 4 formative dimensions). IS-Support alone explained 36% of Satisfaction; IS-Impact alone 70%; in combination both explaining 71% with virtually all influence of ISSupport subsumed by IS-Impact. Key study contributions to research include: (1) validation of IS-Impact in the HR context, (2) validation of a newly conceptualised IS-Support construct as important antecedent of Satisfaction, and (3) validation of the redundancy of IS-Support when gauging IS-Impact. The study also makes valuable contributions to practice, the research track and the sponsoring organisation.