Improving power quality in low-voltage networks containing distributed energy resources

Severe power quality problems can arise when a large number of single-phase distributed energy resources (DERs) are connected to a low-voltage power distribution system. Due to the random location and size of DERs, it may so happen that a particular phase generates excess power than its load demand. In such an event, the excess power will be fed back to the distribution substation and will eventually find its way to the transmission network, causing undesirable voltage-current unbalance. As a solution to this problem, the article proposes the use of a distribution static compensator (DSTATCOM), which regulates voltage at the point of common coupling (PCC), thereby ensuring balanced current flow from and to the distribution substation. Additionally, this device can also support the distribution network in the absence of the utility connection, making the distribution system work as a microgrid. The proposals are validated through extensive digital computer simulation studies using PSCADTM

Indigenous/digital heterogeneities : an actor-network-theory approach

This thesis analysed the theoretical and ontological issues of previous scholarship concerning information technology and indigenous people. As an alternative, the thesis used the framework of actor-network-theory, especially through historiographical and ethnographic techniques. The thesis revealed an assemblage of indigenous/digital enactments striving for relevance and avoiding obsolescence. It also recognised heterogeneities- including user-ambivalences, oscillations, noise, non-coherences and disruptions - as part of the milieu of the daily digital lives of indigenous people. By taking heterogeneities into account, the thesis ensured that the data “speaks for itself” and that social inquiry is not overtaken by ideology and ontology.

Calligraphy and causation : two obstetric management cases - Hirst v Sydney South West Area Health and King v Western Sydney local health network

Two recent decisions of the Supreme Court of New South Wales in the context of obstetric management have highlighted firstly, the importance of keeping legible, accurate and detailed medical records; and secondly, the challenges faced by those seeking to establish causation, particularly where epidemiological evidence is relied upon...

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Random Breath Testing in Australia: Is there an Optimum Level of Intensity?

Background: Random Breath Testing (RBT) is the main drink driving law enforcement tool used throughout Australia. International comparative research considers Australia to have the most successful RBT program compared to other countries in terms of crash reductions (Erke, Goldenbeld, & Vaa, 2009). This success is attributed to the programs high intensity (Erke et al., 2009). Our review of the extant literature suggests that there is no research evidence that indicates an optimal level of alcohol breath testing. That is, we suggest that no research exists to guide policy regarding whether or not there is a point at which alcohol related crashes reach a point of diminishing returns as a result of either saturated or targeted RBT testing. Aims: In this paper we first provide an examination of RBTs and alcohol related crashes across Australian jurisdictions. We then address the question of whether or not an optimal level of random breath testing exists by examining the relationship between the number of RBTs conducted and the occurrence of alcohol-related crashes over time, across all Australian states. Method: To examine the association between RBT rates and alcohol related crashes and to assess whether an optimal ratio of RBT tests per licenced drivers can be determined we draw on three administrative data sources form each jurisdiction. Where possible data collected spans January 1st 2000 to September 30th 2012. The RBT administrative dataset includes the number of Random Breath Tests (RBTs) conducted per month. The traffic crash administrative dataset contains aggregated monthly count of the number of traffic crashes where an individual’s recorded BAC reaches or exceeds 0.05g/ml of alcohol in blood. The licenced driver data were the monthly number of registered licenced drivers spanning January 2000 to December 2011. Results: The data highlights that the Australian story does not reflective of all States and territories. The stable RBT to licenced driver ratio in Queensland (of 1:1) suggests a stable rate of alcohol related crash data of 5.5 per 100,000 licenced drivers. Yet, in South Australia were a relative stable rate of RBT to licenced driver ratio of 1:2 is maintained the rate of alcohol related traffic crashes is substantially less at 3.7 per 100,000. We use joinpoint regression techniques and varying regression models to fit the data and compare the different patterns between jurisdictions. Discussion: The results of this study provide an updated review and evaluation of RBTs conducted in Australia and examines the association between RBTs and alcohol related traffic crashes. We also present an evidence base to guide policy decisions for RBT operations.

Harmonic quality of multilevel cascade inverters with random carrier phase pulse width modulation

The output harmonic quality of N series connected full-bridge dc-ac inverters is investigated. The inverters are pulse width modulated using a common reference signal but randomly phased carrier signals. Through analysis and simulation, probability distributions for inverter output harmonics and vector representations of N carrier phases are combined and assessed. It is concluded that a low total harmonic distortion is most likely to occur and will decrease further as N increases.

On the use of Bluetooth MAC Scanners for live reporting of the transport network

Recently there has been significant interest of researchers and practitioners on the use of Bluetooth as a complementary transport data. However, literature is limited with the understanding of the Bluetooth MAC Scanner (BMS) based data acquisition process and the properties of the data being collected. This paper first provides an insight on the BMS data acquisition process. Thereafter, it discovers the interesting facts from analysis of the real BMS data from both motorway and arterial networks of Brisbane, Australia. The knowledge gained is helpful for researchers and practitioners to understand the BMS data being collected which is vital to the development of management and control algorithms using the data.

Are more city dwellers caught drink driving than country folk? An analysis by random breath testing apprehension rates

Background Random Breath Testing (RBT) remains a central enforcement strategy to deter and apprehend drink drivers in Queensland (Australia). Despite this, there is little published research regarding the exact drink driving apprehension rates across the state as measured through RBT activities. Aims The aim of the current study was to examine the prevalence of apprehending drink drivers in urban versus rural areas. Methods The Queensland Police Service provided data relating to the number of RBT conducted and apprehensions for the period 1 January 2000 to 31 December 2011. Results In the period, 35,082,386 random breath tests (both mobile and stationary) were conducted in Queensland which resulted in 248,173 individuals being apprehended for drink driving offences. Overall drink driving apprehension rates appear to have decreased across time. Close examination of the data revealed that the highest proportion of drink driving apprehensions (when compared with RBT testing rates) was in the Northern and Far Northern regions of Queensland (e.g., rural areas). In contrast, the lowest proportions were observed within the two Brisbane metropolitan regions (e.g., urban areas). However, differences in enforcement styles across the urban and rural regions need to be considered. Discussion and conclusions The research presentation will further outline the major findings of the study in regards to maximising the efficiency of RBT operations both within urban and rural areas of Queensland, Australia.

Brokering evaluations of partnerships in Australian community arts : responding to entrepreneurial tendencies

This article examines motivations and methods for external evaluators in taking on a brokerage relationship between artists, arts managers and governments (national and local) during an appraisal process of community arts events. The argument is situated in our experience evaluating the Creating Queensland programme, a multifaceted community arts programme presented as part of the one of Australia’s largest arts events the Brisbane Festival, in 2009 and 2010. We use this case to identify a number of principles and processes that may assist in establishing an effective evaluation process – defined, for us, as a process in which partners representing different elements of the community arts project can share information in a learning network, or an innovation network, that embraces the idea of continuous improvement. We explain that we, as consultants, are not necessarily the only participants in the evaluation process in a position to broker the decision making about what to research and report on. We argue that empowering each of the delivery partners to act as brokers, using the principles, protocols and processes to negotiate what should be researched, when, how and how it should be shared, is something each delivery partner can do. This can help create a common understanding that can reduce anxieties about using warts-and-all evaluation data to learn, grow and improve in the arts. It can, as a result, be beneficial both for the participating partners and the community arts sector as a whole.

Outcomes of the Chemistry Discipline Network Mapping Exercises: Are the Threshold Learning Outcomes met?

The Chemistry Discipline Network has recently completed two distinct mapping exercises. The first is a snapshot of chemistry taught at 12 institutions around Australia in 2011. There were many similarities but also important differences in the content taught and assessed at different institutions. There were also significant differences in delivery, particularly laboratory contact hours, as well as forms and weightings of assessment. The second mapping exercise mapped the chemistry degrees at three institutions to the Threshold Learning Outcomes for chemistry. Importantly, some of the TLOs were addressed by multiple units at all institutions, while others were not met, or were met at an introductory level only. The exercise also exposed some challenges in using the TLOs as currently written.

Identify disorders in health records using Conditional Random Fields and Metamap: AEHRC at ShARe/CLEF 2013 eHealth Evaluation Lab Task 1

The Australian e-Health Research Centre (AEHRC) recently participated in the ShARe/CLEF eHealth Evaluation Lab Task 1. The goal of this task is to individuate mentions of disorders in free-text electronic health records and map disorders to SNOMED CT concepts in the UMLS metathesaurus. This paper details our participation to this ShARe/CLEF task. Our approaches are based on using the clinical natural language processing tool Metamap and Conditional Random Fields (CRF) to individuate mentions of disorders and then to map those to SNOMED CT concepts. Empirical results obtained on the 2013 ShARe/CLEF task highlight that our instance of Metamap (after ltering irrelevant semantic types), although achieving a high level of precision, is only able to identify a small amount of disorders (about 21% to 28%) from free-text health records. On the other hand, the addition of the CRF models allows for a much higher recall (57% to 79%) of disorders from free-text, without sensible detriment in precision. When evaluating the accuracy of the mapping of disorders to SNOMED CT concepts in the UMLS, we observe that the mapping obtained by our ltered instance of Metamap delivers state-of-the-art e ectiveness if only spans individuated by our system are considered (`relaxed' accuracy).

The future of power in the network era

This article asks questions about the futures of power in the network era. Two critical emerging issues are at work with uncertain outcomes. The first is the emergence of the collaborative economy, while the second is the emergence of surveillance capabilities from both civic, state and commercial sources. While both of these emerging issues are expected by many to play an important role in the future development of our societies, it is still unclear whose values and whose purposes will be furthered. This article argues that the futures of these emerging issues depend on contests for power. As such, four scenarios are developed for the futures of power in the network era using the double variable scenario approach.

Two-stage power network reconfiguration strategy considering node importance and restored generation capacity

Network reconfiguration after complete blackout of a power system is an essential step for power system restoration. A new node importance evaluation method is presented based on the concept of regret, and maximisation of the average importance of a path is employed as the objective of finding the optimal restoration path. Then, a two-stage method is presented to optimise the network reconfiguration strategy. Specifically, the restoration sequence of generating units is first optimised so as to maximise the restored generation capacity, then the optimal restoration path is selected to restore the generating nodes concerned and the issues of selecting a serial or parallel restoration mode and the reconnecting failure of a transmission line are next considered. Both the restoration path selection and skeleton-network determination are implemented together in the proposed method, which overcomes the shortcoming of separate decision-making in the existing methods. Finally, the New England 10-unit 39-bus power system and the Guangzhou power system in South China are employed to demonstrate the basic features of the proposed method.

Travel time prediction on signalised urban arterials by applying SARIMA modelling on Bluetooth data

Travel time prediction has long been the topic of transportation research. But most relevant prediction models in the literature are limited to motorways. Travel time prediction on arterial networks is challenging due to involving traffic signals and significant variability of individual vehicle travel time. The limited availability of traffic data from arterial networks makes travel time prediction even more challenging. Recently, there has been significant interest of exploiting Bluetooth data for travel time estimation. This research analysed the real travel time data collected by the Brisbane City Council using the Bluetooth technology on arterials. Databases, including experienced average daily travel time are created and classified for approximately 8 months. Thereafter, based on data characteristics, Seasonal Auto Regressive Integrated Moving Average (SARIMA) modelling is applied on the database for short-term travel time prediction. The SARMIA model not only takes the previous continuous lags into account, but also uses the values from the same time of previous days for travel time prediction. This is carried out by defining a seasonality coefficient which improves the accuracy of travel time prediction in linear models. The accuracy, robustness and transferability of the model are evaluated through comparing the real and predicted values on three sites within Brisbane network. The results contain the detailed validation for different prediction horizons (5 min to 90 minutes). The model performance is evaluated mainly on congested periods and compared to the naive technique of considering the historical average.

An intuitive dashboard for Bayesian network inference

Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.