Studies in power hardware in the loop (PHIL) simulation using real-time digital simulator (RTDS)

In power hardware in the loop (PHIL) simulations, a real-time simulated power system is interfaced to a piece of hardware, usually called hardware under test (HuT). A PHIL test can be realized using several simulation tools. Among them Real Time Digital Simulator (RTDS) is an ideal tool to perform complex power system simulations in near real-time. Stable operation of the entire system, along with the accuracy of simulation results are the main concerns regarding a PHIL simulation. In this paper, a simulated power network on RTDS will be interfaced to HuT through a voltage source converter (VSC). Issues around stability and other interface problems are studied and a new method to stabilize some unstable PHIL cases is proposed. PHIL simulation results in PSCAD and RSCAD are presented.

Comparison of eight published static finite element models of the intact lumbar spine : predictive power of models improves when combined together

Finite element (FE) model studies have made important contributions to our understanding of functional biomechanics of the lumbar spine. However, if a model is used to answer clinical and biomechanical questions over a certain population, their inherently large inter-subject variability has to be considered. Current FE model studies, however, generally account only for a single distinct spinal geometry with one set of material properties. This raises questions concerning their predictive power, their range of results and on their agreement with in vitro and in vivo values. Eight well-established FE models of the lumbar spine (L1-5) of different research centres around the globe were subjected to pure and combined loading modes and compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges, and their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with published median in vitro values. However, the ranges of predictions were larger and exceeded those reported in vitro, especially for the facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with measured in vivo values. In light of high inter-subject variability, the generalization of results of a single model to a population remains a concern. This study demonstrated that the pooled median of individual model results, similar to a probabilistic approach, can be used as an improved predictive tool in order to estimate the response of the lumbar spine.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

The White Possessive : Property, Power and Indigenous Sovereignty

The White Possessive explores the links between race, sovereignty, and possession through themes of property: owning property, being property, and becoming propertyless. Focusing on the Australian Aboriginal context, Aileen Moreton-Robinson questions current race theory in the first world and its preoccupation with foregrounding slavery and migration. The nation, she argues, is socially and culturally constructed as a white possession. Moreton-Robinson reveals how the core values of Australian national identity continue to have roots in Britishness and colonization, built on the disavowal of Indigenous sovereignty. Whiteness studies are central to Moreton-Robinson’s reasoning, and she shows how blackness works as a white epistemological tool that bolsters the social production of whiteness—displacing Indigenous sovereignties and rendering them invisible in a civil rights discourse, sidestepping issues of settler colonialism. Throughout this critical examination Moreton-Robinson proposes a bold new agenda for critical Indigenous studies, one that involves deeper analysis of the prerogatives of white possession within the role of disciplines.

A flexible tool for integrated planning of active distribution networks

This paper presents a flexible and integrated planning tool for active distribution network to maximise the benefits of having high level s of renewables, customer engagement, and new technology implementations. The tool has two main processing parts: “optimisation” and “forecast”. The “optimization” part is an automated and integrated planning framework to optimize the net present value (NPV) of investment strategy for electric distribution network augmentation over large areas and long planning horizons (e.g. 5 to 20 years) based on a modified particle swarm optimization (MPSO). The “forecast” is a flexible agent-based framework to produce load duration curves (LDCs) of load forecasts for different levels of customer engagement, energy storage controls, and electric vehicles (EVs). In addition, “forecast” connects the existing databases of utility to the proposed tool as well as outputs the load profiles and network plan in Google Earth. This integrated tool enables different divisions within a utility to analyze their programs and options in a single platform using comprehensive information.