Power sharing and stability enhancement of an autonomous microgrid with inertial and non-inertial DGs with DSTATCOM

This paper proposes a method of enhancing system stability with a distribution static compensator (DSTATCOM) in an autonomous microgrid with multiple distributed generators (DG). It is assumed that there are both inertial and non-inertial DGs connected to the microgrid. The inertial DG can be a synchronous machine of smaller rating while inertia less DGs (solar) are assumed as DC sources. The inertia less DGs are connected through Voltage Source Converter (VSC) to the microgrid. The VSCs are controlled by either state feedback or current feedback mode to achieve desired voltage-current or power outputs respectively. The power sharing among the DGs is achieved by drooping voltage angle. Once the reference for the output voltage magnitude and angle is calculated from the droop, state feedback controllers are used to track the reference. The angle reference for the synchronous machine is compared with the output voltage angle of the machine and the error is fed to a PI controller. The controller output is used to set the power reference of the synchronous machine. The rate of change in the angle in a synchronous machine is restricted by the machine inertia and to mimic this nature, the rate of change in the VSCs angles are restricted by a derivative feedback in the droop control. The connected distribution static compensator (DSTATCOM) provides ride through capability during power imbalance in the microgrid, especially when the stored energy of the inertial DG is not sufficient to maintain stability. The inclusion of the DSATCOM in such cases ensures the system stability. The efficacies of the controllers are established through extensive simulation studies using PSCAD.

Directing for the 360 degree frame : developing a directorial approach to performance capture

What happens when the traditional framing mechanisms of our performance environments are removed and we are forced as directors to work with actors in digital environments that capture performance in 360 degrees? As directors contend with the challenges of interactive performance, the emergence of the online audience and the powerful influence of the games industry, how can we approach the challenges of directing work that is performance captured and presented in real time using motion capture and associated 3D imaging software? The 360 degree real time capture of performance, while allowing for an unlimited amount of framing potential, demands a unique and uncompromisingly disciplined style of direction and performance that has thus far remained unstudied and unquantified. By a close analysis of the groundbreaking work of artists like Robert Zemeckis and the Wetta Digital studio it is possible to begin to quantify what the technical requirements and challenges of 360 degree direction might be, but little has been discovered about the challenges of communicating the unlimited potential of framing and focus to the actors who work with these directors within these systems. It cannot be argued that the potential of theatrical space has evolved beyond the physical and moved into a more accessible virtual and digitised form, so how then can we direct for this unlimited potential and where do we place the focus of our directed (and captured) performance?

The logics of good teaching in an audit culture: A Deleuzian analysis

This article examines the attempted reform of education within an emerging audit culture in Australia that has led to the implementation of a high-stakes testing regime known as NAPLAN. NAPLAN represents a machine of auditing, which creates and accounts for data that are used to measure, amongst other things, good teaching. In particular, we address the logics of a policy intervention that aims to improve the quality of education through returning ‘good teaching’. Using Deleuze’s concepts of series, events, copies and simulacra, we suggest that an attempt to return past commonsense logics of ‘good teaching’ as a result of NAPLAN is not possible. In an audit culture as exemplified by NAPLAN, ‘good teaching’ is being reconceptualized through those practices and becomes unrecognizable. Whilst policy claims to improved equity and quality are admirable, this article suggests that the simulacral change to logics of good teaching may actualize something very different.

Direct electrochemical formation of nanostructured amorphous Co(OH)2 on gold electrodes with enhanced activity for the oxygen evolution reaction.

The oxides of cobalt have recently been shown to be highly effective electrocatalysts for the oxygen evolution reaction (OER) under alkaline conditions. In general species such as Co3O4 and CoOOH have been investigated that often require an elevated temperature step during their synthesis to create crystalline materials. In this work we investigate the rapid and direct electrochemical formation of amorphous nanostructured Co(OH)2 on gold electrodes under room temperture conditions which is a highly active precursor for the OER. During the OER some conversion to crystalline Co3O4 occurs at the surface, but the bulk of the material remains amorphous. It is found that the underlying gold electrode is crucial to the materials enhanced performance and provides higher current density than can be achieved using carbon, palladium or copper support electrodes. This catalyst exhibits excellent activity with a current density of 10 mA cm-2 at an overpotential of 360 mV with a high turnover frequency of 2.1 s-1 in 1 M NaOH. A Tafel slope of 56 mV dec-1 at low overpotentials and a slope of 122 mV dec-1 at high overpotentials is consistent with the dual barrier model for the electrocatalytic evolution of oxygen. Significantly, the catalyst maintains excellent activity for up to 24 hr of continuous operation and this approach offers a facile way to create a highly effective and stable material.

The Australian naturalistic driving study: From beginnings to launch

The Australian Naturalistic Driving Study (ANDS), a ground-breaking study of Australian driver behaviour and performance, was officially launched on April 21st, 2015 at UNSW. The ANDS project will provide a realistic perspective on the causes of vehicle crashes and near miss crash events, along with the roles speeding, distraction and other factors have on such events. A total of 360 volunteer drivers across NSW and Victoria - 180 in NSW and 180 in Victoria - will be monitored by a Data Acquisition System (DAS) recording continuously for 4 months their driving behaviour using a suite of cameras and sensors. Participants’ driving behaviour (e.g. gaze), the behaviour of their vehicle (e.g. speed, lane position) and the behaviour of other road users with whom they interact in normal and safety-critical situations will be recorded. Planning of the ANDS commenced over two years ago in June 2013 when the Multi-Institutional Agreement for a grant supporting the equipment purchase and assembly phase was signed by parties involved in this large scale $4 million study (5 university accident research centres, 3 government regulators, 2 third party insurers and 2 industry partners). The program’s second development phase commenced a year later in June 2014 after a second grant was awarded. This paper presents an insider's view into that two year process leading up to the launch, and outlines issues that arose in the set-up phase of the study and how these were addressed. This information will be useful to other organisations considering setting up an NDS.

Towards continuous surveillance of fruit flies using sensor networks and machine vision

In Australia, the Queensland fruit fly (B. tryoni), is the most destructive insect pest of horticulture, attacking nearly all fruit and vegetable crops. This project has researched and prototyped a system for monitoring fruit flies so that authorities can be alerted when a fly enters a crop in a more efficient manner than is currently used. This paper presents the idea of our sensor platform design as well as the fruit fly detection and recognition algorithm by using machine vision techniques. Our experiments showed that the designed trap and sensor platform is capable to capture quality fly images, the invasive flies can be successfully detected and the average precision of the Queensland fruit fly recognition is 80% from our experiment.

Assessing the energy efficiency of gear oils via the FZG test machine

Energy efficient lubricants are becoming increasingly popular. This is due to a global increase in environmental awareness combined with the potential of reducing operating costs. A new test method of evaluating the energy efficiency of gear oils has been described in this report. The method involves measuring the power required by an FZG test rig to run while using a particular test lubricant. For each oil that was being evaluated, the rig was run for 10 minutes at a load stage of 10. Six extreme pressure (EP) industrial gear oils of mineral base were tested. The difference in power requirements between the best and the worst performing oils was 2.77 and 3.24 kW, respectively. This equates to a 14.6% reduction in power, a significant amount if considered in relation to a high powered industrial machine. The oils of superior performance were noticed to run at reduced temperatures. They were also more expensive than the other products of lesser performance.

Condition-based prognosis of machine health

Modern machines are complex and often required to operate long hours to achieve production targets. The ability to detect symptoms of failure, hence, forecasting the remaining useful life of the machine is vital to prevent catastrophic failures. This is essential to reducing maintenance cost, operation downtime and safety hazard. Recent advances in condition monitoring technologies have given rise to a number of prognosis models that attempt to forecast machinery health based on either condition data or reliability data. In practice, failure condition trending data are seldom kept by industries and data that ended with a suspension are sometimes treated as failure data. This paper presents a novel approach of incorporating historical failure data and suspended condition trending data in the prognostic model. The proposed model consists of a FFNN whose training targets are asset survival probabilities estimated using a variation of Kaplan-Meier estimator and degradation-based failure PDF estimator. The output survival probabilities collectively form an estimated survival curve. The viability of the model was tested using a set of industry vibration data.

Automated control of a dragline using machine vision

The research described in this paper is directed toward increasing productivity of draglines through automation. In particular, it focuses on the swing-to-dump, dump, and return-to-dig phases of the dragline operational cycle by developing a swing automation system. In typical operation the dragline boom can be in motion for up to 80% of the total cycle time. This provides considerable scope for improving cycle time through automated or partially automated boom motion control. This paper describes machine vision based sensor technology and control algorithms under development to solve the problem of continuous real time bucket location and control. Incorporation of this capability into existing dragline control systems will then enable true automation of dragline swing and dump operations.