162 resultados para distribution system operator
Resumo:
This paper examines a number of issues in sustainable energy generation and distribution, and explores avenues that are available for integration of our society’s energy supplies. In particular, the paper presents a way in which transport vehicle energy supplies could be integrated with distributed generation schemes to achieve synergistic and beneficial outcomes. The worldwide energy system contains fundamental problems that result directly from the use of unsustainable fuels and a lack of energy system integration. There is a need to adopt an integrated, sustainable energy system for our society. The adoption of distributed generation could result in beneficial restructuring of the energy trade, and a change in the role of energy providers. Inherent benefits in distributed generation schemes would directly combat barriers to installation of renewable generation facilities, which might prove distributed renewable energy sources to be more feasible. The presence of fuel cells, batteries, power electronic inverters and intelligent controls in vehicles of the future provides many opportunities for the integration of vehicle energy supplies into a distributed generation scheme. In such a system, vehicles could play a major role in power generation and storage.
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The aims of this project is to develop demand side response model which assists electricity consumers who are exposed to the market price through aggregator to manage the air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimise the energy cost caused by the air-conditioning load considering the electricity market price and network overload. The model is tested with selected characteristics of the room, Queensland electricity market data from Australian Energy Market Operator and data from the Bureau of Statistics on temperatures in Brisbane, during weekdays on hot days from 2011 - 2012.
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Background Despite the emerging use of treadmills integrated with pressure platforms as outcome tools in both clinical and research settings, published evidence regarding the measurement properties of these new systems is limited. This study evaluated the within– and between–day repeatability of spatial, temporal and vertical ground reaction forces measured by a treadmill system instrumented with a capacitance–based pressure platform. Methods Thirty three healthy adults (mean age, 21.5 ± 2.8 years; height, 168.4 ± 9.9 cm; and mass, 67.8 ± 18.6 kg), walked barefoot on a treadmill system (FDM–THM–S, Zebris Medical GmbH) on three separate occasions. For each testing session, participants set their preferred pace but were blinded to treadmill speed. Spatial (foot rotation, step width, stride and step length), temporal (stride and step times, duration of stance, swing and single and double support) and peak vertical ground reaction force variables were collected over a 30–second capture period, equating to an average of 52 ± 5 steps of steady–state walking. Testing was repeated one week following the initial trial and again, for a third time, 20 minutes later. Repeated measures ANOVAs within a generalized linear modelling framework were used to assess between–session differences in gait parameters. Agreement between gait parameters measured within the same day (session 2 and 3) and between days (session 1 and 2; 1 and 3) were evaluated using the 95% repeatability coefficient. Results There were statistically significant differences in the majority (14/16) of temporal, spatial and kinetic gait parameters over the three test sessions (P < .01). The minimum change that could be detected with 95% confidence ranged between 3% and 17% for temporal parameters, 14% and 33% for spatial parameters, and 4% and 20% for kinetic parameters between days. Within–day repeatability was similar to that observed between days. Temporal and kinetic gait parameters were typically more consistent than spatial parameters. The 95% repeatability coefficient for vertical force peaks ranged between ± 53 and ± 63 N. Conclusions The limits of agreement in spatial parameters and ground reaction forces for the treadmill system encompass previously reported changes with neuromuscular pathology and footwear interventions. These findings provide clinicians and researchers with an indication of the repeatability and sensitivity of the Zebris treadmill system to detect changes in common spatiotemporal gait parameters and vertical ground reaction forces.
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Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.
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Integration of small-scale electricity generators, known as Distributed Generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of synchronous-type generator has potential to give the DG a better chance in participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of the DG as a voltage regulator, and at the same time minimizes interaction with other active devices, such as On-load Tap Changing Transformer (OLTC) and voltage regulator. The technique has been developed based on the concept of control zone, Line Drop Compensation (LDC), as well as the choice of controller's parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.
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Background Nontuberculous mycobacteria (NTM) are normal inhabitants of a variety of environmental reservoirs including natural and municipal water. The aim of this study was to document the variety of species of NTM in potable water in Brisbane, QLD, with a specific interest in the main pathogens responsible for disease in this region and to explore factors associated with the isolation of NTM. One-litre water samples were collected from 189 routine collection sites in summer and 195 sites in winter. Samples were split, with half decontaminated with CPC 0.005%, then concentrated by filtration and cultured on 7H11 plates in MGIT tubes (winter only). Results Mycobacteria were grown from 40.21% sites in Summer (76/189) and 82.05% sites in winter (160/195). The winter samples yielded the greatest number and variety of mycobacteria as there was a high degree of subculture overgrowth and contamination in summer. Of those samples that did yield mycobacteria in summer, the variety of species differed from those isolated in winter. The inclusion of liquid media increased the yield for some species of NTM. Species that have been documented to cause disease in humans residing in Brisbane that were also found in water include M. gordonae, M. kansasii, M. abscessus, M. chelonae, M. fortuitum complex, M. intracellulare, M. avium complex, M. flavescens, M. interjectum, M. lentiflavum, M. mucogenicum, M. simiae, M. szulgai, M. terrae. M. kansasii was frequently isolated, but M. avium and M. intracellulare (the main pathogens responsible for disease is QLD) were isolated infrequently. Distance of sampling site from treatment plant in summer was associated with isolation of NTM. Pathogenic NTM (defined as those known to cause disease in QLD) were more likely to be identified from sites with narrower diameter pipes, predominantly distribution sample points, and from sites with asbestos cement or modified PVC pipes. Conclusions NTM responsible for human disease can be found in large urban water distribution systems in Australia. Based on our findings, additional point chlorination, maintenance of more constant pressure gradients in the system, and the utilisation of particular pipe materials should be considered.
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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.
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Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.
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Electric Energy Storage (EES) is considered as one of the promising options for reducing the need for costly upgrades in distribution networks in Queensland (QLD). However, It is expected, the full potential for storage for distribution upgrade deferral cannot be fully realized due to high cost of EES. On the other hand, EES used for distribution deferral application can support a variety of complementary storage applications such as energy price arbitrage, time of use (TOU) energy cost reduction, wholesale electricity market ancillary services, and transmission upgrade deferral. Aggregation of benefits of these complementary storage applications would have the potential for increasing the amount of EES that may be financially attractive to defer distribution network augmentation in QLD. In this context, this paper analyzes distribution upgrade deferral, energy price arbitrage, TOU energy cost reduction, and integrated solar PV-storage benefits of EES devices in QLD.
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Energy auditing is an effective but costly approach for reducing the long-term energy consumption of buildings. When well-executed, energy loss can be quickly identified in the building structure and its subsystems. This then presents opportunities for improving energy efficiency. We present a low-cost, portable technology called "HeatWave" which allows non-experts to generate detailed 3D surface temperature models for energy auditing. This handheld 3D thermography system consists of two commercially available imaging sensors and a set of software algorithms which can be run on a laptop. The 3D model can be visualized in real-time by the operator so that they can monitor their degree of coverage as the sensors are used to capture data. In addition, results can be analyzed offline using the proposed "Spectra" multispectral visualization toolbox. The presence of surface temperature data in the generated 3D model enables the operator to easily identify and measure thermal irregularities such as thermal bridges, insulation leaks, moisture build-up and HVAC faults. Moreover, 3D models generated from subsequent audits of the same environment can be automatically compared to detect temporal changes in conditions and energy use over time.
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Hand, Foot and Mouth Disease (HFMD) is a self-limiting viral disease that mainly affects infants and children. In contrast with other HFMD causing enteroviruses, Enterovirus71 (EV71) has commonly been associated with severe clinical manifestation leading to death. Currently, due to a lack in understanding of EV71 pathogenesis, there is no antiviral therapeutics for the treatment of HFMD patients. Therefore the need to better understand the mechanism of EV71 pathogenesis is warranted. We have previously reported a human colorectal adenocarcinoma cell line (HT29) based model to study the pathogenesis of EV71. Using this system, we showed that knockdown of DGCR8, an essential cofactor for microRNAs biogenesis resulted in a reduction of EV71 replication. We also demonstrated that there are miRNAs changes during EV71 pathogenesis and EV71 utilise host miRNAs to attenuate antiviral pathways during infection. Together, data from this study provide critical information on the role of miRNAs during EV71 infection.
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In order to dynamically reduce voltage unbalance along a low voltage distribution feeder, a smart residential load transfer system is discussed. In this scheme, residential loads can be transferred from one phase to another to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch and a controller. The master controller, installed at the transformer, observes the power consumption in each house and will determine which house(s) should be transferred from an initially connected phase to another in order to keep the voltage unbalance minimum. The performance of the smart load transfer scheme is demonstrated by simulations.
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A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.
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To minimise the number of load sheddings in a microgrid (MG) during autonomous operation, islanded neighbour MGs can be interconnected if they are on a self-healing network and an extra generation capacity is available in the distributed energy resources (DER) of one of the MGs. In this way, the total load in the system of interconnected MGs can be shared by all the DERs within those MGs. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and MG levels. In this study, first, a hierarchical control structure is discussed for interconnecting the neighbour autonomous MGs where the introduced primary control level is the main focus of this study. Through the developed primary control level, this study demonstrates how the parallel DERs in the system of multiple interconnected autonomous MGs can properly share the load of the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralised power sharing algorithm based on droop control. DER converters are controlled based on a per-phase technique instead of a conventional direct-quadratic transformation technique. In addition, linear quadratic regulator-based state feedback controllers, which are more stable than conventional proportional integrator controllers, are utilised to prevent instability and weak dynamic performances of the DERs when autonomous MGs are interconnected. The efficacy of the primary control level of the DERs in the system of multiple interconnected autonomous MGs is validated through the PSCAD/EMTDC simulations considering detailed dynamic models of DERs and converters.
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This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).