314 resultados para distribution system planning


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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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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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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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The experiences of the loss reduction projects in electric power distribution companies (EPDCs) of Iran are presented. The loss reduction methods, which are proposed individually by 14 EPDCs, corresponding energy saving (ES), Investment costs (IC), and loss rate reductions are provided. In order to illustrate the effectiveness and performance of the loss reduction methods, three parameters are proposed as energy saving per investment costs (ESIC), energy saving per quantity (ESPQ), and investment costs per quantity (ICPQ). The overall ESIC of 14 EPDC as well as individual average and standard deviation of the EISC for each method is presented and compared. In addition, the average and standard deviation of the ESPQs and ICPQs for the loss reduction methods, individually, are provided and investigated. These parameters are useful for EPDCs that intend to reduce the electric losses in distribution networks as a benchmark and as a background in the planning purposes.

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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).

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This paper presents a new method to determine feeder reconfiguration scheme considering variable load profile. The objective function consists of system losses, reliability costs and also switching costs. In order to achieve an optimal solution the proposed method compares these costs dynamically and determines when and how it is reasonable to have a switching operation. The proposed method divides a year into several equal time periods, then using particle swarm optimization (PSO), optimal candidate configurations for each period are obtained. System losses and customer interruption cost of each configuration during each period is also calculated. Then, considering switching cost from a configuration to another one, dynamic programming algorithm (DPA) is used to determine the annual reconfiguration scheme. Several test systems were used to validate the proposed method. The obtained results denote that to have an optimum solution it is necessary to compare operation costs dynamically.

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Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.

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Large penetration of rooftop PVs has resulted in unacceptable voltage profile in many residential distribution feeders. Limiting real power injection from PVs to alleviate over voltage problem is not feasible due to loss of green power and hence corresponding revenue loss. Reactive capability of the PV inverter can be a solution to address over voltage and voltage dip problems to some extent. This paper proposes an algorithm to utilize reactive capability of PV inverters and investigate their effectiveness for voltage improvement based on R/X ratio of the feeder. The length and loading level of the feeder for a particular R/X ratio to have acceptable voltage profile is also investigated. This can be useful for suburban design and residential distribution planning. Furthermore, coordination among different PVs using residential smart meters via a substation based controller is also proposed.

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Introduction This study examines and compares the dosimetric quality of radiotherapy treatment plans for prostate carcinoma across a cohort of 163 patients treated across 5 centres: 83 treated with three-dimensional conformal radiotherapy (3DCRT), 33 treated with intensity-modulated radiotherapy (IMRT) and 47 treated with volumetric-modulated arc therapy (VMAT). Methods Treatment plan quality was evaluated in terms of target dose homogeneity and organ-at-risk sparing, through the use of a set of dose metrics. These included the mean, maximum and minimum doses; the homogeneity and conformity indices for the target volumes; and a selection of dose coverage values that were relevant to each organ-at-risk. Statistical significance was evaluated using two-tailed Welch’s T-tests. The Monte Carlo DICOM ToolKit software was adapted to permit the evaluation of dose metrics from DICOM data exported from a commercial radiotherapy treatment planning system. Results The 3DCRT treatment plans offered greater planning target volume dose homogeneity than the other two treatment modalities. The IMRT and VMAT plans offered greater dose reduction in the organs-at-risk: with increased compliance with recommended organ-at-risk dose constraints, compared to conventional 3DCRT treatments. When compared to each other, IMRT and VMAT did not provide significantly different treatment plan quality for like-sized tumour volumes. Conclusions This study indicates that IMRT and VMAT have provided similar dosimetric quality, which is superior to the dosimetric quality achieved with 3DCRT.

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Tumour necrosis factor (TNF)alpha is implicated in the relationship between obesity and insulin resistance/ type 2 diabetes. In an effort to understand this association better we (i) profiled gene expression patterns of TNF, TNFR1 and TNFR2 and (ii) investigated the effects of TNF on glucose uptake in isolated adipocytes and adipose tissue explants from omental and subcutaneous depots from lean, overweight and obese individuals. TNF expression correlated with expression of TNFR2, but not TNFR1, and TNF and TNFR2 expression increased in obesity. TNFR1 expression was higher in omental than in subcutaneous adipocytes. Expression levels of TNF or either receptor did not differ between adipocytes from individuals with central and peripheral obesity. TNF only suppressed glucose uptake in insulin-stimulated subcutaneous tissue and this suppression was only observed in tissue from lean subjects. These data support a relationship between the TNF system and body mass index (BMI), but not fat distribution, and suggest depot specificity of the TNF effect on glucose uptake. Furthermore, adipose tissue from obese subjects already appears insulin 'resistant' and this may be a result of the increased TNF levels.

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Several analytical methods for Dynamic System Optimum (DSO) assignment have been proposed but they are basically classified into two kinds. This chapter attempts to establish DSO by equilbrating the path dynamic marginal time (DMT). The authors analyze the path DMT for a single path with tandem bottlenecks and showed that the path DMT is not the simple summation of DMT associated with each bottleneck along the path. Next, the authors examined the DMT of several paths passing through a common bottleneck. It is shown that the externality at the bottleneck is shared by the paths in proportion to their demand from the current time until the queue vanishes. This share of the externality is caused by the departure rate shift under first in first out (FIFO) and the externality propagates to the downstream bottlenecks. However, the externalities propagates to the downstream are calculated out if downstream bottlenecks exist. Therefore, the authors concluded that the path DMT can be evaluated without considering the propagation of the externalities, but just as in the evaluation of the path DMT for a single path passing through a series of bottlenecks between the origin and destination. Based on the DMT analysis, the authors finally proposed a heuristic solution algorithm and verified it by comparing the numerical solution with the analytical one.