947 resultados para Distribution generation
Resumo:
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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This paper presents an efficient algorithm for multi-objective distribution feeder reconfiguration based on Modified Honey Bee Mating Optimization (MHBMO) approach. The main objective of the Distribution feeder reconfiguration (DFR) is to minimize the real power loss, deviation of the nodes’ voltage. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective. So the metahuristic algorithm has been applied to this problem. This paper describes the full algorithm to Objective functions paid, The results of simulations on a 32 bus distribution system is given and shown high accuracy and optimize the proposed algorithm in power loss minimization.
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This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection 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. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate 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), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.
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This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.
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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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This thesis is the first comprehensive study of important parameters relating to aerosols' impact on climate and human health, namely spatial variation, particle size distribution and new particle formation. We determined the importance of spatial variation of particle number concentration in microscale environments, developed a method for particle size parameterisation and provided knowledge about the chemistry of new particle formation. This is a significant contribution to our understanding of processes behind the transformation and dynamics of urban aerosols. This PhD project included extensive measurements of air quality parameters using state of the art instrumentation at each of the 25 sites within the Brisbane metropolitan area and advanced statistical analysis.
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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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Synthetic hydrogels selectively decorated with cell adhesion motifs are rapidly emerging as promising substrates for 3D cell culture. When cells are grown in 3D they experience potentially more physiologically relevant cell-cell interactions and physical cues compared with traditional 2D cell culture on stiff surfaces. A newly developed polymer based on poly(2-oxazoline)s has been used for the first time to control attachment of fibroblast cells and is discussed here for its potential use in 3D cell culture with particular focus on cancer cells towards the ultimate aim of high throughput screening of anti-cancer therapies. Advantages and limitations of using poly(2-oxazoline) hydrogels are discussed and compared with more established polymers, especially polyethylene glycol (PEG).
Resumo:
In 1999 the global recorded music industry had experienced a period of growth that had lasted for almost a quarter of a century. Approximately one billion records were sold worldwide in 1974, and by the end of the century, the number of records sold was more than three times as high. At the end of the nineties, spirits among record label executives were high and few music industry executives at this time expected that a team of teenage Internet hackers, led by Shawn Fanning (at the time a student at Northeastern University in Boston) would ignite the turbulent process that eventually would undermine the foundations of the industry.
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Installation of domestic rooftop photovoltaic cells (PVs) is increasing due to feed–in tariff and motivation driven by environmental concerns. Even though the increase in the PV installation is gradual, their locations and ratings are often random. Therefore, such single–phase bi–directional power flow caused by the residential customers can have adverse effect on the voltage imbalance of a three–phase distribution network. In this chapter, a voltage imbalance sensitivity analysis and stochastic evaluation are carried out based on the ratings and locations of single–phase grid–connected rooftop PVs in a residential low voltage distribution network. The stochastic evaluation, based on Monte Carlo method, predicts a failure index of non–standard voltage imbalance in the network in presence of PVs. Later, the application of series and parallel custom power devices are investigated to improve voltage imbalance problem in these feeders. In this regard, first, the effectiveness of these two custom power devices is demonstrated vis–à–vis the voltage imbalance reduction in feeders containing rooftop PVs. Their effectiveness is investigated from the installation location and rating points of view. Later, a Monte Carlo based stochastic analysis is utilized to investigate their efficacy for different uncertainties of load and PV rating and location in the network. This is followed by demonstrating the dynamic feasibility and stability issues of applying these devices in the network.
Resumo:
Natural distributions of most freshwater taxa are restricted geographically, a pattern that reflects dispersal limitation. Macrobrachium rosenbergii is unusual because it occurs naturally in rivers from near Pakistan in the west, across India and Bangladesh to the Malay Peninsula, and across the Sunda Shelf and Indonesian archipelago to western Java. Individuals cannot tolerate full marine conditions, so dispersal between river drainage basins must occur at limited geographical scales when ecological or climatic factors are favorable. We examined molecular diversity in wild populations of M. rosenbergii across its complete natural range to document patterns of diversity and to relate them to factors that have driven evolution of diversity in this species. We found 3 clades in the mitochondrial deoxyribonucleic acid (mtDNA) data set that corresponded geographically with eastern, central, and western sets of haplotypes that last shared a common ancestor 1 × 106 y ago. The eastern clade was closest to the common ancestor of all 3 clades and to the common ancestor with its congener, Macrobrachium spinipes, distributed east of Huxley's Line. Macrobrachium rosenbergii could have evolved in the western Indonesian archipelago and spread westward during the early to mid-Pleistocene to India and Sri Lanka. Additional groups identified in the nuclear DNA data set in the central and western clades probably indicate secondary contact via dispersal between regions and modern introductions that have mixed nuclear and mtDNA genes. Pleistocene sea-level fluctuations can explain dispersal across the Indonesian archipelago and parts of mainland southeastern Asia via changing river drainage connections in shallow seas on wide continental shelves. At the western end of the modern distribution where continental shelves are smaller, intermittent freshwater plumes from large rivers probably permitted larval dispersal across inshore areas of lowered salinity.
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Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.
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Platelet-derived microparticles (PMPs) which are produced during platelet activation contribute to coagulation1 and bind to traumatized endothelium in an animal model2. Such endothelial injury occurs during percutaneous transluminal coronary angioplasty (PTCA), a procedure which restores the diameter of occluded coronary arteries using balloon inflations. However, re-occlusions subsequently develop in 20-25% of patients3, although this is limited by treatment with anti-platelet glycoprotein IIb/IIIa receptor drugs such as abciximab4. However, abciximab only partially decreases the need for revascularisation5, and therefore other mechanisms appear to be involved. As platelet activation occurs during PTCA, it is likely that PMPs may be produced and contribute to restenosis. This study population consisted of 113 PTCA patients, of whom 38 received abciximab. Paired peripheral arterial blood samples were obtained from the PTCA sheath: 1) following heparinisation (baseline); and 2) subsequent to all vessel manipulation (post-PTCA). Blood was prepared with an anti-CD61 (glycoprotein IIIa) fluorescence conjugated antibody to identify PMPs using flow cytometry, and PMP results expressed as a percentage of all CD61 events. The level of PMPs increased significantly from baseline following PTCA in the without abciximab group (paired t test, P=0.019). However, there was no significant change in the level of PMPs following PTCA in patients who received abciximab. Baseline clinical characteristics between patient groups were similar, although patients administered abciximab had more complex PTCA procedures, such as increased balloon inflation pressures (ANOVA, P=0.0219). In this study, we have clearly demonstrated that the level of CD61-positive PMPs increased during PTCA. This trend has been demonstrated previously, although a low sample size prevented statistical significance being attained6. The results of our work also demonstrate that there was no increase in PMPs after PTCA with abiciximab treatment. The increased PMPs may adhere to traumatized endothelium, contributing to re-occlusion of the arteries, but this remains to be determined. References: (1) Holme PA, Brosstad F, Solum NO. Blood Coagulation and Fibrinolysis. 1995;6:302-310. (2) Merten M, Pakala R, Thiagarajan P, Benedict CR. Circulation. 1999;99:2577-2582. (3) Califf RM. American Heart Journal.1995;130:680-684. (4) Coller BS, Scudder LE. Blood. 1985;66:1456-1459. (5) Topol EJ, Califf RM, Weisman HF, Ellis SG, Tcheng JE, Worley S, Ivanhoe R, George BS, Fintel D, Weston M, Sigmon K, Anderson KM, Lee KL, Willerson JT on behalf of the EPIC investigators. Lancet. 1994;343:881-886. (6) Scharf RE, Tomer A, Marzec UM, Teirstein PS, Ruggeri ZM, Harker LA. Arteriosclerosis and Thrombosis. 1992;12:1475-87.
Resumo:
Sediment samples from 13 sampling sites in Deception Bay, Australia were analysed for the presence of heavy metals. Enrichment factors, modified contamination indices and Nemerow pollution indices were calculated for each sampling site to determine sediment quality. The results indicate significant pollution of most sites by lead (average enrichment factor (EF) of 13), but there is also enrichment of arsenic (average EF 2.3), zinc (average EF 2.7) and other heavy metals. The modified degree of contamination indices (average 1.0) suggests that there is little contamination. By contrast, the Nemerow pollution index (average 5.8) suggests that Deception Bay is heavily contaminated. Cluster analysis was undertaken to identify groups of elements. Strong correlation between some elements and two distinct clusters of sampling sites based on sediment type was evident. These results have implications for pollution in complex marine environments where there is significant influx of sand and sediment into an estuarine environment.