999 resultados para Large disturbance


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The Columbus problem has been rigorously solved by Lyapunov's direct approach to the continuous system in gencral cases of large disturbance and the theory has proved to be in strict consistency with Kelvin's experiments.

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Wind generation in highly interconnected power networks creates local and centralised stability issues based on their proximity to conventional synchronous generators and load centres. This paper examines the large disturbance stability issues (i.e. rotor angle and voltage stability) in power networks with geographically distributed wind resources in the context of a number of dispatch scenarios based on profiles of historical wind generation for a real power network. Stability issues have been analysed using novel stability indices developed from dynamic characteristics of wind generation. The results of this study show that localised stability issues worsen when significant penetration of both conventional and wind generation is present due to their non-complementary characteristics. In contrast, network stability improves when either high penetration of wind and synchronous generation is present in the network. Therefore, network regions can be clustered into two distinct stability groups (i.e. superior stability and inferior stability regions). Network stability improves when a voltage control strategy is implemented at wind farms, however both stability clusters remain unchanged irrespective of change in the control strategy. Moreover, this study has shown that the enhanced fault ride-through (FRT) strategy for wind farms can improve both voltage and rotor angle stability locally, but only a marginal improvement is evident in neighbouring regions.

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Modelling the power systems load is a challenge since the load level and composition varies with time. An accurate load model is important because there is a substantial component of load dynamics in the frequency range relevant to system stability. The composition of loads need to be charaterised because the time constants of composite loads affect the damping contributions of the loads to power system oscillations, and their effects vary with the time of the day, depending on the mix of motors loads. This chapter has two main objectives: 1) describe the load modelling in small signal using on-line measurements; and 2) present a new approach to develop models that reflect the load response to large disturbances. Small signal load characterisation based on on-line measurements allows predicting the composition of load with improved accuracy compared with post-mortem or classical load models. Rather than a generic dynamic model for small signal modelling of the load, an explicit induction motor is used so the performance for larger disturbances can be more reliably inferred. The relation between power and frequency/voltage can be explicitly formulated and the contribution of induction motors extracted. One of the main features of this work is the induction motor component can be associated to nominal powers or equivalent motors

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Autonomous guidance of agricultural vehiclesis vital as mechanized farming production becomes more prevalent. It is crucial that tractor-trailers are guided with accuracy in both lateral and longitudinal directions, whilst being affected by large disturbance forces, or slips, owing to uncertain and undulating terrain. Successful research has been concentrated on trajectory control which can provide longitudinal and lateral accuracy if the vehicle moves without sliding, and the trailer is passive. In this paper, the problem of robust trajectory tracking along straight and circular paths of a tractor-steerable trailer is addressed. By utilizing a robust combination of backstepping and nonlinear PI control, a robust, nonlinear controller is proposed. For vehicles subjected to sliding, the proposed controller makes the lateral deviations and the orientation errors of the tractor and trailer converge to a neighborhood near the origin. Simulation results are presented to illustrate that the suggested controller ensures precise trajectory tracking in the presence of slip.

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The well-known power system stabilizer (PSS) is used to generate supplementary control signals for the excitation system of a generator so as to damp low frequency oscillations in the power system concerned. Up to now, various kinds of PSS design methods have been proposed and some of them applied in actual power systems with different degrees. Given this background, the small-disturbance eigenvalue analysis and large-disturbance dynamic simulations in the time domain are carried out to evaluate the performances of four different PSS design methods, including the Conventional PSS (CPSS), Single-Neuron PSS (SNPSS), Adaptive PSS (APSS) and Multi-band PSS (MBPSS). To make the comparisons equitable, the parameters of the four kinds of PSSs are all determined by the steepest descent method. Finally, an 8-unit 24-bus power system is employed to demonstrate the performances of the four kinds of PSSs by the well-established eigenvalue analysis as well as numerous digital simulations, and some useful conclusions obtained.

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In this paper, mechanical properties of silica-filled epoxy resin are tested. The tests show that at elevated temperatures, the material’s properties (e.g. yield stress, flow stress, etc.) vary immonotonically with filler volume fraction. Nanoindentation test results suggest that an interface region, stronger than the matrix, is formed in the materials. The formation of the interface has positive effects on the yield strengths of materials. The addition of particles in the matrix produces a large disturbance in stress distribution, leading to stress concentration in the matrix. The stress concentration has negative effects on the yield strengths of materials. The calculation demonstrates that the maximum stress in samples varies immonotonically with particulate concentration. So, the immonotonic variation of mechanical behavior of materials may be rooted in the contradictory effects of the interface region and the stress concentration caused by particulate addition.

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Indices that report how much a contingency is stable or unstable in an electrical power system have been the object of several studies in the last decades. In some approaches, indices are obtained from time-domain simulation; others explore the calculation of the stability margin from the so-called direct methods, or even by neural networks.The goal is always to obtain a fast and reliable way of analysing large disturbance that might occur on the power systems. A fast classification in stable and unstable, as a function of transient stability is crucial for a dynamic security analysis. All good propositions as how to analyse contingencies must present some important features: classification of contingencies; precision and reliability; and efficiency computation. Indices obtained from time-domain simulations have been used to classify the contingencies as stable or unstable. These indices are based on the concepts of coherence, transient energy conversion between kinetic energy and potential energy, and three dot products of state variable. The classification of the contingencies using the indices individually is not reliable, since the performance of these indices varies with each simulated condition. However, collapsing these indices into a single one can improve the analysis significantly. In this paper, it is presented the results of an approach to filter the contingencies, by a simple classification of them into stable, unstable or marginal. This classification is performed from the composite indices obtained from step by step simulation with a time period of the clearing time plus 0.5 second. The contingencies originally classified as stable or unstable do not require this extra simulation. The methodology requires an initial effort to obtain the values of the intervals for classification, and the weights. This is performed once for each power system and can be used in different operating conditions and for different contingencies. No misplaced classification o- - ccurred in any of the tests, i.e., we detected no stable case classified as unstable or otherwise. The methodology is thus well fitted for it allows for a rapid conclusion about the stability of th system, for the majority of the contingencies (Stable or Unstable Cases). The tests, results and discussions are presented using two power systems: (1) the IEEE17 system, composed of 17 generators, 162 buses and 284 transmission lines; and (2) a South Brazilian system configuration, with 10 generators, 45 buses and 71 lines.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.

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This Study was conducted in Lake Dongtinghu, a large river-connected lake on the Yangtze River flood-plain, China. Our goal was to determine trophic relationships among benthic macroinvertebrates, as well as the effects of flood disturbance on the benthic food web of a river-connected lake. Macroinvertebrates in the lake fed mainly on detritus and plankton (both zooplankton and phytoplankton). Food web Structure in Lake Dongtinghu was characterized by molluscs as the dominant group, low connectance, high level of omnivory. based oil detritus and primary production, and most ingestion concentrating on a few links. Our analyses showed that flood disturbance is an important factor affecting the benthic food web in Lake Dongtinghu. The numbers of species and functional feeding groups (FFGs), and the density and biomass of macroinvertebrates decreased significantly during flooding. Connectance was higher during the flood season than in other seasons, indicating that floods have a strong effect on connectance in this Yangtze River-connected lake. Flood effects on the benthic web were also evident in the decrease of niche overlaps within and anion, FFGs. Our results provide useful information regarding biodiversity conservation on the Yangtze floodplain. Reconstructing and maintaining natural and regular flow regimes between Yangtze lakes and the river is essential for restoration of macroinvertebrates on the floodplain.

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Highlights •We exposed meiofauna to 7 different large macrofauna species at high and low densities. •Macrofauna presence altered nematode community structure and reduced their abundance. •Macrofauna species had similar effects by reducing the few dominant nematode species. •Meio–macrofauna resource competition and spatial segregation are the main drivers. •Trawling effects on macrofauna affect nematode communities indirectly. Diverse assemblages of infauna in sediments provide important physical and biogeochemical services, but are under increasing pressure by anthropogenic activities, such as benthic trawling. It is known that trawling disturbance has a substantial effect on the larger benthic fauna, with reductions in density and diversity, and changes in community structure, benthic biomass, production, and bioturbation and biogeochemical processes. Largely unknown, however, are the mechanisms by which the trawling impacts on the large benthic macro- and megafauna may influence the smaller meiofauna. To investigate this, a mesocosm experiment was conducted whereby benthic nematode communities from a non-trawled area were exposed to three different densities (absent, low, normal) of 7 large (> 10 mm) naturally co-occurring, bioturbating species which are potentially vulnerable to trawling disturbance. The results showed that total abundances of nematodes were lower if these large macrofauna species were present, but no clear nematode abundance effects could be assigned to the macrofauna density differences. Nematode community structure changed in response to macrofauna presence and density, mainly as a result of the reduced abundance of a few dominant nematode species. Any detectable effects seemed similar for nearly all macrofauna species treatments, supporting the idea that there may be a general indirect, macrofauna-mediated trawling impact on nematode communities. Explanations for these results may be, firstly, competition for food resources, resulting in spatial segregation of the meio- and macrobenthic components. Secondly, different densities of large macrofauna organisms may affect the nematode community structure through different intensities of bioturbatory disturbance or resource competition. These results suggest that removal or reduced densities of larger macrofauna species as a result of trawling disturbance may lead to increased nematode abundance and hints at the validity of interference competition between large macrofauna organisms and the smaller meiofauna, and the energy equivalence hypothesis, where a trade-off is observed between groups of organisms that are dependent on a common source of energy.

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A 272-ha grove of dominant Microberlinia bisulcata (Caesalpinioideae) adult trees greater than or equal to 50 cm stem diameter was mapped in its entirety in the southern part of Korup National Park, Cameroon. The approach used an earlier-established 82.5-ha permanent plot with a new surrounding 50-m grid of transect lines. Tree diameters were available from the plot but trees on the grid were recorded as being greater than or equal to 50 cm. The grove consisted of 1028 trees in 2000. Other species occurred within the grove. including the associated subdominants Tetraberlinia bifoliolata and T. korupensis. Microberlinia bisulcata becomes adult at a stein diameter of c. 50 cm and at an estimated age of 50 y. Three oval-shaped subgroves with dimensions c. 8 50 in x 13 50 in (90 ha) were defined. For two of them (within the plot) tree diameters were available. Subgroves differed in their scales and intensities of spatial tree patterns, and in their size frequency distributions, these suggesting differing past dynamics. The modal scale of clumping was 40-50 m. Seed dispersal by pod ejection (to c. 50 in) was evident from the semi-circles of trees at the grove's edge and from the many internal circles (100-200 m diameter). The grove has the capacity. therefore, to increase at c. 100 m per century. To form its present extent and structure. it is inferred that it expanded and infilled from a possibly smaller area of lower adult-tree density. This possibly happened in three waves of recruitment, each one determined by a period of several intense disturbances. Climate records for Africa show that 1740-50 and 1820-30 were periods of drought, and that 1870-1895 was also regionally very dry. Canopy openings allow the light-demanding and fast-growing ectomycorrhizal M. bisulcata to establish, but successive releases are thought to be required to achieve effective recruitment. Nevertheless, in the last 50 y there were no major events and recruitment in the grove was very poor. This present study leads to a new hypothesis of the role of periods of multiple extreme events being the driving factor for the population dynamics of many large African tree species such as M. bisulcata.

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Aims The relationship between biodiversity and ecosystem functioning is among the most active areas of ecological research. Furthermore, enhancing the diversity of degraded ecosystems is a major goal in applied restoration ecology. In grasslands, many species may be locally absent due to dispersal or microsite limitation and may therefore profit from mechanical disturbance of the resident vegetation. We established a seed addition and disturbance experiment across several grassland sites of different land use to test whether plant diversity can be increased in these grasslands. Additionally, the experiment will allow us testing the consequences of increased plant diversity for ecosystem processes and for the diversity of other taxa in real-world ecosystems. Here we present details of the experimental design and report results from the first vegetation survey one year after disturbance and seed addition. Moreover, we tested whether the effects of seed addition and disturbance varied among grassland depending on their land use or pre-disturbance plant diversity. Methods A full-factorial experiment was installed in 73 grasslands in three regions across Germany. Grasslands were under regular agricultural use, but varied in the type and the intensity of management, thereby representing the range of management typical for large parts of Central Europe. The disturbance treatment consisted of disturbing the top 10 cm of the sward using a rotavator or rotary harrow. Seed addition consisted of sowing a high-diversity seed mixture of regional plant species. These species were all regionally present, but often locally absent, depending on the resident vegetation composition and richness of each grassland. Important findings One year after sward disturbance it had significantly increased cover of bare soil, seedling species richness and numbers of seedlings. Seed addition had increased plant species richness, but only in combination with sward disturbance. The increase in species richness, when both seed addition and disturbance was applied, was higher at high land-use intensity and low resident diversity. Thus, we show that at least the early recruitment of many species is possible also at high land-use intensity, indicating the potential to restore and enhance biodiversity of species-poor agricultural grasslands. Our newly established experiment provides a unique platform for broad-scale research on the land-use dependence of future trajectories of vegetation diversity and composition and their effects on ecosystem functioning.

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World economies increasingly demand reliable and economical power supply and distribution. To achieve this aim the majority of power systems are becoming interconnected, with several power utilities supplying the one large network. One problem that occurs in a large interconnected power system is the regular occurrence of system disturbances which can result in the creation of intra-area oscillating modes. These modes can be regarded as the transient responses of the power system to excitation, which are generally characterised as decaying sinusoids. For a power system operating ideally these transient responses would ideally would have a “ring-down” time of 10-15 seconds. Sometimes equipment failures disturb the ideal operation of power systems and oscillating modes with ring-down times greater than 15 seconds arise. The larger settling times associated with such “poorly damped” modes cause substantial power flows between generation nodes, resulting in significant physical stresses on the power distribution system. If these modes are not just poorly damped but “negatively damped”, catastrophic failures of the system can occur. To ensure system stability and security of large power systems, the potentially dangerous oscillating modes generated from disturbances (such as equipment failure) must be quickly identified. The power utility must then apply appropriate damping control strategies. In power system monitoring there exist two facets of critical interest. The first is the estimation of modal parameters for a power system in normal, stable, operation. The second is the rapid detection of any substantial changes to this normal, stable operation (because of equipment breakdown for example). Most work to date has concentrated on the first of these two facets, i.e. on modal parameter estimation. Numerous modal parameter estimation techniques have been proposed and implemented, but all have limitations [1-13]. One of the key limitations of all existing parameter estimation methods is the fact that they require very long data records to provide accurate parameter estimates. This is a particularly significant problem after a sudden detrimental change in damping. One simply cannot afford to wait long enough to collect the large amounts of data required for existing parameter estimators. Motivated by this gap in the current body of knowledge and practice, the research reported in this thesis focuses heavily on rapid detection of changes (i.e. on the second facet mentioned above). This thesis reports on a number of new algorithms which can rapidly flag whether or not there has been a detrimental change to a stable operating system. It will be seen that the new algorithms enable sudden modal changes to be detected within quite short time frames (typically about 1 minute), using data from power systems in normal operation. The new methods reported in this thesis are summarised below. The Energy Based Detector (EBD): The rationale for this method is that the modal disturbance energy is greater for lightly damped modes than it is for heavily damped modes (because the latter decay more rapidly). Sudden changes in modal energy, then, imply sudden changes in modal damping. Because the method relies on data from power systems in normal operation, the modal disturbances are random. Accordingly, the disturbance energy is modelled as a random process (with the parameters of the model being determined from the power system under consideration). A threshold is then set based on the statistical model. The energy method is very simple to implement and is computationally efficient. It is, however, only able to determine whether or not a sudden modal deterioration has occurred; it cannot identify which mode has deteriorated. For this reason the method is particularly well suited to smaller interconnected power systems that involve only a single mode. Optimal Individual Mode Detector (OIMD): As discussed in the previous paragraph, the energy detector can only determine whether or not a change has occurred; it cannot flag which mode is responsible for the deterioration. The OIMD seeks to address this shortcoming. It uses optimal detection theory to test for sudden changes in individual modes. In practice, one can have an OIMD operating for all modes within a system, so that changes in any of the modes can be detected. Like the energy detector, the OIMD is based on a statistical model and a subsequently derived threshold test. The Kalman Innovation Detector (KID): This detector is an alternative to the OIMD. Unlike the OIMD, however, it does not explicitly monitor individual modes. Rather it relies on a key property of a Kalman filter, namely that the Kalman innovation (the difference between the estimated and observed outputs) is white as long as the Kalman filter model is valid. A Kalman filter model is set to represent a particular power system. If some event in the power system (such as equipment failure) causes a sudden change to the power system, the Kalman model will no longer be valid and the innovation will no longer be white. Furthermore, if there is a detrimental system change, the innovation spectrum will display strong peaks in the spectrum at frequency locations associated with changes. Hence the innovation spectrum can be monitored to both set-off an “alarm” when a change occurs and to identify which modal frequency has given rise to the change. The threshold for alarming is based on the simple Chi-Squared PDF for a normalised white noise spectrum [14, 15]. While the method can identify the mode which has deteriorated, it does not necessarily indicate whether there has been a frequency or damping change. The PPM discussed next can monitor frequency changes and so can provide some discrimination in this regard. The Polynomial Phase Method (PPM): In [16] the cubic phase (CP) function was introduced as a tool for revealing frequency related spectral changes. This thesis extends the cubic phase function to a generalised class of polynomial phase functions which can reveal frequency related spectral changes in power systems. A statistical analysis of the technique is performed. When applied to power system analysis, the PPM can provide knowledge of sudden shifts in frequency through both the new frequency estimate and the polynomial phase coefficient information. This knowledge can be then cross-referenced with other detection methods to provide improved detection benchmarks.

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Routing trains within passenger stations in major cities is a common scheduling problem for railway operation. Various studies have been undertaken to derive and formulate solutions to this route allocation problem (RAP) which is particularly evident in mainland China nowadays because of the growing traffic demand and limited station capacity. A reasonable solution must be selected from a set of available RAP solutions attained in the planning stage to facilitate station operation. The selection is however based on the experience of the operators only and objective evaluation of the solutions is rarely addressed. In order to maximise the utilisation of station capacity while maintaining service quality and allowing for service disturbance, quantitative evaluation of RAP solutions is highly desirable. In this study, quantitative evaluation of RAP solutions is proposed and it is enabled by a set of indices covering infrastructure utilisation, buffer times and delay propagation. The proposed evaluation is carried out on a number of RAP solutions at a real-life busy railway station in mainland China and the results highlight the effectiveness of the indices in pinpointing the strengths and weaknesses of the solutions. This study provides the necessary platform to improve the RAP solution in planning and to allow train re-routing upon service disturbances.

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This paper provides a new general approach for defining coherent generators in power systems based on the coherency in low frequency inter-area modes. The disturbance is considered to be distributed in the network by applying random load changes which is the random walk representation of real loads instead of a single fault and coherent generators are obtained by spectrum analysis of the generators velocity variations. In order to find the coherent areas and their borders in the inter-connected networks, non-generating buses are assigned to each group of coherent generator using similar coherency detection techniques. The method is evaluated on two test systems and coherent generators and areas are obtained for different operating points to provide a more accurate grouping approach which is valid across a range of realistic operating points of the system.