959 resultados para simulation tools
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With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.
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Isothermal-isobaric ensemble Monte Carlo simulation studies of adamantane have been carried out at different temperatures. Thermodynamic properties and radial distribution functions calculated by employing a simple potential model based on sitesite interactions show good agreement with experiment and suggest that the solid is orientationally disordered at high temperatures.
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A numerical scheme is presented for accurate simulation of fluid flow using the lattice Boltzmann equation (LBE) on unstructured mesh. A finite volume approach is adopted to discretize the LBE on a cell-centered, arbitrary shaped, triangular tessellation. The formulation includes a formal, second order discretization using a Total Variation Diminishing (TVD) scheme for the terms representing advection of the distribution function in physical space, due to microscopic particle motion. The advantage of the LBE approach is exploited by implementing the scheme in a new computer code to run on a parallel computing system. Performance of the new formulation is systematically investigated by simulating four benchmark flows of increasing complexity, namely (1) flow in a plane channel, (2) unsteady Couette flow, (3) flow caused by a moving lid over a 2D square cavity and (4) flow over a circular cylinder. For each of these flows, the present scheme is validated with the results from Navier-Stokes computations as well as lattice Boltzmann simulations on regular mesh. It is shown that the scheme is robust and accurate for the different test problems studied.
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Spotted gum dominant forests occur from Cooktown in northern Queensland (Qld) to Orbost in Victoria (Boland et al. 2006) and these forests are commercially very important with spotted gum the most commonly harvested hardwood timber in Qld and one of the most important in New South Wales (NSW). Spotted gum has a wide range of end uses from solid wood products through to power transmission poles and generally has excellent sawing and timber qualities (Hopewell 2004). The private native forest resource in southern Qld and northern NSW is a critical component of the hardwood timber industry (Anon 2005, Timber Qld 2006) and currently half or more of the native forest timber resource harvested in northern NSW and Qld is sourced from private land. However, in many cases productivity on private lands is well below what could be achieved with appropriate silvicultural management. This project provides silvicultural management tools to assist extension staff, land owners and managers in the south east Qld and north eastern NSW regions. The intent was that this would lead to improvement of the productivity of the private estate through implementation of appropriate management. The other intention of this project was to implement a number of silvicultural experiments and demonstration sites to provide data on growth rates of managed and unmanaged forests so that landholders can make informed decisions on the future management of their forests. To assist forest managers and improve the ability to predict forest productivity in the private resource, the project has developed: • A set of spotted gum specific silvicultural guidelines for timber production on private land that cover both silvicultural treatment and harvesting. The guidelines were developed for extension officers and property owners. • A simple decision support tool, referred to as the spotted gum productivity assessment tool (SPAT), that allows an estimation of: 1. Tree growth productivity on specific sites. Estimation is based on the analysis of site and growth data collected from a large number of yield and experimental plots on Crown land across a wide range of spotted gum forest types. Growth algorithms were developed using tree growth and site data and the algorithms were used to formulate basic economic predictors. 2. Pasture development under a range of tree stockings and the expected livestock carrying capacity at nominated tree stockings for a particular area. 3. Above-ground tree biomass and carbon stored in trees. •A series of experiments in spotted gum forests on private lands across the study area to quantify growth and to provide measures of the effect of silvicultural thinning and different agro-forestry regimes. The adoption and use of these tools by farm forestry extension officers and private land holders in both field operations and in training exercises will, over time, improve the commercial management of spotted gum forests for both timber and grazing. Future measurement of the experimental sites at ages five, 10 and 15 years will provide longer term data on the effects of various stocking rates and thinning regimes and facilitate modification and improvement of these silvicultural prescriptions.
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Models are abstractions of reality that have predetermined limits (often not consciously thought through) on what problem domains the models can be used to explore. These limits are determined by the range of observed data used to construct and validate the model. However, it is important to remember that operating the model beyond these limits, one of the reasons for building the model in the first place, potentially brings unwanted behaviour and thus reduces the usefulness of the model. Our experience with the Agricultural Production Systems Simulator (APSIM), a farming systems model, has led us to adapt techniques from the disciplines of modelling and software development to create a model development process. This process is simple, easy to follow, and brings a much higher level of stability to the development effort, which then delivers a much more useful model. A major part of the process relies on having a range of detailed model tests (unit, simulation, sensibility, validation) that exercise a model at various levels (sub-model, model and simulation). To underline the usefulness of testing, we examine several case studies where simulated output can be compared with simple relationships. For example, output is compared with crop water use efficiency relationships gleaned from the literature to check that the model reproduces the expected function. Similarly, another case study attempts to reproduce generalised hydrological relationships found in the literature. This paper then describes a simple model development process (using version control, automated testing and differencing tools), that will enhance the reliability and usefulness of a model.
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Polytypes have been simulated, treating them as analogues of a one-dimensional spin-half Ising chain with competing short-range and infinite-range interactions. Short-range interactions are treated as random variables to approximate conditions of growth from melt as well as from vapour. Besides ordered polytypes up to 12R, short stretches of long-period polytypes (up to 33R) have been observed. Such long-period sequences could be of significance in the context of Frank's theory of polytypism. The form of short-range interactions employed in the study has been justified by carrying out model potential calculations.
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FRDC has commissioned a review of the role that existing and future genetic technologies may play in addressing critical challenges facing the exploitation of wild fisheries. Wild fisheries management has been assisted by genetic research for over 50 years and in Australia, this research has been largely funded by FRDC. Both fisheries management and the methods of genetic analysis have changed significantly during this time. Given these dynamics, as well as perceptions that communication between fisheries managers and geneticists has been poor in some cases, there is a strong need to reassess the ways in which genetic research can contribute to fisheries and for all stakeholders to critically examine each other's needs and capabilities.
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Abstract is not available.
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Handwritten description on verso addressed to Herr u. Frau Ernst Weill
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The results are presented of applying multi-time scale analysis using the singular perturbation technique for long time simulation of power system problems. A linear system represented in state-space form can be decoupled into slow and fast subsystems. These subsystems can be simulated with different time steps and then recombined to obtain the system response. Simulation results with a two-time scale analysis of a power system show a large saving in computational costs.
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This paper examines the idea that plasticity in farm management introduces resilience to change and allows farm businesses to perform when operating in highly variable environments. We also argue for the need to develop and apply more integrative assessments of farm performance that combine the use of modelling tools with deliberative processes involving farmers and researchers in a co-learning process, to more effectively identify and implement more productive and resilient farm businesses. In a plastic farming system, farm management is highly contingent on environmental conditions. In plastic farming systems farm managers constantly vary crops and inputs based on the availability of limited and variable resources (e.g. land, water, finances, labour, machinery, etc.), and signals from its operating environment (e.g. climate, markets), with the objective of maximising a number of, often competing, objectives (e.g. maximise profits, minimise risks, etc.). In contrast in more rigid farming systems farm management is more calendar driven and relatively fixed sequences of crops are regularly followed over time and across the farm. Here we describe the application of a whole farm simulation model to (i) compare, in silico, the sensitivity of two farming systems designs of contrasting levels of plasticity, operating in two contrasting environments, when exposed to a stressor in the form of climate change scenarios;(ii) investigate the presence of interactions and feedbacks at the field and farm levels capable of modifying the intensity and direction of the responses to climate signals; and (iii) discuss the need for the development and application of more integrative assessments in the analysis of impacts and adaptation options to climate change. In both environments, the more plastic farm management strategy had higher median profits and was less risky for the baseline and less intensive climate change scenarios (2030). However, for the more severe climate change scenarios (2070), the benefit of plastic strategies tended to disappear. These results suggest that, to a point, farming systems having higher levels of plasticity would enable farmers to more effectively respond to climate shifts, thus ensuring the economic viability of the farm business. Though, as the intensity of the stress increases (e.g. 2070 climate change scenario) more significant changes in the farming system might be required to adapt. We also found that in the case studies analysed here, most of the impacts from the climate change scenarios on farm profit and economic risk originated from important reductions in cropping intensity and changes in crop mix rather than from changes in the yields of individual crops. Changes in cropping intensity and crop mix were explained by the combination of reductions in the number of sowing opportunities around critical times in the cropping calendar, and to operational constraints at the whole farm level i.e. limited work capacity in an environment having fewer and more concentrated sowing opportunities. This indicates that indirect impacts from shifts in climate on farm operations can be more important than direct impacts from climate on the yield of individual crops. The results suggest that due to the complexity of farm businesses, impact assessments and opportunities for adaptation to climate change might also need to be pursued at higher integration levels than the crop or the field. We conclude that plasticity can be a desirable characteristic in farming systems operating in highly variable environments, and that integrated whole farm systems analyses of impacts and adaptation to climate change are required to identify important interactions between farm management decision rules, availability of resources, and farmer's preference.
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Parthenium weed (Parthenium hysterophorus L.) is an erect, branched, annual plant of the family Asteraceae. It is native to the tropical Americas, while now widely distributed throughout Africa, Asia, Oceania, and Australasia. Due to its allelopathic and toxic characteristics, parthenium weed has been considered to be a weed of global significance. These effects occur across agriculture (crops and pastures), within natural ecosystems, and has impacts upon health (human and animals). Although integrated weed management (IWM) for parthenium weed has had some success, due to its tolerance and good adaptability to temperature, precipitation, and CO2, this weed has been predicted to become more vigorous under a changing climate resulting in an altered canopy architecture. From the viewpoint of IWM, the altered canopy architecture may be associated with not only improved competitive ability and replacement but also may alter the effectiveness of biocontrol agents and other management strategies. This paper reports on a preliminary study on parthenium weed canopy architecture at three temperature regimes (day/night 22/15 °C, 27/20 °C, and 32/25 °C in thermal time 12/12 hours) and establishes a threedimensional (3D) canopy model using Lindenmayer-systems (L-systems). This experiment was conducted in a series of controlled environment rooms with parthenium weed plants being grown in a heavy clay soil. A sonic digitizer system was used to record the morphology, topology, and geometry of the plants for model construction. The main findings include the determination of the phyllochron which enables the prediction of parthenium weed growth under different temperature regimes and that increased temperature enhances growth and enlarges the plants canopy size and structure. The developed 3D canopy model provides a tool to simulate and predict the weed growth in response to temperature, and can be adjusted for studies of other climatic variables such as precipitation and CO2. Further studies are planned to investigate the effects of other climatic variables, and the predicted changes in the pathogenic biocontrol agent effectiveness.
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Forest management is facing new challenges under climate change. By adjusting thinning regimes, conventional forest management can be adapted to various objectives of utilization of forest resources, such as wood quality, forest bioenergy, and carbon sequestration. This thesis aims to develop and apply a simulation-optimization system as a tool for an interdisciplinary understanding of the interactions between wood science, forest ecology, and forest economics. In this thesis, the OptiFor software was developed for forest resources management. The OptiFor simulation-optimization system integrated the process-based growth model PipeQual, wood quality models, biomass production and carbon emission models, as well as energy wood and commercial logging models into a single optimization model. Osyczka s direct and random search algorithm was employed to identify optimal values for a set of decision variables. The numerical studies in this thesis broadened our current knowledge and understanding of the relationships between wood science, forest ecology, and forest economics. The results for timber production show that optimal thinning regimes depend on site quality and initial stand characteristics. Taking wood properties into account, our results show that increasing the intensity of thinning resulted in lower wood density and shorter fibers. The addition of nutrients accelerated volume growth, but lowered wood quality for Norway spruce. Integrating energy wood harvesting into conventional forest management showed that conventional forest management without energy wood harvesting was still superior in sparse stands of Scots pine. Energy wood from pre-commercial thinning turned out to be optimal for dense stands. When carbon balance is taken into account, our results show that changing carbon assessment methods leads to very different optimal thinning regimes and average carbon stocks. Raising the carbon price resulted in longer rotations and a higher mean annual increment, as well as a significantly higher average carbon stock over the rotation.