52 resultados para translational energy distribution

em Deakin Research Online - Australia


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In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.

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This paper presents an analytical model of fuel consumption (AMFC) to coordinate the driving power and manage the overall fuel consumption for an internal combustion engine vehicle. The model calculates the different loads applied on the vehicle including road-slope, road-friction, wind-drag, accessories, and mechanical losses. Also, it solves the combustion equation of the engine under different working conditions including various fuel compositions, excess airs and air inlet temperatures. Then it determines the contribution of each load to signify the energy distribution and power flows of the vehicle. Unlike the conventional models in which the vehicle speed needs to be given as an input, the developed model can predict the vehicle speed and acceleration under different working conditions by allowing the speed to vary within a predefined range only. Furthermore, the model indicates the ways to minimises the vehicles' fuel consumption under various driving conditions. The results show that the model has the potential to assist in the vehicle energy management.

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The fact that medical images have redundant information is exploited by researchers for faster image acquisition. Sample set or number of measurements were reduced in order to achieve rapid imaging. However, due to inadequate sampling, noise artefacts are inevitable in Compressive Sensing (CS) MRI. CS utilizes the transform sparsity of MR images to regenerate images from under sampled data. Locally sparsified Compressed Sensing is an extension of simple CS. It localises sparsity constraints for sub-regions rather than using a global constraint. This paper, presents a framework to use local CS for improving image quality without increasing sampling rate or without making the acquisition process any slower. This was achieved by exploiting local constraints. Localising image into independent sub-regions allows different sampling rates within image. Energy distribution of MR images is not even and most of noise occurs due to under-sampling in high energy regions. By sampling sub-regions based on energy distribution, noise artefacts can be minimized. Experiments were done using the proposed technique. Results were compared with global CS and summarized in this paper.

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 The control of energy distribution or energy intensity inside a laser spot using a defocusing method enables the formation of high-quality microchannels of multiple cross-sections in polycarbonate. Moreover, a thermal mathematical model of the process was developed to aid understanding of the process and to allow channel topology prediction.

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In this paper, a hybrid DC microgrid consisting of a diesel generator with a rectifier, a solar photovoltaic (PV) system, and a battery energy storage system is presented in relation to an effective power management strategy and different control techniques are adopted to power electronic interfaces. The solar PV and battery energy storage systems are considered as the main sources of energy sources that supply the load demand on a daily basis whereas the diesel generator is used as a backup for the emergency operation of the microgrid. All system components are connected to a common DC bus through an appropriate power electronics devices (e.g., rectifier systems, DC/DC converter). Also a detailed sizing philosophy of all components along with the energy management strategy is proposed. Energy distribution pattern of each individual component has been conducted based on the monthly basis along with a power management algorithm. The power delivered by the solar PV system and diesel generator is controlled via DC-DC converterand excitation controllers which are designed based on a linearquadratic regulator (LQR) technique as as proportional integral (PI)controllers. The component level power distribution is investigatedusing these controllers under fluctuating load and solar irradiationconditions and comparative results are presented.

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Large-scale renewable energy (RE) integration into the distribution network (DN) causes uncertainties due to its intermittent nature and is a challenging task today. In general RE sources are mostly connected near the end user level, i.e., in the low voltage distribution network. RE integration introduces bi-directional power flows across distribution transformer (DT) and hence DN experiences with several potential problems that includes voltage fluctuations, reactive power compensation and poor power factor in the DN. This study identifies the potential effects causes due to large-scale integration of RE into the Berserker Street Feeder, Frenchville Substation under Rockhampton DN. From the model analyses, it has clearly evident that voltage of the Berserker Street Feeder fluctuates with the increased integration of RE and causes uncertainties in the feeder as well as the DN.

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Wind energy is one of the most promising renewable energy sources due to its availability and climate-friendly attributes. Large-scale integration of wind energy sources creates potential technical challenges due to the intermittent nature that needs to be investigated and mitigated as part of developing a sustainable power system for the future. Therefore, this study developed simulation models to investigate the potential challenges, in particular voltage fluctuations, zone substation, and distribution transformer loading, power flow characteristics, and harmonic emissions with the integration of wind energy into both the high voltage (HV) and low voltage (LV) distribution network (DN). From model analysis, it has been clearly indicated that influences of these problems increase with the increased integration of wind energy into both the high voltage and low voltage distribution network, however, the level of adverse impacts is higher in the LV DN compared to the HV DN.

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The new found ability to measure physical attributes of the marine environment at high resolution across broad spatial scales has driven the rapid evolution of benthic habitat mapping as a field in its own right. Improvement of the resolution and ecological validity of seafloor habitat distribution models has, for the most part, paralleled developments in new generations of acoustic survey tools such as multibeam echosounders. While sonar methods have been well demonstrated to provide useful proxies of the relatively static geophysical patterns that reflect distribution of benthic species and assemblages, the spatially and temporally variable influence of hydrodynamic energy on habitat distribution have been less well studied. Here we investigate the role of wave exposure on patterns of distribution of near-shore benthic habitats. A high resolution spectral wave model was developed for a 624 km2 site along Cape Otway, a major coastal feature of western Victoria, Australia. Comparison of habitat classifications implemented using the Random Forests algorithm established that significantly more accurate estimations of habitat distribution were obtained by including a fine-scale numerical wave model, extended to the seabed using linear wave theory, than by using depth and seafloor morphology information alone. Variable importance measures and map interpretation indicated that the spatial variation in wave-induced bottom orbital velocity was most influential in discriminating habitat classes containing the canopy forming kelp Ecklonia radiata, a foundation kelp species that affects biodiversity and ecological functioning on shallow reefs across temperate Australasia. We demonstrate that hydrodynamic models reflecting key environmental drivers on wave-exposed coastlines are important in accurately defining distributions of benthic habitats. This study highlights the suitability of exposure measures for predictive habitat modeling on wave-exposed coastlines and provides a basis for continuing work relating patterns of biological distribution to remotely-sensed patterns of the physical environment.

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This chapter presents an unbalanced multi-phase optimal power flow (UMOPF) based planning approach to determine the optimum capacities of multiple distributed generation units in a distribution network. An adaptive weight particle swarm optimization algorithm is used to find the global optimum solution. To increase the efficiency of the proposed scheme, a co-simulation platform is developed. Since the proposed method is mainly based on the cost optimization, variations in loads and uncertainties within DG units are also taken into account to perform the analysis. An IEEE 123 node distribution system is used as a test distribution network which is unbalanced and multi-phase in nature, for the validation of the proposed scheme. The superiority of the proposed method is investigated through the comparisons of the results obtained that of a Genetic Algorithm based OPF method. This analysis also shows that the DG capacity planning considering annual load and generation uncertainties outperform the traditional well practised peak-load planning.

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Ring spinning has been and will continue to be an important system for making staple yarns from different fibers in the textile industry. But high power consumption and low productivity remain the two outstanding problems with ring spinning. Based on an analysis of power distribution during yarn winding in ring spinning, models for the ratio of energy consumption to yarn production over a full yarn package are established. Spindle speed, yarn count, and package diameter are the three key parameters affecting this ratio. The effects on energy consumption of these parameters are discussed through a case study. The energy-to-production ratio increases with increased package diameter but decreases with increased spindle speed and/or yarn count (tex). The results will help guide spinners in minimizing energy consumption in ring spinning.

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A model of a yam package is established for a ring spinning system. The yarn layer, surface area, and mass of the yam package are formulated with respect to the diameters of the empty bobbin and full yarn package, yarn count, and yarn winding-on time. Based on the principles of dynamics and aerodynamics, models of the power requirements for overcoming the skin friction drag, increasing the kinetic energy of the yarn package (bobbin and wound yarn), and overcoming the yarn wind-on tension are developed. The skin friction coefficient on the surface of a rotating yam package is obtained from experiment. The power distribution during yam packaging is discussed based on a case study. The results indicate that overcoming the skin friction drag during yarn winding consumes the largest amount of energy. The energy required to overcome the yarn wind-on tension is also significant.

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Aims To investigate body size and body fat relationships and fat distribution in young healthy men drawn from New Zealand European, Pacific Island, and Asian Indian populations.
Method A total of 114 healthy men (64 European, 31 Pacific Island, 19 Asian Indian) aged 17–30 years underwent measurements of height, weight, and body composition by total body dual-energy X-ray absorptiometry (DXA). Body mass index (BMI) was then calculated. Percent body fat (%BF), fat-free mass, bone mineral content, bone mineral density, abdominal fat, thigh fat, and appendicular skeletal muscle mass (ASMM) were obtained from the DXA scans.
Results For the same BMI, %BF for Pacific Island men was 4% points lower and for Asian Indian men was 7–8% points higher compared to Europeans. Compared to European men for the same %BF, BMI was 2–3 units higher for Pacific Island, and 3–6 units lower for Asian Indian. The ratio of abdominal fat to thigh fat, adjusted for height, weight, and %BF, was significantly higher for Asian Indian men than European (p=0.022) and Pacific Island (p=0.002) men. ASMM, adjusted for height and weight, was highest in Pacific Island and lowest in Asian Indian men.
Conclusions The relationship between %BF and BMI is different for European, Pacific Island, and Asian Indian men which may, at least in part, be due to differences in muscularity. Asian Indians have more abdominal fat deposition than their European and Pacific Island counterparts. Use of universal BMI cut-off points are not appropriate for comparison of obesity prevalence between these ethnic groups.