952 resultados para Unmanned Aerial Vehicle (UAV)


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Electric vehicles are a key prospect for future transportation. A large penetration of electric vehicles has the potential to reduce the global fossil fuel consumption and hence the greenhouse gas emissions and air pollution. However, the additional stochastic loads imposed by plug-in electric vehicles will possibly introduce significant changes to existing load profiles. In his paper, electric vehicles loads are integrated into an 5-unit system using a non-convex dynamic dispatch model. The actual infrastructure characteristics including valve-point effects, load balance constrains and transmission loss have been included in the model. Multiple load profiles are comparatively studied and compared in terms of economic and environmental impacts in order o identify patterns to charge properly. The study as expected shows ha off-peak charging is the best scenario with respect to using less fuels and producing less emissions.

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Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

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Electric vehicles (EV) are proposed as a measure to reduce greenhouse gas emissions in transport and support increased wind power penetration across modern power systems. Optimal benefits can only be achieved, if EVs are deployed effectively, so that the exhaust emissions are not substituted by additional emissions in the electricity sector, which can be implemented using Smart Grid controls. This research presents the results of an EV roll-out in the all island grid (AIG) in Ireland using the long term generation expansion planning model called the Wien Automatic System Planning IV (WASP-IV) tool to measure carbon dioxide emissions and changes in total energy. The model incorporates all generators and operational requirements while meeting environmental emissions, fuel availability and generator operational and maintenance constraints to optimize economic dispatch and unit commitment power dispatch. In the study three distinct scenarios are investigated base case, peak and off-peak charging to simulate the impacts of EV’s in the AIG up to 2025.

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As the emphasis on initiatives that can improve environmental efficiency while simultaneously maintaining economic viability has escalated in recent years, attention has turned to more radical concepts of operation. In particular, the cruiser–feeder concept has shown potential for a new generation, environmentally friendly, air-transport system to alleviate the growing pressure on the passenger air-transportation network. However, a full evaluation of realizable benefits is needed to determine how the design and operation of potential feeder-aircraft configurations impact on the feasibility of the overall concept. This paper presents an analysis of a cruiser–feeder concept, in which fuel is transferred between the feeder and the cruiser in an aerial-refueling configuration to extend range while reducing cruiser weight, compared against the effects of escalating existing technology levels while retaining the existing passenger levels. Up to 14% fuel-burn and 12% operating-cost savings can be achieved when compared to a similar technology-level aircraft concept without aerial refueling, representing up to 26% in fuel burn and 25% in total operating cost over the existing operational model at today’s standard fleet technology and performance. However, these potential savings are not uniformly distributed across the network, and the system is highly sensitive to the routes serviced, with reductions in revenue-generation potential observed across the network for aerial-refueling operations due to reductions in passenger revenue.

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There are many uncertainties in forecasting the charging and discharging capacity required by electric vehicles (EVs) often as a consequence of stochastic usage and intermittent travel. In terms of large-scale EV integration in future power networks this paper develops a capacity forecasting model which considers eight particular uncertainties in three categories. Using the model, a typical application of EVs to load levelling is presented and exemplified using a UK 2020 case study. The results presented in this paper demonstrate that the proposed model is accurate for charge and discharge prediction and a feasible basis for steady-state analysis required for large-scale EV integration.

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Re-imagining of the aerial transportation system has become increasingly important as the need for significant environmental and economic efficiency gains has become ever more prevalent. A number of studies have highlighted the benefits of the adoption of air to air refuelling within civil aviation. However, it also opens up the potential for increased flexibility in operations through smaller aircraft, shifting emphasis away from the traditional hub and spoke method of operation towards the more flexible Point to Point operations. It is proposed here that one technology can act as an enabler for the other, realising benefits that neither can realise as a standalone. The impact of an air-toair refuelling enabled point to point system is discussed, and the affect on economic and environmental cost metrics relative to traditional operations evaluated. An idealised airport configuration study shows the difference in fuel burn for point to point networks to vary from -23% to 28% from that of Hub and Spoke depending on the configuration. The sensitive natures of the concepts are further explored in a second study based on real airport configurations. The complex effect of the choice of a Point to Point or Hub and Spoke system on fuel burn, operating cost and revenue potential is highlighted. Fuel burn savings of 15% can be experienced with AAR over traditional refuelling operations, with point to point networks increasing the available seat miles (by approximately 20%) without a proportional increase in operating cost or fuel.

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The Copney Stone Circle Complex, Co. Tyrone, N. Ireland, is an important Bronze Age site forming part of the Mid-Ulster Stone Circle Complex. The Environment Service: Historic Monuments and Buildings (ESHMB) initiated a program of bog-clearance in August 1994 to excavate the stone circles. This work was completed by October 1994 and the excavated site was surveyed in August 1995. Almost immediately, the rate at which the stones forming the circles were breaking down was noted and a program of study initiated to make recommendations upon the conservation of this important site. Digital photogrammetric techniques were applied to aerial images of the stone circles and digital terrain models created from the images at a range of scales. These provide base data sets for comparison with identical surveys to be completed in successive years and will allow the rate of deterioration, and the areas most affected, of the circles to be determined. In addition, a 2D analysis of the stones provides an accurate analysis of the absolute 2D dimensions of the stones for rapid desktop computer analysis by researchers remote from the digital photogrammetric workstation used in the survey.

The products of this work are readily incorporated into web sites, educational packages and databases. The technique provides a rapid and user friendly method of presentation of a large body of information and measurements, and a reliable method of storage of the information from Copney should it become necessary to re-cover the site.

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In recent years, a wide variety of centralised and decentralised algorithms have been proposed for residential charging of electric vehicles (EVs). In this paper, we present a mathematical framework which casts the EV charging scenarios addressed by these algorithms as optimisation problems having either temporal or instantaneous optimisation objectives with respect to the different actors in the power system. Using this framework and a realistic distribution network simulation testbed, we provide a comparative evaluation of a range of different residential EV charging strategies, highlighting in each case positive and negative characteristics.

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A periodic monitoring of the pavement condition facilitates a cost-effective distribution of the resources available for maintenance of the road infrastructure network. The task can be accurately carried out using profilometers, but such an approach is generally expensive. This paper presents a method to collect information on the road profile via accelerometers mounted in a fleet of non-specialist vehicles, such as police cars, that are in use for other purposes. It proposes an optimisation algorithm, based on Cross Entropy theory, to predict road irregularities. The Cross Entropy algorithm estimates the height of the road irregularities from vehicle accelerations at each point in time. To test the algorithm, the crossing of a half-car roll model is simulated over a range of road profiles to obtain accelerations of the vehicle sprung and unsprung masses. Then, the simulated vehicle accelerations are used as input in an iterative procedure that searches for the best solution to the inverse problem of finding road irregularities. In each iteration, a sample of road profiles is generated and an objective function defined as the sum of squares of differences between the ‘measured’ and predicted accelerations is minimized until convergence is reached. The reconstructed profile is classified according to ISO and IRI recommendations and compared to its original class. Results demonstrate that the approach is feasible and that a good estimate of the short-wavelength features of the road profile can be detected, despite the variability between the vehicles used to collect the data.

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Highway structures such as bridges are subject to continuous degradation primarily due to ageing and environmental factors. A rational transport policy requires the monitoring of this transport infrastructure to provide adequate maintenance and guarantee the required levels of transport service and safety. In Europe, this is now a legal requirement - a European Directive requires all member states of the European Union to implement a Bridge Management System. However, the process is expensive, requiring the installation of sensing equipment and data acquisition electronics on the bridge. This paper investigates the use of an instrumented vehicle fitted with accelerometers on its axles to monitor the dynamic behaviour of bridges as an indicator of its structural condition. This approach eliminates the need for any on-site installation of measurement equipment. A simplified half-car vehicle-bridge interaction model is used in theoretical simulations to test the possibility of extracting the dynamic parameters of the bridge from the spectra of the vehicle accelerations. The effect of vehicle speed, vehicle mass and bridge span length on the detection of the bridge dynamic parameters are investigated. The algorithm is highly sensitive to the condition of the road profile and simulations are carried out for both smooth and rough profiles

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Highway structures such as bridges are subject to continuous degradation primarily due to ageing, loading and environmental factors. A rational transport policy must monitor and provide adequate maintenance to this infrastructure to guarantee the required levels of transport service and safety. Increasingly in recent years, bridges are being instrumented and monitored on an ongoing basis due to the implementation of Bridge Management Systems. This is very effective and provides a high level of protection to the public and early warning if the bridge becomes unsafe. However, the process can be expensive and time consuming, requiring the installation of sensors and data acquisition electronics on the bridge. This paper investigates the use of an instrumented 2-axle vehicle fitted with accelerometers to monitor the dynamic behaviour of a bridge network in a simple and cost-effective manner. A simplified half car-beam interaction model is used to simulate the passage of a vehicle over a bridge. This investigation involves the frequency domain analysis of the axle accelerations as the vehicle crosses the bridge. The spectrum of the acceleration record contains noise, vehicle, bridge and road frequency components. Therefore, the bridge dynamic behaviour is monitored in simulations for both smooth and rough road surfaces. The vehicle mass and axle spacing are varied in simulations along with bridge structural damping in order to analyse the sensitivity of the vehicle accelerations to a change in bridge properties. These vehicle accelerations can be obtained for different periods of time and serve as a useful tool to monitor the variation of bridge frequency and damping with time.