7 resultados para coal train scheduling


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Coal-fired power plants may enjoy a significant advantage relative to gas plants in terms of cheaper fuel cost. Still, this advantage may erode or even turn into disadvantage depending on CO2 emission allowance price. This price will presumably rise in both the Kyoto Protocol commitment period (2008-2012) and the first post-Kyoto years. Thus, in a carbon-constrained environment, coal plants face financial risks arising in their profit margins, which in turn hinge on their so-called "clean dark spread". These risks are further reinforced when the price of the output electricity is determined by natural gas-fired plants' marginal costs, which differ from coal plants' costs. We aim to assess the risks in coal plants' margins. We adopt parameter values estimated from empirical data. These in turn are derived from natural gas and electricity markets alongside the EU ETS market where emission allowances are traded. Monte Carlo simulation allows to compute the expected value and risk profile of coal-based electricity generation. We focus on the clean dark spread in both time periods under different future scenarios in the allowance market. Specifically, bottom 5% and 10% percentiles are derived. According to our results, certain future paths of the allowance price may impose significant risks on the clean dark spread obtained by coal plants.

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36 p.

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One of the most challenging problems in mobile broadband networks is how to assign the available radio resources among the different mobile users. Traditionally, research proposals are either speci c to some type of traffic or deal with computationally intensive algorithms aimed at optimizing the delivery of general purpose traffic. Consequently, commercial networks do not incorporate these mechanisms due to the limited hardware resources at the mobile edge. Emerging 5G architectures introduce cloud computing principles to add flexible computational resources to Radio Access Networks. This paper makes use of the Mobile Edge Computing concepts to introduce a new element, denoted as Mobile Edge Scheduler, aimed at minimizing the mean delay of general traffic flows in the LTE downlink. This element runs close to the eNodeB element and implements a novel flow-aware and channel-aware scheduling policy in order to accommodate the transmissions to the available channel quality of end users.

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The aim of this research study has been to design a gain scheduling (GS) digital controller in order to control the voltage of an islanded microgrid in the presence of fast varying loads (FVLs), and to compare it to a robust controller. The inverter which feeds the microgrid is connected to it through an inductance-capacitor-inductance (LCL) filter. The oscillatory and nonlinear behaviour of the plant is analyzed in the whole operating zone. Afterwards, the design of the controllers which contain two loops in cascade are described. The first loop concerns the current control, while the second is linked to the voltage regulation. Two controllers, one defined as Robust and another one as GS controller, are designed for the two loops, emphasizing in their robustness and their ability to damp the oscillatory plant behaviour. To finish, some simulations are carried out to study and compare the two kinds of controllers in different operating points. The results show that both controllers damp the oscillatory behaviour of the plant in closed loop (CL), and that the GS controller ensures a better rejection of current disturbances from FVLs.

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This paper deals with the resource allocation problem aimed at maximizing users' perception of quality in wireless channels with time-varying capacity. First of all, we model the subjective quality-aware scheduling problem in the framework of Markovian decision processes. Then, given that the obtaining of the optimal solution of this model is unachievable, we propose a simple scheduling index rule with closed-form expression by using a methodology based on Whittle approach. Finally, we analyze the performance of the achieved scheduling proposal in several relevant scenarios, concluding that it outperforms the most popular existing resource allocation strategies.

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The evolution of the railway sector depends, to a great extent, on the deployment of advanced railway signalling systems. These signalling systems are based on communication architectures that must cope with complex electromagnetical environments. This paper is outlined in the context of developing the necessary tools to allow the quick deployment of these signalling systems by contributing to an easier analysis of their behaviour under the effect of electromagnetical interferences. Specifically, this paper presents the modelling of the Eurobalise-train communication flow in a general purpose simulation tool. It is critical to guarantee this communication link since any lack of communication may lead to a stop of the train and availability problems. In order to model precisely this communication link we used real measurements done in a laboratory equipped with elements defined in the suitable subsets. Through the simulation study carried out, we obtained performance indicators of the physical layer such as the received power, SNR and BER. The modelling presented in this paper is a required step to be able to provide quality of service indicators related to perturbed scenarios.