20 resultados para ESEO spacecraft simulator thermal power

em Deakin Research Online - Australia


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This paper firstly expounds that the reheat-regenerative Rankine power cycle is a suitable cycle for the parabolic trough collector, a popular kind of collector in the power industry. In a thermal power cycle, the higher the temperature at which heat is supplied, the higher the efficiency of the cycle. On the other hand, for a given kind of collector at the same exiting temperature, the higher the temperature of the fluid entering the collector, the lower the efficiency of the collector. With the same exiting temperature of the solar field and the same temperature differences at the hottest end of the superheater/reheater and at the pinch points in the heat exchangers (e.g., the boiler) in the cycle, the efficiencies of the system are subject to the temperature of the fluid entering the collector or the saturation temperature at the boiler. This paper also investigates the optimal thermal and exergetic efficiencies for the combined system of the power cycle and collector. To make most advantage of the collector, the exiting fluid is supposed to be at the maximum temperature the collector can harvest. Hence, the thermal and exergetic efficiencies of the system are related to the saturation temperature at the boiler here.


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Fossil fuel based power generation is and will still be the back bone of our world economy, albeit such form of power generation significantly contributes to global CO2 emissions. Solar energy is a clean, environmental friendly energy source for power generation, however solar photovoltaic electricity generation is not practical for large commercial scales due to its cost and high-tech nature. Solar thermal is another way to use solar energy to generate power. Many attempts to establish solar (solo) thermal power stations have been practiced all over the world. Although there are some advantages in solo solar thermal power systems, the efficiencies and costs of these systems are not so attractive. Alternately by modifying, if possible, the existing coal-fired power stations to generate green sustainable power, a much more efficient means of power generation can be reached. This paper presents the concept of solar aided power generation in conventional coal-fired power stations, i.e., integrating solar (thermal) energy into conventional fossil fuelled power generation cycles (termed as solar aided thermal power). The solar aided power generation (SAPG) concept has technically been derived to use the strong points of the two technologies (traditional regenerative Rankine cycle with relatively higher efficiency and solar heating at relatively low temperature range). The SAPG does not only contribute to increase the efficiencies of the conventional power station and reduce its emission of the greenhouse gases, but also provides a better way to use solar heat to generate the power. This paper presents the advantages of the SAPG at conceptual level.

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Solar-aided power generation (SAPG) is capable of integrating solar thermal energy into a conventional thermal power plant, at multi-points and multi-levels, to replace parts of steam extractions in the regenerative Rankine cycle. The integration assists the power plant to reduce coal (gas) consumption and pollution emission or to increase power output. The overall efficiencies of the SAPG plants with different solar replacements of extraction steam have been studied in this paper. The results indicate that the solar thermal to electricity conversion efficiencies of the SAPG system are higher than those of a solar-alone power plant with the same temperature level of solar input. The efficiency with solar input at 330 °C can be as high as 45% theoretically in a SAPG plant. Even the low-temperature solar heat at about 85 °C can be used in the SAPG system to heat the lower temperature feedwater, and the solar to electricity efficiency is nearly 10%. However, the low-temperature heat resource is very hard to be used for power generation in other types of solar power plants. Therefore, the SAPG plant is one of the most efficient ways for solar thermal power generation.

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Water shortage is a major problem facing the power industry in many nations around the world. The largest consumer of water in most power plants is the wet cooling tower. To assist water and energy saving for thermal power stations using conventional evaporative wet cooling towers, a hybrid cooling system is proposed in this paper. The hybrid cooling system may consists of all or some of an air pre-cooler, heat pump, heat exchangers, and adsorption chillers together with the existing cooling tower. The hybrid cooling system described in the paper, consisting of a metal hydride heat pump operating in conjunction with the existing wet cooling tower, is capable of achieving water saving by reducing the temperature of warm water entering the cooling tower. Cooler inlet water temperatures effectively reduce the cooling load on existing towers. This will ultimately reduce the amount of water lost to the air by evaporation whilst still achieving the same cooling output. At the same time, the low grade waste energy upgraded by the metal hydride heat pump, in the process of cooling the water, can be used to replace the bleed of steam for the lower stage feed heaters which will increase overall cycle efficiency.

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This thesis proposes the concept of a hybrid cooling system to minimise water consumption in thermal power stations. It identifies that a significant amount of water can be potentially saved by the proposed system. Additional energy input requirements were less than previous approaches considered.

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This paper presents a H∞ dynamic output feedback control scheme for load frequency control (LFC) of interconnected power systems with multiple input timedelays. In this study, electric vehicles (EVs) are participated in the LFC to support reheated thermal power units to rapidly suppress load and frequency fluctuations. A mathematical model of an interconnected power system is first introduced. This model takes into consideration of the different time delays in control inputs; specifically the communication/information delays between the control center and the fleet of EVs. We then derive stabilization conditions in terms of feasible linear matrix inequalities (LMIs) for the proposed system and develop an effective algorithm to parameterize H∞ controllers ensuring stability of the closed-loop system with H∞ performance. Extensive simulations are given to show the effectiveness of the proposed control method.

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Positive Unit commitment and economic dispatch are two important decisions in thermal power generation scheduling. The tasks involve determination and allocation of power generation to thermal units that minimize the total power generation cost and satisfy the production constraints.This paper presents a cascade Genetic Algorithm and Particle Swarm Optimization (GA-PSO) approach for solving thermal power generation scheduling based on a layered matrix encoding structure.The proposed hybrid method is compared to layered matrix encoding GA using the thermal power generation problem given in Williams [1] to demonstrate its effectiveness in generating an optimal, cost-effective power generation schedule.The results showed that cascade GA-PSO outperformed the layered matrix encoding GA in minimizing the total power production cost for unit commitment and power dispatch problems.

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To decrease the consumption of fossil fuels, research has been done on utilizing low grade heat, sourced from industrial waste streams. One promising thermoenergy conversion system is a thermogalvanic cell; it consists of two identical electrodes held at different temperatures that are placed in contact with a redox-based electrolyte [1, 2]. The temperature dependence of the direction of redox reactions allows power to be extracted from the cell [3, 4]. This study aims to increase the power conversion efficiency and reduce the cost of thermogalvanic cells by optimizing the electrolyte and utilizing a carbon based electromaterial, reduced graphene oxide, as electrodes. Thermal conductivity measurements of the K3Fe(CN)6/K4Fe(CN)6 solutions used, indicate that the thermal conductivity decreases from 0.591 to 0.547 W/m K as the concentration is increased from 0.1 to 0.4 M. The lower thermal conductivity allowed a larger temperature gradient to be maintained in the cell. Increasing the electrolyte concentration also resulted in higher power densities, brought about by a decrease in the ohmic overpotential of the cell, which allowed higher values of short circuit current to be generated. The concentration of 0.4 MK3Fe(CN)6/K4Fe(CN)6 is optimal for thermal harvesting applications using R-GO electrodes due to the synergistic effect of the reduction in thermal flux across the cell and the enhancement of power output, on the overall power conversion efficiency. The maximum mass power density obtained using R-GO electrodes was 25.51 W/kg (three orders of magnitude higher than platinum) at a temperature difference of 60 _C and a K3Fe(CN)6/K4Fe(CN)6 concentration of 0.4 M.

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This letter presents a novel approach to the load-frequency control (LFC) of interconnected power systems. Based on functional observers theory, quasi-decentralized functional observers (QDFOs) are designed to implement any given global PI state feedback controller. The designed functional observers are decoupled from each other and also of low-order; thus, they are cost effective and easy to implement. Although the proposed approach is applicable to N- area power systems, an example of a two-area interconnected power system with reheat thermal turbines is considered for simplicity.

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This paper proposes a hybrid computational framework based on Sequential Quadratic Programming (SQP) and Particle Swarm Optimization (PSO) to address the Combined Unit Commitment and Emission (CUCE) problem. By considering a model which includes both thermal generators and wind farms, the proposed hybrid computational framework can minimize the scheduling cost and greenhouse gases emission cost. The viability of the proposed hybrid technique is demonstrated using a set of numerical case studies. Moreover, comparisons are performed with other optimization algorithms. The simulation results show that our hybrid method is better in terms of the speed and accuracy. The main contribution of this paper is the development of a emission unit commitment model integrating with wind energy and combining the SQP and PSO methods to achieve faster and better performance optimization