Design method for s-CO2 gas turbine power plants

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Design method for s-CO2 gas turbine power plants ( design-method-s-co2-gas-turbine-power-plants )

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92 Conclusions and recommendations The design of the components is focused on the regenerators and the cooler only. For the former, Printed Circuit Heat Exchangers are chosen as the best available options mainly due to their compactness and resistance to high pressures and temperatures. There is little information regarding the performance of this equipment given by its manufacturer. Thus, several expressions of the heat transfer coefficient and pressure drop are tested and validated against the rating values of a real PCHE. The best correlations are those given by Hesselgraves [52], and they are chosen to calculate the weight of the regenerators as function of the discharge pressure and pressure loss. The weight of the components decreases with larger discharge pressures since also the power decreases. Similarly, the larger the pressure loss, the lower the weight since larger losses lead to higher CO2 mass flow rate, which increases the heat transfer coefficient and the pressure drop, decreasing the required travel length and the size of the PCHE. The cooler is designed as an air cooled heat exchanger. The fan power is required to be minimal and the plain fins with staggered tube arrays match this feature. The model is based on the discretization of the tubes and the analysis of each element as a independent control volume. Two correlations are tested against a well known commercial software in order to validate them. The correlations of Ferreira [7] give the best results and they are taken for the design of this component. An optimization procedure which considers several geometries is developed and the solution characterized by the lowest fan power is chosen. The optimization shows that the lower the fan power consumption, the higher the weight. This is due to the larger number of tubes that increases the flow area reducing the air Reynolds number and pressure drop. In the final part of the work, two study cases are analyzed with the developed tool. The first case regards the application of s-CO2 turbines for aerospace propulsion systems. One of the best available turbofans is set as the reference engine and its thermodynamic analysis gives the performance characteristics that are to be overcome by the s-CO2 system. Although both the recompression and the regenerative Brayton cycles meet these requirements, the weight of the regenerators is much larger than the weight of the reference engine. This leads to the conclusion that, with the design procedures for stationary power applications used in this work, the application s-CO2 systems is not suitable for these objectives. The second case deals with power generation by means of Solar Concentrating Power systems, since the operating temperatures needed by this technology match the requirements of the s-CO2 with efficiencies larger than the current applications. Previous works show that the solar power tower is the technology that could be best coupled with s-CO2. The heliostat field represents the largest cost in these systems and for this reason the model that obtains the number of heliostats and its distribution is developed. Additionally, the model gives the individual field efficiencies which allow to evaluate the related costs and implement further optimization options. Finally, a general statement of an optimization problem applied to the second study case is presented. It takes into account both cycle performance and components dimensioning, and can be solved using the tools developed in the previous chapters. It consists in a multi- objective problem whose targets are to maximize the efficiency and minimize the cost of the system. Although the problem is not solved due to large computational time required, further improvements in the computer routines could allow to do so by means of genetic algorithms, which are suitable methods for multi-objective problems with not a single optimal solution but J.S. Bahamonde Noriega Master of Science Thesis

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