Academic literature on the topic 'Kalina cycle'

The primary objective of this work is to determine the Kalina cycle's suitability for thermal power conversion from a pressurized water reactor. Several previous papers have examined this application, but these either lack proof of concept or make unfeasible assumptions. This work expands current knowledge by simulating the Kalina cycle and comparing it to current pressurized water reactor Rankine cycles in order to identify which is more efficient. Prerequisite to the modeling is a simulation tool capable of modeling the thermodynamics of ammonia/water mixtures. Instead of using an existing program, a new one called Clearwater is used. This tool is based on a preexisting Gibbs free energy "super" equation of state. Algorithms for vapor-liquid equilibrium calculations and phase identification are presented. Clearwater will be distributed online as open-source code to aid future developers of ammonia/water power and refrigeration cycles. A comparison of single-stage Kalina and Rankine cycles driven by heat from PWR core coolant suggests that the Kalina cycle is not well suited to the application. Any benefit from the Kalina cycle's ability to match temperature profiles in the boiling region of the steam generator is outweighed by other drawbacks. These include the cycle's 1) increased turbine exhaust pressure and 2) lower average heat absorption temperature caused by its working fluid's relatively high liquid heat capacity, both of which lower efficiency. Having concluded this, an attempt is made to quantify the conditions under which the Kalina cycle produces more power than the Rankine cycle. Both cycles are optimized for a range of heat source inlet and outlet temperatures between 350 ℃ and 525 ℃. When both cycles absorb the same amount of heat from the source"”i.e., when source outlet temperature is constrained"” the Kalina cycle is less effective for small source temperature drops. When outlet temperature is unconstrained, the Kalina cycle outperforms the Rankine cycle for all but the lowest inlet temperature. This is due to the Kalina cycle's non-isothermal boiling profile, which allows it to absorb low temperature heat at relatively high pressure. Because of its isothermal boiling profile, the Rankine cycle cannot capture low temperature heat as effectively, so it performs worse over large, unconstrained source temperature drops.

This master’s thesis analyses Kalina cycle, a power cycle where ammonia – water solution is used as a working fluid. The first part of this study introduces us to the Kalina cycle, presents its advantages and disadvantages, characteristics of the working fluid and its applications. Second section concerns with the method of cycle design and describes the calculation model made in this thesis. The calculation model is attached in a separate .XLSM file. The third part shows calculation of the cycle for given parameters, determination of cycle efficiency and main proportions of the thermal turbine. In the conclusion are the interpretations of the calculations results.

Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2010.<br>Committee Chair: Mayor, James Rhett; Committee Member: Garimella, Srinivas; Committee Member: Jeter, Sheldon. Part of the SMARTech Electronic Thesis and Dissertation Collection.

This Diploma thesis describes design of the computational model of Uehara power cycle, with ammonia-water mixture used as working fluid. First part is dedicated to issue of determination working mixture thermodynamic properties, which are essential for computational model design. The second part of this thesis describes the methodology of computing power cycle by system matrix solving method. For purposes of methodology testing, model of Kalina power cycle was also created. Computational models of Uehara and Kalina cycles are designed in Excel and are an integral part of this thesis. Text part also includes a description of their user interface, calculation algorithm and detailed description of the design methodology.

<p>The world demand for electrical power increasescontinuously, requiring efficient and low-cost methods forpower generation. This thesis investigates two advanced powercycles with mixtures as the working fluid: the Kalina cycle,alternatively called the ammonia-water cycle, and theevaporative gas turbine cycle. These cycles have the potentialof improved performance regarding electrical efficiency,specific power output, specific investment cost and cost ofelectricity compared with the conventional technology, sincethe mixture working fluids enable efficient energyrecovery.</p><p>This thesis shows that the ammonia-water cycle has a betterthermodynamic performance than the steam Rankine cycle as abottoming process for natural gas-fired gas and gas-dieselengines, since the majority of the ammonia-water cycleconfigurations investigated generated more power than steamcycles. The best ammonia-water cycle produced approximately40-50 % more power than a single-pressure steam cycle and 20-24% more power than a dual-pressure steam cycle. The investmentcost for an ammonia-water bottoming cycle is probably higherthan for a steam cycle; however, the specific investment costmay be lower due to the higher power output.</p><p>A comparison between combined cycles with ammonia-waterbottoming processes and evaporative gas turbine cycles showedthat the ammonia-water cycle could recover the exhaust gasenergy of a high pressure ratio gas turbine more efficientlythan a part-flow evaporative gas turbine cycle. For a mediumpressure ratio gas turbine, the situation was the opposite,except when a complex ammonia-water cycle configuration withreheat was used. An exergy analysis showed that evaporativecycles with part-flow humidification could recover energy asefficiently as, or more efficiently than, full-flow cycles. Aneconomic analysis confirmed that the specific investment costfor part-flow cycles was lower than for full-flow cycles, sincepart-flow humidification reduces the heat exchanger area andhumidification tower volume. In addition, the part-flow cycleshad lower or similar costs of electricity compared with thefull-flow cycles. Compared with combined cycles, the part-flowevaporative cycles had significantly lower total and specificinvestment costs and lower or almost equal costs ofelectricity; thus, part-flow evaporative cycles could competewith the combined cycle for mid-size power generation.</p><p><b>Keywords:</b>power cycle, mixture working fluid, Kalinacycle, ammonia-water mixture, reciprocating internal combustionengine, bottoming cycle, gas turbine, evaporative gas turbine,air-water mixture, exergy</p>

An investigation into the performance of several combined gas-steam power generating plants’ cycles was undertaken at the School of Engineering and Technology at the University of Hertfordshire and it is predominantly analytical in nature. The investigation covered in principle the aspect of the fundamentals and the performance parameters of the following cycles: gas turbine, steam turbine, ammonia-water, partial oxidation and the absorption chiller. Complete thermal analysis of the individual cycles was undertaken initially. Subsequently, these were linked to generate a comprehensive computer model which was employed to predict the performance and characteristics of the optimized combination. The developed model was run using various input parameters to test the performance of the cycle’s combination with respect to the combined cycle’s efficiency, power output, specific fuel consumption and the temperature of the stack gases. In addition, the impact of the optimized cycles on the generation of CO2 and NOX was also investigated. This research goes over the thermal power stations of which most of the world electrical energy is currently generated by. Through which, to meet the increase in the electricity consumption and the environmental pollution associated with its production as well as the limitation of the natural hydrocarbon resources necessitated. By making use of the progressive increase of high temperature gases in recent decades, the advent of high temperature material and the use of large compression ratios and generating electricity from high temperature of gas turbine discharge, which is otherwise lost to the environment, a better electrical power is generated by such plant, which depends on a variety of influencing factors. This thesis deals with an investigation undertaken to optimize the performance of the combined Brayton-Rankine power cycles' performance. This work includes a comprehensive review of the previous work reported in the literature on the combined cycles is presented. An evaluation of the performance of combined cycle power plant and its enhancements is detailed to provide: A full understanding of the operational behaviour of the combined power plants, and demonstration of the relevance between power generations and environmental impact. A basic analytical model was constructed for the combined gas (Brayton) and the steam (Rankine) and used in a parametric study to reveal the optimization parameters, and its results were discussed. The role of the parameters of each cycle on the overall performance of the combined power cycle is revealed by assessing the effect of the operating parameters in each individual cycle on the performance of the CCPP. P impacts on the environment were assessed through changes in the fuel consumption and the temperature of stack gases. A comprehensive and detailed analytical model was created for the operation of hypothetical combined cycle power and power plant. Details of the operation of each component in the cycle was modelled and integrated in the overall all combined cycle/plant operation. The cycle/plant simulation and matching as well as the modelling results and their analysis were presented. Two advanced configurations of gas turbine cycle for the combined cycle power plants are selected, investigated, modelled and optimized as a part of combined cycle power plant. Both configurations work on fuel rich combustion, therefore, the combustor model for rich fuel atmosphere was established. Additionally, models were created for the other components of the turbine which work on the same gases. Another model was created for the components of two configurations of ammonia water mixture (kalina) cycle. As integrated to the combined cycle power plant, the optimization strategy considered for these configurations is for them to be powered by the exhaust gases from either the gas turbine or the gases leaving the Rankine boiler (HRSG). This included ChGT regarding its performance and its environmental characteristics. The previously considered combined configuration is integrated by as single and double effect configurations of an ammonia water absorption cooling system (AWACS) for compressor inlet air cooling. Both were investigated and designed for optimizing the triple combination power cycle described above. During this research, tens of functions were constructed using VBA to look up tables linked to either estimating fluids' thermodynamic properties, or to determine a number of parameters regarding the performance of several components. New and very interesting results were obtained, which show the impact of the input parameters of the individual cycles on the performance parameters of a certain combined plant’s cycle. The optimized parameters are of a great practical influence on the application and running condition of the real combined plants. Such influence manifested itself in higher rate of heat recovery, higher combined plant thermal efficiency from those of the individual plants, less harmful emission, better fuel economy and higher power output. Lastly, it could be claimed that various concluding remarks drawn from the current study could help to improve the understanding of the behaviour of the combined cycle and help power plant designers to reduce the time, effort and cost of prototyping.

This thesis includes two essays that are focused on developing multivariate filter approaches to be used for extracting common cyclical components where the common components can be used as an estimator of a business cycle. The first chapter aims to develop an optimal multivariate filter in order to extract common cyclical components of macroeconomic indicators. The filter allows macroeconomic series to be modeled as a phase shifted version of a coinciding business cycle (BC) while keeping other time series components such as the stochastic trend and idiosyncratic shocks intact (i.e. they are individually specified for each series). Earlier studies of Rünstler (2004), Valle e Azevedo et al. (2006) have applied phase shift in the form of a delay parameter when specifying lead-lag cycles. However, the lead-lag relationship is defined by rotating the baseline cycle which leads to loss of information. This deficiency is especially important if one considers working in continuous time. Therefore, this paper improves on the former technique by allowing a more flexible phase shift mechanism on the original BC. This in turn should lead to more realistic estimates and filters considering that the underlying data is generated through a continuous time framework. The study starts by presenting a structure for bi-variate time series system and then extends to model to incorporate a structure for three time series and beyond. Kalman filter and smoothing recursions are applied to compute the smoothed cycle estimates and to construct the likelihood function. Using simulated data, we test both model specifications by carrying out a grid search of the initial delay parameter to see the likelihood behavior as the parameter moves into fractional neighborhoods. Afterwards, applying the methodology to a set of EU countries and macroeconomic indicators; the study aims to shed light to the presence of cyclical heterogeneity at country level economic activity for major EU member states. A second empirical study provides analysis on how the model can be implemented for assigning a lead/lag ordering to three main economic indicators of a single country. The second chapter implements a multivariate non-parametric filtering approach; the Vertical Multivariate Singular Spectrum Analysis (V-MSSA) of Hassani and Mahmoudvand (2013) and Golyandina et al. (2013). to be applied for identifying a common economic cycle indicator. The methodology is a data-driven procedure that can decompose a time series into many sub components. By exploiting this ability of the SSA, the paper aims to first extract cyclical components based on frequency characteristics and then follow by choosing only common cyclical component pairs with-in the business cycle frequency spectrum. These components will then be aggregated for constructing an EU region wide Business cycle indicator. The chapter outlines each steps of the algorithm that will eventually identify the SSA filter to act as a band-pass filter. The study then proceeds with simulation based data where the common cycle can be controlled and extracted a priori as a benchmark to the SSA-based filter estimates. The study follows with an empirical analysis similar to the framework set in Valle e Azevedo et al. (2006) with the aim to identify a Euro region business cycle indicator. The SSA based filter estimate is compared with Euro region economic activity indicators; the EuroCoin and the quarterly GDP growth rate of the EU area. Our results presents evidence of a successful alternative for tracing the cyclical position of the EU economy from a much smaller data set. Moreover, the constructed indicator also could serve as an unobserved proxy for a monthly growth cycle. A further analysis is also conducted to reveal whether the SSA based approach can be considered as an alternative to parametric filtering methods by providing results of common cycle extraction using Unobserved component model alternatives.<br>This thesis includes two essays that are focused on developing multivariate filter approaches to be used for extracting common cyclical components where the common components can be used as an estimator of a business cycle. The first chapter aims to develop an optimal multivariate filter in order to extract common cyclical components of macroeconomic indicators. The filter allows macroeconomic series to be modeled as a phase shifted version of a coinciding business cycle (BC) while keeping other time series components such as the stochastic trend and idiosyncratic shocks intact (i.e. they are individually specified for each series). Earlier studies of Rünstler (2004), Valle e Azevedo et al. (2006) have applied phase shift in the form of a delay parameter when specifying lead-lag cycles. However, the lead-lag relationship is defined by rotating the baseline cycle which leads to loss of information. This deficiency is especially important if one considers working in continuous time. Therefore, this paper improves on the former technique by allowing a more flexible phase shift mechanism on the original BC. This in turn should lead to more realistic estimates and filters considering that the underlying data is generated through a continuous time framework. The study starts by presenting a structure for bi-variate time series system and then extends to model to incorporate a structure for three time series and beyond. Kalman filter and smoothing recursions are applied to compute the smoothed cycle estimates and to construct the likelihood function. Using simulated data, we test both model specifications by carrying out a grid search of the initial delay parameter to see the likelihood behavior as the parameter moves into fractional neighborhoods. Afterwards, applying the methodology to a set of EU countries and macroeconomic indicators; the study aims to shed light to the presence of cyclical heterogeneity at country level economic activity for major EU member states. A second empirical study provides analysis on how the model can be implemented for assigning a lead/lag ordering to three main economic indicators of a single country. The second chapter implements a multivariate non-parametric filtering approach; the Vertical Multivariate Singular Spectrum Analysis (V-MSSA) of Hassani and Mahmoudvand (2013) and Golyandina et al. (2013). to be applied for identifying a common economic cycle indicator. The methodology is a data-driven procedure that can decompose a time series into many sub components. By exploiting this ability of the SSA, the paper aims to first extract cyclical components based on frequency characteristics and then follow by choosing only common cyclical component pairs with-in the business cycle frequency spectrum. These components will then be aggregated for constructing an EU region wide Business cycle indicator. The chapter outlines each steps of the algorithm that will eventually identify the SSA filter to act as a band-pass filter. The study then proceeds with simulation based data where the common cycle can be controlled and extracted a priori as a benchmark to the SSA-based filter estimates. The study follows with an empirical analysis similar to the framework set in Valle e Azevedo et al. (2006) with the aim to identify a Euro region business cycle indicator. The SSA based filter estimate is compared with Euro region economic activity indicators; the EuroCoin and the quarterly GDP growth rate of the EU area. Our results presents evidence of a successful alternative for tracing the cyclical position of the EU economy from a much smaller data set. Moreover, the constructed indicator also could serve as an unobserved proxy for a monthly growth cycle. A further analysis is also conducted to reveal whether the SSA based approach can be considered as an alternative to parametric filtering methods by providing results of common cycle extraction using Unobserved component model alternatives.

Submitted by Leonardo Correia (lehito@gmail.com) on 2012-06-29T16:37:54Z No. of bitstreams: 1 tese.pdf: 743259 bytes, checksum: 3aa4903f65bfe4fe1e02efdfb5a75fb1 (MD5)<br>Approved for entry into archive by Vera Lúcia Mourão (vera.mourao@fgv.br) on 2012-06-29T16:56:35Z (GMT) No. of bitstreams: 1 tese.pdf: 743259 bytes, checksum: 3aa4903f65bfe4fe1e02efdfb5a75fb1 (MD5)<br>Made available in DSpace on 2012-06-29T17:03:30Z (GMT). No. of bitstreams: 1 tese.pdf: 743259 bytes, checksum: 3aa4903f65bfe4fe1e02efdfb5a75fb1 (MD5) Previous issue date: 2012-06-01<br>O objetivo desse trabalho é obter um conjunto de evidências empíricas a respeito da dinâmica econômica de curto-prazo das regiões brasileiras para avaliar se as diferenças regionais resultam em ausência de sincronia econômica. Foi construida uma séries de evidências acerca do comportamento cíclico das regiões brasileiras, sendo uma parte delas por datação via o algoritmo de Bry Boschan e outra parte por meio da construção de um indicador do nível de atividade, pela metodologia de Stock e Watson de fatores dinâmicos. Em decorrência à dificuldade de disponibilidade de dados, só foi possível analisar dez estados brasileiros. Apesar das evidências geradas pelo algoritmo de Bry Boschan terem diferenças em relação as evidências geradas pelo modelo de Stock Watson, foi possível constatar que os ciclos regionais são bastante diferentes se comparados com os ciclos nacionais, sendo São Paulo o Estado que possui a maior sincronia e os Estados de Pernambuco e Rio Grande do Sul as menores. No entanto, duas recessões foram captadas na maioria dos estados, a de 2002 e a de 2008, sugerindo o quanto esses períodos foram abrangentes sendo que boa parte dos estados foi afetada.<br>The main objective of this study is to build empirical evidences regarding the economic dynamic of the Brazilian states in order to evaluate the absence of economic synchronism is resulted by regional differences. To build these evidences, two frameworks were used, the Bry Boschan algorithm and the Stock Watson dynamic factor model. Due to the lack of data, this analysis could only be made for ten out of 26 Brazilian states. Although there are considerable differences between these frameworks, it is posible to conclude that the synchronization between the analyzed cycles is limited. The most synchronized is Sao Paulo and the less is Pernambuco and Rio Grande do Sul. However, two recessions were detected by the models in most states: the 2002 and the 2008, sugesting the extension of the impact in overall economy of those periods.