Micro-Turbine Design Point Definition Using Genetic Algorithm With Single and Multi-Objective Optimization

Author(s):  
Diogo F. Cavalca ◽  
Cleverson Bringhenti

During a gas turbine development phase an important engineer task is to find the appropriate engine design point that meet the required specifications. This task can be very arduous because all possible operating points in the gas turbine operational envelope need to be analyzed, for the sake of verification of whether or not the established performance might be achieved. In order to support engineers to best define the engine design point that meet required performance a methodology was developed in this work. To accomplish that a computer program was written in Matlab®. In this program was incorporated the thermoeconomic and thermodynamic optimization. The thermodynamic calculation process was done based in enthalpy and entropy function and then validated using a commercial program. The methodology uses genetic algorithm with single and multi-objective optimization. The micro gas turbine cycle chosen to study was the recuperated. The cycle efficiency, total cost and specific work were chosen as objective functions, while the pressure ratio, compressor and turbine polytropic efficiencies, turbine inlet temperature and heat exchange effectiveness were chosen as decision variables. For total cost were considered the fixed costs (equipment, installation, taxes, etc.) and variable costs (fuel, environmental and O&M). For emissions were taken into account the NOx, CO and UHC. An economic analysis was done for a recuperated cycle showing the costs behavior for different optimized design points. The optimization process was made for: single-objective, where each objective was optimized separately; two-objectives, where they were optimized in pairs; three-objectives, where it was optimized in trio. After, the results were compared each other showing the possible design points.

Author(s):  
H Sayyaadi ◽  
H R Aminian

A regenerative gas turbine cycle with two particular tubular recuperative heat exchangers in parallel is considered for multi-objective optimization. It is assumed that tubular recuperative heat exchangers and its corresponding gas cycle are in design stage simultaneously. Three objective functions including the purchased equipment cost of recuperators, the unit cost rate of the generated power, and the exergetic efficiency of the gas cycle are considered simultaneously. Geometric specifications of the recuperator including tube length, tube outside/inside diameters, tube pitch, inside shell diameter, outer and inner tube limits of the tube bundle and the total number of disc and doughnut baffles, and main operating parameters of the gas cycle including the compressor pressure ratio, exhaust temperature of the combustion chamber and the air mass flowrate are considered as decision variables. Combination of these objectives anddecision variables with suitable engineering and physical constraints (including NO x and CO emission limitations) comprises a set of mixed integer non-linear problems. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms, namely non-dominated sorting genetic algorithm. This approach is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained, and a final optimal solution is selected in a decision-making process.


Author(s):  
Hang Zhao ◽  
Qinghua Deng ◽  
Wenting Huang ◽  
Dian Wang ◽  
Zhenping Feng

Supercritical CO2 Brayton cycles (SCO2BC) including the SCO2 single-recuperated Brayton cycle (RBC) and recompression recuperated Brayton cycle (RRBC) are considered, and flexible thermodynamic and economic modeling methodologies are presented. The influences of the key cycle parameters on thermodynamic performance of SCO2BC are studied, and the comparative analyses on RBC and RRBC are conducted. Nondominated Sorting Genetic Algorithm II (NSGA-II) is selected for the Pareto-based multi-objective optimization of the RRBC, with the maximum exergy efficiency and the lowest cost per power (k$/kW) as its objectives. Artificial neural network (ANN) is chosen to accelerate the parameters query process. It is shown that the cycle parameters such as heat source temperature, turbine inlet temperature, cycle pressure ratio, and pinch temperature difference of heat exchangers have significant effects on the cycle exergy efficiency. The exergy destruction of heat exchanger is the main reason why the exergy efficiency of RRBC is higher than that of the RBC under the same cycle conditions. RBC has a cost advantage from economic perspective, while RRBC has a much better thermodynamic performance, and could rectify the temperature pinching problem that exists in RBC. It is also shown that there is a conflicting relationship between the cycle cost/cycle power (CWR) and the cycle exergy efficiency. The optimization results could provide an optimum tradeoff curve enabling cycle designers to choose their desired combination between the efficiency and cost. ANN could help the users to find the SCO2BC parameters fast and accurately.


Author(s):  
Marcelo Ramos Martins ◽  
Diego F. Sarzosa Burgos

The cost of a new ship design heavily depends on the principal dimensions of the ship; however, dimensions minimization often conflicts with the minimum oil outflow (in the event of an accidental spill). This study demonstrates one rational methodology for selecting the optimal dimensions and coefficients of form of tankers via the use of a genetic algorithm. Therein, a multi-objective optimization problem was formulated by using two objective attributes in the evaluation of each design, specifically, total cost and mean oil outflow. In addition, a procedure that can be used to balance the designs in terms of weight and useful space is proposed. A genetic algorithm was implemented to search for optimal design parameters and to identify the nondominated Pareto frontier. At the end of this study, three real ships are used as case studies.


Author(s):  
E. Lo Gatto ◽  
Y. G. Li ◽  
P. Pilidis

Gas turbine gas path diagnostics is heavily dependent on performance simulation models accurate enough around a chosen diagnostic operating point, such as design operating point. With current technology, gas turbine engine performance can be predicted easily with thermodynamic models and computer codes together with basic engine design data and empirical component information. However the accuracy of the prediction is highly dependent on the quality of those engine design data and empirical component information such as component characteristic maps but such expensive information is normally exclusive property of engine manufacturers and only partially disclosed to engine users. Alternatively, estimated design data and assumed component information are used in the performance prediction. Yet, such assumed component information may not be the same as those of real engines and therefore poor off-design performance prediction may be produced. This paper presents an adaptive method to improve the accuracy of off-design performance prediction of engine models near engine design point or other points where detailed knowledge is available. A novel definition of off-design scaling factors for the modification of compressor maps is developed. A Genetic Algorithm is used to search the best set of scaling factors in order to adapt the predicted off-design engine performance to observed engine off-design performance. As the outcome of the procedure, new compressor maps are produced and more accurate prediction of off-design performance is provided. The proposed off-design performance adaptation procedure is applied to a model civil aero engine to test the effectiveness of the adaptive approach. The results show that the developed adaptive approach, if properly applied, has great potential to improve the accuracy of engine off-design performance prediction in the vicinity of engine design point although it does not guarantee the prediction accuracy in the whole range of off-design conditions. Therefore, such adaptive approach provides an alternative method in producing good engine performance models for gas turbine gas path diagnostic analysis.


2018 ◽  
Vol 22 (6 Part A) ◽  
pp. 2641-2651 ◽  
Author(s):  
Moein Shamoushaki ◽  
Mehdi Ehyaei

In this paper, exergy, exergoeconomic, and exergoenvironmental analysis of a gas turbine cycle and its optimization has been carried out by MOPSO algorithm. Three objective functions, namely, total cost rate, exergy efficiency of cycle, and CO2 emission rate have been considered. The design variables considered are: compressor pressure ratio, combustion chamber inlet temperature, gas turbine inlet temperature, compressor, and gas turbine isentropic efficiency. The impact of change in gas turbine inlet temperature and compressor pressure ratio on CO2 emission rate as well as impact of changes in gas turbine inlet temperature on exergy efficiency of the cycle has been investigated in different compressor pressure ratios. The results showed that with increase in compressor pressure ratio and gas turbine inlet temperature, CO2 emission rate decreases, that is this reduction is carried out with a steeper slope at lower pressure compressor ratio and gas turbine inlet temperature. The results showed that exergy efficiency of the cycle increases with increase in gas turbine inlet temperature and compressor pressure ratio. The sensitivity analysis of fuel cost changes was performed on objective functions. The results showed that at higher exergy efficiencies total cost rate is greater, and sensitivity of fuel cost optimum solutions is greater than Pareto curve with lower total cost rate. Also, the results showed that sensitivity of changes in fuel cost rate per unit of energy on total cost rate is greater than the rate of CO2 emission.


Author(s):  
S. Y. Kim ◽  
M. R. Park ◽  
S. Y. Cho

This paper describes on/off design performance of a 50KW turbogenerator gas turbine engine for hybrid vehicle application. For optimum design point selection, a relevant pa4rameter study is carried out. The turbogenerator gas turbine engine for a hybrid vehicle is expected to be designed for maximum fuel economy, ultra low emissions, and very low cost. A compressor, combustor, turbine, and a permanent-magnet generator will be mounted on a single high speed (80,000 rpm) shaft that will be supported on air bearings. As the generator is built into the shaft, gearbox and other moving parts become unnecessary and thus will increase the system’s reliability and reduce the manufacturing cost. The engine has a radial compressor and turbine with design point pressure ratio of 4.0. This pressure ratio was set based on calculation of specific fuel consumption and specific power variation with pressure ratio. For the turbine inlet temperature, a rather conservative value of 1100K was selected. Designed mass flow rate was 0.5 kg/sec. Parametric study of the cycle indicates that specific work and efficiency increase at a given pressure ratio and turbine inlet temperature. Off design analysis shows that the gas turbine system reaches self operating condition at about N/NDP = 0.48. Bleeding air for a turbine stator cooling is omitted considering the low TIT in the present engine and to enable the simple geometric configuration for manufacturing purpose. Various engine performance simulations including ambient temperature influence, surging at part load condition; transient analysis were performed to secure the optimum engine operating characteristics. Surge margin throughout the performance analysis were maintained to be over 50% approximately. Present analysis will be compared with performance test result which is scheduled at the end of 1998.


Author(s):  
A. F. Massardo ◽  
M. Scialò

The thermoeconomic analysis of gas turbine based cycles is presented and discussed in this paper. The thermoeconomic analysis has been performed using the ThermoEconomic Modular Program (TEMP V.5.0) developed by the Authors (Agazzani and Massardo, 1997). The modular structure of the code allows the thermoeconomic analysis for different scenarios (turbine inlet temperature, pressure ratio, fuel cost, installation costs, operating hours per year, etc.) of a large number of advanced gas turbine cycles to be obtained in a fast and reliable way. The simple cycle configuration results have been used to assess the cost functions and coefficient values. The results obtained for advanced gas turbine based cycles (intercooled, re-heated, regenerated and their combinations) are presented using new and useful representations: cost vs. efficiency, cost vs. specific work, and cost vs. pressure ratio. The results, including productive diagram configurations, are discussed in detail and compared to one another.


Author(s):  
Roozbeh Zomorodian ◽  
Hiwa Khaledi ◽  
Mohammad Bagher Ghofrani

Application of Cogeneration systems based gas turbine for heat and power production is increasing. Because of finite natural energy resources and increasing energy demand the cost effective design of energy systems is essential. CGAM problem as a cogeneration system is considered here for analyzing. Two new approaches are considered, first in thermodynamic model of gas turbine and cogeneration system considering blade cooling of gas turbine and second using genetic algorithm for optimization. The problem has been optimized from thermodynamic and Thermoeconomic view point. Results show that Turbine Inlet Temperature (TIT) in thermodynamic optimum condition is higher than thermoeconomic one, while blade cooling technology must be better for optimum thermodynamic condition. Heat recovery of recuperator is lower in thermoeconomic case; also, stack temperature is higher relative to thermodynamic case. The sensitivity of the optimal solution to the decision variables is studied. It has been shown that while for both thermodynamic and thermoeconomic optimum condition, pressure ratio, blade cooling technology factor and pinch-point temperature difference (only for thermoeconomic case) has the lowest effect, turbomachinary efficiencies (epically compressor polytropic efficiency) have the major effect on performance of cycle. Finally; a new product known as Mercury 50 gas turbine is studied for a cogeneration system and it has been optimized thermoeconomicly. Results show good agreement with manufacturer data.


Author(s):  
Sanjay ◽  
Onkar Singh ◽  
B. N. Prasad

The paper deals with the thermodynamic performance of combined and cogeneration cycles using the state of the art gas turbines. A configuration has been conceptualized using the latest gas turbine MS9001H that uses steam to cool the hot gas path components. In order to study the effect of cooling means, the same gas turbine is subjected to transpiration air cooling. Using the above mentioned conceptualized topping cycle, the bottoming cycle selected consists of a two-pressure reheat heat recovery steam generator (HRSG) with reheat having two options. First option is the integrated system (IS), which is a combined/cogeneration cycle, and the other is called the normal cogeneration cycle (NC). Both of these cycles are subjected to steam and transpiration air-cooling. The cycle performance is predicted based on parameteric study which has been carried out by modeling the various elements of cycle such as gas, compressor combustor, cooed gas turbine, HRSG steam turbine, condenser, etc. The performance is predicted for parameters such as fuel utilization efficiency (ηf), power-to-heat-ratio (PHR), coolant flow requirements, plant specific work, etc. as a function of independent parameters such as compressor pressure ratio (rpc) and turbine inlet temperature (TIT), etc. The results predicted will be helpful for designers to select the optimum compressor pressure ratio and TIT to achieve the target fuel utilization efficiency, and PHR at the target plant specific work.


Author(s):  
Meherwan P. Boyce ◽  
Cyrus B. Meher-Homji ◽  
A. N. Lakshminarasimha

A wide variety of gas turbine based cycles exist in the market today with several technologies being promoted by individual Original Equipment Manufacturers. This paper is focused on providing users with a conceptual framework within which to view these cycles and choose suitable options for their needs. A basic parametric analysis is provided to show the interdependency of Turbine Inlet Temperature (TIT) and Pressure Ratio on cycle efficiency and specific work.


Sign in / Sign up

Export Citation Format

Share Document