{"title":"基于RSM的蓄热式燃气轮机电厂性能分析与优化","authors":"Moumtez Bensouici, Mohamed Walid Azizi, Fatima Zohra Bensouici","doi":"10.15282/ijame.20.3.2023.10.0824","DOIUrl":null,"url":null,"abstract":"In the present study, a thermodynamic analysis of thermal performance is carried out in a regenerative GT power plant. The optimization procedure of design parameters is realized by the response surface methodology (RSM). The thermodynamic simulations were carried out using the EES code for numerous variables such as compression ratio (2≤rp≤12), inlet temperature (273≤T1≤313K), turbine inlet temperature (1200≤T3≤1600K), and regenerator effectiveness (45≤ε≤85%). Analysis of variance (ANOVA) was carried out to identify the process parameters that influence thermal efficiency (ηth) and specific fuel consumption (SFC). Then, a second-order regression model was developed to correlate the process parameters with ηth and SFC. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are ηth=50.61% and SFC=0.117 kg/kWh, corresponding to process parameters T1=273.26K, T3=1597.64K, rp=6.95 and ε=84.89%. Lastly, verification simulations were conducted to validate the importance of the generated statistical models.","PeriodicalId":13935,"journal":{"name":"International Journal of Automotive and Mechanical Engineering","volume":"14 1","pages":"0"},"PeriodicalIF":1.0000,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance Analysis and Optimization of Regenerative Gas Turbine Power Plant using RSM\",\"authors\":\"Moumtez Bensouici, Mohamed Walid Azizi, Fatima Zohra Bensouici\",\"doi\":\"10.15282/ijame.20.3.2023.10.0824\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the present study, a thermodynamic analysis of thermal performance is carried out in a regenerative GT power plant. The optimization procedure of design parameters is realized by the response surface methodology (RSM). The thermodynamic simulations were carried out using the EES code for numerous variables such as compression ratio (2≤rp≤12), inlet temperature (273≤T1≤313K), turbine inlet temperature (1200≤T3≤1600K), and regenerator effectiveness (45≤ε≤85%). Analysis of variance (ANOVA) was carried out to identify the process parameters that influence thermal efficiency (ηth) and specific fuel consumption (SFC). Then, a second-order regression model was developed to correlate the process parameters with ηth and SFC. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are ηth=50.61% and SFC=0.117 kg/kWh, corresponding to process parameters T1=273.26K, T3=1597.64K, rp=6.95 and ε=84.89%. Lastly, verification simulations were conducted to validate the importance of the generated statistical models.\",\"PeriodicalId\":13935,\"journal\":{\"name\":\"International Journal of Automotive and Mechanical Engineering\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2023-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Automotive and Mechanical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15282/ijame.20.3.2023.10.0824\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Automotive and Mechanical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15282/ijame.20.3.2023.10.0824","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
Performance Analysis and Optimization of Regenerative Gas Turbine Power Plant using RSM
In the present study, a thermodynamic analysis of thermal performance is carried out in a regenerative GT power plant. The optimization procedure of design parameters is realized by the response surface methodology (RSM). The thermodynamic simulations were carried out using the EES code for numerous variables such as compression ratio (2≤rp≤12), inlet temperature (273≤T1≤313K), turbine inlet temperature (1200≤T3≤1600K), and regenerator effectiveness (45≤ε≤85%). Analysis of variance (ANOVA) was carried out to identify the process parameters that influence thermal efficiency (ηth) and specific fuel consumption (SFC). Then, a second-order regression model was developed to correlate the process parameters with ηth and SFC. Consequently, numerical and graphical optimizations were performed to achieve multi-objective optimization for the desired criteria. According to the desirability function approach, it can be seen that the optimum objective functions are ηth=50.61% and SFC=0.117 kg/kWh, corresponding to process parameters T1=273.26K, T3=1597.64K, rp=6.95 and ε=84.89%. Lastly, verification simulations were conducted to validate the importance of the generated statistical models.
期刊介绍:
The IJAME provides the forum for high-quality research communications and addresses all aspects of original experimental information based on theory and their applications. This journal welcomes all contributions from those who wish to report on new developments in automotive and mechanical engineering fields within the following scopes. -Engine/Emission Technology Automobile Body and Safety- Vehicle Dynamics- Automotive Electronics- Alternative Energy- Energy Conversion- Fuels and Lubricants - Combustion and Reacting Flows- New and Renewable Energy Technologies- Automotive Electrical Systems- Automotive Materials- Automotive Transmission- Automotive Pollution and Control- Vehicle Maintenance- Intelligent Vehicle/Transportation Systems- Fuel Cell, Hybrid, Electrical Vehicle and Other Fields of Automotive Engineering- Engineering Management /TQM- Heat and Mass Transfer- Fluid and Thermal Engineering- CAE/FEA/CAD/CFD- Engineering Mechanics- Modeling and Simulation- Metallurgy/ Materials Engineering- Applied Mechanics- Thermodynamics- Agricultural Machinery and Equipment- Mechatronics- Automatic Control- Multidisciplinary design and optimization - Fluid Mechanics and Dynamics- Thermal-Fluids Machinery- Experimental and Computational Mechanics - Measurement and Instrumentation- HVAC- Manufacturing Systems- Materials Processing- Noise and Vibration- Composite and Polymer Materials- Biomechanical Engineering- Fatigue and Fracture Mechanics- Machine Components design- Gas Turbine- Power Plant Engineering- Artificial Intelligent/Neural Network- Robotic Systems- Solar Energy- Powder Metallurgy and Metal Ceramics- Discrete Systems- Non-linear Analysis- Structural Analysis- Tribology- Engineering Materials- Mechanical Systems and Technology- Pneumatic and Hydraulic Systems - Failure Analysis- Any other related topics.