IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v320y2022ics0306261922006511.html
   My bibliography  Save this article

Multi-objective performance optimization and control for gas turbine Part-load operation Energy-saving and NOx emission reduction

Author

Listed:
  • Ma, Yujia
  • Liu, Jinfu
  • Zhu, Linhai
  • Li, Qi
  • Guo, Yaqiong
  • Liu, Huanpeng
  • Yu, Daren

Abstract

This work aims to apply the multi-objective optimization method to gas turbine part-load energy-saving and NOx (Nitrogen Oxides) emission reduction problem. For power generation gas turbines, energy-saving is based on raising the thermal efficiency of the system. This is always based on regulating the variable geometries of the plant. However, in this process, the combustion condition would be changed, which would further change the NOx pollutant emission level. Therefore, in this paper, the conflict between gas turbine thermal efficiency enhancement and NOx emission reduction is discovered and analyzed with a nonlinear model. To solve this multi-objective optimization problem, GA (Genetic Algorithm), a global optimization algorithm, is applied. The two objectives are thermal efficiency for energy-saving and NOx Emission Index (EINOx) for pollution reduction. The fuel mass flow rate and compressor Inlet Guide Vane (IGV) position are the decision variables. Optimization is conducted for 50% to 90% nominal power levels and 5 °C to 25 °C ambient temperatures. With the non-inferior solutions on the Pareto Front and a trade-off decision, the selected gas turbine optimum working point can be obtained with a nonlinear converter module. For 15 °C, 70% nominal power working condition, increasing the fuel mass flow rate by 0.216% and IGV degree by 10.344% can bring a 46.273% reduction of EINOx, with the cost of a 0.212% decline in the thermal efficiency. The sensitivity analysis of the Pareto Frontiers to power level and ambient temperature is carried out. Then the level of energy-saving is analyzed by calculating the cost of fuel, and a trade-off suggestion is given. In the end, the values of the decision variables and objective functions under three trade-off scenarios are calculated and listed in a table, with which the final solution can be decided conveniently according to practical demands.

Suggested Citation

  • Ma, Yujia & Liu, Jinfu & Zhu, Linhai & Li, Qi & Guo, Yaqiong & Liu, Huanpeng & Yu, Daren, 2022. "Multi-objective performance optimization and control for gas turbine Part-load operation Energy-saving and NOx emission reduction," Applied Energy, Elsevier, vol. 320(C).
    • Handle: RePEc:eee:appene:v:320:y:2022:i:c:s0306261922006511
    DOI: 10.1016/j.apenergy.2022.119296
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922006511
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.119296?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pires, Thiago S. & Cruz, Manuel E. & Colaço, Marcelo J. & Alves, Marco A.C., 2018. "Application of nonlinear multivariable model predictive control to transient operation of a gas turbine and NOX emissions reduction," Energy, Elsevier, vol. 149(C), pages 341-353.
    2. Kayadelen, Hasan Kayhan & Ust, Yasin, 2017. "Thermodynamic, environmental and economic performance optimization of simple, regenerative, STIG and RSTIG gas turbine cycles," Energy, Elsevier, vol. 121(C), pages 751-771.
    3. Song, Yin & Gu, Chun-wei & Ji, Xing-xing, 2015. "Development and validation of a full-range performance analysis model for a three-spool gas turbine with turbine cooling," Energy, Elsevier, vol. 89(C), pages 545-557.
    4. Tsoutsanis, Elias & Meskin, Nader & Benammar, Mohieddine & Khorasani, Khashayar, 2014. "A component map tuning method for performance prediction and diagnostics of gas turbine compressors," Applied Energy, Elsevier, vol. 135(C), pages 572-585.
    5. Khidr, Kareem I. & Eldrainy, Yehia A. & EL-Kassaby, Mohamed M., 2017. "Towards lower gas turbine emissions: Flameless distributed combustion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1237-1266.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Yu-Zhi & Zhao, Xu-Dong & Xiang, Heng-Chao & Tsoutsanis, Elias, 2021. "A sequential model-based approach for gas turbine performance diagnostics," Energy, Elsevier, vol. 220(C).
    2. Zong, Chao & Ji, Chenzhen & Cheng, Jiaying & Zhu, Tong & Guo, Desan & Li, Chengqin & Duan, Fei, 2022. "Toward off-design loads: Investigations on combustion and emissions characteristics of a micro gas turbine combustor by external combustion-air adjustments," Energy, Elsevier, vol. 253(C).
    3. Kim, Jeong Ho & Kim, Tong Seop, 2019. "A new approach to generate turbine map data in the sub-idle operation regime of gas turbines," Energy, Elsevier, vol. 173(C), pages 772-784.
    4. Tu, Yaojie & Xu, Shunta & Xu, Mingchen & Liu, Hao & Yang, Wenming, 2020. "Numerical study of methane combustion under moderate or intense low-oxygen dilution regime at elevated pressure conditions up to 8 atm," Energy, Elsevier, vol. 197(C).
    5. Mohammadpour, Mohammadreza & Houshfar, Ehsan & Ashjaee, Mehdi & Mohammadpour, Amirreza, 2021. "Energy and exergy analysis of biogas fired regenerative gas turbine cycle with CO2 recirculation for oxy-fuel combustion power generation," Energy, Elsevier, vol. 220(C).
    6. Cheng, Xianda & Zheng, Haoran & Dong, Wei & Yang, Xuesen, 2023. "Performance prediction of marine intercooled cycle gas turbine based on expanded similarity parameters," Energy, Elsevier, vol. 265(C).
    7. Son, Seongmin & Jeong, Yongju & Cho, Seong Kuk & Lee, Jeong Ik, 2020. "Development of supercritical CO2 turbomachinery off-design model using 1D mean-line method and Deep Neural Network," Applied Energy, Elsevier, vol. 263(C).
    8. Xu, Shunta & Xi, Liyang & Tian, Songjie & Tu, Yaojie & Chen, Sheng & Zhang, Shihong & Liu, Hao, 2023. "Numerical investigation of pressure and H2O dilution effects on NO formation and reduction pathways in pure hydrogen MILD combustion," Applied Energy, Elsevier, vol. 350(C).
    9. Shizheng Liu & Ningbo Zhao & Jianguo Zhang & Jialong Yang & Zhiming Li & Hongtao Zheng, 2019. "Experimental and Numerical Investigations of Plasma Ignition Characteristics in Gas Turbine Combustors," Energies, MDPI, vol. 12(8), pages 1-16, April.
    10. Yang, Xiao & He, Zhihong & Qiu, Penghua & Dong, Shikui & Tan, Heping, 2019. "Numerical investigations on combustion and emission characteristics of a novel elliptical jet-stabilized model combustor," Energy, Elsevier, vol. 170(C), pages 1082-1097.
    11. Alizadeh, Sadegh & Rezazadeh, Ali Akbar & Avami, Akram, 2024. "A cutting-edge tool for sustainable environmental management through life cycle assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    12. Kang, Do Won & Kim, Tong Seop, 2018. "Model-based performance diagnostics of heavy-duty gas turbines using compressor map adaptation," Applied Energy, Elsevier, vol. 212(C), pages 1345-1359.
    13. Montazerinejad, H. & Eicker, U., 2022. "Recent development of heat and power generation using renewable fuels: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    14. Cheng, Xianda & Zheng, Haoran & Yang, Qian & Zheng, Peiying & Dong, Wei, 2023. "Surrogate model-based real-time gas path fault diagnosis for gas turbines under transient conditions," Energy, Elsevier, vol. 278(PA).
    15. Alessandro Rosini & Alessandro Palmieri & Damiano Lanzarotto & Renato Procopio & Andrea Bonfiglio, 2019. "A Model Predictive Control Design for Power Generation Heavy-Duty Gas Turbines," Energies, MDPI, vol. 12(11), pages 1-17, June.
    16. He, Li & Fan, Yilin & Bellettre, Jérôme & Yue, Jun & Luo, Lingai, 2020. "A review on catalytic methane combustion at low temperatures: Catalysts, mechanisms, reaction conditions and reactor designs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    17. Liao, Zengbu & Zhan, Keyi & Zhao, Hang & Deng, Yuntao & Geng, Jia & Chen, Xuefeng & Song, Zhiping, 2024. "Addressing class-imbalanced learning in real-time aero-engine gas-path fault diagnosis via feature filtering and mapping," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    18. Hosseinalipour, S.M. & Fattahi, A. & Khalili, H. & Tootoonchian, F. & Karimi, N., 2020. "Experimental investigation of entropy waves’ evolution for understanding of indirect combustion noise in gas turbine combustors," Energy, Elsevier, vol. 195(C).
    19. Cody Allen & Mauricio Oliveira, 2022. "A Minimal Cardinality Solution to Fitting Sawtooth Piecewise-Linear Functions," Journal of Optimization Theory and Applications, Springer, vol. 192(3), pages 930-959, March.
    20. Kong, Xiaobing & Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Lee, Kwang Y., 2023. "Stable feedback linearization-based economic MPC scheme for thermal power plant," Energy, Elsevier, vol. 268(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:320:y:2022:i:c:s0306261922006511. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.