IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i19p4860-d1487550.html
   My bibliography  Save this article

Enhancing the Energy Performance of a Gas Turbine: Component of a High-Efficiency Cogeneration Plant

Author

Listed:
  • Roxana Grigore

    (The Department of Power Engineering and Computer Science, Faculty of Engineering, “Vasile Alecsandri” University of Bacau, 600115 Bacau, Romania)

  • Aneta Hazi

    (The Department of Power Engineering and Computer Science, Faculty of Engineering, “Vasile Alecsandri” University of Bacau, 600115 Bacau, Romania)

  • Ioan Viorel Banu

    (The Department of Power Engineering and Computer Science, Faculty of Engineering, “Vasile Alecsandri” University of Bacau, 600115 Bacau, Romania)

  • Sorin Eugen Popa

    (The Department of Power Engineering and Computer Science, Faculty of Engineering, “Vasile Alecsandri” University of Bacau, 600115 Bacau, Romania)

  • Sorin Gabriel Vernica

    (The Department of Power Engineering and Computer Science, Faculty of Engineering, “Vasile Alecsandri” University of Bacau, 600115 Bacau, Romania)

Abstract

Cogeneration is widely recognized as one of the most efficient methods of electricity generation, with gas turbine-based systems playing a critical role in ensuring reliability, sustainability, and consistent power output. This paper presents an energy efficiency analysis of a 14 MW high-efficiency cogeneration unit, featuring a modernized gas turbine as its core component. Since gas turbines often operate under varying loads due to fluctuating demand, this study examines their performance at 100%, 75%, and 50% load levels. It is observed that the efficiency of the gas turbine declines as the load decreases, primarily due to losses resulting from deviations from the design flow conditions. A detailed energy balance, Sankey diagram, and a comparative analysis of performance metrics against the manufacturer’s guarantees are provided for each load scenario. The results indicate that net thermal efficiency decreases by 10.7% at 75% load and by 30.6% at 50% load compared to nominal performance at full load. The performance at full load closely aligns with the values guaranteed by the gas turbine supplier. The gross electrical power output is 1.33% higher than the guaranteed value, and the thermodynamic circuit’s efficiency is 0.49% higher under real conditions. This study represents the initial phase of transitioning the turbine to operate on a fuel blend of natural gas and up to 20% hydrogen, with the goal of reducing CO 2 emissions. As a novel contribution, this paper provides a systematized method for calculating and monitoring the in-service performance of gas turbines. The mathematical model is implemented using the Mathcad Prime 8.0 software, which proves to be beneficial for both operators and researchers.

Suggested Citation

  • Roxana Grigore & Aneta Hazi & Ioan Viorel Banu & Sorin Eugen Popa & Sorin Gabriel Vernica, 2024. "Enhancing the Energy Performance of a Gas Turbine: Component of a High-Efficiency Cogeneration Plant," Energies, MDPI, vol. 17(19), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:19:p:4860-:d:1487550
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/19/4860/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/19/4860/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Rufeng & Chen, Yan & Li, Zhengmao & Jiang, Tao & Li, Xue, 2024. "Two-stage robust operation of electricity-gas-heat integrated multi-energy microgrids considering heterogeneous uncertainties," Applied Energy, Elsevier, vol. 371(C).
    2. Donato Cecere & Eugenio Giacomazzi & Antonio Di Nardo & Giorgio Calchetti, 2023. "Gas Turbine Combustion Technologies for Hydrogen Blends," Energies, MDPI, vol. 16(19), pages 1-29, September.
    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. Khusniddin Alikulov & Zarif Aminov & La Hoang Anh & Tran Dang Xuan & Wookyung Kim, 2024. "Comparative Technical and Economic Analyses of Hydrogen-Based Steel and Power Sectors," Energies, MDPI, vol. 17(5), pages 1-30, March.
    2. Fabio Massaro & Maria Luisa Di Silvestre & Marco Ferraro & Francesco Montana & Eleonora Riva Sanseverino & Salvatore Ruffino, 2024. "Energy Hub Model for the Massive Adoption of Hydrogen in Power Systems," Energies, MDPI, vol. 17(17), pages 1-31, September.
    3. Beata Kurc & Xymena Gross & Natalia Szymlet & Łukasz Rymaniak & Krystian Woźniak & Marita Pigłowska, 2024. "Hydrogen-Powered Vehicles: A Paradigm Shift in Sustainable Transportation," Energies, MDPI, vol. 17(19), pages 1-38, September.
    4. Simona Di Fraia & Rafał Figaj & Musannif Shah & Laura Vanoli, 2024. "Biomass-Driven Polygeneration Coupled to Power-to-X: An Energy and Economic Comparison Between On-Site Electric Vehicle Charging and Hydrogen Production," Energies, MDPI, vol. 17(21), pages 1-24, November.
    5. Keyong Hu & Qingqing Yang & Lei Lu & Yu Zhang & Shuifa Sun & Ben Wang, 2025. "Two-Stage Distributionally Robust Optimal Scheduling for Integrated Energy Systems Considering Uncertainties in Renewable Generation and Loads," Mathematics, MDPI, vol. 13(9), pages 1-30, April.
    6. Donato Cecere & Matteo Cimini & Simone Carpenella & Jan Caldarelli & Eugenio Giacomazzi, 2024. "Composition and Injection Angle Effects on Combustion of an NH 3 /H 2 /N 2 Jet in an Air Crossflow," Energies, MDPI, vol. 17(20), pages 1-21, October.
    7. Yongjie Yang & Yulong Li & Yan Cai & Hui Tang & Peng Xu, 2024. "Data-Driven Golden Jackal Optimization–Long Short-Term Memory Short-Term Energy-Consumption Prediction and Optimization System," Energies, MDPI, vol. 17(15), pages 1-20, July.
    8. Eugenio Giacomazzi & Donato Cecere & Matteo Cimini & Simone Carpenella, 2023. "Direct Numerical Simulation of a Reacting Turbulent Hydrogen/Ammonia/Nitrogen Jet in an Air Crossflow at 5 Bar," Energies, MDPI, vol. 16(23), pages 1-17, November.
    9. Zhong, Junjie & Zhao, Yirui & Cao, Yijia, 2024. "Collaborative optimization for energy hub and load aggregator considering the carbon intensity-driven and uncertainty-aware," Energy, Elsevier, vol. 312(C).
    10. Yinguo Yang & Ying Yang & Qiuyu Lu & Dexu Liu & Pingping Xie & Mu Wang & Zhenfan Yu & Yang Liu, 2024. "Comprehensive Evaluation of a Pumped Storage Operation Effect Considering Multidimensional Benefits of a New Power System," Energies, MDPI, vol. 17(17), pages 1-16, September.
    11. Zhiming Gu & Tingzhe Pan & Bo Li & Xin Jin & Yaohua Liao & Junhao Feng & Shi Su & Xiaoxin Liu, 2024. "Enhancing Photovoltaic Grid Integration through Generative Adversarial Network-Enhanced Robust Optimization," Energies, MDPI, vol. 17(19), pages 1-15, September.
    12. Xu Guo & Yang Li & Feng Wu & Linjun Shi & Yuzhe Chen & Hailun Wang, 2024. "Optimal Battery Storage Configuration for High-Proportion Renewable Power Systems Considering Minimum Inertia Requirements," Sustainability, MDPI, vol. 16(17), pages 1-23, September.
    13. István Péter Kondor, 2025. "Sustainable Fuels for Gas Turbines—A Review," Sustainability, MDPI, vol. 17(13), pages 1-23, July.
    14. Shuang Zeng & Heng Zhang & Fang Wang & Baoqun Zhang & Qiwen Ke & Chang Liu, 2024. "Two-Stage Optimization Scheduling of Integrated Energy Systems Considering Demand Side Response," Energies, MDPI, vol. 17(20), pages 1-23, October.
    15. Rabeea M. Ghazal & Abdulrazzak Akroot & Hasanain A. Abdul Wahhab & Abdulrahman E. J. Alhamd & Ameer Hasan Hamzah & Mothana Bdaiwi, 2024. "The Influence of Gas Fuel Enrichment with Hydrogen on the Combustion Characteristics of Combustors: A Review," Sustainability, MDPI, vol. 16(21), pages 1-32, October.
    16. Dongqi Huang & Pengwei Sun & Wenfeng Yao & Chang Liu & Hefeng Zhai & Yehao Gao, 2025. "Bi-Level Planning of Grid-Forming Energy Storage–Hydrogen Storage System Considering Inertia Response and Frequency Parameter Optimization," Energies, MDPI, vol. 18(15), pages 1-26, July.
    17. Yulia Mozzhegorova & Galina Ilinykh & Vladimir Korotaev, 2024. "Life Cycle Assessment of a Gas Turbine Installation," Energies, MDPI, vol. 17(2), pages 1-24, January.
    18. Liu, Jia & Tang, Zao & Liu, Yikui & Zhou, Yue & Zeng, Peter Pingliang & Wu, Qiuwei, 2025. "Region-inspired distributed optimal dispatch of flexibility providers in coordinated transmission-distribution framework," Energy, Elsevier, vol. 319(C).
    19. Wenjie Pan & Jun Han & Chao Cai & Haofei Chen & Hong Liu & Zhengyang Xu, 2025. "Holistic Hosting Capacity Enhancement Through Sensitivity-Driven Flexibility Deployment and Uncertainty-Aware Optimization in Modern Distribution Networks," Energies, MDPI, vol. 18(3), pages 1-30, February.
    20. Seung-Jin Yoon & Kyung-Sang Ryu & Chansoo Kim & Yang-Hyun Nam & Dae-Jin Kim & Byungki Kim, 2024. "Optimal Bidding Scheduling of Virtual Power Plants Using a Dual-MILP (Mixed-Integer Linear Programming) Approach under a Real-Time Energy Market," Energies, MDPI, vol. 17(15), pages 1-16, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jeners:v:17:y:2024:i:19:p:4860-:d:1487550. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.