Performance prediction of the combined cycle power plant with inlet air heating under part load conditions

Shucheng Wang, Zhitan Liu, Rasmus Cordtz, Muhammad Imran, Zhongguang Fu

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A combined cycle power plant with inlet air heating (CCPP-IAH) system is proposed to solve the problems of ice and humidity blockages in winter climate. The performance of the CCPP-IAH system under part load conditions is analyzed via both experimental and simulation methods. The application of the inlet air heating technology significantly improves the part load efficiency and enhances the operational safety of the combined cycle power plant under complex meteorological conditions. Results show that a higher inlet air temperature will contribute a lower gas turbine thermal efficiency for proposed system. However, the heated inlet air by the recovered energy in heat recovery steam generator raises efficiencies for both the heat recovery steam generator and the overall system. The fuel consumption drops by 0.02 kg/s and 0.03 kg/s under the power load of 65% and 80%, respectively. The inlet air humidity decrease to 30% under the heated inlet air temperature of 303 K. Moreover, the exergy destruction for both Brayton cycle part and Rankine cycle part decrease with the inlet air temperature increasing. The daily fossil fuel will raise up to 2.9 ton/day and to 5.1 ton/day under the power load of 65% and 80%, respectively. The annual economic benefit from energy saving is more than $ 5.88 × 105 and the payback period is less than 3 years.
Original languageEnglish
Article number112063
JournalEnergy Conversion and Management
Early online date25 Sep 2019
Publication statusPublished - 15 Nov 2019


Bibliographical note

© 2019, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Funding: Natural Science Foundation of Beijing (3162030) and the Fundamental Research Funds for the Central Universities (2018QN035).


  • CCPP
  • Combined cycle power plant
  • Experimental test
  • Inlet air heating
  • Optimization
  • Part load

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