Abstract
As the proportion of renewable energy is increasing steadily in the electricity market, gas turbines (GTs) need to operate under the partial load more frequently. Thus, it is necessary to diagnose the GT performance using partial load data. The variations in the characteristic parameters of the compressor should be identified according to the angle of inlet guide vane (IGV), which plays the key role in controlling GT power, to improve the accuracy of performance diagnosis at partial load. This paper proposes a method to identify the variations using actual operation data. The method consists of two steps. The first step evaluates the effect of compressor fouling using full load operating data. The second step quantifies the effect of changes in IGV angle using partial load operating data. The method was applied to the operation data of a 170 MW class gas turbine. The changes in flow capacity, pressure ratio, and compressor efficiency according to the IGV angle were identified, and formulas to describe the variations were derived. The significance of the proposed method is that it does not require detailed information of the compressor behavior change from the manufacturer but uses the actual operating data of the GT users.
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Abbreviations
- A :
-
Area (m2)
- α:
-
Angle (°)
- CCPP :
-
Combined cycle power plant
- CDT :
-
Compressor discharge temperature (°C)
- CDP :
-
Compressor discharge pressure (kPa)
- FC :
-
Flow capacity
- g :
-
Gravitational acceleration (m2/s)
- GT :
-
Gas turbine
- h :
-
Specific enthalpy (kJ/kg)
- IGV :
-
Inlet guide vane
- LHV :
-
Lower heating value (kJ/kg)
- N :
-
Rotational speed (RPM)
- P :
-
Pressure (kPa)
- PR :
-
Pressure ratio (−)
- R :
-
Gas constant (kJ/kg·K)
- SF :
-
Scaling factor
- T :
-
Temperature (°C)
- TIT :
-
Turbine inlet temperature (°C)
- TET :
-
Turbine exhaust temperature (°C)
- γ :
-
Specific heat ratio (−)
- ṁ :
-
Mass flow rate (kg/s)
- ΔP :
-
Pressure drop (−)
- Ẇ :
-
Power output (MW)
- η :
-
Efficiency (%)
- a :
-
Air
- comp :
-
Compressor
- d :
-
Design point
- effi :
-
Efficiency
- f :
-
Fuel
- FC :
-
Flow capacity
- fouling :
-
Fouling
- g :
-
Gas
- gen :
-
Generator
- in :
-
Inlet
- IGV :
-
Inlet guide vane
- mech :
-
Mechanical
- net :
-
Net
- off :
-
Off-design case
- out :
-
Outlet
- PR :
-
Pressure ratio
- s :
-
Isentropic compression or expansion
- turb :
-
Turbine
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Acknowledgments
This work was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) and the Ministry of Trade, Industry and Energy (MOTIE) of the Republic of Korea (No.20193310100050).
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The major contents of this paper are based on the doctoral dissertation of the first author.
Jae Hong Lee received his Ph.D. degree from the Department of Mechanical Engineering, Inha University in 2021 and is currently working at the R&D Center of Doosan Enerbility, Korea. His research interests include the performance diagnosis of gas turbine-based power plants.
Do Won Kang received his Ph.D. degree from the Department of Mechanical Engineering, Inha University in 2015 and is currently working in Department of Zero-carbon Fuel Power Generation at Korea Institute of Machinery & Materials. His research interests include design and analysis of gas turbine-based power generation system.
Ji Hun Jeong received his Master’s degree from the Department of Mechanical Engineering, Inha University in 2019 and is currently working on doctoral degree in the same department. His research interests include performance analysis and simulation of gas turbine operation.
Tong Seop Kim is a Professor in the Dept. of Mechanical Engineering, Inha University. He received his Ph.D. degree from Seoul National University, Korea, and has been working at Inha University since 2000. His research interests include design and analysis of advanced energy systems including gas/steam turbine based power plants.
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Lee, J.H., Kang, D.W., Jeong, J.H. et al. Quantification of variations in the compressor characteristics of power generation gas turbines at partial loads using actual operation data. J Mech Sci Technol 37, 1509–1521 (2023). https://doi.org/10.1007/s12206-023-0236-9
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DOI: https://doi.org/10.1007/s12206-023-0236-9