Off-design performance improvement of twin-shaft gas turbine by variable geometry turbine and compressor besides fuel control

A novel procedure for finding the optimum values of design parameters of industrial twin-shaft gas turbines at various ambient temperatures is presented here. This paper focuses on being off design due to various ambient temperatures. The gas turbine modeling is performed by applying compressor and turbine characteristic maps and using thermodynamic matching method. The gas turbine power output is selected as an objective function in optimization procedure with genetic algorithm. Design parameters are compressor inlet guide vane angle, turbine exit temperature, and power turbine inlet nozzle guide vane angle. The novel constrains in optimization are compressor surge margin and turbine blade life cycle. A trained neural network is used for life cycle estimation of high pressure (gas generator) turbine blades. Results for optimum values for nozzle guide vane/inlet guide vane (23°/27°–27°/6°) in ambient temperature range of 25–45 ℃ provided higher net power output (3–4.3%) and more secured compressor surge margin in comparison with that for gas turbines control by turbine exit temperature. Gas turbines thermal efficiency also increased from 0.09 to 0.34% (while the gas generator turbine first rotor blade creep life cycle was kept almost constant about 40,000 h). Meanwhile, the averaged values for turbine exit temperature/turbine inlet temperature changed from 831.2/1475 to 823/1471°K, respectively, which shows about 1% decrease in turbine exit temperature and 0.3% decrease in turbine inlet temperature.

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