Publication

Abstract : Gas turbine plants are used for isolated and standalone operations. They are mainly used in oil fields, desert areas, off shore installations and bio gas plants. An effective control strategy is required to keep the system stable under disturbance. The Transfer function model of heavy duty gas turbine has been developed by Rowen [1] based upon his field experience and the tests he conducted in the gas turbine plants. This model has been used in many works such as, the dynamic analysis of combined cycle plant [2], twin shaft gas turbine model [3], combustion turbine model [4] and even in micro turbine power generation [5]. The transfer function simplification has been validated [6]. The droop governor is found to be an appropriate one [7]. The droop setting value and rotor time constant have been optimized [8]. After tuning the parameters, the response of the gas turbine plant shows steady state error. To improve the transient and steady state response, PID controller is required. The parameters of PID controller have been tuned using ZN method and the steady state error is removed. In this paper, Artificial Neural Network is used for control which uses backpropagation algorithm for training. The trained ANN brings back the system to steady state. It is found that ANN controller yields a better response than the conventional PID controller.