Open AccessSteam Turbine Governor (STG) Controller Design Based on Particle Swarm Optimization (PSO)
Author(s) -
Farah Ayad Abdul Majeed
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1105/1/012050
Subject(s) - pid controller , control theory (sociology) , overshoot (microwave communication) , particle swarm optimization , settling time , controller (irrigation) , turbine , governor , engineering , load rejection , steam turbine , open loop controller , control engineering , step response , computer science , temperature control , mechanical engineering , control (management) , closed loop , agronomy , machine learning , artificial intelligence , biology , aerospace engineering , electrical engineering
A reheat and non-reheat steam turbines governor is a component of the turbine control system that regulates rotational speed in response to changing load conditions. The governor output signal manipulates the position of a steam inlet valve or nozzles which in turn regulates the steam flow to the turbine. The application of PID (proportional integral derivative (controller has been widely used from small industry to high technology industry. Tuning the parameters of a PID controller is very important in PID control, Ziegler-Nichols method also used to tune the coefficients of a PID controller. The compensation has been proposed to be 4%, 6%, 8%, 10% and 15% of the actual load. This paper evaluates the feasibility of using the Particle Swarm Optimization (PSO) method for determining the optimal PID controller parameters for steam turbine speed control. The PSO optimization technique is compared with Ziegler-Nichols method and (PID) controllers. It is validated that PSO based controller is more efficient in reducing the steady-states error, settling time, rising time, and overshooting limit in speed control of the steam turbine control. In which the maximum peak overshoot has been reduced from 44.8% in case of the original system without any controller to 3.45% for the case of PSO based controller and that for 15% load change.