Optimal Design of PID-Based Low-Pass Filter for Gas Turbine Using Intelligent Method

• Main Authors: Mohammad Eslami, Mohammad Reza Shayesteh, Majid Pourahmadi
• Format: Article
• Language: English
• Published: IEEE 2018-01-01
• Series: IEEE Access
• Subjects: Stability analysis; IABC method; gas turbine; Rowen model
• Online Access: https://ieeexplore.ieee.org/document/8306826/

Due to the ever-increasing demands for electrical energy in industrial and domestic consumption, the use of gas turbines in power plants has great importance for the generation of electrical energy while taking less time. In this case, analyzing the role of gas turbines in the generation of electrical energy and their performance in the stability of power systems has special importance. Therefore, acquiring the suitable model for gas turbines and estimating various factors in modeling can consider as main part of power system stability. The purpose of this paper is originally a detailed dynamic modeling of a gas turbine based on the Rowen design and then controlling it to get most stability of power system by a new intelligent procedure. In next step, the most commonly accruing faults in gas turbine which can lead to control difficulty in power system are considered for analysis in the proposed simulation. Gas turbine in combined cycle power plant has ability for changing operation condition rapidly and more frequently. So its useful life is lesser than steam turbine. Gas turbine controller must increase its useful life because of high expenditure of gas turbine constructing. Damage mitigating control or life extend control is to design a controller to get better tradeoff between dynamic act and structural durability in a power system. Finally, the proposed interactive artificial bee colony method is employed to design a better controller and the design has been done under different working conditions to get the best results from proportional-integral-differential type controller parameters with low-pass filter compare to genetic algorithm and particle swarm optimization.