الفهرس | Only 14 pages are availabe for public view |
Abstract Large and/or sustained interconnection frequency deviations can cause underor over-frequency relaying and force some loads and generator units out. Under undesirable conditions, this may result in a cascading failure and system frequency collapse that can lead to blackout. Therefore, the speed governing systems of many large thermal generating units include auxiliary control features designed to assist in limiting unit overspeed following load rejection. These controls could adversely affect the performance of the units under system disturbance conditions. Therefore, a local power station optimal frequency controller is presented as a tool to ensure the sustainability of the formed islands after uncontrollable system separation. Two-area single-reheat thermal system is considered and it focused on an island with excess generation to be equipped with PID controller. The PID controller is tuned using Genetic Algorithm (GA) technique for optimal response. Results have been compared with the conventional controller based on Zeigler-Nichols (ZN) method in order to demonstrate the superior efficiency of the proposed (GA) technique in tuning the PID controller. An adaptive PID frequency controller using Artificial Neural Networks (ANN) is presented. PID controller parameters are tuned using GA to minimize integral square error over a wide-range of tie line interruptions. The values of the PID controller parameters obtained from GA are used for ANN training. Therefore, the proposed technique could tune the PID controller parameters online for optimal response at any other power interruption. Testing of the developed technique shows that the proposed controller could present optimal performance over a wide-range of tie line interruptions and it capable of improving the transient frequency response of thermal power plants. Results are provided in the form of time domain simulations via MATLAB/SIMULINK tool. |