Optimal PID Parameters based Ant Colony Optimization algorithm of power system with non-linearity and boiler dynamics

摘要

Proportional-Integral-Derivative (PID) and Proportional-Integral (PI) controllers are applied into the power system to examine the controller performance. Therefore, this work describes the application of an Artificial Intelligence (AI) optimization technique to design Proportional-Integral-Derivative (PID) controller for Load Frequency Control (LFC) of single area re-heat thermal power system. The PI-/PID-controllers gain values are optimized using conventional method and AI optimization technique; respectively. Further, the proposed technique effectiveness is analyzed by considering non-linearity and Boiler dynamics into the same power system. Comparing the power system response with/without non-linearity, it is proved that the response will have more oscillation in the case of using non-linearity and boiler dynamics (BD). Moreover, robustness of the analysis is carried out via varying the governor's time constants, turbine, re-heater and power system in about +50% to -50% from its nominal value by the 25% step.