Ant colony optimization algorithm based PID controller for LFC of single area power system with non-linearity and boiler dynamics

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-/ PIDcontrollers gain values are optimized using conventional method and AI optimization technique; respectively. In additional, the proposed technique effectiveness is analyzed by adding non-linearity and Boiler dynamics into the same investigated power system. A comparison of the power system with/ without non-linearity is performed. Moreover, robust 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.

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