In this study, a novel artificial intelligence technique known as Ant Colony Optimization (ACO) is used for optimal tuning of PID controller for load frequency control. The system proposed here is a single area with reheat thermal system containing nonlinearities represented by Generation Rate Constraint (GRC), dead band and wide range of parameters. Three different cost functions have been suggested for tuning the PID controller. The closed loop response using these values of PID gains has been compared with Ziegler-Nichols (ZN) tuned one, the system has been tested for various load changes to reveal the effectiveness of the proposed technique.
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