Ant-based optimal tuning of PID controllers for load frequency control in power systems

Frequency fluctuations in power system result from high penetration of distributed generation as well as sudden load changes, system uncertainties, and parameters variations. If adequate control actions are not put into place, the fluctuations in power system frequency may deteriorate the normal operation of the system. This paper proposes a robust, intelligent control technique using Ant Colony Optimization algorithms for optimal tuning of proportional, integral and derivative controllers. The goal is to enhance load frequency control capabilities in smart power systems. The designed algorithm is applied to a power system consisting of a coal thermal plant, photovoltaic power generation as a renewable energy source, as well as heat pump water heaters and electric vehicles as controllable loads. Simulation results obtained using Matlab under various practical operating conditions confirm the correctness of system analysis and superior performance of the proposed scheme. The results of the simulation illustrate that the system with the proposed control scheme is more stable, and can achieve a fast response in the face of system uncertainties, parameter variations and fluctuations from distributed energy sources, as compared to the conventional PID controller and the model predictive control scheme.