AGC for Multi-Area Interconnected Using Computational Algorithm
Abstract
This article outcome is a comparative analysis of Automatic Generation Control (AGC) of a multi-area interconnected hydrothermal gas system in different modes using computational algorithm controllers for the electrical and mechanical governors. Two areas have been implemented. The first area comprises a Thermal and Hydropower station, while the second area consists of a Thermal and Gas power station. The AGC of a multi-area power system is examined to increase frequency stability using improved PID controllers under 1%∆P. The multi-technique is used to tune the gains of PID and its Sine Cosine Algorithms (SCA), Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), and Genetic Algorithms (GA). The Implementation determines the validity of the four intelligent techniques for tuning the PID controller parameters to improve the frequency and tie-line deviation difficulties and increase the power system's stability. Finally, the SCA's comparison of dynamic performance to settling time, overshoot, and undershoot in frequency and tie-line power deviations proved to be slightly better than other algorithms with some convergence in results.
Keywords: automatic generation control, PID controller, computational algorithm, power systems.
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