The characteristics of linked power networks include nonlinear loads and variable point functioning. When a variety of parameters change, a power system’s demand for both active and reactive power fluctuates often, never remaining constant. While changes in actual power affect the system frequency, changes in reactive power change the magnitude of the voltage. By balancing the system with respect to variations in load and losses incurred, control in and around generation aims to achieve the desired response from the given system. Effective and affordable management of all aspects of power dynamics depends on control strategies. The system operating point and frequency will both be significantly shifted by the load variation, leading to the system’s eventual instability. In this study, the response for a single area system with variations in load and frequency is analyzed and presented using genetic algorithm-tuned controllers, reducing the influence of performance indices such as integral square error. This includes both PID controllers and PID controllers with fractional orders. The simulation results are presented in comparison with the two tuned controllers.

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Control of Frequency Deviation and Area Control Error in LFC Using Genetic Algorithm-Tuned FOPID by Minimizing Performance Index

  • A. S. Anitha Nair

摘要

The characteristics of linked power networks include nonlinear loads and variable point functioning. When a variety of parameters change, a power system’s demand for both active and reactive power fluctuates often, never remaining constant. While changes in actual power affect the system frequency, changes in reactive power change the magnitude of the voltage. By balancing the system with respect to variations in load and losses incurred, control in and around generation aims to achieve the desired response from the given system. Effective and affordable management of all aspects of power dynamics depends on control strategies. The system operating point and frequency will both be significantly shifted by the load variation, leading to the system’s eventual instability. In this study, the response for a single area system with variations in load and frequency is analyzed and presented using genetic algorithm-tuned controllers, reducing the influence of performance indices such as integral square error. This includes both PID controllers and PID controllers with fractional orders. The simulation results are presented in comparison with the two tuned controllers.