Optimized Intelligent Coordinator for Load Frequency Control in a Two-Area System with PV Plant and Thermal Generator

This paper proposes an optimal fuzzy-based coordination approach for thermal generator and solar photovoltaic (PV) plant in a two-area power system. The proposed intelligent coordinator is designed for valid adjustment of integral gain of secondary control loop in thermal generator and the proportional gain in PV plant. The classic controllers are generally applied with a constant gain for nominal operation state of the system. However, the proposed fuzzy method illustrates a favorable performance in load perturbations by fine tuning of classic conventional controllers' gains. In this study, particle swarm optimization algorithm is used to optimize the fuzzy controller's scaling factors. To demonstrate the effectiveness of the proposed optimal fuzzy controller, it is applied on a two-area power system with different generation unit in each area. Three scenarios of variations in load and solar radiation are implemented to illustrate the adequate performance of the controller in disturbances. A comparison with two optimization methods, known as firefly algorithm and genetic algorithm, is presented to approve the superiority of the controller.

Automated summary

This paper proposes an optimal fuzzy-based coordination approach for thermal generator and solar photovoltaic (PV) plant in a two-area power system. The proposed method fine-tunes the gains of classic conventional controllers to improve performance in load perturbations. The fuzzy controller's scaling factors are optimized using the particle swarm optimization algorithm. The effectiveness of the proposed optimal fuzzy controller is demonstrated through simulations on a two-area power system.