LOAD-FREQUENCY OPTIMIZATION WITH HEURISTIC TECHNIQUES IN A AUTONOMOUS HYBRID AC MICROGRID

Abstract

The main problem that arises during the operation of all these power systems is load-frequency control. Load-frequency control is a common problem of power systems that are connected to an interconnected system. Variations in the frequency in the interconnected power systems can lead to large-scale and serious instability problems. And in microgrids, load-frequency control is of great importance in order to provide active power balancing, especially when the microgrids are connected to the main grid. In this study, AC microgrid structures and their basic control cycles are examined. A sample autonomous hybrid AC microgrid structure was modeled in the MATLAB environment and an autonomous hybrid AC microgrid system isolated from the main grid was considered to be the case study. In this case, the controller gains are determined according to the Optic Inspired Optimization, Bacterial Swarm Optimization, Artificial Bee Colony Optimization, Ant Colony Optimization, Grey Wolf Colony Optimization algorithms, costing with the ISE performance criteria which are commonly recognized in the literature. The controller gains determined by optimization were simulated for time domain responses in the generated model and the results were analyzed.