A review on fractional order (FO) controllers' optimization for load frequency stabilization in power networks

Keeping generation and demand balance is a fundamental requirement in power networks. It maintains frequency of the system within permissible limits. For microgrids, this balance is important to keep tie-line power below a certain threshold. Managing load frequency deviations is indispensable for microgrids and can be managed by coordinating generators, loads as well as other components such as energy storage devices and electric vehicles. Therefore, Load Frequency Stabilization (LFS) research has gained a lot of traction in this field. Building on the importance of this concept, this paper constructs different fractional order (FO) control stratagems which have been applied in different frequency response models. In order to achieve the targeted assignment, the impact of incremental control action of different FO controllers along with the system constraints has been considered for better system dynamics. Moreover, the current research work illustrates the structural control operation with transfer function analysis of different FO controllers considered for multiple single/multi-area power network. To optimally tune the existing FO controller parameters, application of several optimization techniques corresponding to the frequency regulation issues have been undertaken. Furthermore, a visualization of complete utilization of classified FO controllers and their corresponding optimization techniques have been analyzed. In order to make the performance elegant, a review has been performed on application of different existing error functions (J) and some recently developed modified error functions. Finally, the performance of modified J considering different FO controllers have been depicted. (C) 2021 Published by Elsevier Ltd.

Automated summary

This paper explores the Load Frequency Stabilization (LFS) and its significance in microgrids, constructing various fractional order (FO) control strategies for experimentation. By considering system constraints and optimizing adjustment, the performance of different FO controllers is demonstrated.