e-Prime: Advances in Electrical Engineering, Electronics and Energy (Mar 2024)
An adaptive wide-area neuro-fuzzy based controller for variable frequency transformer in damping inter-area oscillations
Abstract
Due to the dynamic, non-linear, and complex character of large-scale power networks, prolonged inadequately damped low frequency oscillations may develop, leading to loss of synchronisation of generating units. Flexible AC transmission controller when equipped with an appropriate additional damping mechanism offers substantial damping in mitigating these oscillations. In this context, a smart flexible transmission device namely variable frequency transformer (VFT) is integrated into a multimachine power system network to effectively damp low-frequency oscillations. An adaptive model free neuro-fuzzy inference system (ANFIS) based damping controller is developed for VFT in order to damp inter-area oscillations. The ANFIS is a resilient and intelligent system that combines fuzzy logic and neural network capabilities with attributes like robustness, adaptability, speed, and flexibility. The proposed damping controller, which provides additional damping proportionate to the frequency variation, was included into the VFT’s power loop. The controller input is determined as the center-of-inertia difference of generator rotor speeds and is a remote signal delivered by a wide-area measuring system. Depending on the observability of crucial modes, participation factor (PF) investigation is used to extract the appropriate feedback signal, which provides details on the overall the system’s dynamics. The ANFIS-based scheme for the VFT is designed to impart sufficient damping qualities to the critical modes of the examined system under a variety of operating conditions. Using extensive non-linear time-domain simulations and eigenvalue analysis, the effectiveness of the suggested technique was evaluated on a popular 2-area, 4-generator, 11-bus test system.
