| Title |
Deslgn of Adaptive Neuro - Fuzzy Precompensator for Enhancement of Power System Stability |
| Authors |
Hyeng-Hwan Chung ; Mun-Kyu Chung ; Jeong-Phil Lee ; Joon-Tark Lee |
| Abstract |
In this paper, we design the Adaptive Neuro-Fuzzy Precompensator(ANFP) for the suppression of low-frequency oscillation and the improvement of system stability. Here, ANFP is designed to compensate the conventional Power System Stabilizer(PSS). This design technique has the structural merit that is easily implemented by adding ANFP to an existing PSS. Firstly, the Fuzzy Precompensator with learning ability is constructed and is directly learned from the input and output data of the generating unit. Because the ANFP has the property of learning, fuzzy rules and membership functions of the compensator can be automatically tuned by learning algorithm. Learning is based on the minimization of the error evaluated by comparing the output of the ANFP and a desired controller. Case studies show the proposed scheme can be provided the good damping of the power system over the wide range of operating conditions and improved the dynamic performance of the system. |