Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJACSA.2018.090319
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 3, 2018.
Abstract: This paper proposes a new smart under frequency load shedding (UFLS) scheme, based on Takagi-Sugeno (TS) fuzzy inference system and flexible load priority. The proposed scheme consists of two parts. First part consists of fuzzy load shed amount estimation module (FLSAEM) which uses TS-fuzzy to estimate the amount of load shed and sends its value to accurate load shedding module (ALSM) to perform accurate load shedding using flexible load priority. The performance of the proposed scheme is tested for intentional islanding case and increment of sudden load in the system. Moreover, the response of the proposed scheme is compared with adaptive UFLS scheme to highlight its advantages. The simulation results show that the proposed UFLS scheme provides the accurate load shedding due to advantage of flexible priority whereas adaptive UFLS scheme due to fixed load priority does not succeed to achieve accurate load shedding.
J. A. Laghari, Suhail Ahmed Almani, Jagdesh Kumar and Hazlie Mokhlis, “A Smart Under-Frequency Load Shedding Scheme based on Takagi-Sugeno Fuzzy Inference System and Flexible Load Priority” International Journal of Advanced Computer Science and Applications(IJACSA), 9(3), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090319