Multi-area optimal adaptive under-frequency load shedding control based on ANFIS approach

This paper presents a new optimization approach for solving the under-frequency load shedding (UFLS) problem in power systems. UFLS is a very important function in maintaining the power system within its safe operating limits.It is also the last resort in the event of frequency instability. This paper investigates the use of an adaptive neuro-fuzzy inference system (ANFIS)-based controller. The proposed ANFIS provides optimal response compared to conventional load shedding and other methods. The proposed approach is based on the simulation of the multi-zone load frequency control problem. Rate of change of frequency, voltage deviation and tie-line power transit are used as inputs to the ANFIS. The outputs in the first level are the optimal frequency threshold (Fth) values, and in the second level, they are the quantity of load shedding. Numerical results based on the IEEE 39 power system and the Algerian grid are used to demonstrate the effectiveness of the proposed approach in finding the optimal UFLS control compared with the conventional method as well as the results of the other intelligent method. The comparison showed that the proposed scheme gave the best response in all scenarios.