ANFIS based Neuro-Fuzzy Controller in LFC of Wind-Micro Hydro-Diesel Hybrid Power System

Abstract

paper presents the design and analysis of Neuro-Fuzzy controller based on Adaptive Neuro-Fuzzy Inference System (ANFIS) architecture for Load frequency control of an isolated wind-micro hydro-diesel hybrid power system, to regulate the frequency deviation and power deviations. Due to the sudden load changes and intermittent wind power, large frequency fluctuation problem can occur. This newly developed control strategy combines the advantage of neural networks and fuzzy inference system and has simple structure that is easy to implement. So, in order to keep system performance near its optimum, it is desirable to track the operating conditions and use updated parameters to control the system. Simulations of the proposed ANFIS based Neuro- Fuzzy controller in an isolated wind-micro hydro-diesel hybrid power system with different load disturbances are performed. Also, a conventional proportional Integral (PI) controller and a fuzzy logic (FL) controller were designed separately to control the same hybrid power system for the performance comparison. The performance of the proposed controller is verified from simulations and comparisons. Simulation results show that the performance of the proposed ANFIS based Neuro-Fuzzy Controller damps out the frequency deviation and attains the steady state value with less settling time. The proposed ANFIS based Neuro-Fuzzy controller provides best control performance over a wide range of operating conditions.