Application of An Adaptive Network-based Fuzzy Inference System to Control a Hybrid Solar and Wind Grid-Tie Inverter

Abstract

In this paper, the application of an Adaptive Network-based Fuzzy Inference System (ANFIS) to control a hybrid solar and wind grid-tie inverter in order to reduce power oscillations and enhance power quality is presented. To extract the maximum power from the PV system, a Perturb and Observe (P&O) algorithm is presented that tracks the Maximum Power Point (MPP). Time-domain simulation results of the studied system are performed in MATLAB/SIMULINK under different operating conditions such as changing irradiation and short-circuit faults in the power grid. From the simulation results, it can be concluded that the designed ANFIS controller and the proposed P&O algorithm perform better than the traditional PI controller and improve transient responses under severe operating conditions.

Interleaved boost converter voltage regulation using hybrid ANFIS-PID controller for off-grid microgrid

“…The ANFIS control structure utilizes the Sugeno-type fuzzy systems [22]. The structure consists of a collection of units organized into five interconnected layers [23], [24] that are tuned automatically by the hybrid learning algorithm. The significance of each layer and detailed operation of the 2-input-1-output ANFIS structure is presented in [22].…”

“…The simulated results depicted better performance of the ANFIS in voltage regulation. Truong et al [24] controlled the inverter DC voltage in a solar and wind grid-tie system using an ANFIS controller. The ANFIS controller performed better than the proportional integral (PI) controller in reducing overshoot and settling time.…”