Open AccessApplication of An Adaptive Network-based Fuzzy Inference System to Control a Hybrid Solar and Wind Grid-Tie Inverter
Author(s) -
DinhNhon Truong,
Van-Thuyen Ngo,
Mi Sa-Nguyen Thi,
An-Quoc Hoang
Publication year - 2021
Publication title -
engineering, technology and applied science research/engineering, technology and applied science research
Language(s) - English
Resource type - Journals
eISSN - 2241-4487
pISSN - 1792-8036
DOI - 10.48084/etasr.4413
Subject(s) - adaptive neuro fuzzy inference system , control theory (sociology) , controller (irrigation) , maximum power point tracking , inverter , computer science , transient (computer programming) , matlab , grid , maximum power principle , power (physics) , fuzzy logic , control engineering , fuzzy control system , photovoltaic system , engineering , control (management) , electrical engineering , voltage , mathematics , artificial intelligence , physics , geometry , quantum mechanics , agronomy , biology , operating system
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.