Open AccessTransient stability enhancement of a grid‐connected wind farm using an adaptive neuro‐fuzzy controlled‐flywheel energy storage system
Author(s) -
Taj Talha Ahmed,
Hasanien Hany M.,
Alolah Abdulrahman I.,
Muyeen Syed M.
Publication year - 2015
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2014.0345
Subject(s) - transient (computer programming) , control theory (sociology) , flywheel , flywheel energy storage , fault (geology) , engineering , controller (irrigation) , wind power , electric power system , interconnection , fuzzy logic , energy storage , computer science , automotive engineering , power (physics) , electrical engineering , control (management) , telecommunications , agronomy , physics , quantum mechanics , artificial intelligence , seismology , biology , geology , operating system
With the rapid growth of the wind energy systems in the past years and their interconnection with the existing power system networks, it has become very significant to analyse and enhance the transient stability of the wind energy conversion systems connected to the grid. This study investigates the transient stability enhancement of a grid‐connected wind farm using doubly‐fed induction machine‐based flywheel energy storage system. A cascaded adaptive neuro‐fuzzy controller (ANFC) is introduced to control the insulated gate bipolar transistor switches‐based frequency converter to enhance the transient stability of the grid‐connected wind farm. The performance of the proposed control strategy is analysed under a severe symmetrical fault condition on both a single‐machine infinite bus model and the IEEE‐39 bus New England test system. The transient performance of the system is investigated by comparing the results of the system using the proposed ANFCs with that of the black‐box optimisation technique‐based proportional–integral controllers. The validity of the system is verified by the simulation results which are carried out using PSCAD/EMTDC environment.