Journal
IET POWER ELECTRONICS
Volume 11, Issue 9, Pages 1507-1518Publisher
WILEY
DOI: 10.1049/iet-pel.2017.0174
Keywords
intelligent control; power grids; AC-DC power convertors; DC-AC power convertors; fuzzy control; power system interconnection; wind power plants; wind turbines; power generation control; permanent magnet generators; synchronous generators; maximum power point trackers; decentralised control; power system stability; compensation; Lyapunov methods; linear matrix inequalities; closed loop systems; intelligent control; grid-connected AC-DC-AC power converter; WECS; T-S fuzzy interconnected system modelling; wind-energy conversion system; Takagi-Sugeno fuzzy model; wind turbine; permanent magnet synchronous generator; power electronic converter; maximum power point tracker; DC-bus voltage control; decentralised stabilisation; interconnected nonlinear subsystem; parallel distributed compensation concept; decentralised fuzzy controller; Lyapunov theory; linear matrix inequalities tool; closed-loop fuzzy system
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Control of power converters is undoubtedly an essential issue in wind-energy systems. This study focuses on the development of a control scheme dedicated to a wind-energy conversion system (WECS) based on Takagi-Sugeno (T-S) fuzzy model. The treated system includes a wind turbine followed by a permanent magnet synchronous generator and power electronic converters. After describing the elements constituting the WECS, the main objectives of control are to extract the maximum amount of available power and to control the DC-bus voltage. The proposed approach is based on the concept of decentralised stabilisation. First, as to reduce the complexity of the system, the WECS is divided into two interconnected non-linear subsystems. Then, each subsystem is represented by a T-S fuzzy model. Using the parallel distributed compensation concept, a decentralised fuzzy controller is synthesised for each subsystem. Sufficient conditions are derived from Lyapunov theory and the local feedback gains for each controller are calculated by using linear matrix inequalities tools. Therefore, the whole closed-loop fuzzy system is stable using the elaborated fuzzy control scheme. Simulation results are included to show the performance of the proposed algorithm.
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