Abstract
Recently, wind energy conversion systems (WECSs) have attracted attention due to their effective application in renewable energy sources. It is a complex system with multi-variables, strong coupling, non-linearity, and variable parameters; however, traditional control systems are inadequate in answering the demands of complex systems. In order to solve the complexity and improve the transient stability during grid faults and power fluctuations, this paper proposes a fuzzy logic system with the linear extended state observer (FLS-LESO) applied to WECSs based on a permanent magnet synchronous generator (PMSG). The FLS-LESO consists of a fuzzy logic controller, a conventional PD controller, and the linear extended state observer (LESO). This paper analyzes the mathematical model of a wind power system and combines it with LESO to improve the estimation accuracy of the observer and further improve the control performance. In the simulation study, the control performance of the FLS-LESO was also tested under various operating conditions using the MATLAB/Simulink simulation platform to verify the correctness and effectiveness of the control system.
Highlights
Because of the abundant necessity of energy harvest and continuous depletion of fossil fuels, demands of renewable energy sources are gaining more attention [1,2]
The fault ride-through (FRT) capability of wind turbines is a vital issue for the electrical energy generated from wind energy and contributes reliable grid integration
This proposes a new control from approach capability to of wind turbines is a vital issue for paper the electrical energy generated wind using the method that is implemented in the based on a to improve the energy and contributes to reliable grid integration
Summary
Because of the abundant necessity of energy harvest and continuous depletion of fossil fuels, demands of renewable energy sources are gaining more attention [1,2]. A superconducting fault current limiter (SFCL) was implemented for the FRT enhancement of a PMSG in Reference [17]. This requires additional circuit links, which increases the design difficulty of WECS, and increases the upfront investment and maintenance cost. Soft computing methods are widely implemented in wind power applications, such as for maximum power point tracking (MPPT) control, pitch control, fault diagnosis, wind power integration, wind turbine power control, and prediction of wind speed and power. The fuzzy logic control is a type of soft computing method that overcomes the uncertainties of some systems [25].
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