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Control of the rated production power of DFIG-wind turbine using adaptive PSO and PI conventional controllers

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TLDR
In this article , an assessment study between the adaptive particle swarm optimisation (PSO) technique and conventional proportional integral (PI) controller of the pitch control system in limiting the electrical output power at the rated value of DFIG is introduced.
Abstract
Production of rated power and protection of generator and power converter from an overload are necessary. Therefore, measuring the accurate value of the pitch angle of the doubly fed induction generator (DFIG) wind turbine is essential. An assessment study between the adaptive particle swarm optimisation (PSO) technique and conventional proportional integral (PI) controller of the pitch control system in limiting the electrical output power at the rated value of DFIG is introduced in this study. Pitch control with PSO is designed by solving the nonlinear equation of pitch angle at each wind speed higher than rated wind speed. The PI controller gains of the pitch system are evaluated to keep the power limited at rated value. Accuracy in measuring pitch angle is essential because a small difference in pitch angle value results in an overload on the generator. The performance of each parameter of DFIG with a detailed analysis is studied. The simulation shows that the pitch control system with PSO technique gives better results in regulating the DFIG output power compared to PI controller method under wind speed variation.

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Journal ArticleDOI

Raw Anode Volume Density Prediction Algorithm Based on the Genetic Algorithm

Danyang Cao, +1 more
TL;DR: Experimental results show that in terms of production data, the optimization ability of the neural network model structure is significantly improved compared with other algorithms, with the root mean square error of the prediction value of the raw anode volume density is 0.005, which is smaller error than other methods.
Journal ArticleDOI

Subspace Data-Driven Control for Linear Parameter Varying Systems

TL;DR: In this paper , a subspace data driven control for linear parameter changing system with scheduling parameters is presented, where only the data matrix is utilized to represent the output prediction value in the future various time instants.
Journal ArticleDOI

Design of a Closed-Loop Error-in-Variable System Controller and Its Application in Quadrotor UAV

TL;DR: In this article , the authors proposed a closed-loop variable system model with error (both input and output signals are disturbed by noise) and designed the controller of the system using minimum variance control.
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