Research on Single Neuron Adaptive PID Control for MPPT of Wind Power System Using Switched Reluctance Generator

2012 ◽  
Vol 608-609 ◽  
pp. 770-774
Author(s):  
Hong Hua Wang ◽  
Cheng Liang Wang

Switched reluctance generator (SRG) has a promising prospect for variable speed wind energy application because of its ruggedness, advantage cost, simplicity and ability to work over wide speed ranges. This paper presents the application of a single neuron adaptive PID algorithm to the problem of maximum power point tracking (MPPT) control in the wind power system using SRG, and a 750W, three phase (6/4) SRG prototype is chosen for the study. The nonlinear characteristics of the SRG and the wind turbine are described firstly, then the optimal speed tracking strategy based on the single neuron adaptive PID control for MPPT of the wind power system using SRG is investigated in the paper. Based on the developed model in MATLAB environment, simulation studies are performed in various conditions including a step change in the wind speed or in the load of SRG. Simulation results show the control system can quickly and steadily track the optimal curve to realize the MPPT with excellent dynamic and static performances, which verify the effectiveness of the control strategy investigated in the paper.

2013 ◽  
Vol 397-400 ◽  
pp. 1398-1402
Author(s):  
Hai Long Li

Control strategy of permanent magnet synchronous generator (PMSG) in variable speed wind power system has been design in this paper. The decoupling control can be realized by PWM converter with the field oriented strategy, and a novel adjusted method is discussed with excitation component compensation. Power characters and model of wind turbine are studied, and the simple maximum power point tracking (MPPT) algorithm is executed. Moreover, the complete control strategy is expressed considering the model limit of PMSG. The design adopted can feasible realize the predominant control within the permissible wind speed. The analysis and investigation results all have been confirmed that the excellent dynamic states and steady states performances of the control strategy.


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