2021
DOI: 10.3390/machines9070135
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Development and Application of Fuzzy Proportional-Integral Control Scheme in Pitch Angle Compensation Loop for Wind Turbines

Abstract: Wind energy is regarded as one of the oldest energy sources and has played a significant role. As the nature of wind changes continuously, the generated power varies accordingly. Generation of the pitch angle of a wind turbine’s blades is controlled to prevent damage during high wind speed. This paper presents the development and application of a fuzzy proportional integral control scheme combined with traditional proportional control in the dynamic behavior of pitch angle-regulated wind turbine blades. The co… Show more

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Cited by 15 publications
(7 citation statements)
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References 41 publications
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“…Te second project includes 110 turbines, with a total capacity of 220 MW. Te last project includes 60 turbines which has a 120 MW capacity [28][29][30]. Te model is simulated using MATLAB/SIMULINK by three separated wind turbine blocks that present the three projects, each scaled by 20 MW, so the projects are simulated as 240 MW ( (2) to C1,C2…”
Section: Studied Model Configurationmentioning
confidence: 99%
“…Te second project includes 110 turbines, with a total capacity of 220 MW. Te last project includes 60 turbines which has a 120 MW capacity [28][29][30]. Te model is simulated using MATLAB/SIMULINK by three separated wind turbine blocks that present the three projects, each scaled by 20 MW, so the projects are simulated as 240 MW ( (2) to C1,C2…”
Section: Studied Model Configurationmentioning
confidence: 99%
“…The above requirements for LVRT can be encountered by two methods: integrating energy storage systems (ESS) [14,15] for wind systems, and developing optimized control techniques [16][17][18] to control the performance of an integrated ESS.…”
Section: Low Voltage Ride Through (Lvrt)mentioning
confidence: 99%
“…A controller based on fuzzy logic (FL) is implemented for the battery charge/discharge and described in this paper. e FL controller will generate for each fuzzy set in the membership function a degree of membership after obtaining the inputs, and then it will evaluate the fuzzy set memberships and decide which rules would be used before being converted into a signal as an output control [32,33].…”
Section: Battery Power Managementmentioning
confidence: 99%