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Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

邮发代号 80-972

2019 Impact Factor: 2.657

Frontiers in Energy  2019, Vol. 13 Issue (4): 742-756   https://doi.org/10.1007/s11708-017-0462-x
  研究论文 本期目录
基于无传感器最大功率点跟踪策略和SCIG驱动风力发电机的内模控制器的新型功率捕获优化
YAAKOUBI Ali EL1(), ATTARI Kamal1, ASSELMAN Adel1, DJEBLI Abdelouahed2
1. Optic and Photonic Team, Faculty of Sciences, Abdelmalek Essaaidi University, Tetouan 93002, Morocco
2. Energetics, Fluid Mechanics and Materials Laboratory, Abdelmalek Essaadi University, Tetouan 93002, Morocco
Novel power capture optimization based sensorless maximum power point tracking strategy and internal model controller for wind turbines systems driven SCIG
Ali EL YAAKOUBI1(), Kamal ATTARI1, Adel ASSELMAN1, Abdelouahed DJEBLI2
1. Optic and Photonic Team, Faculty of Sciences, Abdelmalek Essaaidi University, Tetouan 93002, Morocco
2. Energetics, Fluid Mechanics and Materials Laboratory, Abdelmalek Essaadi University, Tetouan 93002, Morocco
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摘要:

在使用可再生能源替代传统能源的趋势下,使用强大的软计算方法以帮助实现这些能源的快速增长变得尤其重要。在此背景下,本文引入了一种新型结构来优化和控制由基于鼠笼异步发电机(SCIG)并接入电网的变速风力发电机而产生的能量。通过基于模糊逻辑的最大功率跟踪(MPPT)算法来实现风能发电的优化策略,并通过内模(IM)控制器实现发电机的控制策略。在矢量控制技术中并入了三个内模控制器以替代比例积分(PI)控制器,以实现所提出的优化策略。提出了将MPPT与MI控制器结合以替代传统的叶尖速比(TSR)技术,以避免诸如风速测量和风力发电机(WT)特性的不确定而引起的任何干扰。根据Matlab/Simulink中一个六风能转化系统模型的仿真结果可得,本文所提出的控制系统拓扑结构是可靠的,并能使系统保持在所期望的响应附近运行。

Abstract

Under the trends to using renewable energy sources as alternatives to the traditional ones, it is important to contribute to the fast growing development of these sources by using powerful soft computing methods. In this context, this paper introduces a novel structure to optimize and control the energy produced from a variable speed wind turbine which is based on a squirrel cage induction generator (SCIG) and connected to the grid. The optimization strategy of the harvested power from the wind is realized by a maximum power point tracking (MPPT) algorithm based on fuzzy logic, and the control strategy of the generator is implemented by means of an internal model (IM) controller. Three IM controllers are incorporated in the vector control technique, as an alternative to the proportional integral (PI) controller, to implement the proposed optimization strategy. The MPPT in conjunction with the IM controller is proposed as an alternative to the traditional tip speed ratio (TSR) technique, to avoid any disturbance such as wind speed measurement and wind turbine (WT) characteristic uncertainties. Based on the simulation results of a six KW-WECS model in Matlab/Simulink, the presented control system topology is reliable and keeps the system operation around the desired response.

Key wordspower optimization    wind energy conversion system    maximum power point tracking (MPPT)    fuzzy logic    internal model (IM) controller
收稿日期: 2016-04-20      出版日期: 2019-12-26
通讯作者: YAAKOUBI Ali EL     E-mail: ali.elyaakoubi@gmail.com
Corresponding Author(s): Ali EL YAAKOUBI   
 引用本文:   
YAAKOUBI Ali EL, ATTARI Kamal, ASSELMAN Adel, DJEBLI Abdelouahed. 基于无传感器最大功率点跟踪策略和SCIG驱动风力发电机的内模控制器的新型功率捕获优化[J]. Frontiers in Energy, 2019, 13(4): 742-756.
Ali EL YAAKOUBI, Kamal ATTARI, Adel ASSELMAN, Abdelouahed DJEBLI. Novel power capture optimization based sensorless maximum power point tracking strategy and internal model controller for wind turbines systems driven SCIG. Front. Energy, 2019, 13(4): 742-756.
 链接本文:  
https://academic.hep.com.cn/fie/CN/10.1007/s11708-017-0462-x
https://academic.hep.com.cn/fie/CN/Y2019/V13/I4/742
Fig.1  
Fig.2  
Fig.3  
Fig.4  
Δ Ωr Δ Pr
NB NM NS Z PS PM PB
NB PB PB PM Z NM NB NB
NM PB PM PS Z NS NM NB
NS PM PS PS Z NS NS NM
Z NB NM NS Z PS PM PB
PS NM NS NS Z PS PS PM
PM NB NM NS Z PS PM PB
PB NB NB NS Z PS PB PB
Tab.1  
Fig.5  
Fig.6  
Parameters Value
k1 0.001
k2 0.001
k3 40
ar 1.3
asq 14
asd 16
Tab.2  
Parameters Value
Rated power/kW 6
Inertia turbine/(kg·m–2) 3
Inertia generator /(kg·m–2) 0.01
R/m 2.5
i 6.25
ρ 2
η 0.95
Rs/Rr 1.265/1.430
Ls/Lr 0.1452/0.1452
Lm/H 0.1397
Us/fs 220 V/50 Hz
wslip/(Rad·s–1) 100p
Tab.3  
Fig.7  
Fig.8  
Fig.9  
Fig.10  
Fig.11  
Fig.12  
IAE ISE
PI controller 4.06 5.67
IM controller 3.78 4.23
Tab.4  
Fig.13  
A swept area of the WT
B gearbox ratio
i current
Jt the equivalent inertia of the WT and the generator
L inductance
p number of pole pair
R rotor WT radius
r resistance
s laplace operator
v voltage
z delay operator
Φ flux linkage
ω synchronous speed
Ω rotational speed
θ angle position
β Pitch angle
λ Tip speed ratio
Superscript
* set point
opt optimal value
Subscript
a,b and c three phase components
d d-axis
DC direct current
e electrical
g generator
gr grid
m mutual
q q-axis
r rotor
s stator
  
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