In this work, an intelligent artificial control of a variable speed wind turbine (PMSG) is proposed. First, a mathematical model of turbine written at variable speed is established to investigate simulations results. ...In this work, an intelligent artificial control of a variable speed wind turbine (PMSG) is proposed. First, a mathematical model of turbine written at variable speed is established to investigate simulations results. In order to optimize energy production from wind, a pitch angle and DC bus control law is synthesized using PI controllers. Then, an intelligent artificial control such as fuzzy logic and artificial neural network control is applied. Its simulated performances are then compared to those of a classical PI controller. Results obtained in MATLAB/Simulink environment show that the fuzzy and the neuro control is more robust and has superior dynamic performance and hence is found to be a suitable replacement of the conventional PI controller for the high performance drive applications.展开更多
该文以10 k W的直驱永磁同步风力发电机(PMSG)为具体对象,对直驱永磁同步风力发电机组进行建模及仿真研究,在Matlab/Simuliuk平台上建立永磁同步风力发电机组各个子系统的数学模型。在发电环节整体动态仿真模型的基础上,采用变转速变桨...该文以10 k W的直驱永磁同步风力发电机(PMSG)为具体对象,对直驱永磁同步风力发电机组进行建模及仿真研究,在Matlab/Simuliuk平台上建立永磁同步风力发电机组各个子系统的数学模型。在发电环节整体动态仿真模型的基础上,采用变转速变桨距角的控制策略,针对变桨距控制系统设计了PID控制器,并调节PID参数,较好地实现控制器的性能。展开更多
The asymmetric or periodically varying blade loads resulted by wind shear become more significant as the blade length is increased to capture more wind power.Additionally,compared with the onshore wind turbines,their ...The asymmetric or periodically varying blade loads resulted by wind shear become more significant as the blade length is increased to capture more wind power.Additionally,compared with the onshore wind turbines,their offshore counterparts are subjected to additional wave loadings in addition to wind loadings within their lifetime.Therefore,vibration control and fatigue load mitigation are crucial for safe operation of large-scale offshore wind turbines.In view of this,a multi-body model of an offshore bottom-fixed wind turbine including a detailed drivetrain is established in this paper.Then,an individual pitch controller(IPC)is designed using disturbance accommodating control.State feedback is used to add damping in flexible modes of concern,and a state estimator is designed to predict unmeasured signals.Continued,a coupled aero-hydro-servo-elastic model is constructed.Based on this coupled model,the load reduction effect of IPC and the dynamic responses of the drivetrain are investigated.The results showed that the designed IPC can effectively reduce the structural loads of the wind turbine while stabilizing the turbine power out-put.Moreover,it is found that the drivetrain dynamic responses are improved under IPC.展开更多
In recent times,wind energy receives maximum attention and has become a significant green energy source globally.The wind turbine(WT)entered into several domains such as power electronics that are employed to assist t...In recent times,wind energy receives maximum attention and has become a significant green energy source globally.The wind turbine(WT)entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and grid.The turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power extraction.The pitch control angle is employed to effectively operate the WT at the above nominal wind speed.Besides,the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep WTs in a safe operating region.To achieve this,proportional–integral–derivative(PID)controllers are widely used and the choice of optimal parameters in the PID controllers needs to be properly selected.With this motivation,this paper designs an oppositional brain storm optimization(OBSO)based fractional order PID(FOPID)design for sustainable and secure energy in WT systems.The proposed model aims to effectually extract the maximum power point(MPPT)in the low range of weather conditions and save the WT in high wind regions by the use of pitch control.The OBSO algorithm is derived from the integration of oppositional based learning(OBL)concept with the traditional BSO algorithm in order to improve the convergence rate,which is then applied to effectively choose the parameters involved in the FOPID controller.The performance of the presented model is validated on the pitch control of a 5 MW WT and the results are examined under different dimensions.The simulation outcomes ensured the promising characteristics of the proposed model over the other methods.展开更多
文摘In this work, an intelligent artificial control of a variable speed wind turbine (PMSG) is proposed. First, a mathematical model of turbine written at variable speed is established to investigate simulations results. In order to optimize energy production from wind, a pitch angle and DC bus control law is synthesized using PI controllers. Then, an intelligent artificial control such as fuzzy logic and artificial neural network control is applied. Its simulated performances are then compared to those of a classical PI controller. Results obtained in MATLAB/Simulink environment show that the fuzzy and the neuro control is more robust and has superior dynamic performance and hence is found to be a suitable replacement of the conventional PI controller for the high performance drive applications.
文摘该文以10 k W的直驱永磁同步风力发电机(PMSG)为具体对象,对直驱永磁同步风力发电机组进行建模及仿真研究,在Matlab/Simuliuk平台上建立永磁同步风力发电机组各个子系统的数学模型。在发电环节整体动态仿真模型的基础上,采用变转速变桨距角的控制策略,针对变桨距控制系统设计了PID控制器,并调节PID参数,较好地实现控制器的性能。
基金This paper is financially supported by the Scientific Research Foundation of Chongqing University of Technology(Grant Nos.2020ZDZ023 and 2019ZD124)the Project of Science and Technology Research Program of Chongqing Education Commission of China(Grant No.KJQN202101133)the National Natural Science Foundation Cultivation Program of Chongqing University of Technology(Grant No.2021PYZ14).
文摘The asymmetric or periodically varying blade loads resulted by wind shear become more significant as the blade length is increased to capture more wind power.Additionally,compared with the onshore wind turbines,their offshore counterparts are subjected to additional wave loadings in addition to wind loadings within their lifetime.Therefore,vibration control and fatigue load mitigation are crucial for safe operation of large-scale offshore wind turbines.In view of this,a multi-body model of an offshore bottom-fixed wind turbine including a detailed drivetrain is established in this paper.Then,an individual pitch controller(IPC)is designed using disturbance accommodating control.State feedback is used to add damping in flexible modes of concern,and a state estimator is designed to predict unmeasured signals.Continued,a coupled aero-hydro-servo-elastic model is constructed.Based on this coupled model,the load reduction effect of IPC and the dynamic responses of the drivetrain are investigated.The results showed that the designed IPC can effectively reduce the structural loads of the wind turbine while stabilizing the turbine power out-put.Moreover,it is found that the drivetrain dynamic responses are improved under IPC.
基金Deputyship for Research and Innovation,Ministry of Education in Saudi Arabia,project number(IFPRC-040-135-2020)。
文摘In recent times,wind energy receives maximum attention and has become a significant green energy source globally.The wind turbine(WT)entered into several domains such as power electronics that are employed to assist the connection process of a wind energy system and grid.The turbulent characteristics of wind profile along with uncertainty in the design of WT make it highly challenging for prolific power extraction.The pitch control angle is employed to effectively operate the WT at the above nominal wind speed.Besides,the pitch controller needs to be intelligent for the extraction of sustainable secure energy and keep WTs in a safe operating region.To achieve this,proportional–integral–derivative(PID)controllers are widely used and the choice of optimal parameters in the PID controllers needs to be properly selected.With this motivation,this paper designs an oppositional brain storm optimization(OBSO)based fractional order PID(FOPID)design for sustainable and secure energy in WT systems.The proposed model aims to effectually extract the maximum power point(MPPT)in the low range of weather conditions and save the WT in high wind regions by the use of pitch control.The OBSO algorithm is derived from the integration of oppositional based learning(OBL)concept with the traditional BSO algorithm in order to improve the convergence rate,which is then applied to effectively choose the parameters involved in the FOPID controller.The performance of the presented model is validated on the pitch control of a 5 MW WT and the results are examined under different dimensions.The simulation outcomes ensured the promising characteristics of the proposed model over the other methods.
