Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainti...Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.展开更多
In this paper, an attitude maneuver control problem is investigated for a rigid spacecraft using an array of two variable speed control moment gyroscopes （VSCMGs） with gimbal axes skewed to each other. A mathematica...In this paper, an attitude maneuver control problem is investigated for a rigid spacecraft using an array of two variable speed control moment gyroscopes （VSCMGs） with gimbal axes skewed to each other. A mathematical model is constructed by taking the spacecraft and the gyroscopes together as an integrated system, with the coupling interaction between them considered. To overcome the singular issues of the VSCMGs due to the conventional torque-based method, the first-order derivative of gimbal rates and the second-order derivative of the rotor spinning velocity, instead of the gyroscope torques, are taken as input variables. Moreover, taking external disturbances into account, a feedback control law is designed for the system based on a method of nonlinear model predictive control （NMPC）. The attitude maneuver can be realized fast and smoothly by using the proposed controller in this paper.展开更多
To solve the coupling relationship between the strip automatic gauge control and the looper control in traditional control strategy of tandem hot rolling,a distributed model predictive control(DMPC)strategy for the ta...To solve the coupling relationship between the strip automatic gauge control and the looper control in traditional control strategy of tandem hot rolling,a distributed model predictive control(DMPC)strategy for the tandem hot rolling was explored,and a series of simulation experiments were carried out.Firstly,based on the state space analysis method,the multivariable dynamic transition process of hot strip rolling was studied,and the state space model of a gauge-looper integrated system in tandem hot rolling was established.Secondly,DMPC strategy based on neighborhood optimization was proposed,which fully considered the coupling relationship in this integrated system.Finally,a series of experiments simulating disturbances and emergency situations were completed with actual rolling data.The experimental results showed that the proposed DMPC control strategy had better performance compared with the traditional proportional-integral control and centralized model predictive control,which is applicable for the gauge-looper integrated system.展开更多
A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation （DISOPE） was proposed for nonlinear cascade systems under network environment. Under the d...A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation （DISOPE） was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.展开更多
A continuous-time Model Predictive Controller was proposed using Kautz function in order to improve the performance of Load Frequency Control(LFC).A dynamic model of an interconnected power system was used for Model P...A continuous-time Model Predictive Controller was proposed using Kautz function in order to improve the performance of Load Frequency Control(LFC).A dynamic model of an interconnected power system was used for Model Predictive Controller(MPC)design.MPC predicts the future trajectory of the dynamic model by calculating the optimal closed loop feedback gain matrix.In this paper,the optimal closed loop feedback gain matrix was calculated using Kautz function.Being an Orthonormal Basis Function(OBF),Kautz function has an advantage of solving complex pole-based nonlinear system.Genetic Algorithm(GA)was applied to optimally tune the Kautz function-based MPC.A constraint based on phase plane analysis was implemented with the cost function in order to improve the robustness of the Kautz function-based MPC.The proposed method was simulated with three area interconnected power system and the efficiency of the proposed method was measured and exhibited by comparing with conventional Proportional and Integral(PI)controller and Linear Quadratic Regulation(LQR).展开更多
Based on the two-dimensional （2D） system theory, an integrated predictive iterative learning control （2D-IPILC） strategy for batch processes is presented. First, the output response and the error transition model ...Based on the two-dimensional （2D） system theory, an integrated predictive iterative learning control （2D-IPILC） strategy for batch processes is presented. First, the output response and the error transition model predictions along the batch index can be calculated analytically due to the 2D Roesser model of the batch process. Then, an integrated framework of combining iterative learning control （ILC） and model predictive control （MPC） is formed reasonably. The output of feedforward ILC is estimated on the basis of the predefined process 2D model. By min- imizing a quadratic objective function, the feedback MPC is introduced to obtain better control performance for tracking problem of batch processes. Simulations on a typical batch reactor demonstrate that the satisfactory tracking performance as well as faster convergence speed can be achieved than traditional proportion type （P- t-we） ILC despite the model error and disturbances.展开更多
The integrated energy systems(IESs)offer a practical solution for achieving low-carbon targets in residential buildings.However,IES encounters several challenges related to increased energy consumption and costs due t...The integrated energy systems(IESs)offer a practical solution for achieving low-carbon targets in residential buildings.However,IES encounters several challenges related to increased energy consumption and costs due to fluctuations in renewable energy generation.Leveraging building flexibility to address these power fluctuations within IES is a promising strategy,which requires coordinated control between air-conditioning systems and other IES components.This study proposes a cross-time-scale control framework that contains optimal scheduling and on-the-fly flexible control to reduce the cost impacts of a residential IES system equipped with photovoltaic(PV)panels,batteries,a heat pump,and a domestic hot water tank.The method involves three key steps:solar irradiance prediction,day-ahead optimal scheduling of energy storage,and intra-day flexible control of the heat pump.The method is validated through a high-fidelity residential building model with actual weather and energy usage data in Frankfurt,Germany.Results reveal that the proposed method limits the cost increase to just 2.67% compared to the day-ahead schedule,whereas the cost could increase by 7.39% without the flexible control.Additionally,computational efficiency is enhanced by transforming the mixed-integer programming(MIP)into nonlinear programming(NLP)problem via introducing action-exclusive constraints.This approach offers valuable support for residential IES operations.展开更多
To achieve low-carbon economic operation of hydrogen-doped integrated energy systems while mitigating the stochastic impact of new energy outputs on the system,the coordinated operation mode of hydrogen-doped gas turb...To achieve low-carbon economic operation of hydrogen-doped integrated energy systems while mitigating the stochastic impact of new energy outputs on the system,the coordinated operation mode of hydrogen-doped gas turbines and electrolyzers is focused on,as well as a hybrid energy storage scheme involving both hydrogen and heat storage and an optimized scheduling model for integrated energy systems encompassing electricity-hydrogen-heat-cooling conversions is established.A model predictive control strategy based on deep learning prediction and feedback is proposed,and the effectiveness and superiority of the proposed strategy are demonstrated using error penalty coefficients.Moreover,the introduction of hydrogen energy exchange and ladder carbon trading is shown to effectively guide the low-carbon economic operation of hydrogen-doped integrated energy systems across multiple typical scenarios.A sensitivity analysis is conducted based on this framework,revealing that increases in the hydrogen doping ratio of turbines and the carbon base price led to higher system operation costs but effectively reduce carbon emissions.展开更多
自然风速的随机性与波动性,风电机组输出功率易出现剧烈波动,不仅降低风能利用效率,还会对电网频率稳定性造成显著冲击,给电力系统安全带来极大隐患。针对这一问题,提出一种考虑风速变化的频率综合控制策略。该策略首先采用模型预测控制...自然风速的随机性与波动性,风电机组输出功率易出现剧烈波动,不仅降低风能利用效率,还会对电网频率稳定性造成显著冲击,给电力系统安全带来极大隐患。针对这一问题,提出一种考虑风速变化的频率综合控制策略。该策略首先采用模型预测控制(model predictive control,MPC)对阵风信号进行优化处理,精准提取有效风速,据此生成最优转速参考值,有效提升最大功率点跟踪(maximum power point tracking,MPPT)的风能捕获效率与稳定性;进而将提取的有效风速作为模糊控制的关键输入,构建自适应虚拟惯性控制模块,通过动态调整控制参数,增强风电机组对电网频率变化的响应速度与调节能力,提升一次调频性能。在MATLAB/Simulink仿真平台搭建仿真模型,模拟不稳定风速工况进行测试,验证所提策略的有效性。仿真结果表明,该综合控制策略能够有效平抑风电机组输出功率的波动,显著抑制电网系统频率的快速变化,为不稳定风速下风电并网系统的安全稳定运行提供可靠保障。展开更多
To address harmonic current proliferation and parameter sensitivity in conventional vector model predictive control(V-MPC)for dual-three-phase permanent magnet synchronous generators(DTP-PMSGs),a harmonic subspace-inc...To address harmonic current proliferation and parameter sensitivity in conventional vector model predictive control(V-MPC)for dual-three-phase permanent magnet synchronous generators(DTP-PMSGs),a harmonic subspace-incorporated disturbance-rejection MPC strategy is proposed.First,an enhanced virtual voltage vector synthesis technique is developed in which three optimal voltage vectors per control sector are strategically combined to achieve full-amplitude and omnidirectional voltage coverage,eliminating harmonic subspace excitation.Second,a super-twisting integral disturbance observer is designed to dynamically estimate and compensate for parameter mismatches and nonlinear rectification disturbances,thereby enhancing the robustness against model inaccuracies.Third,a composite harmonic suppression controller is proposed to replace traditional PI regulators,enabling zero-steady-state error tracking of fundamental currents while actively attenuating harmonic subspace components.Experimental validations confirm that the proposed methodology improves the fundamental current-tracking accuracy,significantly suppresses harmonic currents,and maintains a robust dynamic response under parameter variations.展开更多
This paper presents an Ethernet based hybrid method for predicting random time-delay in the networked control system.First,db3 wavelet is used to decompose and reconstruct time-delay sequence,and the approximation com...This paper presents an Ethernet based hybrid method for predicting random time-delay in the networked control system.First,db3 wavelet is used to decompose and reconstruct time-delay sequence,and the approximation component and detail components of time-delay sequences are fgured out.Next,one step prediction of time-delay is obtained through echo state network(ESN)model and auto-regressive integrated moving average model(ARIMA)according to the diferent characteristics of approximate component and detail components.Then,the fnal predictive value of time-delay is obtained by summation.Meanwhile,the parameters of echo state network is optimized by genetic algorithm.The simulation results indicate that higher accuracy can be achieved through this prediction method.展开更多
For the recent expansion of renewable energy applications, Wind Energy System (WES) is receiving much interest all over the world. However, area load change and abnormal conditions lead to mismatches in frequency and ...For the recent expansion of renewable energy applications, Wind Energy System (WES) is receiving much interest all over the world. However, area load change and abnormal conditions lead to mismatches in frequency and scheduled power interchanges between areas. These mismatches have to be corrected by the LFC system. This paper, therefore, proposes a new robust frequency control technique involving the combination of conventional Proportional-Integral (PI) and Model Predictive Control (MPC) controllers in the presence of wind turbines (WT). The PI-MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. A frequency response dynamic model of a single-area power system with an aggregated generator unit is introduced, and physical constraints of the governors and turbines are considered. The proposed technique is tested on the single-area power system, for enhancement of the network frequency quality. The validity of the proposed method is evaluated by computer simulation analyses using Matlab Simulink. The results show that, with the proposed PI-MPC combination technique, the overall closed loop system performance demonstrated robustness regardless of the presence of uncertainties due to variations of the parameters of governors and turbines, and loads disturbances. A performance comparison between the proposed control scheme, the classical PI control scheme and the MPC is carried out confirming the superiority of the proposed technique in presence of doubly fed induction generator (DFIG) WT.展开更多
In this paper, an optimal control scheme for wind turbine output torque and power regulation under the influence of wind disturbances is presented. The system considered is a dynamic mechanical-based model with pitch ...In this paper, an optimal control scheme for wind turbine output torque and power regulation under the influence of wind disturbances is presented. The system considered is a dynamic mechanical-based model with pitch and generator torque actuators for controlling the pitch and generator torque. The performance of linear matrix inequality (LMI) formalism of linear quadratic regulator (LQR);linear quadratic regulator with integral action (LQRI) and model predictive control (MPC) were compared in response to a step change in wind disturbance. It is shown by Matlab simulation that the LQRI outperformed both LQR and MPC controllers.展开更多
基金supported by the National Key Research and Development Project of China(2018YFE0122200).
文摘Effective source-load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems(IESs).They can overcome the challenges introduced by the uncertainties of new energies and various types of loads in the IES.Accordingly,a robust optimal dispatching method for the IES based on a robust economic model predictive control(REMPC)strategy considering source-load power interval prediction is proposed.First,an operation model of the IES is established,and an interval prediction model based on the bidirectional long short-term memory network optimized by beetle antenna search and bootstrap is formulated and applied to predict the photovoltaic power and the cooling,heating,and electrical loads.Then,an optimal dispatching scheme based on REMPC is devised for the IES.The source-load interval prediction results are used to improve the robustness of the REPMC and reduce the influence of source-load uncertainties on dispatching.An actual IES case is selected to conduct simulations;the results show that compared with other prediction techniques,the proposed method has higher prediction interval coverage probability and prediction interval normalized averaged width.Moreover,the operational cost of the IES is decreased by the REMPC strategy.With the devised dispatching scheme,the ability of the IES to handle the dispatching risk caused by prediction errors is enhanced.Improved dispatching robustness and operational economy are also achieved.
基金supported by the National Natural Science Foundation of China(Nos.11372130,11290153,and 11290154)
文摘In this paper, an attitude maneuver control problem is investigated for a rigid spacecraft using an array of two variable speed control moment gyroscopes （VSCMGs） with gimbal axes skewed to each other. A mathematical model is constructed by taking the spacecraft and the gyroscopes together as an integrated system, with the coupling interaction between them considered. To overcome the singular issues of the VSCMGs due to the conventional torque-based method, the first-order derivative of gimbal rates and the second-order derivative of the rotor spinning velocity, instead of the gyroscope torques, are taken as input variables. Moreover, taking external disturbances into account, a feedback control law is designed for the system based on a method of nonlinear model predictive control （NMPC）. The attitude maneuver can be realized fast and smoothly by using the proposed controller in this paper.
基金This work was supported by the National Key R&D Program of China(Grant Nos.2018YFB1308700)the National Natural Science Foundation of China(Grant Nos.U21A20117 and 52074085+1 种基金the Fundamental Research Funds for the Central Univer-sities(Grant No.N2004010)the Liaoning Revitalization Talents651 Program(XLYC1907065).
文摘To solve the coupling relationship between the strip automatic gauge control and the looper control in traditional control strategy of tandem hot rolling,a distributed model predictive control(DMPC)strategy for the tandem hot rolling was explored,and a series of simulation experiments were carried out.Firstly,based on the state space analysis method,the multivariable dynamic transition process of hot strip rolling was studied,and the state space model of a gauge-looper integrated system in tandem hot rolling was established.Secondly,DMPC strategy based on neighborhood optimization was proposed,which fully considered the coupling relationship in this integrated system.Finally,a series of experiments simulating disturbances and emergency situations were completed with actual rolling data.The experimental results showed that the proposed DMPC control strategy had better performance compared with the traditional proportional-integral control and centralized model predictive control,which is applicable for the gauge-looper integrated system.
基金This work was supportedbytheNationalNaturalScienceFoundationofChina(No.60474051),theProgramforNewCenturyExcellentTalentsinUniversityofChina(NCET),andtheSpecializedResearchFundfortheDoctoralProgramofHigherEducationofChina(No.20020248028).
文摘A novel distributed model predictive control scheme based on dynamic integrated system optimization and parameter estimation （DISOPE） was proposed for nonlinear cascade systems under network environment. Under the distributed control structure, online optimization of the cascade system was composed of several cascaded agents that can cooperate and exchange information via network communication. By iterating on modified distributed linear optimal control problems on the basis of estimating parameters at every iteration the correct optimal control action of the nonlinear model predictive control problem of the cascade system could be obtained, assuming that the algorithm was convergent. This approach avoids solving the complex nonlinear optimization problem and significantly reduces the computational burden. The simulation results of the fossil fuel power unit are illustrated to verify the effectiveness and practicability of the proposed algorithm.
文摘A continuous-time Model Predictive Controller was proposed using Kautz function in order to improve the performance of Load Frequency Control(LFC).A dynamic model of an interconnected power system was used for Model Predictive Controller(MPC)design.MPC predicts the future trajectory of the dynamic model by calculating the optimal closed loop feedback gain matrix.In this paper,the optimal closed loop feedback gain matrix was calculated using Kautz function.Being an Orthonormal Basis Function(OBF),Kautz function has an advantage of solving complex pole-based nonlinear system.Genetic Algorithm(GA)was applied to optimally tune the Kautz function-based MPC.A constraint based on phase plane analysis was implemented with the cost function in order to improve the robustness of the Kautz function-based MPC.The proposed method was simulated with three area interconnected power system and the efficiency of the proposed method was measured and exhibited by comparing with conventional Proportional and Integral(PI)controller and Linear Quadratic Regulation(LQR).
基金Supported in part by the State Key Development Program for Basic Research of China(2012CB720505)the National Natural Science Foundation of China(61174105,60874049)
文摘Based on the two-dimensional （2D） system theory, an integrated predictive iterative learning control （2D-IPILC） strategy for batch processes is presented. First, the output response and the error transition model predictions along the batch index can be calculated analytically due to the 2D Roesser model of the batch process. Then, an integrated framework of combining iterative learning control （ILC） and model predictive control （MPC） is formed reasonably. The output of feedforward ILC is estimated on the basis of the predefined process 2D model. By min- imizing a quadratic objective function, the feedback MPC is introduced to obtain better control performance for tracking problem of batch processes. Simulations on a typical batch reactor demonstrate that the satisfactory tracking performance as well as faster convergence speed can be achieved than traditional proportion type （P- t-we） ILC despite the model error and disturbances.
基金supported by the National Key Research and Development Program of China(2022YFB4200902)。
文摘The integrated energy systems(IESs)offer a practical solution for achieving low-carbon targets in residential buildings.However,IES encounters several challenges related to increased energy consumption and costs due to fluctuations in renewable energy generation.Leveraging building flexibility to address these power fluctuations within IES is a promising strategy,which requires coordinated control between air-conditioning systems and other IES components.This study proposes a cross-time-scale control framework that contains optimal scheduling and on-the-fly flexible control to reduce the cost impacts of a residential IES system equipped with photovoltaic(PV)panels,batteries,a heat pump,and a domestic hot water tank.The method involves three key steps:solar irradiance prediction,day-ahead optimal scheduling of energy storage,and intra-day flexible control of the heat pump.The method is validated through a high-fidelity residential building model with actual weather and energy usage data in Frankfurt,Germany.Results reveal that the proposed method limits the cost increase to just 2.67% compared to the day-ahead schedule,whereas the cost could increase by 7.39% without the flexible control.Additionally,computational efficiency is enhanced by transforming the mixed-integer programming(MIP)into nonlinear programming(NLP)problem via introducing action-exclusive constraints.This approach offers valuable support for residential IES operations.
基金supported by Key project of the National Natural Science Foundation of China(Grant No.U2243243)National key research and development program(Grant No.2022YFE0101600)。
文摘To achieve low-carbon economic operation of hydrogen-doped integrated energy systems while mitigating the stochastic impact of new energy outputs on the system,the coordinated operation mode of hydrogen-doped gas turbines and electrolyzers is focused on,as well as a hybrid energy storage scheme involving both hydrogen and heat storage and an optimized scheduling model for integrated energy systems encompassing electricity-hydrogen-heat-cooling conversions is established.A model predictive control strategy based on deep learning prediction and feedback is proposed,and the effectiveness and superiority of the proposed strategy are demonstrated using error penalty coefficients.Moreover,the introduction of hydrogen energy exchange and ladder carbon trading is shown to effectively guide the low-carbon economic operation of hydrogen-doped integrated energy systems across multiple typical scenarios.A sensitivity analysis is conducted based on this framework,revealing that increases in the hydrogen doping ratio of turbines and the carbon base price led to higher system operation costs but effectively reduce carbon emissions.
文摘自然风速的随机性与波动性,风电机组输出功率易出现剧烈波动,不仅降低风能利用效率,还会对电网频率稳定性造成显著冲击,给电力系统安全带来极大隐患。针对这一问题,提出一种考虑风速变化的频率综合控制策略。该策略首先采用模型预测控制(model predictive control,MPC)对阵风信号进行优化处理,精准提取有效风速,据此生成最优转速参考值,有效提升最大功率点跟踪(maximum power point tracking,MPPT)的风能捕获效率与稳定性;进而将提取的有效风速作为模糊控制的关键输入,构建自适应虚拟惯性控制模块,通过动态调整控制参数,增强风电机组对电网频率变化的响应速度与调节能力,提升一次调频性能。在MATLAB/Simulink仿真平台搭建仿真模型,模拟不稳定风速工况进行测试,验证所提策略的有效性。仿真结果表明,该综合控制策略能够有效平抑风电机组输出功率的波动,显著抑制电网系统频率的快速变化,为不稳定风速下风电并网系统的安全稳定运行提供可靠保障。
基金Supported by National Science Fund for Distinguished Young Scholars(52023073).
文摘To address harmonic current proliferation and parameter sensitivity in conventional vector model predictive control(V-MPC)for dual-three-phase permanent magnet synchronous generators(DTP-PMSGs),a harmonic subspace-incorporated disturbance-rejection MPC strategy is proposed.First,an enhanced virtual voltage vector synthesis technique is developed in which three optimal voltage vectors per control sector are strategically combined to achieve full-amplitude and omnidirectional voltage coverage,eliminating harmonic subspace excitation.Second,a super-twisting integral disturbance observer is designed to dynamically estimate and compensate for parameter mismatches and nonlinear rectification disturbances,thereby enhancing the robustness against model inaccuracies.Third,a composite harmonic suppression controller is proposed to replace traditional PI regulators,enabling zero-steady-state error tracking of fundamental currents while actively attenuating harmonic subspace components.Experimental validations confirm that the proposed methodology improves the fundamental current-tracking accuracy,significantly suppresses harmonic currents,and maintains a robust dynamic response under parameter variations.
基金supported by National Natural Science Foundation of China(No.61034005)
文摘This paper presents an Ethernet based hybrid method for predicting random time-delay in the networked control system.First,db3 wavelet is used to decompose and reconstruct time-delay sequence,and the approximation component and detail components of time-delay sequences are fgured out.Next,one step prediction of time-delay is obtained through echo state network(ESN)model and auto-regressive integrated moving average model(ARIMA)according to the diferent characteristics of approximate component and detail components.Then,the fnal predictive value of time-delay is obtained by summation.Meanwhile,the parameters of echo state network is optimized by genetic algorithm.The simulation results indicate that higher accuracy can be achieved through this prediction method.
文摘For the recent expansion of renewable energy applications, Wind Energy System (WES) is receiving much interest all over the world. However, area load change and abnormal conditions lead to mismatches in frequency and scheduled power interchanges between areas. These mismatches have to be corrected by the LFC system. This paper, therefore, proposes a new robust frequency control technique involving the combination of conventional Proportional-Integral (PI) and Model Predictive Control (MPC) controllers in the presence of wind turbines (WT). The PI-MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. A frequency response dynamic model of a single-area power system with an aggregated generator unit is introduced, and physical constraints of the governors and turbines are considered. The proposed technique is tested on the single-area power system, for enhancement of the network frequency quality. The validity of the proposed method is evaluated by computer simulation analyses using Matlab Simulink. The results show that, with the proposed PI-MPC combination technique, the overall closed loop system performance demonstrated robustness regardless of the presence of uncertainties due to variations of the parameters of governors and turbines, and loads disturbances. A performance comparison between the proposed control scheme, the classical PI control scheme and the MPC is carried out confirming the superiority of the proposed technique in presence of doubly fed induction generator (DFIG) WT.
文摘In this paper, an optimal control scheme for wind turbine output torque and power regulation under the influence of wind disturbances is presented. The system considered is a dynamic mechanical-based model with pitch and generator torque actuators for controlling the pitch and generator torque. The performance of linear matrix inequality (LMI) formalism of linear quadratic regulator (LQR);linear quadratic regulator with integral action (LQRI) and model predictive control (MPC) were compared in response to a step change in wind disturbance. It is shown by Matlab simulation that the LQRI outperformed both LQR and MPC controllers.
