变速风力发电机组的经济模型预测控制
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摘要
在风力发电控制系统中,模型预测控制是降低发电成本、提高能源利用率的有效方式。经济模型预测控制,旨在用一个优化问题实现不同区域控制目标,同时实现运行区域间的高效切换。以5 MW风电机组作为研究对象,对两种控制策略进行了仿真对比。结果表明经济模型预测控制不仅实现机组不同区域的控制目标同时提高闭环经济性能,尤其在区域切换过程中,可以有效提高风能利用,减小结构疲劳,对改善风电的电能质量,延长机组使用寿命具有重要意义。
For the wind energy conversation system(WECS), model predictive control(MPC) has become an effective way to reduce the cost of generating electricity and improve the utilization of energy. This paper presents a new control strategy, economic model predictive control(EMPC), to achieve control objectives of WECS with one on-line optimization problem, while realizing efficient switching between two operation regions. The simulation research of the 5 MW WECS has been carried out aiming to compare the classical MPC and EMPC. The simulation results show that the EMPC can achieve the objectives while improving wind energy capture and reducing the fatigue load, especially in the switching process which has great significance on the improvement of the power quality and prolonging the service life of the facilities.
For the wind energy conversation system(WECS), model predictive control(MPC) has become an effective way to reduce the cost of generating electricity and improve the utilization of energy. This paper presents a new control strategy, economic model predictive control(EMPC), to achieve control objectives of WECS with one on-line optimization problem, while realizing efficient switching between two operation regions. The simulation research of the 5 MW WECS has been carried out aiming to compare the classical MPC and EMPC. The simulation results show that the EMPC can achieve the objectives while improving wind energy capture and reducing the fatigue load, especially in the switching process which has great significance on the improvement of the power quality and prolonging the service life of the facilities.
引文
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[24]Henriksen L C.Model Predictive Control of a Wind Turbine[D].Technical University of Denmark,2007.
[25]张雷,李海东,李建林.基于LQR方法的风电机组变桨距控制的动态建模与仿真分析[J].太阳能学报,2008,29(7):781-785.Zhang L,Li H D,Li J L.Dynamic Modeling and Simulation of Pitch Control Strategy for Wind Turbine[J].Acta Energiae Solaris Sinica,2008,29(7):781-785.
[26]Jonkman J,Butterfield S,Musial W,et al.Definition of a 5-MWReference Wind Turbine for Offshore System Development[R].National Renewable Energy Laboratory,2009.
[27]Biegler L T.Nonlinear Programming:Concepts,Algorithms,and Applications to Chemical Processes[M].Society for Industrial and Applied Mathematics,2010.
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[2]耿华,杨耕.变速变桨距风电系统的功率水平控[J].中国电机工程学报,2008,28(25):130-137.Geng H,Yang G.Output power level of variable-speed variable pitch wind generators[J].Proceedings of the CSEE,2008,28(25):130-137.
[3]韩兵,周腊吾,陈浩.大型风电机组激光雷达辅助模型预测控制方法[J].中国电机工程学报,2016,36(18):5062-5069.Han B,Zhou L W,Chen H.Approach to Model Predictive Control of Large Wind Turbine Using Light Detection and Ranging Measurements[J].Proceedings of the CSEE,2016,36(18):5062-5069.
[4]Kong W,Chai T,Ding J.Multifurnace Optimization in Electric Smelting Plants by Load Scheduling and Control[J].IEEE Transactions on Automation Science and Engineering,2014,11(3):850-862.
[5]Chai T,Zhai L,Yue H.Multiple models and neural networks based decoupling control of ball mill coal-pulverizing systems[J].Journal of Process Control,2011,21(3):351-366.
[6]Wang L,Cao L,Lei Z.Non-linear tip speed ratio cascade control for variable speed high power wind turbines:a backstepping approach[J].Iet Renewable Power Generation,2018,12(8):968-972.
[7]黄守道,卢季宁,黄科元.优化爬山算法在直驱永磁风力发电系统中的应用[J].控制理论与应用,2010,27(9):1221-1226.Huang S D,Lu J N,Huang K Y.Optimized hill-climb search algorithm applied to directly driven wind-turbine with permanent-magnet synchronous generator[J].Control Theory&Applications,2010,27(9):1221-1226.
[8]Chen Z,Guerrero J M,Blaabjerg F.A Review of the State of the Art of Power Electronics for Wind Turbines[J].IEEE Transactions on Power Electronics,2009,24(8):1859-1875.
[9]赵永祥,夏长亮,宋战锋.变速恒频风力发电系统风机转速非线性PID控制[J].中国电机工程学报,2008,28(11):133-138.Zhao Y X,Xia C L,Song Z F.Nonlinear PID rotating speed control of variable speed constant frequency wind turbine system[J].Proceedings of the CSEE,2008,28(11):133-138.
[10]Liu X,Han Y,Wang C.Second-order sliding mode control for power optimization of DFIG-based variable speed wind turbine[J].Iet Renewable Power Generation,2017,11(2):408-418.
[11]Ma M M,Chen H,Liu X J.Moving horizon h∞,control of variable speed wind turbines with actuator saturation[J].Renewable Power Generation Iet,2014,8(5):498-508.
[12]Zhou P,Chai T Y,Sun J.Intelligence-Based Supervisory Control for Optimal Operation of a DCS-Controlled Grinding System[J].IEEETransactions on Control Systems Technology,2013,21(1):162-175.
[13]Zhou P,Chai T Y,Sun J.Intelligence-Based Supervisory Control for Optimal Operation of a DCS-Controlled Grinding System[J].IEEETransactions on Control Systems Technology,2013,21(1):162-175.
[14]Chai T Y,Zhao L,Qiu J,et al.Integrated Network-Based Model Predictive Control for Setpoints Compensation in Industrial Processes[J].IEEE Transactions on Industrial Informatics,2013,9(1):417-426.
[15]Chai T Y,Ding J,Yu G,et al.Integrated Optimization for the Automation Systems of Mineral Processing[J].IEEE Transactions on Automation Science&Engineering,2014,11(4):965-982.
[16]丁进良,杨翠娥,陈远东.复杂工业过程智能优化决策系统的现状与展望[J].自动化学报,2018,44(11):1931-1943.Ding J L,Yang C E,Chen Y D.Research Progress and Prospects of Intelligent Optimization Decision Making in Complex Industrial Process[J].Acta Automatica Sinica,2018,44(11):1931-1943.
[17]朱宇蒙,李少远.网络化控制系统的预测控制方法设计[J].控制工程,2013,20(3):426-430.Zhu Y M,Li S Y.Design of Networked Predictive Control in Networked Control Systems[J].Control Engineering of China,2013,20(3):426-430.
[18]Angeli D,Amrit R,Rawlings J B.On average performance and stability of economic model predictive control[J].IEEE transactions on automatic control,2012,57(7):1615-1626.
[19]Heidarinejad M,Liu J F,Christofides P D.Economic model predictive control of nonlinear process systems using Lyapunov techniques[J].Aiche Journal,2012,58(3):855-870.
[20]Kohler J,Muller M A,Allgower F.Nonlinear reference tracking:An economic model predictive control perspective[J].IEEETransactions on Automatic Control,2018,64(1):254-269.
[21]何德峰.约束非线性系统稳定经济模型预测控制[J].自动化学报,2016,42(11):1680-1690.He D F.Stabilizing Economic Model Predictive Control of Constrained Nonlinear Systems[J].Acta Automatica Sinica,2016,42(11):1680-1690.
[22]Zhang X,Bao J,Wang R,et al.Dissipativity based distributed economic model predictive control for residential microgrids with renewable energy generation and battery energy storage[J].Renewable Energy,2017,100(1):18-34.
[23]Liu X J,Cui J H.Economic model predictive control of boiler-turbine system[J].Journal of Process Control,2018,66:59-67.
[24]Henriksen L C.Model Predictive Control of a Wind Turbine[D].Technical University of Denmark,2007.
[25]张雷,李海东,李建林.基于LQR方法的风电机组变桨距控制的动态建模与仿真分析[J].太阳能学报,2008,29(7):781-785.Zhang L,Li H D,Li J L.Dynamic Modeling and Simulation of Pitch Control Strategy for Wind Turbine[J].Acta Energiae Solaris Sinica,2008,29(7):781-785.
[26]Jonkman J,Butterfield S,Musial W,et al.Definition of a 5-MWReference Wind Turbine for Offshore System Development[R].National Renewable Energy Laboratory,2009.
[27]Biegler L T.Nonlinear Programming:Concepts,Algorithms,and Applications to Chemical Processes[M].Society for Industrial and Applied Mathematics,2010.
[28]Munteanu I,Bratcu A I,Cutululis N A,et al.Optimal Control of Wind Energy Systems,Towards a Global Approach[M].Springer London,2008.