摘要
静止同步串联补偿器(Static Synchronous Series Compensator, SSSC)作为柔性交流输电系统(Flexible AC Transmission Systems, FACTS)的重要装置之一,具有响应速度快、控制精度高、动态性能好等优越性。快速潮流控制是SSSC的主要功能之一,然而选择好的控制方法是充分发挥其潮流控制作用的关键。
论文首先在两相同步旋转d-q坐标系下建立了SSSC的数学模型,在分析此模型的基础上提出了基于输入变换的有功和无功解耦策略,给出了能使输电线路上有功和无功实现动态解耦和实现静态解耦的输入变换矩阵。结合有功和无功动态解耦策略,利用神经网络自整定PI算法设计了SSSC的潮流控制器。
根据SSSC控制系统的特点,把SSSC的控制分为两部分,即内环控制和外环控制,每个部分都有其明确的被控制对象,并可以分别独立的设计其控制器。在内环控制中,考虑到由于电感的存在,线路电流在电容电压稳定前不会有大的变化,选择SSSC装置本身为被控对象,以SSSC的电容电压为控制目标,选用传统的PID控制器去维持电容电压的稳定。考虑到传统PID控制器的参数很难整定、不具有适应性和响应时间长等方面的缺陷,利用人工神经网络和传统PID控制器相结合的方法设计了神经网络自整定PID控制器,并用此控制器去控制直流侧电容电压。因为利用神经网络的非线性拟合能力在线整定PID控制器的3个参数,使其适应系统的变化,所以解决了传统PID控制器由于参数固定而产生的缺陷。在外环控制中,选择装设SSSC的输电线路为被控对象,以输电线路的有效阻抗为控制目标,选择传统的PID控制器去控制线路的有效阻抗。但是,装设SSSC的输电线路是一个复杂的非线性系统,传统的PID控制器的控制效果不理想。本文采用启发式近似动态规划(Heuristic Dynamic Programming, HDP)算法设计了SSSC外环控制器,控制器总共包含3个神经网络,即模型网络、评价网络和动作网络,动作网络的作用是产生控制量,而评价网络的作用是评价这个控制量的好坏,它们互相协作,从而得到最佳的控制序列。由于将一个复杂的大系统分成两个设计相对容易的子系统,并且每个子系统都有各自的控制对象,所以降低了控制器的复杂性和设计的难度。
在MATLAB动态仿真环境中对所建立的神经网络模型、所设计的内环控制器和外环控制器进行了仿真,并与传统的PID控制器进行了对比,仿真结果验证了该控制器的有效性和适用性。
Static synchronous series compensator (SSSC) with advantages of faster response, higher control precision and perfect dynamic performance is one of the important FACTS (Flexible AC Transmission Systems) devices. One of the main functions of SSSC is fast power flow control, which will be fully played by the choice of a good control method.
A two- machine system mathematic model is built in a synchronously rotating d-q frame by using Park's transformation, in which the power systems with SSSC is controlled object. In the deeply research of the mathematic model, a d-q axes decoupling method based on the input transformation is proposed, using which the transmission line active and reactive power flow can be decoupled. Meanwhile, the decoupling model which can be used for dynamic decoupling and the transformation matrix which can be used for static decoupling are present. Afterwards the outer-loop controller of SSSC is designed with the neural network self-tuning PI algorithm in the basic of dynamic decoupling.
According to the characteristics of SSSC control system, the control of SSSC is able to divide into two parts which have the controlled objects and can be independently designed respectively, namely inner-loop control and outer-loop control. In inner control strategy, because of the existence of inductance, the transmission line current will not be changes greatly before the capacitance voltage stability, of which is taken into account the traditional PID controller is used to maintain the stability of capacitor voltage, in which the SSSC device itself is selected as control object, and taken the capacitor voltage as control objective. However, considering the defects of tuning difficult, inadaptability and long response time of traditional PID controller, a neural network self-tuning PID controller which is emplied to control DC side capacitor voltage is designed using artificial neural networks and traditional PID controller. The three parameters of traditional PID controller can be tunning on line using neural network which has nonlinear fitting ability, so as to adapt the changes of controlled system. Therefore the traditional PID controller's defects arised due to fixed parameters are able to overcome.
In outer control strategy, the traditional PID controller is used to control transmission line effective impedance, in which the transmission line installed with SSSC is selected as control object and taken the effective impedance as control objective. However, the traditional PID controller is not satisfied to morden control since the power system installed with SSSC is a complex nonlinear system. Therefore, the outer controller using Heuristic Dynamic Programming (HDP) is designed for SSSC. The controller based HDP contains a total of three neural networks, in which the model network is to estimate the system's output, the action network to give the control variable, and the critic network to value this control variable.
In this paper, the complicacy and design difficulty of SSSC controller are able to debase because a large complex system is divided into two small systems whose controllers are easily designed correspondingly and control objects are unambiguous.
A studying example is carried out to estimate good robustness and adaptability of the proposed controller in the MATLAB dynamic simulation platform. The results verified the availability and feasibility of the proposed control strategy in power flow control of power systems.
引文
[1]何大愚.柔性交流输电系统概念研究的新发展[J].电网技术,1997,21(2):9-14
[2]谢小荣,姜齐荣.柔性交流输电系统的原理与应用[M].北京:清华大学出版社,2006:13-58
[3]解大.可控串联补偿(TCSC)的稳态及动态分析[D].上海:上海交通大学,1999
[4]周俊宇.静止同步串联补偿器在电力系统中的应用综述[J].电气应用,2006,25(4):51-54
[5]刘隽,李兴源,姚大伟,等.静止同步串联补偿器与静止无功补偿器的相互作用分析与协调控制[J].电网技术,2008,32(1):20-25
[6]宁改娣,何世杰,王跃,等.静止同步串联补偿器抑制次同步谐振研究[J].西安交通大学学报,2008,42(2):189-193
[7]刘慧威.静止同步串联补偿器的数学建模及其仿真研究[D].北京:华北电力大学,2006
[8]Griffo A, Lauria D. Two-Leg Three-Phase Inverter Control for STATCOM and SSSC Applications [J]. IEEE Trans. on Power Delivery,2008,23(1):361-370
[9]Mihalic R, Papic I. Mathematical models and simulation of a static synchronous series compensator[A]. International Conference on Electric Power Engineering[C]. Budapest, Hungary,1999:266-271
[10]Zhang X P. Advanced modeling of the multi-control functional static synchronous series compensator in Newton power flow [J]. IEEE Trans. on Power Systems,2003, 18(4):1410-1416
[11]张彦魁,张焰,吴蓓,等.包含多控制模式及运行极限的静止同步补偿器建模[J].上海交通大学学报,2006,40(3):539-542
[12]Kalyan K S. SSSC--static synchronous series compensator Theory, Model and Applications [J]. IEEE Trans. on Power Delivery,1998,13(1):241-246.
[13]Sunil K L, Arindam G. Modeling and control design of a static synchronous series compensator [J]. IEEE Trans. on Power Delivery,1999,14(4): 1448-1457
[14]刘黎明,康勇,陈坚,等SSSC建模、控制策略及性能[J].电工技术学报,2006,21(9):37-47
[15]张兴,袁祖慧,谢震.基于静止同步串联补偿器的VSC-HVDC控制策略[J].系统仿真学报,2009,21(10):2999-3002
[16]郭成,李群湛.基于改进PSO算法的SSSC广域阻尼控制器设计[J].电工技术学报,2010,25(1):151-158
[17]Wei Qiao, Venayagamoorthy G K, Harley R G. Missing-Sensor-Fault-Tolerant Control for SSSC FACTS Device with Real-Time Implementation [J]. IEEE Trans. on Power Delivery,2009,24(2):740-750
[18]Zhao J J, Guo J B, Zhou X X. Modeling of static synchronous series compensator in Newton power flow calculation in PSASP[A]. Asia and Pacific Transmission and Distribution Conference and Exhibition[C].Dalian, China,2005:1-5
[19]Zhang X P, Xue C F, Godfrey K R. Modelling of the static synchronous series compensator (SSSC) in three-phase Newton power flow [J]. IEE Proceedings on Transmission and Distribution,2004,151(4):486-496
[20]姜旭,肖湘宁,尹忠东,等.H桥级联式SSSC直流侧电容值选择及自励启动充能策略[J].电工技术学报,2007,31(3):41-46
[21]姜旭,肖湘宁.级联结构SSSC的RTDS小步长建模[J].高电压技术,2006,32(10):72-78
[22]姜旭,肖湘宁,赵洋.H桥级联式SSSC阻抗补偿域及准稳态模型[J].电工技术学报,2007,22(4):136-147
[23]王庆红,胡国根.一种基于48脉波电压源逆变器的静止同步串联补偿器的设计与建模[J].中国电机工程学报,2001,21(5):61-66
[24]王庆红,胡国根.一种基于48脉波电压源逆变器的静止同步串联补偿器的设计与建模_上[J].中国电机工程学报,2001,13(2):56-57
[25]孙玉坤STATCOM非线性H 2/H_∞混合控制与模块化嵌入式数字系统研究[D].镇江:江苏大学,2008
[26]梁凯,许江涛,尚培祥.基于模糊规则的SSSC智能控制器设计[J].电力科学与工程,2010,26(3):44-48
[27]薛亚丽,李东海,徐峰,等.最优PI控制器参数整定及评价[J].清华大学学报,2004,44(8):1067-1070
[28]孙海顺,马凡,刘黎明,等.一种UPFC模糊PI自整定控制[J].电工技术学报,2007,22(9):136-142
[29]Kiam H A, Chong G, Yun L. PID control system analysis, design, and technology[J]. IEEE Trans. on Control Systems Technology,2005,13(4):559-576
[30]El-Moursi M S, Sharaf A M. Novel controllers for the 48-Pulse VSC STATCOM and SSSC for Voltage Regulation and Reactive Power Compensation [J]. IEEE Trans. on Power Systems,2005,20(4):1987-1997
[31]David F, Venkataramanan G Modeling and Control of the Static Synchronous Series Compensator under Different Operating Modes[A]. IEEE Power Electronics Specialists Conference[C]. Orlando, USA,2007:2443-2479
[32]Liu L M, Zhang Y G, Zhu P C, et al. Double Closed Loop Control and Analysis for A Static Synchronous Series Compensator[A]. IEEE 36th Power Electronics Specialists Conference[C]. Recife, Brazil,2005:354-360
[33]Hatziadoniu C J, Funk A T. Development of a control scheme for a series-connected solid-state synchronous voltage source [J]. IEEE Trans. on Power Delivery,1996,11 (2):1138-1146
[34]王辉,王耀南,许维东.基于模糊自整定PI控制的SSSC潮流控制器研究[J].电工技术学报,2004,19(7):67-69
[35]Abdelazim T, Malik O P. Adaptive fuzzy control of SSSC to improve damping of power system oscillations[A]. IEEE Power Engineering Society General Meeting[C]. Montreal,Canada,2006,6-10
[36]Sze K M, Snider L A, Chung T S, et al. An intelligent fuzzy controlled SSSC to enhance power system stability[A].2004 International Conference on Power System[C]. Suntec City, Singapore,2004:1183-1188
[37]Kannan S, Jayaram S, Salama M M A. Fuzzy logic based supplementary controller for static synchronous series compensator[A]. IEEE Canadian Conference on Electrical and Computer Engineering[C]. Waterloo, Canada, 1998:489-492
[38]Sadeghzadeh S M, Ansarian M. Neuro-Fuzzy Control of SSSC and SMES for Transient Stability Improvement of Power System Transmission Lines[A]. International Joint Conference on Neural Networks[C]. Vancouver, Canada, 2006:859-863
[39]吴文胜,颜伟,华智明.静止同步串联补偿器的最优控制研究与仿真[J].四川电力技术,2001,24(2):7-7,38
[40]Amany E Z. Optimal sizing of SSSC controllers to minimize transmission loss and a novel model of SSSC to study transient response [J]. Electric Power Systems Research,2008,78(11):1856-1866
[41]卢强,孙元章.电力系统非线性控制[M].北京:科学出版社,1997:20-45
[42]孟范伟,何朕,王毅,等.非线性系统的线性化[J].电机与控制学报,2008,12(1):89-92
[43]孙元章,杨志平,王志芳,等.非线性控制及其对电压稳定性改善的研究[J].电力系统自动化,1996,20(6):21-26
[44]颜伟,吴文胜,华智明SSSC非线性控制的直接反馈线性化方法[J].中国电机工程学报,2003,23(3):67-68
[45]王超,舒乃秋,吕小静.基于非线性控制理论的SSSC控制器的研究[J].电力科学与工程,2004,37(4):36-38
[46]赵建军,郭剑波,周孝信.静止同步补偿器变参数非线性暂态稳定控制器的设计[J].电网技术,2005,29(21):16-20
[47]Ghaisari J, Bakhshai A, Jain P K. A nonlinear control approach to increase power oscillations damping by means of the SSSC[A].2005 IEEE Power Engineering Society General Meeting[C]. California,USA,2005:1601-1608
[48]Poshtan M, Singh B N, Rastgoufard P. A Nonlinear Control Method for SSSC to Improve Power System Stability[A]. International Conference on Power Electronics, Drives and Energy Systems[C]. New Delhi, India,2006:1-7
[49]Zhao Y, Xiao X N. Study of Nonlinear Control of SSSC Based on Differential Geometry Approach[A].2nd IEEE Conference on Industrial Electronics and Applications[C]. Harbin, China,2007:1118-1122
[50]赵洋,肖湘宁.级联式SSSC上层非线性控制方法[J].高电压技术,2008,34(3):587-586
[51]吴文胜.静止同步串联补偿器的模型及其控制方式研究[D].重庆:重庆大学,2001
[52]许维东.静止同步串联补偿装置的智能PIE控制研究[D].长沙:湖南大学,2001
[53]雎刚,徐治皋.一种基于变结构的预测控制算法及其应用研究[J].中国电机工程学报,2001,21(7):111-116
[54]刘金琨.先进PID控制及其MATLAB仿真[M].北京:电子工业出版社,2007:94-134
[55]郑恩让,聂诗良.控制系统仿真[M].北京:中国林业出版社,2006:9-26
[56]罗安,唐杰,涂春鸣,等.基于神经元自适应PID的STATCOM直接电压控制方法[J].电力系统自动化,2007,31(12):77—80
[57]楚红波.基于BP神经网络的STATCOM控制研究[D].南宁:广西大学,2006
[58]Wei Qiao, Harley R G. Indirect adaptive internal neural-control for a static synchronous series compensator (SSSC) connected to a power system[A]. 31st Annual Conference of IEEE on Industrial Electronics Society[C]. North Carolina, USA,2005:6-13
[59]Wei Qiao, Ronald G H, Ganesh K V. A fault-tolerant P-Q decoupled control scheme for static synchronous series compensator[A]. IEEE Power Engineering Society General Meeting[C]. Montreal, Canada,2006:8-12
[60]Ngamroo I, Kongprawechnon W. A robust controller design of SSSC for stabilization of frequency oscillations in interconnected power systems [J]. Electric Power Systems Research,2003,67(3):161-176
[61]Wei Qiao, Harley R G. Fault-Tolerant Control for SSSC Using Neural Networks and PSO[A]. Power Systems Conference and Exposition[C], Atlanta, USA,2006: 952-958
[62]Wei Qiao, Harley R G Fault-Tolerant Optimal Neurocontrol for a Static Synchronous Series Compensator Connected to a Power Network [J]. IEEE Trans, on Industry Applications,2006,44(1):76-84
[63]Wei Qiao, Harley R G Venayagamoorthy G K. Neural-network-based intelligent control for improving dynamic performance of FACTS devices[A].2007 iREP Sympos Bulk Power System Dynamics and Control[C]. Charleston, USA,2007:1-9
[64]Haro P Z, Ramirez J M. SSSC's Adaptive Neural Control[A]. International Joint Conference on Neural Networks[C]. Vancouver, USA,2006:2267-2273
[65]Pillai G N, Ghosh A, Joshi A. Robust control of SSSC to improve torsional damping[A]. IEEE Power Engineering Society Winter Meeting[C]. Columbus,USA, 2001:1115-1120
[66]Mohagheghi S, Venayagamoorthy G K, Harley R G. Adaptive Critic Designs Based Coupled Neurocontrollers for a Static Compensator[A].2006 IEEE International Conference on Control Applications[C]. Munich, Germany,2006:470-475
[67]Sidhartha P. Multi-objective evolutionary algorithm for SSSC-based controller design [J]. Electric Power Systems Research,2009,79(6):937-946
[68]李娟,周兴福,李淑琴.基于精确反馈线性化方法的SSSC非线性控制器[J].电网技术,2008,32(2):12-15
[69]秦砺寒.基于串联同步静止补偿器SSSC作用的电力系统电压稳定性研究[D].南宁:广西大学,2008
[70]Liu Qing, Wang Zengping, Zheng Zhenhua. Non-unit Transient Protection Based on Signal Complexity for Series Compensated Transmission Lines [J]. Proceeding of the CSEE,2010,30(13):81-88
[71]Xiangning Xiao, Benfeng Gao, Chengyong Zhao. A novel SSR-damping scheme based on imbalance operation of SSSC[A].2010 International Conference on Power System Technology[C]. Hangzhou, China,2010:1-5
[72]赵建军,郭剑波,周孝信.利用附加节点注入电流法设计静止同步串联补偿器的潮流控制器[J].中国电机工程学报,2005,25(23):1-6
[73]杨琪,王辉.基于人工神经网络控制算法的SSSC潮流控制器设计[J].电机电器技术,2005,(5):17-20
[74]SUNIL K L, GHOSH A. Static synchronous series compensator design, control and application [J]. Electric power systems research,1999, 49(2):139-148
[75]许维东,王辉,阳月令.静止同步串联补偿器SSSC [J].电工技术,2001,(2):40-41
[76]汪普林.静止同步串联补偿器的应用分析[J].南华大学学报(理工版)2002,16(3):21-24
[77]Bongiorno M, Svensson J, Angquist L. Single-Phase VSC Based SSSC for Subsynchronous Resonance Damping [J]. IEEE Trans. on Power Delivery,2008, 23(3):1544-1552
[78]CASTRO M S, AYRES H M, DACOSTA V F, et al. Impacts of the SSSC control modes on small-signal and transient stability of a power system [J]. Electric power systems research,2007,77(1):139-148
[79]赵建军,郭剑波,周孝信,等.静态同步串联补偿器稳态特性分析与详细数学模型的建立[J].中国电力,2005,38(10):11-16
[80]韩立群.人工神经网络理论、设计及应用[M].北京,化学工业出版社,2007:1-52
[81]张鹏,李颖晖,肖蕾.基于递归神经网络的伺服系统自适应反步控制[J].系统仿真学报,2008,20(6):1475-1478
[82]石宇静,柴天佑.基于神经网络与多模型的非线性自适应广义预测控制[J].自动化学报,2007,33(5):540-545
[83]Liang Xuebin, Wang Jun. A recurrent neural network for nonlinear optimization with a continuously differentiable objective functions and bound constraints [J]. IEEE Trans. on Neural Networks,2000,11(6):1251-1262
[84]Patino H D, Liu D. Neural network-based model reference adaptive control system [J]. IEEE Trans. on Systems, Man, and Cybernetics,2000,30(1): 198-206
[85]叶伟宝.基于近似动态规划的倒立摆控制[D].南宁:广西大学,2007
[86]贾琰.基于近似动态规划的交通控制算法的研究[D].北京:北京交通大学,2008
[87]康琦,汪镭,安静,等.基于近似动态规划的微粒群系统参数优化研究[J].自动化学报,2010,36(8):1171-1181
[88]赵琰,邓玮,张玉艳.基于近似动态规划的神经网络控制及在电力系统中应用[J].东北电力技术,2009,30(4):10-12
[89]Balakrishnan S N, Jie Ding, Lewis F L. Issues on Stability of ADP Feedback Controllers for Dynamical Systems[J]. IEEE Trans. on Systems, Man and Cybernetics,2008,38(4):913-917
[90]Lin W S, Yang P C. DHP Adaptive Critic Motion Control of Autonomous Wheeled Mobile Robot[A]. IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning[C]. Honolulu, USA,2007:311-317
[91]JONG M L, LEE J H. Approximate dynamic programming-based approaches for input-output data-driven control of nonlinear processes [J]. Automatica,2005, 41(7):1281-1288
[92]Jung-Wook P, Harley R G, Venayagamoorthy G K. New External Neuro-Controller for Series Capacitive Reactance Compensator in a Power Network [J]. IEEE Trans. on Power Systems,2004,19(3):1462-1472
[93]Park J W, Harley R G, Venayagamoorthy G K. A Novel Dual Heuristic Programming Based Optimal Control of a Series Compensator in the Electric Power Transmission System[A]. International Joint Conference on Neural Networks[C]. Portland, USA,2007,2976-2981
[94]Tousi M R, Hosseinian S H. DHP Adaptive Critic Based Control of STATCOM in power system[A]. Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies[C]. Nanjing,China,2008:1533-1537
[95]林小峰,喻亮,宋绍剑.自适应评价设计的执行依赖方法[J].控制工程,2008,15(4):427-427
[96]金玉洁,毛承雄,王丹,等.静止同步补偿器的最优控制策略[J].电力系统及其自动化学报,2007,19(5):71-76
[97]王超,舒乃秋,吕小静.基于非线性控制理论的SSSC控制器的研究[J].中国电力,2004,37(4):36-38
[98]颜伟,吴文胜,华智明,等.SSSC非线性控制的直接反馈线性化方法[J].中国电机工程学报,2003,23(3):66-68
[99]Zhao Yang, Xiao Xiangning, Xudong Jia. Nonlinear PID controller of H-bridge cascade SSSC top level control[A]. Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies[C]. Nanjing, China,2008:1826-1830
[100]Ahmadian K T M, Kazemi K. A Decoupling Technique to Improve the Efficacy of the Vector Control Model for SSSC[A]. Power India Conference[C]. New Delhi, India,2006:6-10
[101]陈增强,孙明玮,袁著祉,等.基于模糊神经网络的PI自适应控制器[J].华东理工大学学报,2002,28(增刊):45-48
[102]刘敬,吕立华.基于模糊推理的PI控制器参数整定方法[J].控制工程,2007,(S2):30-32
[103]Pradhan A C, LehnP W. Frequency-Domain Analysis of the Static Synchronous Series Compensator [J]. IEEE Trans. on power delivery,2006,21(1):440-449