基于虚拟仪器的水力机组运行实时监测系统研究
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摘要
水电是我国重点发展的绿色能源,水电生产具有开停机方便、运行费用低,对环境污染小等优点,合理充分地利用水电能源对我国的经济发展起着巨大的推动作用,因此有效地对水力机组运行参数进行检测、分析、优化,对水轮机组高效稳定运行将起到重要作用。
     本文采用虚拟仪器技术,通过LabVIEW和MATLAB混合编程的方法,开发了一套水力机组运行实时监测系统,该系统不仅实现了水轮机运行参数的实时检测、分析、计算以及水力机组能量特性模型的建立,而且为建立水力机组优化运行系统打下基础。
     本文主体分为三部分,每部分内容如下:
     第一部分:采用虚拟仪器的概念,构建了实时监测系统的硬件结构并详细介绍了硬件的选型设计。该系统的硬件部分主要采用了美国NI公司的产品,包括信号调理设备以及数据采集卡,经过试验验证,该系统硬件结构不论采集精度、速度以及抗干扰能力都能够满足实时监测系统的要求。
     第二部分:利用图形化编程语言LabVIEW建立了岗南水电站1~3号机组的运行参数数据采集系统,实现了水轮机的工作水头、流量、出力等参数的实时在线监测、显示、处理以及存储,同时可根据水力机组实时监测的数据计算水轮机的运行效率,并实时显示,使工作人员随时了解水轮机的运行状况。
     第三部分:在水力机组运行参数数据采集系统的基础上,利用LabVIEW和MATLAB混合编程技术,构建了水轮机能量特性模型,开发了水力机组运行工况实时监测系统,该系统可以实现在水轮机的三维能量特性曲面图上实时显示水轮机的运行工况点的功能,以便运行人员直观地了解水轮机的运行状况,从而对整个机组进行合理调节,使机组运行于高效区。
     本系统的开发对于充分利用水资源,提高水电站的经济效益,实现水力机组的高效稳定运行及优化运行均具有一定的实际指导意义。
Hydroelectricity is regarded as green energy of mainly development in our country. It has many characteristics such as quick start-up, low operation outlay and low pollution. How to make full use of hydro-electric power will enormously promotes the development of our country’s economic. Therefore, to test, analyze and optimize the hydraulic parameters effectively will play an important role in the efficient and reliable operation of hydro-generating units.
     A real-time monitoring system of operation of hydro-generating units based on virtual instrument techniques was designed in this paper by using LabVIEW and MATLAB mix programming method.This system not only realizes the real-time detection, analysis and computation of the hydraulic parameters and the creation of energy characteristics model of hydro-generating units,but also it laies the foundation of the establishment of optimal operation system of hydro-generating units.
     The paper is made of three parts,which were showed below:
     The first part is to build the hardware structure of the real-time monitoring system adopting the idea of virtual instrument,and the design of hardware is discussed in detail.The main hardware of the system uses the products which are developed by National Instruments(NI),such as signal conditioning equipment and data acquisition card.After the test ,it can be proved that the hardware structure of this system,whether acquisition accuracy,speed or anti-jamming ability,is able to meet the requirements of the real-time monitoring system.
     The second part is to build the data acquisition system of NO.1 to NO.3 units processing parameter in Gangnan hydropower station by LabVIEW.With the system,the real-time monitor,display,data processing and storage of turbine operating parameters such as water level,water flux and the output are achieved.The hydraulic efficiency can be calculated and displayed real-timely according to the real-time monitoring data of hydro-generating units,so that the operators can hold the running status of turbine at any time.
     The third part is to build the energy characteristics model of turbine and develop the real-time monitoring system of operating conditions for hydro-generating units based on the data acquisition system of hydraulic parameters by using LabVIEW and MATLAB mix programming method. With the system,the operating condition points of turbine can be displayed in real-time on the surface graph of energy characteristics of turbine,so that the operators can hold the running status of turbine directly,and adjust the entire units reasonably.
     Development of system has practical guidance for the utilization of water resources, the enhancement of hydroelectric power station economic efficiency, the realization of efficient and stable operation and optimal operation of hydro-generating units.
引文
[1]马跃先,马希金,阎振真.小型水电站优化运行与管理[M].郑州:黄河水利出版社,2000
    [2]王定一,伍永刚.水电厂用计算机实现自动发电控制的经济效益[J].水力发电,1994,(1):17~49
    [3]张勇传.水电站经济运行[M].北京:水利电力出版社,1984
    [4]徐晨光.水电站厂内经济运行理论与实践[D].西安:西安理工大学博士学位论文,2004
    [5] Georgakakos,Yao H.,and YuY. Control models for hydroelectric energy optimization.Water Resources Research,VOL33,No.10,p2367~2379,1997
    [6] L.M.Rux.An Incremental Economic Dispatch Method for Cascaded Hydroelectric Power Plants[J].IEEE Trans.on Power Systems.1993,8(3):1266~1273
    [7] H.Habibellahzadeh,GX.Luo,et al.Hydrothermal Optimal Power Flow Based on A Combined Linearand Nonlinear Programming Methodology[J].IEEE Trans on Power Systems.1989,4(2):530~537
    [8] Hansom M,L.Lafond,et al.Modeling and Resolution of the Medium Term Energy Generation Planning Problem for alarge Hydroelectric System[J].Management Science.1980,26(7):659~668
    [9]邓晓娟.遗传算法及其在三峡梯级水电厂优化调度中的应用[D].武汉:华中科技大学硕士学位论文,2002
    [10] R.H.Liang,YYHsu.Scheduling of hydroelectric generations using artificial neural network[J]. IEE Proc.Gener.Transm.Distrib.1994,141(5):452~458
    [11]马光文,王黎,GA.Walters.水电厂群优化调度的FP遗传算法[J].水力发电学报,1996,55(4):21~28
    [12]卢文秀.抽水蓄能机组的状态监测和故障诊断[J].中国电力,2000,33(4):19~22
    [13]吴建红,等.水轮发电机组的状态监测与故障诊断[J].水电厂自动化,1998,(4):68~70
    [14]张雪桂,等.大型水电厂设备状态监测及诊断系统[J].水力发电,1998,(11):23~24
    [15] Park J H.Economical load dispatch for piecewise quadratic cost function using Hopfeild Neural Network[J].IEEE Trans.on Power Systems,1993,8(3)
    [16] Allemong J J. Multiphase power flow solutions using EMPT and neural method[J].IEEE Trans.on power Systems,1993,8(4)
    [17] De Mello, F.P., R.J, B.Rells et al, Automatic Generation Control: Part I-Process Modeling[J]. IEE PES Summer Meeting, 1992, (7):9~14
    [18] Castro, F, Pescina. M, Llort. G, Reliability improvements of the Guri Hydroelectric Power Plant computer control system AGC and AVC[J], IEEE Transactions on energy conversion, 1992,7(3) :447~452
    [19]刘晓亭,等.水力机组现场测试手册[M].水利电力出版社,1993
    [20]张强.水电站水轮发电机组效率在线监测系统的开发与研究[D].南京:河海大学硕士学位论文,2004
    [21]李郁侠,范华秀.水电站测流目前状况及其发展[J].陕西水力发电,1993,9(4):56~62
    [22]魏春雷,郑凯.张河湾蓄能电站超声波流量测量系统及应用[J].水电厂自动化,2009,30(1):26~28
    [23]杜文忠.水力机组测试技术[M].北京:水利水电出版社,1995
    [24]张巍,王琳.新丰江水电厂机组效率测试及结果分析[J].广东水利水电,2008,(2):76~78
    [25]袁世娟,郑蔓丽.水力机组流量实时在线监测技术[J].广东水利水电,2004,(4):19~22
    [26]赵旭光,孙亚权,赵涌,等.基于可编程控制器的水电机组水力参数自动监测系统[J].湖北水力发电,2004,(54):59~61
    [27]张江滨.蜗壳差压法测流流量系数的近似率定[J].西北农业大学学报,1996,24(1):70~74
    [28]刘君华,申忠如,郭福田.现代测试技术与系统集成[M].北京:电子工业出版社,2004
    [29]周娟,袁良豪,曹德森.压力传感器信号调理电路设计[J].北京生物医学工程,2007,26(4):395~398
    [30]张重雄.虚拟仪器技术分析与设计[M].北京:电子工业出版社,2007
    [31]黎琼,陈文庆,温泉彻.通用数据采集系统的信号调理[J].湛江师范学院学报,2004,25(6):119~123
    [32]雷振山,赵晨光,魏丽,等.LabVIEW8.2基础教程[M].北京:中国铁道出版社,2008
    [33] National Instruments:SCXITM Getting Started with SCXI.July 2000 Edition Part Number 320515F-01.
    [34] http://www.gkong.com/co/fanhua/pro_content.asp?products_id=283627;2009年9月13日
    [35] NI 622x Specifications[Z]. National Instruments,2008:29
    [36]孙林丽,纪峰,李福援,等.虚拟仪器在复合电解加工中的应用[J].计算机应用技术,2006,33(2):41~43
    [37]梁森,欧阳三泰,王侃夫.自动检测技术及应用[M].北京:机械工业出版社,2006
    [38]温建力.图形化编程语言LabVIEW[J].商业经济,2009,(5):88~90
    [39]王磊,陶梅.精通LabVIEW 8.0[M].北京:电子工业出版社,2007
    [40] YAMAMOTOI Tomoichiro.Apparatus for controlling hydraulic elevator[P].United States Patent US 4593792,1986,10
    [41] Djurovic Igor,Stankovic Ljubisa.Virtual instrument for time-frequency analysis[J].IEEE Transactions on Instrumentation and Measurement,1999,(12):1086~1092
    [42] Heinrichs.G,Rongen.h,Jamal.R.LabVIEW for sensor data acquisition[J].Trends in Analytical Chemistry,1999,18:19~23
    [43]侯国屏,王珅,叶齐鑫.LabVIEW7.1编程与虚拟仪器设计[M].北京:清华大学出版社,2005
    [44] Norma Dorst.Using LabVIEW to Create Multithreaded Vis for Maximum Performance and Reliability[J].Application Note 114.www.ni.com
    [45]阮奇桢.第四课:图形化编程语言在虚拟仪器系统中的应用[J].工业设计,2009,(8):18
    [46]孙艳宾.基于虚拟仪器的水力机组振动、噪声测试分析系统的研究与开发[D].成都:西华大学硕士学位论文,2006
    [47]邵丽萍,王伟岭,朱红岩.Access数据库技术与应用[M].北京:清华大学出版社,2007
    [48]张冰,戴晓强,朱志宇.ADO和LabSQL在数据库操作方面的应用[J].微计算机信息,2005,21(10-2):88~90
    [49]李春雨,郑培,牛亚尊,等.LabVIEW中利用LabSQL访问数据库的实现[J].仪器仪表用户,2009,16(2):122~123
    [50]刘祖鹏.利用LabSQL实现虚拟仪器数据的数据库存储[J].河南机电高等专科学校学报,2009,17(1):24~25
    [51]江玉玲.浅析远程监测系统中的数据传输与数据管理[J].仪表技术,2009,(8):43~45
    [52]刘大恺.水轮机[M].北京:中国水利水电出版社,1996
    [53]葛哲学,孙志强.神经网络理论与MATLAB R2007实现[M].北京:电子工业出版社,2007
    [54] Moody J,DarKen C.Fast learning in networks of locally-tuned processing units[J].Neural Computation,1989,1(2):281~294
    [55] S.G.Fabri and V.Kadirkamanathan.Dynamic Strueture Neural Networks for Stable Adaptive Control of Nonlinear Systems[J].IEEE Trans.Neural Networks,1996,7(5):1151~1167
    [56] S,Chen.Nonlinear Time Series Modeling and Predietion Using Gaussian RBF Networks with Enhanced Clusting and RLS Leaming[J].Electronics Letters,1995, 31(2):117~118
    [57] D.L.Yu,J.B.Gomm,and D.Willians.Sensor Fault Diagnosis in a Chemieal Process via RBF Neural Networks[J].Control Engineering Practiee,1999,7:49~55
    [58] Q.Zhao,Z.Bao.Target recognition based on radial basis function network[J].in:Proeessing of International Joint Conference on Neural Network,1993,V3.NAGOYA,JAPAN,3:2735~2738
    [59]闻新,周露,李翔,等.MATLAB神经网络仿真与应用[M].北京:科学出版社,2003
    [60]薛新华.人工神经网络在地基土液化判别中的作用[D].青岛:中国海洋大学硕士学位论文,2004
    [61] Howard Demuth,Mark Beale.Neural network toolbox user’s guide Version 4[M].The Mathworks Inc,2001
    [62]侯媛彬,杜京义,汪梅.神经网络[M].西安:西安电子科技大学出版社,2007
    [63]夏昌浩,杨力森,李宁,等.一种高精度热电偶模型及其测温虚拟实现[J].微计算机信息,2007,23(3-1):162~164
    [64]魏艳强,刘海琳,宁红云.基于RBF神经网络的公路货运量预测方法研究[J].天津理工大学学报,2008,24(1):17~20
    [65]许东,吴铮.基于MATLAB6.x的系统分析与设计[M].西安:西安电子科技大学出版社,2002
    [66]刘婧然,马英杰,雷晓云,等.径向基函数人工神经网络在棉花耗水量预测中的应用[J].新疆农业大学学报,2009,32(1):85~88
    [67]童官军,杨世凤,王建新.基于LabVIEW的神经网络PID自适应控制器的设计与应用[J].天津科技大学学报,2005,20(4):80~83
    [68]徐明,于业明.LabVIEW中MATLAB的调用[J].山东理工大学学报(自然科学版),2005,19(4):92~95

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