Application of Data Reconciliation in Steam Turbine Performance Monitoring

doi:10.11930/j.issn.1004-9649.201805001

Abstract

Abstract: In the steam turbine thermodynamic cycle, the measuring system has provided redundant measuring points. Generally, the main water flow, the main condensate flow and the feed water pump inlet flow are chosen as the mainstream in the on-site performance calculation. In this paper, by using the data reconciliation method, the redundant flow measurement point information is taken to perform data reconciliation calculation regarding the performance data of a real power plant. Then the uncertainty changes of the calculation result are analyzed. The result shows that the data reconciliation can effectively reduce the uncertainty of the calculation result.

Key words: steam turbine, thermodynamic performance, data reconciliation, uncertainty, redundancy, heat rate

CLC Number:

TK267

HU Jiangen, GU Zhenghao, BAO Jinsong, ZHU Meifang, ZHANG Bao. Application of Data Reconciliation in Steam Turbine Performance Monitoring[J]. Electric Power, 2018, 51(12): 124-131.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201805001

https://www.electricpower.com.cn/EN/Y2018/V51/I12/124

References 17

[1]	付昶. 火电机组"热耗率"定义综述[J]. 热力发电, 2016, 45(8):1-5. FU Chang. Definition review of heat rate in thermal power plant evaluation[J]. Thermal Power Generation, 2016, 45(8):1-5.
[2]	张志恒, 孙戈, 钟农兵. 汽轮机性能试验热耗率不确定度的分析计算[J]. 四川电力技术, 2014, 37(3):82-85
[3]	李辉. 基于在线支持向量回归算法的电站热耗率模型[J]. 中国电力, 2014, 47(7):21-25. LI Hui. The turbine heat rate modal based on accurate online support vector regression algorithm[J]. Electric Power, 2014, 47(7):21-25.
[4]	王学军. 汽轮机热力性能试验中不确定度的计算[J]. 热力发电, 2001, 30(4):30-36
[5]	Reason John, 孙钜江, 依春林. 现场校验凝结水测流喷嘴[J]. 黑龙江电力, 1991, 13(5):58-59.
[6]	张才稳. 汽轮机性能试验ASME流量喷嘴及GB/T2624-93喷嘴校验[J]. 电力科学与工程, 2009, 25(1):34-37. ZHANG Caiwen. ASME flow nozzles and GB/T 2624-93 flow nozzles calibration for turbine testing[J]. Electric Power Science and Engineering, 2009, 25(1):34-37.
[7]	周卫庆, 王顺, 李辉, 等. 一种基于遗传算法的热工数据校正方法[J]. 热力发电, 2017, 46(3):45-50. ZHOU Weiqing, WANG Shun, LI Hui, et al. A thermal data rectification method based on genetic algorithm[J]. Thermal Power Generation, 2017, 46(3):45-50.
[8]	程新华, 张庆国, 刘富国. 发电厂风粉流体测量系统的数据校正[J]. 热力发电, 2014, 43(11):35-40. CHENG Xinhua, ZHANG Qingguo, LIU Fuguo. Data reconciliation for air and fuel flow measurements system in power plant[J]. Thermal Power Generation, 2014, 43(11):35-40.
[9]	秦德华. 发电厂厂级监控信息系统数据校正新方法[J]. 热力发电, 2012, 41(6):80-82. QIN Dehua. A new correction method for data in plant-level supervisory information system[J]. Thermal Power Generation, 2012, 41(6):80-82.
[10]	王培红, 陈强, 李琳, 等. 厂级监控系统中数据校正算法模型研究[J]. 东南大学学报(自然科学版), 2005, 35(1):11-15. WANG Peihong, CHEN Qiang, LI Lin, et al. Research on algorithm model for data rectification in supervisory information system[J]. Journal of Southeast University (Natural Science Edition), 2005, 35(1):11-15.
[11]	Langenstein M, Jansky J. Process data reconciliation in nuclear power plants[J]. La Radiologia Medica, 2003, 107(1-2):47-57.
[12]	CHEN P C, Andersen H. The implementation of the data validation process in a gas turbine performance monitoring system[C]//ASME Turbo Expo 2005:Power for Land, Sea, and Air. Reno-Tahoe, Nevada, USA, 2005:609-616.
[13]	JIANG X, LIU P, LI Z. Data reconciliation for steam turbine on-line performance monitoring[J]. Applied Thermal Engineering, 2014, 70(1):122-130.
[14]	郭江龙, 李琼, 姚力强, 等. 基于冗余测量的汽轮机性能计算基准流量数据在线检验方法[J]. 河北电力技术, 2015, 34(3):1-2. GUO Jianglong, LI Qiong, YAO Liqiang, et al. Base flow online monitoring calibration method based on redundancy flow steam turbine performance calculation[J]. Hebei Electric Power, 2015, 34(3):1-2.
[15]	刘凯. 汽轮机性能试验不确定度分析方法的探讨[J]. 江苏电机工程, 2007, 26(4):1-5. LIU Kai. Analysis of turbine performance test uncertainty[J]. Jiangsu Electrical Engineering, 2007, 26(4):1-5.
[16]	Llanos C E, Sánchez M C, Maronna R A. Classification of systematic measurement errors within the framework of robust data reconciliation[J]. Industrial & Engineering Chemistry Research, 2017, 56(34):9617-9628.
[17]	MEI Congli, SU Hongye, CHU Jian. An NT-MT combined method for gross error detection and data reconciliation[J]. Chinese Journal of Chemical Engineering, 2006, 14(5):592-596.