Apriori-Based Association Rule Algorithm and Its Application in Power Plant

doi:10.16182/j.issn1004731x.joss.201801034

Abstract

Abstract: The data mining technology for historical data of power plant has the problem of low efficiency as the data dimension is high and data size is large. Some parameters are set without theoretical guidance and the objective parameter value is not reasonably determined in the corresponding algorithm of data mining. A mining algorithm with improved quantitative association rule based on Apriori is proposed. Aiming at the economical operation of power plant, target guidance is used to constrain the dimension and compress the quantity in sample space, which improves the mining efficiency and determines the parameter’s target value reasonably. The operation data of a 300MW unit is analyzed and its results show that the improved quantitative association rule algorithm can improve the efficiency of data mining and determine the parameter value more accurately.

Key words: quantitative association rule, optimal parameter value, economic index, metarule-guided

CLC Number:

TP274

Huang Wencheng, Jia Li, Peng Daogang, Li Wang. Apriori-Based Association Rule Algorithm and Its Application in Power Plant[J]. Journal of System Simulation, 2018, 30(1): 266-271.

References

[1] 王秋平, 陈志强, 魏浩. 基于数据挖掘的电站运行参数目标值优化[J]. 电力科学与工程, 2015, 31(7): 19-24.Wang Qiuping, Chen Zhiqiang, Wei Hao. The summary of optimal operation parameters in power station based on the Data Mining[J]. Electric Power Science and Engineering, 2015, 31(7): 19-24.
[2] 刘宝玲, 何钧, 曾暄. 嵌套式数据挖掘技术在电站工况分析中的应用[J]. 电站系统工程, 2014, 30(5):13-17, 22.Liu Baoling, He Jun, Zeng Xuan. The Application of Nested Data Mining in Power Plant Operating Condition Analysis[J]. Power System Engineering, 2014, 30(5): 13-17, 22.
[3] 李建强. 基于数据挖掘的电站运行优化理论研究与应用[D]. 保定: 华北电力大学, 2006. LI Jian-qiang. The research and application of data mining in power plant operation optimization[D]. Baoding: North China Electric Power University, 2006.
[4] 牛成林. 增量数据挖掘及其在电站运行中的理论研究及应用[D]. 北京: 华北电力大学, 2010. Niu Chenglin. The research and application of incremental updating data mining in power plant operation optimization[D]. Beijing: North China Electric Power University, 2010.
[5] Jiawei Han, Micheline Kamber.数据挖掘概念与技术[M]. 范明, 孟小峰, 等译. 北京: 机械工业出版社, 2001. Jiawei Han, Micheline Kamber. Data Mining: Concepts and Techniques [M]. San Francisco: Morgan Kaufmann Publishers,2001.
[6] Liu Baoling, He Jun, Liu Guangming.A Study of Working Conditions Based on Cluster Analysis[C]. APPEEC, 2010.
[7] 冉鹏. 基于动态数据挖掘的电站热力系统运行优化方法研究[D]. 北京: 华北电力大学, 2012. Ran Peng. Research on operation optimization of power plant thermal system by dynamic data mining approaches[D]. Beijing: North China Electric Power University, 2012.
[8] 洪军, 崔彦锋, 毕小龙, 等. 机组在线运行优化系统及实时目标工况的确定[J]. 电力系统自动化, 2007, 31(6): 86-90.Hong Jun, Cui Yanfeng, Bi Xiaolong, et al. A unit on-line operation optimization system and determination of real-time optimum operation mode[J]. Automation of Electric Power Systems, 2007, 31(6): 86-90.
[9] 赖晨捷. 数据挖掘技术在电厂厂级监控信息系统中的应用实施[D]. 上海: 上海交通大学, 2014.Lai Chenjie. The application of data mining technology in power plant supervisory information system[D]. Shanghai: Shanghai Jiao Tong University, 2014.
[10] 任浩仁, 李蔚, 盛德仁, 等. 火电机组变工况下运行指标应达值的分析[J]. 中国电机工程学报, 1999, 19(9): 50-52,56.Ren haoRen, Li Wei, Sheng Deren, et al. The analyze of operation index for the power unit under different loads[J]. Proceedings of the CSEE, 1999, 19(9): 50-52, 56.
[11] 陈丹丹. 基于粗糙集的电站运行数据分析与运行优化 [D]. 保定: 华北电力大学, 2013.Chen Dandan. Data analysis and operation optimization in power plant based on rough set theory [D]. Beijing: North China Electric Power University, 2013.
[12] 李娟, 张春发. 主蒸汽参数对机组热经济性影响的计算模型研究[J]. 电力科学与工程, 2007, 23(4): 7-10.Li Juan, Zhang Chunfa. Study on calculation model for unit heat economy on the impact of main steam parameter[J]. Electric Power Science and Engineering, 2007, 23(4): 7-10.
[13] 翟少磊, 黄孝彬, 刘吉臻. 基于工况划分的电厂经济性指标挖掘[J]. 中国电力, 2009, 42(7): 68-71.Zhai Shaolei, Huang Xiaobin, Liu Jizhen. Data miningto economic norms of power plant based on condition division[J]. Electric Power, 2009, 42(7): 68-71.
[14] 李蔚, 刘长东, 盛德仁, 等. 国内火电厂运行优化系统的现状和发展方向[J]. 电站系统工程, 2004 , 20(1): 59 -61.Li Wei, Liu Changdong, Sheng Deren, et al. Status and development trend of economic operation and optimization system in domestic coal-fired power plant[J]. Power System Engineering, 2004, 20(1): 59-61.
[15] 贾立, 柴宗君. 火电机组主蒸汽温度神经模糊-PID串级控制[J]. 控制工程, 2013, 20(5): 877-881.JIA Li, CHAI Zhong-jun. Neuro-fuzzy Based PID Cascade Control of Main Steam Temperature of Fire Electrical Engineering Set[J]. Control Engineering of China, 2013, 20(5): 877-881.
[16] 李建强, 牛成林, 谷俊杰, 等. 数据挖掘在火电厂运行参数优化目标值确定中的应用[J]. 华北电力大学学报, 2008, 35(4): 53-56.LI Jianqiang, NIU Chenglin, GU Junjie, LIU Jizhen, Application of data mining in optimal parameters value of power plant[J]. Journal of North China Electric Power University, 2008, 35(4): 53-56.