Data-mining massive real-time data in a power plant: challenges, problems and solutions

2002 ◽  
Vol 3 (5) ◽  
pp. 538-542 ◽  
Author(s):  
Chen Jian-hong ◽  
Ren Hao-ren ◽  
Sheng De-ren ◽  
Li Wei
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Time Data ◽  
Real Time Data ◽  
Problems And Solutions

Early Warning of Power Plant Equipment Based on Massive Real-Time Data Mining Technology

2014 ◽  
Vol 599-601 ◽  
pp. 1487-1490 ◽  
Author(s):  
Li Kun Zheng ◽  
Kun Feng ◽  
Xiao Qing Xiao ◽  
Wei Qiao Song
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Early Warning ◽  
Time Data ◽  
Mining Technology ◽  
Equipment Safety ◽  
State Evaluation ◽  
Power Plant Equipment ◽  
Real Time Data

This paper mainly discusses the application of the mass real-time data mining technology in equipment safety state evaluation in the power plant and the realization of the equipment comprehensive quantitative assessment and early warning of potential failure by mining analysis and modeling massive amounts of real-time data the power equipment. In addition to the foundational technology introduced in this paper, the technology is also verified by the application case in the power supply side remote diagnosis center of Guangdong electric institute.

The Applications of Real-Time Data Mining Technology in Fault Prediction of Power Plant Generator

2015 ◽  
Vol 740 ◽  
pp. 351-354
Author(s):  
Feng Li ◽  
Hong Bin Wang ◽  
Dao Jun Deng ◽  
Yan Xia Zhang
Keyword(s):  
Data Mining ◽  
Power Plant ◽  
Real Time ◽  
Thermal Power Plant ◽  
Thermal Power ◽  
Fault Prediction ◽  
Time Data ◽  
Mining Technology ◽  
Online Security ◽  
Real Time Data

This paper mainly discusses the applications of real-time data mining technology in fault prediction of power plant generator. Massive real-time historical data of thermal power plant turbine generator equipment is stored to realize comprehensive quantitative assessment of thermal power plant turbine generator’s online security status and potential failure Early Warning. It is based on the Real-time data mining analysis and modeling techniques.

Real-Time Thermodynamic Performance Monitoring and Optimum Thermoeconomic Operation of Power Plants

2011 ◽  
Author(s):  
G. Hariharan ◽  
B. Kosanovic
Keyword(s):  
Linear Programming ◽  
Power Plant ◽  
Real Time ◽  
Power Plants ◽  
Operating Conditions ◽  
Recursive Least Squares ◽  
Time Data ◽  
Real Time Data ◽  
One Step ◽  
Inputs And Outputs

The ability of modern power plant data acquisition systems to provide a continuous real-time data feed can be exploited to carry out interesting research studies. In the first part of this study, real-time data from a power plant is used to carry out a comprehensive heat balance calculation. The calculation involves application of the first law of thermodynamics to each powerhouse component. Stoichiometric combustion principles are applied to calculate emissions from fossil fuel consuming components. Exergy analysis is carried out for all components by the combined application of the first and second laws of thermodynamics. In the second part of this study, techniques from the field of System Identification and Linear Programming are brought together in finding thermoeconomically optimum plant operating conditions one step ahead in time. This is done by first using autoregressive models to make short-term predictions of plant inputs and outputs. Then, parameter estimation using recursive least squares is used to determine the relations between the predicted inputs and outputs. The estimated parameters are used in setting up a linear programming problem which is solved using the simplex method. The end result is knowledge of thermoeconomically optimum plant inputs and outputs one step ahead in time.

scholarly journals Data Preprocessing: The Techniques for Preparing Clean and Quality Data for Data Analytics Process

2021 ◽  
Vol 13 (0203) ◽  
pp. 78-81
Author(s):  
Ashish P. Joshi ◽  
Biraj V. Patel
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Real Time ◽  
Data Preprocessing ◽  
Quality Data ◽  
Data Conversion ◽  
Time Data ◽  
Quality Of Data ◽  
Real Time Data ◽  
Integration Data

The model and pattern for real time data mining have an important role for decision making. The meaningful real time data mining is basically depends on the quality of data while row or rough data available at warehouse. The data available at warehouse can be in any format, it may huge or it may unstructured. These kinds of data require some process to enhance the efficiency of data analysis. The process to make it ready to use is called data preprocessing. There can be many activities for data preprocessing such as data transformation, data cleaning, data integration, data optimization and data conversion which are use to converting the rough data to quality data. The data preprocessing techniques are the vital step for the data mining. The analyzed result will be good as far as data quality is good. This paper is about the different data preprocessing techniques which can be use for preparing the quality data for the data analysis for the available rough data.

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