Health level assessment method of thermal power generating unit based on data analysis

Abstract

The invention discloses a health level evaluation method of a thermal power generating unit based on data analysis, belongs to the field of thermal power generation, The aim of invention is to providea health level evaluation method of a thermal power generating unit based on data analysis to evaluate the operation status. The main points of the technical scheme are as follows: S1, acquiring historical operation data for a period of time from the real-time information monitoring and management system of thermal power generating units, screening the historical operation data, and selecting thehealthy operation data; S2, determining the parameters to be measured, selecting the independent variables related to the parameters, and carrying out curve fitting on the parameters and the independent variables related to the parameters to establish a mathematical model of each parameter; S3: establishing the scoring rules based on the mathematical models of each parameter. The method can be used to realize the real-time prediction of parameters and to judge whether the predicted value is normal or not.

Description

technical field [0001] The invention relates to the field of thermal power generation, in particular to a method for evaluating the health level of a thermal power generating set based on data analysis. Background technique [0002] For a relatively long period of time, thermal power generation still occupies a dominant position in my country's electricity production. A power plant is a complex series-parallel system composed of multiple interrelated subsystems, and its safe and reliable operation is particularly important. Performance monitoring technology is widely used in power plants to ensure their safe operation. In terms of performance monitoring of thermal power units, the current mainstream monitoring methods are mainly based on physical mechanism modeling platforms. These platforms have not fully utilized the massive production and operation data of the explosive growth in power plants. To tap the value wealth contained in these data, It will provide great help f...

AI Technical Summary

Problems solved by technology

At present, big data analysis and research in the field of energy and power at home and abroad are mainly applied to the power demand side and renewable energy power generation, such as demand side response, user management, dynamic pricing, wind power and solar power prediction, etc., in the performance monitoring of thermal power equipment Not yet fully applied on

[0004] At present, the conventional monitoring methods of power generation equipment all use absolute value alarms. When the operating parameters exceed the set value, an alarm will be generated. Therefore, the condition maintenance of power generation equipment is still basically post-processing. This single monitoring method is difficult to detect the early stage of the equipment in time Symptoms and their development trend tracking, greatly increasing the probability of equipment failure eventually leading to forced downtime

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