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Dynamic distributed monitoring method for varying-condition operation of million-kilowatt ultra supercritical set

An ultra-supercritical unit and distributed monitoring technology, applied in electrical testing/monitoring, etc., can solve problems that have not been seen in research reports

Active Publication Date: 2018-09-04
ZHEJIANG UNIV
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  • Abstract
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  • Claims
  • Application Information

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  • Dynamic distributed monitoring method for varying-condition operation of million-kilowatt ultra supercritical set
  • Dynamic distributed monitoring method for varying-condition operation of million-kilowatt ultra supercritical set
  • Dynamic distributed monitoring method for varying-condition operation of million-kilowatt ultra supercritical set

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Embodiment Construction

[0069] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific examples.

[0070] A million-kilowatt ultra-supercritical unit is a typical non-stationary process, and some of the variables have obvious non-stationary characteristics, such as the circulating water pressure of the condenser, the inlet steam pressure of the high-pressure heater, and the condensed water volume at the inlet of the deaerator. The present invention takes No. 8 unit of Jiahua Gas Power Plant as an example. The unit has a power of 10,000MW and is an ultra-supercritical unit of one million kilowatts. It includes 159 process variables, and these variables involve pressure, temperature, water level, flow rate, etc.

[0071] Such as figure 1 As shown, the present invention is a dynamic distributed monitoring method for the operation of million-kilowatt ultra-supercritical units under variable operating conditions, comprising the following s...

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Abstract

The invention discloses a dynamic distributed monitoring method for varying-condition operation of a million-kilowatt ultra supercritical set. Aimed at a typical large-scale non-stationary process ofthe million-kilowatt ultra supercritical set, sparse con-integration analysis and a dynamic feature extraction method are combined for fault detection as well as recognition of condition change. Via the method, components of the large-scale process can be divided into different variable groups automatically, static and dynamic process information is extracted from each variable group, the static process information is modeled and monitored, and the dynamic process information is also modeled and monitored. The process information is dug deeply, and normal condition change of the process can beeffectively distinguished from a real process fault. The method can be used to solve the problem in monitoring the process of the large-scale non-stationary dynamic system, namely the million-kilowatt ultra supercritical set, improve the process monitoring performance, help an onsite engineer master operation state of the set accurately, ensure the safety of the million-kilowatt ultra supercritical set, and improve the production benefit.

Description

technical field [0001] The invention belongs to the field of statistical monitoring of large-scale non-stationary processes, in particular to a dynamic distributed monitoring method oriented to the operation of million-kilowatt ultra-supercritical units under variable operating conditions. Background technique [0002] The electric power industry is the most important basic energy industry of our country's national economy and the focus of economic development strategy. my country is short of oil and gas, and rich in coal resources. Coal power has been the main source of electricity in my country for a long time. The process of coal-fired power generation is becoming increasingly complex and large-scale. The environment of the large-scale coal-fired power generation process is complex, and the site has the characteristics of high temperature, high pressure, and high noise. The million-kilowatt ultra-supercritical unit is the most advanced high-efficiency and large-capacity...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B23/02
Inventor 赵春晖孙鹤
Owner ZHEJIANG UNIV
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