Supercritical thermal power generating unit dynamic working condition identification method based on big data

A thermal power unit and working condition identification technology, which is applied in computer control, instruments, simulators, etc., can solve problems such as low efficiency, difficulty in obtaining accurate models, and high uncertainty, and achieve the effect of increasing the probability of success and improving the ability of identification

Pending Publication Date: 2022-03-01
CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0019] Aiming at the deficiencies in the prior art, the present invention provides a method for identifying dynamic operating conditions of supercritical thermal power units based on big data, which solves the problem of estab

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  • Supercritical thermal power generating unit dynamic working condition identification method based on big data
  • Supercritical thermal power generating unit dynamic working condition identification method based on big data
  • Supercritical thermal power generating unit dynamic working condition identification method based on big data

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[0048] The technical solutions in the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0049] Original data source:

[0050] The data used in this example comes from "Modern Engineering Cybernetics", author Han Pu, published in China Electric Power Press in 2017. Among them, data_step_io1.mat, data_step_io2.mat, data_step_io3.mat, data_step_io4.mat, data_step_io5.mat, and data_step_iomat respectively contain the u1, u2, u3, y1, y2, y3 used in the previous article, and the data comes from the DCS historical database records The data under the normal operation of the unit within a continuous 45-hour period, the sampling period Ts=10 seconds. For ease of observation, the above data are shown in image 3 , Figure 4 middle.

[0051] In Modern Engineering Cybernetics, particle swarm algorithm is used to identify the dynamic model of the data, and the results are shown in Table 1.

[0052] Table 1. Dynamic model of...

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Abstract

The invention provides a supercritical thermal power generating unit dynamic working condition identification method based on big data. The method comprises the following steps: constructing a Dw sequence by using a relative entropy calculation method; performing piecewise linear representation on the Dw sequence, and recording coordinates xL and xR of left and right end points of each straight line segment; the minimum value Dmin and the maximum value Dmax of the Dw sequence are recorded, and the maximum change amplitude dD = Dmax-Dmin of the Dw sequence is calculated; a wave crest section or a wave trough section in the Dw sequence is taken, the minimum value Smin and the maximum value Smin in the section of sequence are recorded, the maximum change amplitude dS = Smax-Smin is calculated, and when dS and dD meet a certain numerical relationship, the data section with the coordinate values xL and xR of the left end point and the right end point of the wave crest section or the wave trough section is the required dynamic working condition section; according to the method, the identification capability of the data during the operation of the supercritical thermal power generating unit is improved, the data segment really corresponding to the dynamic working condition in a large amount of data is extracted, and production and researchers can conveniently establish a corresponding model more accurately for analysis, so that the operation state of the supercritical thermal power generating unit can be known more clearly.

Description

technical field [0001] The invention relates to the technical field of industrial big data, in particular to a method for identifying dynamic working conditions of a supercritical thermal power unit based on big data. Background technique [0002] The supercritical unit uses a once-through boiler, and its coordinated control system (Coordinated Control System, CCS) is a typical MIMO (Multi-Input Multi-Output) object. Many scholars at home and abroad have conducted extensive research on the modeling and control of the coordinated control system of thermal power units. From the perspective of control characteristics, the main difference between once-through boilers and drum boilers lies in the change of the ratio of fuel to water, which causes the working fluid in the boiler to change. Changes in storage, thereby changing the proportion of each heating area. [0003] In the CCS control scheme of the supercritical unit, the load (main steam flow), steam temperature, and steam ...

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Application Information

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IPC IPC(8): G05B19/042
CPCG05B19/0423G05B2219/25257
Inventor 申忠利
Owner CHANGSHA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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