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Coal using amount prediction method based on behavior analysis of operation team and group of coal-fired unit

A coal-fired unit and behavior analysis technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as low forecasting accuracy, and achieve the effect of improving accuracy, strengthening collaborative early warning capabilities, and improving the level

Inactive Publication Date: 2016-03-23
STATE GRID CORP OF CHINA +2
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Problems solved by technology

In the practical application of this method, because it ignores the inhomogeneity of coal consumption level fluctuations caused by different operating teams of coal-fired units, different ambient temperatures, different coal quality and different heating loads, its prediction accuracy is often low, and it needs to be improved urgently.

Method used

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Embodiment Construction

[0015] The present invention will be specifically introduced below in conjunction with specific embodiments.

[0016] Taking a 1000MW class ultra-supercritical heating unit as an example, its normal operation mechanism is five shifts and three shifts. The coal consumption prediction method is introduced below taking this unit as an example:

[0017] (1) Clustering of sample data: first, classify and divide unit operation and calculation data according to the schedule, and then divide according to ambient temperature (divided at intervals of 1°C), heating flow (divided at intervals of 1t / h ), equivalent load coal supply (divided at intervals of 0.05t / MWh) for data subdivision and classification, and massive data are classified and screened according to the four dimensions of shift group-environment temperature-equivalent load coal supply-heat supply flow ; After the preliminary division is completed, use the k-means algorithm to sort out the sample space, and automatically merg...

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Abstract

The invention discloses a coal using amount prediction method based on behavior analysis of an operation team and group of a coal-fired unit. On the basis of mass operation data of the coal-fired unit, the operation behavior characteristics of the operation team and group of the coal-fired unit are extracted and analyzed in the quantitative manner, the external ambient temperature change is taken into consideration, the power supply coal consumption of the coal-fired unit in the specific condition can be predicted quantitatively, and further the coal using amount index of the unit is predicted. The accuracy of coal amount predication of the unit can be effectively improved, the performance of power scheduling is improved, related governmental departments and power scheduling departments can master information as available days of stored coal according to the coal storage data reported by a power plant, and thus, scientifically and reasonably plan the generating load, and the electricity-coal cooperated early warning capability is reinforced.

Description

technical field [0001] The invention relates to a coal consumption prediction method, in particular to a coal consumption prediction method based on the behavior analysis of coal-fired unit operation teams. Background technique [0002] At present, the coal consumption forecast of coal-fired units is mainly based on the relationship between the power generation and coal consumption of electric power companies over the years, and the linear regression method is used to analyze the highest mathematical expectation of coal consumption and predict the coal consumption for a period of time in the future. . In the practical application of this method, because it ignores the inhomogeneity of coal consumption level fluctuations caused by different operating teams of coal-fired units, different ambient temperatures, different coal qualities, and different heating loads, its prediction accuracy is often low and needs to be improved urgently. Contents of the invention [0003] In or...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y04S10/50
Inventor 孙虹孙栓柱周春蕾代家元孙彬王其祥高进王林张友卫李春岩王明刘成魏威
Owner STATE GRID CORP OF CHINA
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