Power station boiler coal ash generation amount online prediction method and system based on LSTM

A forecasting method and technology for power station boilers, which are applied in forecasting, biological neural network models, data processing applications, etc., can solve problems such as difficult forecasting, large errors, and inconvenient practical application, and achieve reduction in equipment production loss and safe storage. The effect of exploiting, improving accuracy and usability

Pending Publication Date: 2022-07-01
NORTHWEST ELECTRIC POWER DESIGN INST OF CHINA POWER ENG CONSULTING GROUP
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Problems solved by technology

The former is not comprehensive and has large errors; the latter formula needs to be matched with different boiler types and fuel types because the Q4 coefficient is an empirical value. The calculation is cumbersome and complicated, and there are many inconveniences in practical application.
[0004] Due to various factors such as different boiler forms, operating environment (combustion mode, flue gas flow rate, furnace heat load, boiler operating load, etc.) and coal quality, the generated coal ash presents complex changing characteristics, so that the amount of coal ash does not vary. It is a generally applicable online calculation model, and it is difficult to accurately predict it

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  • Power station boiler coal ash generation amount online prediction method and system based on LSTM
  • Power station boiler coal ash generation amount online prediction method and system based on LSTM
  • Power station boiler coal ash generation amount online prediction method and system based on LSTM

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Embodiment Construction

[0059] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0060] The invention proposes an LSTM-based on-line prediction method for the generation of coal ash in power station boilers. The LSTM neural network is suitable for processing time-series related data, and can reflect the main parameters affecting the generation of coal ash in the boiler, so that the coal ash in the boiler can be reflected. Production forecasts are more accurate. The prediction method of boiler coal ash generation based on LSTM deep learning can record the required data for a long time and can predict online, with a long prediction period and high precision, which can meet the dynamic prediction requirements of power generation enterprises for boiler coal ash generation.

[0061] See figure 2 , an LSTM-based online prediction method for power plant boiler coal ash generation, comprising the following steps:

[0062] Step 1:...

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Abstract

The invention discloses a power station boiler coal ash generation amount online prediction method and system based on LSTM. The method comprises the steps that the boiler coal ash generation amount and historical data of main influence parameters are collected to obtain incidence relation data, and normalization processing is conducted on the incidence relation data; dividing the incidence relation data after normalization processing into a training set and a test set; performing training fitting on a pre-established boiler coal ash generation quantity LSTM network model by using the data in the training set; combining the prediction data with the data in the test set, and performing overfitting evaluation on the boiler coal ash generation quantity LSTM network model after training and fitting; and sampling the current generated data on line, inputting the boiler coal ash generation quantity LSTM network model without overfitting, and predicting the boiler coal ash generation quantity value in the future time. Required data can be recorded for a long time, online prediction can be achieved, the prediction period is long, precision is high, and the requirement of power generation enterprises for dynamic prediction of the boiler coal ash generation amount is met.

Description

technical field [0001] The invention belongs to the technical field of solid waste monitoring, and in particular relates to an LSTM-based on-line prediction method and system for coal ash generation amount of a power station boiler. Background technique [0002] When coal is used as fuel in thermal power plants, the boiler will produce a large amount of coal ash after burning coal. Part of the coal ash (fly ash) in the flue is collected by dust removal for comprehensive utilization, and the other part is discharged into the atmosphere with the flue gas through the chimney. With the improvement of national environmental protection requirements, the coal ash emission indicators produced by boilers are undoubtedly becoming more and more strict, which requires power generation enterprises to accurately control the operation of coal ash emissions from boilers. The amount of coal ash produced by traditional boilers is given in the design stage based on the maximum / minimum operati...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06K9/62G06N3/04
CPCG06Q10/04G06Q50/06G06N3/044G06F18/214
Inventor 康爱军徐创学雷嵘李鹏文亚军龚杰
Owner NORTHWEST ELECTRIC POWER DESIGN INST OF CHINA POWER ENG CONSULTING GROUP
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