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Method for on-line prediction of real-time load of power plant

A technology of power plant load and real-time load, applied in the direction of electric digital data processing, instrumentation, calculation, etc., can solve problems such as single modeling means, poor scalability, unclear physical meaning of parameters, etc., to achieve flexible and highly understandable models Sexuality, convenience for analysis and understanding

Inactive Publication Date: 2015-12-30
BOHAI UNIV
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Problems solved by technology

These methods have certain applicable conditions. In the process of modeling and forecasting, there are generally problems such as single modeling means, unclear physical meaning of parameters, and poor scalability.

Method used

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  • Method for on-line prediction of real-time load of power plant
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  • Method for on-line prediction of real-time load of power plant

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Embodiment Construction

[0044] The specific implementation manners of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0045] This embodiment uses sensors to collect on-site online operation data of generator sets through the network, and collects real-time load data of power plants. Taking the load data of a large thermal power plant shown in Table 1 as an example, the time is a certain month in 2014, and the sampling period is 15 minutes, a total of 90 minutes of data collection, specific data in Table 1. Among them, 1 to 6 data are original data, and the seventh is the power plant load data at the next moment, that is, forecast data.

[0046] Table 1 Load data of a large thermal power plant

[0047] Number of data

1

2

3

4

5

6

7

Actual load (MW)

207.7

216.2

231.3

241.3

274.0

275.3

280.3

[0048] A real-time load online forecasting method for a power plant, such as...

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Abstract

The invention provides a method for on-line prediction of real-time load of a power plant. The method comprises the steps of load data of the power plant at a current moment, obtaining power plant load data at the historical moment, and performing fractional order accumulation pretreatment; using a power plant load original data fractional order accumulation generation sequence to build a fractional order accumulation GM (1,1) model for predicting power plant load data; utilizing the power plant load data predicting model to predict the power plant load data at a next moment in real time; and correcting real-time prediction results of the power plant load data at the next moment. The fractional order accumulation GM (1,1) model for predicting the power plant real-time load data is adopted, small-sample historical data are adopted in the modeling process, the problems in storage, calculation and complexity caused by large data volume are solved, the data utilization rate is improved effectively, intermediate data parameter analysis and results have high understandability, and the analysis and understanding by machine set operators are facilitated.

Description

technical field [0001] The invention relates to the technical field of power plant data forecasting, in particular to an online real-time load forecasting method of a power plant. Background technique [0002] The real-time data of the thermal power unit records the operation process of the power plant equipment and operators, and provides an important decision-making basis for the operation, maintenance and accident handling of the power plant. These data have positive guiding significance for improving the production efficiency and economic safety of the power plant, and also help to improve the operation optimization, fault diagnosis and condition maintenance technology of the power plant. With the development of power station SIS and MIS, a large amount of historical data is stored in the database, which also brings difficulties to data storage and analysis. Research on the overall characteristics and development trends of real-time data of important parameters of therm...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00G06N3/12
CPCY04S10/50
Inventor 杨洋郭继宁李兵赵震王东
Owner BOHAI UNIV
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