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Method for determining thermal power unit operation optimization target value based on FP-Growth algorithm

A technology for operation optimization and thermal power unit, which is applied in the field of electric power engineering to achieve the effect of improving mining efficiency

Active Publication Date: 2019-11-12
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0006] The technical problem to be solved by the present invention is to overcome the defects of the Apriori algorithm in the prior art and provide a method for determining the target value of thermal power unit operation optimization parameters with short time consumption, low memory usage and high efficiency in mining massive data

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  • Method for determining thermal power unit operation optimization target value based on FP-Growth algorithm
  • Method for determining thermal power unit operation optimization target value based on FP-Growth algorithm
  • Method for determining thermal power unit operation optimization target value based on FP-Growth algorithm

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Embodiment Construction

[0040] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0041] The FP-Growth algorithm is a memory-based association rule mining algorithm, which only needs to scan the data set twice and does not generate candidate item sets. Compared with the Apriori algorithm, the FP-Growth algorithm runs faster and occupies less computer resources. Especially when dealing with big data, the advantages of FP-Growth algorithm are more obvious. The massive historical data of generating units has high-dimensional properties, so the research on unit operation optimization based on FP-Growth algorithm is more meaningful.

[0042] In order to improve the efficiency of data mining algorithms in mining massive data, existing literatures have carried out parallel improvemen...

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Abstract

The invention discloses a method for determining a thermal power unit operation optimization target value based on Apache Spark and an improved FP-Growth algorithm. The method includes the following steps of: S1, selecting influence parameters of a power supply coal consumption rate, collecting historical operation data according to the influence parameters, and performing data preprocessing and steady-state detection; S2, screening operation optimization parameters from the influence parameters of the power supply coal consumption rate by using Pearson correlation analysis; S3, improving an FP-Growth algorithm based on a matrix technology; S4, parallelizing the improved FP-Growth algorithm based on Apache Spark; S5, discretizing the data of the operation optimization parameters, mining afrequent pattern from a data set by using the parallel improved FP-Growth algorithm, inversely discretizing a mining result, and sorting out the mining result to obtain the target value of the unit operation optimization parameters under various working conditions. The method for determining the target value of the thermal power unit operation optimization parameters disclosed by the invention isbased on the Apache Spark and the improved FP-Growth algorithm, and has the advantages of short time consumption, low memory usage and high efficiency of mining massive data.

Description

technical field [0001] The invention relates to a method for determining a thermal power unit operation optimization target value based on Apache Spark and an improved FP-Growth algorithm, and belongs to the technical field of electric power engineering. Background technique [0002] In recent years, in the face of new situations such as air pollution control and climate change response, energy conservation and emission reduction work has been further deepened, and generating units are facing greater pressure to improve efficiency. Since the equipment with energy-saving potential in the unit has basically undergone energy-saving transformation, the energy-saving and emission-reduction work needs to be implemented in daily work and operation, and develop in a more refined direction. Therefore, the research on operation optimization is very important to the energy saving and emission reduction work of the unit. [0003] Reasonable determination of the target value is the prem...

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Application Information

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IPC IPC(8): G05B17/02
CPCG05B17/02Y02D10/00
Inventor 林金星缪宇航
Owner NANJING UNIV OF POSTS & TELECOMM
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