Material supplier production capacity monitoring and abnormity early warning method based on electricity consumption analysis

A technology of production capacity and power consumption, which is applied in the field of material supplier production capacity monitoring and abnormal early warning based on power consumption analysis, can solve the problem of large manpower and material resources demand for supplier production risk prevention work, and the safety and stability of the power grid system. Hidden dangers, insufficient capacity of suppliers, etc.

Pending Publication Date: 2019-08-16
国网江苏省电力有限公司物资分公司 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Insufficient production capacity of suppliers and the risk of production shutdown due to economic problems are the main reasons for delayed delivery of materials
At the same time, when some suppliers themselves cannot meet the production needs, they have illegal operations of outsourcing orders without authorization, resulting in the inability to effectively guarantee the quality of materials, and laying hidden dangers to the construction of power grids and the safe and stable operation of the system.
[0003] Insufficient production capacity of suppliers

Method used

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  • Material supplier production capacity monitoring and abnormity early warning method based on electricity consumption analysis
  • Material supplier production capacity monitoring and abnormity early warning method based on electricity consumption analysis
  • Material supplier production capacity monitoring and abnormity early warning method based on electricity consumption analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0072] Embodiment 1 Monthly early warning of production status of material suppliers

[0073] A kind of monthly early warning in the material supplier production monitoring and early warning model method based on electricity consumption analysis, comprises the following steps (such as figure 1 ), first use the normalization method to standardize the data, and use the wavelet decomposition to separate the power consumption data into trends and fluctuations, so as to dig out the abnormal power consumption data; predict the supplier's power consumption data in the next month by using the neural network algorithm , use the re-sampling method to predict a reasonable fluctuation range, and set a warning range for electricity consumption in the next month.

[0074] Set up the early warning model target, dig out the possible abnormal power consumption data in the historical data, and the month when the abnormal power consumption occurs, predict the power consumption data of the next m...

Embodiment 2

[0130] Example 2 Annual early warning example and optimization of material supplier production monitoring and early warning

[0131] When conducting annual early warning research, collect the electricity consumption and main business data of a certain type of material supplier from 2011 to 2013, and obtain the electricity consumption value per unit income of the supplier from 2011 to 2013, through statistical analysis (such as Figure 8 ), the distribution of the series is relatively average, showing a gradual enlargement trend, which is in line with the normal distribution in statistics, the deviation of the series distribution is not large, and there are occasional maximum values ​​(such as Figure 9 ). Based on this, the average value is selected as the reference value of electricity consumption per unit income of the year. At the same time, through the statistical analysis of the electricity consumption data per unit income in the past year and the observation of the data ...

Embodiment 3

[0142] Embodiment 3 Quarterly early warning of material supplier production monitoring and early warning

[0143] The quarterly power consumption warning for suppliers is based on the analysis of the annual power consumption per unit revenue standard, and the supplier’s quarterly power consumption per unit revenue is used as a reference indicator.

[0144] Quarterly electricity consumption per unit income is calculated as follows:

[0145] Quarterly electricity consumption per unit income (kWh / 10,000 yuan) = sum of electricity consumption in the past three months (kWh) / (1 / 4×annual main business income) (10,000 yuan)

[0146] Take the average as the reference value of electricity consumption per unit income in the quarter. At the same time, through statistical analysis of historical quarterly electricity consumption data per unit income and observation of the data relationship between the minimum, average, and maximum values, the same industry, suppliers The lowest value of qu...

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Abstract

The invention belongs to the field of power industry, particularly relates to the field of power industry material supplier management and supervision, and more particularly relates to a material supplier production capacity monitoring and abnormity early warning method based on power consumption analysis. Monthly production capacity monitoring and abnormal early warning are carried out on material suppliers. Power consumption analysis model is established, the historical power consumption of the single sample of the supplier is analyzed; electricity consumption data are separated into trendsand fluctuations through wavelet analysis; abnormal data points in the historical electricity consumption data are mined by using a low-order differential denoising method; Lagrangian interpolation method replacement is carried out on the abnormal data points to obtain a new fluctuation trend; scientific methods such as a neural network algorithm, a re-sampling method and the like are adopted, themonthly electricity consumption data and reasonable fluctuation intervals of the supplier are predicted by utilizing a plurality of groups of trend charts processed by different methods, and a monthly electricity consumption early warning interval is set, so that the real-time monitoring of the electricity consumption of the supplier and the timely early warning of abnormal production conditionsare realized. According to the method, the material categories of the power consumption standard values within the year and the season of the supplier are analyzed, and industrial standard setting suggestions are given.

Description

technical field [0001] The invention belongs to the field of electric power industry, especially the field of management and supervision of material suppliers in the electric power industry, and more specifically relates to a material supplier production capacity monitoring and abnormal early warning method based on electricity consumption analysis. Background technique [0002] Supplier production monitoring and early warning issues have always been the focus of power companies. Insufficient capacity of suppliers and the risk of production stoppage due to economic problems are the main reasons for the delayed delivery of materials. At the same time, when some suppliers cannot meet their own production needs, they have illegal operations of outsourcing orders without authorization, resulting in the inability to effectively guarantee the quality of materials, and burying hidden dangers to the construction of power grids and the safe and stable operation of the system. [000...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/04G06Q10/0635G06Q50/06Y02P90/82
Inventor 袁黎王新年井伟殷玮珺肖少非卞华星杨店飞房红梁辰张有志
Owner 国网江苏省电力有限公司物资分公司
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