Direct dispersion separation modeling prediction control method under multiple weather types based on GRA-LMBP weights

A technology of weather type and predictive control, which is applied in the direction of weather condition forecasting, meteorology, measuring devices, etc., can solve the problem of low model accuracy, improve accuracy, improve prediction accuracy, reduce root mean square error and average relative error Effect

Inactive Publication Date: 2019-08-16
SHANGHAI UNIVERSITY OF ELECTRIC POWER
View PDF6 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The "straight-scatter separation" forecasting model is divided into daily scale, monthly scale and hourly scale. The current researc

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Direct dispersion separation modeling prediction control method under multiple weather types based on GRA-LMBP weights
  • Direct dispersion separation modeling prediction control method under multiple weather types based on GRA-LMBP weights
  • Direct dispersion separation modeling prediction control method under multiple weather types based on GRA-LMBP weights

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0053] Such asfigure 1 Shown is the schematic flow sheet of the inventive method, and concrete steps are as follows:

[0054] S1: Statistical collection of meteorological data and radiation data in Beijing for many years. Meteorological data include total cloud cover, visibility, etc., and radiation data include total radiation, direct radiation, diffuse radiation, etc. Using the normal fitting method to select a typical meteorological year for the data;

[0055] S2: correct the sharpness index, divide the weather type according to the revised sharpness index and count the proportion of each weather type;

[0056] S3: For each weather type, principal component analysis (PCA) and gray relational analysis (GRA) are used to extract mutually independent principal component factors and correlation degree comparisons from the original multiple scattering ratio influence factors with correlation. large variable

[0057] S4: For each weather type, use the support vector machine (SV...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a direct dispersion separation modeling prediction control method under multiple weather types based on GRA-LMBP weights. Firstly, performing statistics and collection on meteorological radiation data of many years in Beijing area, selecting typical meteorological years according to a normal fitting method and using a revised definition index to classify the weather types;secondly, using support vector machine (SVM), gray relational analysis (GRA) based support vector machine GRA-SVM and principal component analysis (PCA) based support vector machine (PCA-SVM) prediction models to obtain prediction results of three single models under each weather type; then using the gray relational analysis to obtain the weight coefficient of each model under each weather type;then fitting an LMBP neural network prediction model according to each single model prediction result and prediction weight coefficient under each weather type; and finally, using the weight coefficients obtained by the LMBP model to calculate the combined prediction model prediction results of each weather type. Compared with the prior art, the direct dispersion separation modeling prediction control method under multiple weather types based on the GRA-LMBP weights has the advantages of high precision, good calculation stability and the like.

Description

technical field [0001] The invention relates to one, in particular to a GRA-LMBP weight-based direct-dispersive separation modeling predictive control method under multi-weather types. Background technique [0002] The National Energy Administration pointed out at a press conference in early 2019 that by the end of 2018, my country's installed capacity of renewable energy power generation had reached 728 million kilowatts, a year-on-year increase of 12%, of which photovoltaic power generation installed capacity was 174 million kilowatts, a year-on-year increase of 34%, ranking first in the world. 1 person. The new installed capacity of photovoltaic power generation in the whole year was 44.26 million kilowatts, second only to the newly installed capacity in 2017, and the second highest in history. In 2019, my country will focus on promoting the high-quality development of photovoltaic power generation, continue to promote the development of the photovoltaic industry, and mai...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G01W1/10G06F17/50
CPCG01W1/10G06F30/20
Inventor 李芬王悦杨勇刘海风林逸伦赵晋斌
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products