Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Short-term load prediction based on meteorological similar day and error correction

A technology for short-term load forecasting and error correction, applied in the fields of instruments, data processing applications, resources, etc., which can solve the problems of undisclosed contacts, troubles of electric power workers, troubles of load forecasting work, etc.

Inactive Publication Date: 2017-02-15
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
View PDF0 Cites 33 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, based on the above-mentioned theories, the variability of meteorological conditions has still caused considerable trouble to the power system load forecasting work. The internal relationship between meteorological conditions and the numerical characteristics of forecast errors has not been disclosed, nor has it been disclosed in the prior art. The relationship between the changing main weather factors and the load, which caused troubles for electric workers

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
  • Short-term load prediction based on meteorological similar day and error correction
  • Short-term load prediction based on meteorological similar day and error correction
  • Short-term load prediction based on meteorological similar day and error correction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0061] 1 Regression analysis of meteorological factors based on SPSS

[0062] 1.1 Establishment of multiple regression analysis model

[0063] In real life, people often want to perform statistical analysis on a dependent variable, but there are often more than one independent variable affecting the dependent variable. For example, k independent variables X need to be considered 1 , X 2 ,...,X k When the relationship between the dependent variable y and the dependent variable y, the principle of least squares method is used to establish a multiple linear regression model as:

[0064] y=y'+μ=b 0 +b 1 x 1 +b 2 x 2 +...+b i x i +...+b k x k (1)

[0065] It can be seen from formula (1) that the dependent variable y is composed of two parts. The first part y′ is the estimated value of the dependent variable y, which represents the part that can be determined by the variable; u is the residual, which represents the part that is not determined by the independent variabl...

Embodiment 2

[0140] In order to verify the applicability of the load forecasting principle including the simulation relative error, the load data and meteorological data of a certain area are used in the calculation example for forecasting, and MATLAB programming is used for simulation.

[0141] In this embodiment, one day in each of the four seasons of spring, summer, autumn and winter in 2014 in this region is selected as the forecast date, which are recorded as A1, A2, A3, and A4 respectively. For a certain forecast day, determine the season it belongs to, use real-time meteorological data as the basis for selecting similar days, and then establish a similar day forecast error sample set, conduct uniform sampling based on the systematic sampling method, and sort the sampling results according to the volatility analysis. Figure 4 It is the compensation error result obtained from the volatility analysis of A1~A4 and the final fitting error after sorting.

[0142] The prediction result of...

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, which relates to the scheduling, operating, and planning field of the power system, discloses a short-term load prediction based on meteorological similar day and error correction. According to the invention, a meteorological factor regression analysis is carried out by using SPSS software; meteorological factors affecting a load most obviously in all seasons are selected; and weights of all factors are determined and are used as a basis for selecting a meteorological similar day. A historical prediction error data sample set is established; for a certain prediction day, an error data sample establishment set of a similar day is extracted, and a probability density distributed fitting model is established. An error fluctuation situation of a prediction point is analyzed to obtain a compensation value of a predicted error; and an error sample value closest to the error compensation value is selected as an error fitting value of this time and is superposed on the prediction value. Therefore, the prediction precision is improved.

Description

technical field [0001] The invention relates to the field of power system dispatching, operation and planning, in particular to a short-term load forecasting method based on meteorological similar days and error correction. Background technique [0002] General short-term load forecasting has become an important part of power system dispatching, operation and planning. Under the marketization trend of my country's power industry, the results of load forecasting have become the key to power companies to formulate production and marketing plans and improve economic benefits. The load of the power system has its own inherent periodic law, and is also affected by many factors, such as climate conditions, economic development level, energy supply mode, etc. Due to the differences in load characteristics between regions, the load forecasting work for different regions should be combined with the actual local conditions, and the factors affecting the load should be considered on t...

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): G06Q10/06G06Q50/06
CPCG06Q10/06375G06Q10/06313G06Q50/06
Inventor 高亚静孙永健杨文海周晓洁
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com