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A method for decompose and forecasting electric quantity of meteorological influence

A forecasting method and meteorological technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as large forecasting errors and lack of theoretical basis, and achieve the effect of improving accuracy and reducing errors

Pending Publication Date: 2019-02-01
NANJING ELECTRIC POWER ENG DESIGN +4
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Conventional forecasting methods rely on the practical experience of forecasters combined with the relationship between some simple variables, often lacking scientific theoretical basis, resulting in large forecasting errors

Method used

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  • A method for decompose and forecasting electric quantity of meteorological influence
  • A method for decompose and forecasting electric quantity of meteorological influence
  • A method for decompose and forecasting electric quantity of meteorological influence

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0022] In this embodiment, a method for predicting the decomposition and prediction of electricity influenced by weather is proposed, which includes the following steps:

[0023] S1: Set the base month: the default spring base month is May, and the autumn base month is October;

[0024] S2: Calculate meteorological correlation: divide the data into two parts, winter and summer, and calculate the data separately. If the month belongs to November-April, then calculate the winter correlation. If the month belongs to June-September, calculate the summer correlation. The base month is not involved in the calculation, the correlation calculation formula is get correlation data;

[0025] S3: Calculating the growth rate of monthly weather-influenced electricity: pass y to the correlation data in S2 t =y i -y j and δ=(y t / y j )*100% formula to calculate the monthly weather-affected electricity growth rate and display the correlation coefficient;

[0026] S4: Display: display t...

Embodiment 2

[0031] Taking the data of a certain region from 2014 to 2017 as an example, Table 1 shows the monthly electricity consumption of businesses in a certain region over the years. The amount of weather-affected electricity is obtained by subtracting the closest historical basic monthly electricity from the average amount of electricity, as shown in Table 3. Table 4 shows the growth rate of commercial weather-affected electricity in a certain area from 2014 to 2017, and calculates summer weather-related indicators and weather-affected electricity, and winter weather-affected electricity. The correlation between weather-related indicators and weather-affected electricity has been standardized in order to unify each year. The analysis results are shown in Table 5 and Table 6.

[0032]

[0033]

[0034] Table 1

[0035] Average daily electricity

Year 2014

2015

2016

2017

January

16.34

20.33

21.09

24.52

February

19.39

22.39...

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Abstract

The invention discloses a meteorological influence power quantity decomposition prediction method, comprising the following steps: S1. Setting a base month: the default spring base month is May, and the autumn base month is October; S2: Calculate Meteorological Correlation: Calculate data separately in winter and summer. If the month belongs to November to April, the winter correlation is calculated. If the month belongs to July to September, the summer correlation is calculated, but the base month is not involved in the calculation. The correlation formula is shown in the description to obtain the correlation data. S3: Calculate monthly meteorological impact power growth rate: for the correlation data in S2 via yt=yi-Yj and delta = (yt / yj) * 100% formula to obtain monthly meteorological influence power growth rate and show correlation coefficient. According to the scientific theory, it is concluded that meteorological factors are the important factors that affect the load forecasting,and the accuracy of load forecasting is improved, and the error is small.

Description

technical field [0001] The invention relates to the technical field of welding, in particular to a method for predicting the decomposition and prediction of electricity influenced by weather. Background technique [0002] Forecasting is the basis, premise and basis for correct decision-making. Correct forecasting of regional power demand levels is an important basis for power companies at all levels to guide power system planning and operation. Power load analysis and prediction needs to combine the past and present known economic situation, social development and power market conditions, through the analysis and research of historical data, to explore and grasp the internal relationship between relevant factors and power load and the law of development and change, so that according to the planning The forecast of the economic situation and social development during the period is used to calculate the future power demand situation. [0003] Today, with the further deepening...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 史静葛毅李琥刘国静牛文娟韩俊杰刘丽新罗欣刘梅
Owner NANJING ELECTRIC POWER ENG DESIGN
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