A residential electricity consumption forecasting method based on electro-chemical index
A forecasting method and electricity consumption technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as potential electricity consumption estimation errors of household appliances, and achieve the effect of improving accuracy and effectiveness
Active Publication Date: 2019-02-19
SHANGHAI UNIVERSITY OF ELECTRIC POWER
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Problems solved by technology
However, this method ignores the changes in the power, frequency of use and hours of use of various household appliances with the development of society, so there is a large error in the estimation of the potential power consumption of household appliances
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[0059] 1) Investigate the inventory and power of major household appliances
[0060] Investigate the average number of households with major household electrical appliances through the Statistical Yearbook N i , check the power of each major household appliance, and calculate the average power P of each major household appliance i , and the results are shown in Table 1. Among them, the power of tape recorders, video cameras, DVD players, video cameras, and mobile phones is less than 40W, which contributes little to residents' electricity consumption and can be ignored in calculations.
[0061] Table 1 The average number of major household electrical appliances in a city per 100 households
[0062]
[0063]
[0064] 2) Calculate the frequency factor of household appliances
[0065] The use time of different household appliances is obtained through the form of family visits and surveys, and the survey results are integrated to obtain the annual use time parameters of ma...
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The invention relates to a residential electricity consumption forecasting method based on an electro-chemical index, comprising the following steps: 1) the average holding amount Ni and the average power Pi of the main household appliances of 100 households are counted; 2) acquiring the service time of the household appliance and calculating the frequency factors of various household appliances;3) calculating a correction factor lambda i of the household appliance; 4) calculating electrification index HEA; 5) Constructing the multiple linear regression model, using the electrical index HEA,the total household Aj and the per capita disposable income Bj as input to the multiple linear regression model, and using the resident electricity consumption Yj as the output value for training, andpredicting the residential power consumption based on the trained multiple linear regression model. prediction. Compared with the prior art, the invention has the advantages of comprehensive consideration, high correlation, accuracy and effectiveness.
Description
technical field [0001] The invention relates to the forecasting of electricity consumption of residents, in particular to a forecasting method of electricity consumption of residents based on electrification index. Background technique [0002] There are many factors that affect residents' electricity consumption, including household disposable income, building area size, residential area climate, family size, household appliance ownership and usage rates, family living habits, and policy promotion. Household appliances are the loads of residents' electricity consumption, and their inventory is the biggest factor affecting residents' electricity consumption. However, the effective inventory of household appliances lacks a unified evaluation standard, and effective comparisons between different household appliances cannot be carried out. It is too one-sided to rely solely on power and comparison and ignore the frequency and duration of use of household appliances. When forec...
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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 夏飞彭运赛彭道刚孟珊珊柴闵康张洁蒋碧鸿
Owner SHANGHAI UNIVERSITY OF ELECTRIC POWER