Regional carbon emission calculation method based on electric power big data and time sequence
A time-series, carbon emission technology, applied in digital data processing, calculation, data processing applications, etc., can solve the problems of uncertainty, large regional carbon emission calculation errors, etc., to achieve simple and efficient methods and accurate calculation results reliable results
Pending Publication Date: 2022-07-22
GUANGXI POWER GRID CORP
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[0003] The purpose of the present invention is to provide a method for calculating regional carbon emissions based on electric power big data and time series, which can solve the problems of large errors and uncertainties in the calculation of regional carbon emissions in the prior art
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[0028] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.
[0029] The embodiments of the present disclosure are described below through specific specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only some, but not all, embodiments of the present disclosure. The present disclosure can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments may be combined with each other under the condition of no conflict. Based on the embodiments in the present disclosure, all ot...
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The invention discloses a regional carbon emission calculation method based on electric power big data and a time sequence, and the method comprises the steps: obtaining regional electric power big data, and extracting the power consumption of each industry of a region; performing time sequence analysis on the electricity consumption of each industry in the region, and dividing the electricity consumption of each industry into a long-term trend factor, a seasonal cycle factor, a cycle factor and a randomness factor; calculating a joint confidence interval of the electricity consumption of each industry by using the random factor variance of the electricity consumption of each industry, and obtaining a joint confidence interval of the regional electricity consumption; and carrying out weighted calculation by combining the joint confidence interval of the regional electricity consumption and the industry carbon emission coefficient to obtain a regional carbon emission interval. The power big data and the time sequence analysis are combined, the time sequence analysis method and the joint confidence interval method are used for calculating the confidence interval of the carbon emission, uncertainty is introduced in calculation of the carbon emission, and overall mastering of the regional carbon emission is enhanced.
Description
technical field [0001] The invention relates to the field of carbon emission calculation, in particular to a regional carbon emission calculation method based on electric power big data and time series. Background technique [0002] The current carbon emission measurement methods mainly include the following: actual measurement method, input-output method, input coefficient method, and prediction methods using various machine learning models, etc. The actual measurement method is the measurement data obtained through on-site monitoring. And calculate the carbon emissions based on this, but for an entire region, the complete monitoring conditions that integrate various factors are very harsh, not to mention the consumption of human, material and financial resources will be huge, so for a region's carbon emissions calculation It is not applicable; the input-output method uses the input-output model in economic statistics to calculate the carbon emissions of the entire producti...
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Login to View More IPC IPC(8): G06F16/2458G06Q50/06G06Q50/26
CPCG06F16/2462G06F16/2474G06Q50/06G06Q50/26
Inventor 周春丽林溪桥岑剑峰周珑卢纯颢覃惠玲陈志君王鹏程敏
Owner GUANGXI POWER GRID CORP