Big data analysis method and device based on hybrid energy data
A technology of mixing energy and analysis methods, applied in the computer field, can solve problems such as increasing the cost of energy plants and lack of technical solutions
Active Publication Date: 2021-12-21
武汉超云科技有限公司
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Problems solved by technology
However, reducing carbon dioxide emissions will increase the cost of energy plants, so there are some energy plants that modify carbon dioxide emission data to pretend to achieve the goal of carbon dioxide emission indicators
And prior art lacks the technical scheme that solves this phenomenon
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[0047] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0048] refer to figure 1 , the embodiment of the present application provides a big data analysis method based on mixed energy data, including the following steps:
[0049] S1. The big data analysis server obtains the pre-bound first sample server and second sample server; wherein, the first sample server corresponds to the first energy plant, the second sample server corresponds to the second energy plant, and the first energy plant The factory is the upstream factory of the second energy factory;
[0050] S2. Send a first sample sensing data request message to the firs...
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The invention discloses a big data analysis method based on hybrid energy data. The method comprises the following steps: acquiring a first sample server and a second sample server which are bound in advance; acquiring a first sample sensing data set; acquiring a second sample sensing data set; performing binding and labeling processing to generate sample data labeled with a first index, calling a deep neural network model, and training the deep neural network model to obtain an index prediction model; respectively acquiring a first sensing data set and a second sensing data set, and acquiring a second index; jointly inputting the data into an index prediction model for processing to obtain a predicted index value, and calculating a difference value between the predicted index value and the second index; if the difference value is less than the preset threshold value, determining that the hybrid energy plant operates normally, so the purpose of distinguishing fake data is achieved, and the purpose of carbon neutralization is promoted to be truly achieved.
Description
technical field [0001] This application relates to the computer field, in particular to a big data analysis method and device based on mixed energy data. Background technique [0002] To achieve the goal of carbon neutrality, we need to start from two aspects, that is, we need to reduce the emission of carbon dioxide and increase the absorption of carbon dioxide. In terms of carbon dioxide emissions, energy plants account for a part of the proportion. These energy plants, such as petrochemical plants (oil refineries, etc.), and power plants (thermal power plants, etc.), will inevitably emit carbon dioxide during the production process. In order to achieve carbon neutrality, macro regulation is required to control the CO2 emissions of these energy plants as a whole. However, reducing carbon dioxide emissions will increase the cost of energy plants, so there are some energy plants that modify carbon dioxide emission data to pretend to achieve the goal of carbon dioxide emiss...
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Login to View More IPC IPC(8): H04L29/08G06N3/04G06N3/08
CPCH04L67/12G06N3/08G06F2219/10G06N3/045
Inventor 裴雅琼
Owner 武汉超云科技有限公司