CN113177686A - Energy consumption abnormity judgment method based on carbon consumption index - Google Patents
Energy consumption abnormity judgment method based on carbon consumption index Download PDFInfo
- Publication number
- CN113177686A CN113177686A CN202110334633.6A CN202110334633A CN113177686A CN 113177686 A CN113177686 A CN 113177686A CN 202110334633 A CN202110334633 A CN 202110334633A CN 113177686 A CN113177686 A CN 113177686A
- Authority
- CN
- China
- Prior art keywords
- energy consumption
- carbon
- consumption
- energy
- index
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000005265 energy consumption Methods 0.000 title claims abstract description 149
- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 118
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 113
- 238000000034 method Methods 0.000 title claims abstract description 23
- 230000002159 abnormal effect Effects 0.000 claims abstract description 26
- 238000011156 evaluation Methods 0.000 claims abstract description 22
- 238000009826 distribution Methods 0.000 claims abstract description 16
- 239000003245 coal Substances 0.000 claims description 14
- 238000004519 manufacturing process Methods 0.000 claims description 11
- 238000004458 analytical method Methods 0.000 claims description 7
- 230000005611 electricity Effects 0.000 claims description 7
- 238000005259 measurement Methods 0.000 claims description 4
- 230000008859 change Effects 0.000 abstract description 3
- 238000011161 development Methods 0.000 description 8
- 238000005516 engineering process Methods 0.000 description 5
- 230000009467 reduction Effects 0.000 description 5
- 230000009466 transformation Effects 0.000 description 5
- 230000005856 abnormality Effects 0.000 description 4
- 238000004134 energy conservation Methods 0.000 description 4
- 230000006872 improvement Effects 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 3
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 239000002028 Biomass Substances 0.000 description 1
- 229910002092 carbon dioxide Inorganic materials 0.000 description 1
- 239000001569 carbon dioxide Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 238000011038 discontinuous diafiltration by volume reduction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 238000013341 scale-up Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/82—Energy audits or management systems therefor
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/84—Greenhouse gas [GHG] management systems
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an energy consumption abnormity judging method based on a carbon consumption index, which overcomes the problems that in the prior art, whether energy consumption is abnormal or not is judged only from the energy consumption perspective, productivity is not combined, and a plurality of types of energy are required to be monitored and judged, and time and labor are consumed, and comprises the following steps: analyzing and comparing big data, and setting an energy consumption evaluation index; acquiring energy data and output value data, and converting the acquired energy data into carbon emission; calculating an energy carbon consumption index according to the carbon emission and the obtained output value data; comparing the obtained carbon consumption index with the evaluation index, and analyzing and judging whether the energy consumption is abnormal or not; and analyzing the distribution of the industry in the region according to the energy consumption situation. The energy consumption and the output value are combined, the energy consumption grade is judged by calculating the carbon consumption index, the unit output value carbon emission change of each area is reflected, and the influence of factors such as an industrial structure, new energy utilization and the like on the carbon consumption is shown.
Description
Technical Field
The invention relates to the field of data monitoring and diagnosis, in particular to an energy consumption abnormity judgment method based on a carbon consumption index.
Background
The promotion of ecological civilization and energy transformation is a major mission in the current development, and how to realize clean low-carbon development, develop comprehensive energy service, guide clean, efficient and economical energy consumption habits, accelerate the conversion of energy consumption from price reduction to volume reduction and improve the energy utilization efficiency is a difficult point. Before this, the energy consumption level needs to be judged first to determine the further development direction.
For energy consumption, although methods for judging whether energy consumption is abnormal by respectively detecting electric quantity, coal quantity and the like exist at present, one-way detection of certain energy consumption is adopted, total detection is not adopted, and because production levels of all areas are different, the judgment of whether energy consumption is abnormal is not accurate only from the perspective of energy consumption. For example, the invention named as a method and a device for monitoring energy consumption abnormity is disclosed in 2015, 4 month and 22 days of the Chinese patent office, and the publication number is CN 104534285A. The invention discloses a method and a device for monitoring energy consumption abnormity, wherein the monitoring method comprises the steps of S1, setting an energy consumption abnormity prejudgment threshold value; s2, acquiring energy consumption data of each preset time interval in the current day and energy consumption data of each preset time interval in the previous day, and respectively acquiring the lowest energy consumption time interval and the lowest energy consumption value of the current day and the previous day; s3, judging whether the lowest energy consumption value of the current day is larger than the energy consumption abnormity prejudgment threshold value, if so, turning to the step S4, and if not, judging that no energy consumption abnormity exists; s4, judging whether the lowest energy consumption value of the current day is larger than the lowest energy consumption value of the previous day, if so, judging that energy source abnormality exists and the energy consumption abnormality occurs after the lowest energy consumption time period of the previous day, and if not, judging that the energy consumption abnormality does not exist. The invention can accurately judge whether the energy consumption is abnormal or not and the specific time period when the energy consumption is abnormal, but only judge whether the energy consumption is abnormal or not from the energy consumption perspective.
Disclosure of Invention
The invention aims to solve the problems that whether energy consumption is abnormal or not is judged only from the energy consumption perspective and productivity is not combined, and a plurality of types of energy are required to be monitored and judged, so that time and labor are consumed in the prior art, and provides an energy consumption abnormity judgment method based on a carbon consumption index.
In order to achieve the purpose, the invention adopts the following technical scheme: an energy consumption abnormity judgment method based on a carbon consumption index is characterized by comprising the following steps:
s1: analyzing and comparing big data, and setting an energy consumption evaluation index;
s2: acquiring energy data and output value data, and converting the acquired energy data into carbon emission;
s3: calculating an energy carbon consumption index according to the carbon emission and the obtained output value data;
s4: comparing the obtained carbon consumption index with the evaluation index, and analyzing and judging whether the energy consumption is abnormal or not;
s5: and analyzing the distribution of the industry in the region according to the energy consumption situation.
According to the invention, the carbon consumption indexes in the typical region are analyzed and compared through big data, and the energy consumption evaluation index is set accordingly. The carbon consumption index is used for evaluating the carbon emission of unit output values of the regions, objectively reflecting the carbon emission intensity of each region, and accurately showing the influence of factors such as industrial structures, new energy utilization and the like on the carbon consumption. After the evaluation indexes are set, for the area to be evaluated, firstly, energy consumption data of enterprises on the rule in the area are obtained, then the energy data are converted into carbon emission data, a carbon consumption index is calculated according to a formula, then the carbon consumption index is compared with the evaluation indexes, the energy consumption level of the area is judged, and the enterprises in the area are planned according to the energy consumption level. The data source is a data report obtained by a government department. The carbon consumption index accurately reflects the carbon emission level of unit output value of each area, assists government departments in classified accurate strategy, promotes enterprise transformation and upgrading and new energy development, strives to create energy-saving, consumption-reducing and green development atmosphere, and provides a brand-new idea for government accurate analysis and scientific decision.
Preferably, the step S1 is further expressed as:
s1.1: selecting a plurality of areas with outstanding industrial structures for measuring and calculating the carbon emission;
s1.2: and comparing and analyzing the measurement results, and setting an evaluation index.
The areas with prominent industrial structure comprise areas with enterprises on the high-carbon emission gauge, areas with enterprises on the low-carbon emission gauge and areas with equivalent number of enterprises on the high-carbon emission and low-carbon emission gauges. And obtaining a result according to the selected representative area, thereby obtaining an evaluation index which is more reliable.
Preferably, in step S1.1, the carbon emission includes carbon emission from regional power, coal, oil, and gas.
And (3) carrying out quantitative analysis on indexes such as carbon emission, output value and the like generated by main energy consumption of regional production and management on the basis of the statistical data of the same aperture, and fully embodying objectivity. The specific statistical period can be quarterly, semi-annually and annually, and the carbon emission is rounded to two decimal places. Meanwhile, as new energy is an important development direction for energy conservation and consumption reduction at present, the carbon emission generated by electricity does not include the carbon emission generated by electricity generation of the new energy in the region. The new energy refers to renewable energy developed and utilized on the basis of new technology, and comprises solar energy, biomass energy, wind energy, geothermal energy, wave energy, ocean current energy, tidal energy and the like.
Preferably, the evaluation indexes in step S1.2 are specifically: energy consumption is divided into five grades according to the carbon consumption index:
the carbon consumption index is less than or equal to 0.6, is grade 1, represents low energy consumption,
the carbon consumption index is more than 0.6 and less than or equal to 0.8, the grade is 2, which represents that the energy consumption is lower,
the carbon consumption index is more than 0.8 and less than or equal to 1.2, is grade 3, represents that the energy consumption is close to the average level of the region,
the carbon consumption index is more than 1.2 and less than or equal to 2, the grade is 4, which represents that the energy consumption is higher,
the carbon consumption index is more than or equal to 2 and is grade 5, which indicates high energy consumption.
The energy consumption is divided into five grades according to the carbon consumption index, and the lower the grade is, the lower the energy consumption is, namely, the lower the carbon emission amount of the same output value produced in the area is. Energy consumption is graded, so that the method is beneficial to assisting government departments in classified and accurate strategy, promoting enterprise transformation and upgrade and new energy development, and striving to create an energy-saving, consumption-reducing and green development atmosphere.
Preferably, the step S2 further includes:
s2.1: collecting main energy data of production and operation of enterprises on a rule in a certain period of an area to be detected and a total production and operation value of the enterprises on the rule in the same period of the area;
s2.2: converting all the obtained energy data into standard coal in a unified way according to carbon emission factors published by the ecological environment department, and then converting the standard coal into carbon emission;
s2.3: and carrying out accurate statistics and analysis on the generated carbon emission and the obtained output value data.
The scale-up enterprises refer to enterprises with more than scale, the national standards set the scale requirements of enterprises in different industries, and the enterprises with more than scale reach the standard by taking annual output as a measurement standard. The main energy sources comprise energy sources such as electricity and gas and the like without new energy sources, and the total output value of the production and operation of the enterprises on the scale is the sum of the output values of the enterprises on the scale in the area. The electricity consumption data comes from the electricity marketing system, and other energy consumption and output value data come from the statistical data of government related departments such as a bureau of departure and change, a bureau of credit, a tax bureau and the like. The energy is converted into standard coal according to various energy sources published by the ecological environment department, and then the standard coal is converted into carbon emission by the standard coal combustion and carbon dioxide coefficients.
Preferably, the method for calculating the carbon consumption index in step S3 includes:
the carbon consumption index is the carbon emission generated by the total energy consumption of the regular enterprises in a certain period of a certain area/the total output of the regular enterprises in the same period of the area.
The total energy consumption of the regular enterprises is the sum of main energy consumed by all the regular enterprises, and the statistical period can be quarterly, semi-annually or annually. The carbon consumption index is obtained by combining the carbon emission of an enterprise with the total production value, so that the energy consumption grade is judged, the energy consumption grade is judged only from the carbon emission, the consideration is more comprehensive, and the obtained data is more reliable. And when the carbon consumption index is calculated, two digits after the decimal point are reserved according to a rounding principle.
Preferably, the step S4 is further expressed as:
s4.1: comparing the calculated carbon consumption index with the energy consumption evaluation index, and judging the energy consumption level of the carbon consumption index;
s4.2: and judging whether the energy consumption is abnormal or not according to the energy consumption grade judging standard.
The carbon consumption index is converted into a corresponding energy consumption grade, the judgment of the number is converted into a range, and whether the energy consumption is abnormal or not is judged more accurately.
Preferably, in step S4.2, the energy consumption level evaluation criterion is:
the energy consumption grade is less than or equal to 3, which indicates that the energy consumption is normal; an energy consumption level greater than 3 indicates an energy consumption anomaly.
The energy consumption level is less than or equal to 3, which indicates that the energy consumption is below the integral average energy consumption level of the region, and the energy consumption is in a normal state; more than 3 indicates higher energy consumption and belongs to an abnormal state. . Enterprises in the region with abnormal power-assisted energy consumption can save energy and reduce emission conveniently according to local conditions, and the efficiency is improved.
Preferably, the step S5 is further expressed as:
s5.1: analyzing the distribution conditions of the high-carbon-consumption industry and the new energy industry in the area to be detected according to the judged energy consumption level in the step 4;
s5.2: and adjusting the industrial structure in the area to be detected according to the industrial distribution condition obtained by analysis.
The relationship between the industrial situation and the energy consumption level is: the energy consumption level is less than 3, which means that the new energy industry is relatively centralized; the energy consumption level is equal to 3, which indicates that the distribution of the high-energy-consumption industry and the distribution of the new-energy industry are close to the average level of the region; the energy consumption grade is more than 3, which means that the high energy consumption industry is more concentrated. By combining the energy consumption level with the industrial distribution, the industrial structure in the test area can be judged according to the energy consumption level, and the influence of factors such as the industrial structure, the new energy utilization and the like on the carbon consumption is shown. And analyzing the industrial structure in the region according to the obtained energy consumption level, and being beneficial to adjusting the energy structure of enterprises in the region. For areas with high energy consumption and centralized industries, related energy supply units preferentially provide comprehensive energy service and professional technology transformation help, and government departments reward and support policies according to energy conservation and emission reduction of enterprises and upgrading performance.
Therefore, the invention has the following beneficial effects: 1. the obtained energy data are all converted into carbon emission, and whether the energy consumption is abnormal can be judged by only calculating one index, so that the cost is saved; 2. the carbon emission change of unit output value of each area is reflected by calculating the energy carbon consumption index; 3. the influence of factors such as industrial structure and new energy utilization on carbon consumption is shown by calculating the carbon consumption indexes of different areas.
Drawings
FIG. 1 is a flow chart of the operation of the present invention.
Detailed Description
The invention is described in further detail below with reference to the following detailed description and accompanying drawings:
in the embodiment shown in fig. 1, an energy consumption abnormality determination method based on a carbon consumption index can be seen, and the operation flow is as follows:
the first step is as follows: analyzing and comparing big data, and setting energy consumption evaluation index
Selecting a plurality of areas with outstanding industrial structures for measuring and calculating the carbon emission; and then comparing and analyzing the measurement results, and setting an evaluation index. The evaluation index divides the carbon consumption index into five grades to evaluate the energy consumption, and is specifically set as follows:
the carbon consumption index is less than or equal to 0.6, is grade 1, represents low energy consumption,
the carbon consumption index is more than 0.6 and less than or equal to 0.8, the grade is 2, which represents that the energy consumption is lower,
the carbon consumption index is more than 0.8 and less than or equal to 1.2, is grade 3, represents that the energy consumption is close to the average level of the region,
the carbon consumption index is more than 1.2 and less than or equal to 2, the grade is 4, which represents that the energy consumption is higher,
the carbon consumption index is more than or equal to 2 and is grade 5, which indicates high energy consumption.
The second step is that: acquiring energy data and output value data, and converting the acquired energy data into carbon emission
Collecting main energy data of production and operation of enterprises on a rule in a certain period of a region to be detected and a total output value of production and operation of the enterprises on the rule in the same period of the region, wherein the main energy comprises electricity, gas, oil and coal, and the total output value is the sum of the production and operation output values of all the enterprises on the rule in the region to be detected; then, according to carbon emission factors published by ecological environment departments, the obtained energy data are all uniformly converted into standard coal, and then the standard coal is converted into carbon emission; and carrying out accurate statistics and analysis on the generated carbon emission and the obtained output value data.
The example collects the total energy consumption (in standard coal) and total output value of enterprises in 2020 years on the rules of villages and towns in a certain county, and converts the total energy consumption into carbon emission, and the results are as follows:
the third step: calculating the energy carbon consumption index according to the carbon emission and the obtained output value data
By the formula:
carbon consumption index is carbon emission generated by total energy consumption of regular enterprises in a certain period in a certain area/total output of regular enterprises in the same period in the area
Calculating to obtain 2020 carbon consumption index of each village and town in the county:
the fourth step: comparing the obtained carbon consumption index with the evaluation index, and analyzing and judging whether the energy consumption is abnormal
Comparing the calculated carbon consumption index with the energy consumption evaluation index, and judging the energy consumption level of the carbon consumption index; and judging whether the energy consumption is abnormal or not according to the energy consumption grade judging standard. For levels 4 and 5 we consider the energy consumption abnormal.
In the embodiment, 11 towns in the county are investigated, wherein 7 regions are grade 1, and the energy consumption is low; 2 areas are grade 2, so that the energy consumption is low; one area is level 3, close to the area average; one area is level 4, the energy consumption is high, and the area belongs to an energy consumption abnormal state.
Fifthly, analyzing the distribution situation of the industry in the area according to the energy consumption situation
Analyzing the distribution conditions of the high-carbon-consumption industry and the new energy industry in the area to be detected according to the judged energy consumption level in the step 4; and adjusting the industrial structure in the area to be detected according to the industrial distribution condition obtained by analysis.
The energy consumption level is less than 3, which means that the new energy industry is relatively centralized; the energy consumption level is equal to 3, which indicates that the distribution of the high-energy-consumption industry and the distribution of the new-energy industry are close to the average level of the region; the energy consumption grade is more than 3, which means that the high energy consumption industry is more concentrated. For the region with the level of 4, the related energy supply units provide comprehensive energy services and professional technology improvement help, and government departments give preferential benefits and support according to actual policies, so that the energy-saving, consumption-reducing, quality-improving and efficiency-improving effects of enterprises are assisted. For the region with the grade of 5, related energy supply units preferentially provide comprehensive energy service and professional technology transformation assistance, and government departments reward and support policies according to energy conservation and emission reduction of enterprises and upgrading performance.
In the embodiment, the lowest carbon consumption index is in the town of Xiaopu, and the county new energy industry is centralized; the highest carbon consumption index is in the pinch town, 4.45 times of the pinch town, and is a high-carbon-consumption industrial distribution area. Energy supply units are required to provide comprehensive energy services and professional technology improvement help, government departments give preferential benefits and support according to actual policies, and enterprises are assisted in energy conservation, consumption reduction, quality improvement and efficiency improvement.
The above-described embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit of the invention as set forth in the claims.
Claims (9)
1. An energy consumption abnormity judgment method based on a carbon consumption index is characterized by comprising the following steps:
s1: analyzing and comparing big data, and setting an energy consumption evaluation index;
s2: acquiring energy data and output value data, and converting the acquired energy data into carbon emission;
s3: calculating an energy carbon consumption index according to the carbon emission and the obtained output value data;
s4: comparing the obtained carbon consumption index with the evaluation index, and analyzing and judging whether the energy consumption is abnormal or not;
s5: and analyzing the distribution of the industry in the region according to the energy consumption situation.
2. The method for determining abnormal energy consumption based on carbon consumption index as claimed in claim 1, wherein the step S1 is further represented as:
s1.1: selecting a plurality of areas with outstanding industrial structures for measuring and calculating the carbon emission;
s1.2: and comparing and analyzing the measurement results, and setting an evaluation index.
3. The method for determining abnormal energy consumption based on carbon consumption index according to claim 2, wherein in step S1.1, the carbon emission includes carbon emission generated by regional electricity, coal, oil and gas.
4. The method for judging the abnormal energy consumption based on the carbon consumption index as claimed in claim 2, wherein the evaluation indexes in the step S1.2 are specifically:
energy consumption is divided into five grades according to the carbon consumption index:
the carbon consumption index is less than or equal to 0.6, is grade 1 and represents low energy consumption;
the carbon consumption index is more than 0.6 and less than or equal to 0.8, the grade is 2, and the energy consumption is low;
the carbon consumption index is more than 0.8 and less than or equal to 1.2, the grade is 3, and the energy consumption is close to the average level of the region;
the carbon consumption index is more than 1.2 and less than or equal to 2, and is grade 4, which represents that the energy consumption is higher;
the carbon consumption index is more than or equal to 2 and is grade 5, which indicates high energy consumption.
5. The method as claimed in claim 1, wherein the step S2 further comprises:
s2.1: collecting main energy data of production and operation of enterprises on a rule in a certain period of an area to be detected and a total production and operation value of the enterprises on the rule in the same period of the area;
s2.2: converting all the obtained energy data into standard coal in a unified way according to carbon emission factors published by the ecological environment department, and then converting the standard coal into carbon emission;
s2.3: and carrying out accurate statistics and analysis on the generated carbon emission and the obtained output value data.
6. The method for judging the abnormal energy consumption based on the carbon consumption index as claimed in claim 1, wherein the method for calculating the carbon consumption index in the step S3 is as follows:
the carbon consumption index is the carbon emission generated by the total energy consumption of the regular enterprises in a certain period of the area to be measured/the total output of the regular enterprises in the same period of the area.
7. The method for determining abnormal energy consumption based on carbon consumption index as claimed in claim 1, wherein the step S4 is further represented as:
s4.1: comparing the calculated carbon consumption index with the energy consumption evaluation index, and judging the energy consumption level of the carbon consumption index;
s4.2: and judging whether the energy consumption is abnormal or not according to the energy consumption grade judging standard.
8. The method according to claim 7, wherein in the step S4.2, the energy consumption level criterion is:
the energy consumption grade is less than or equal to 3, which indicates that the energy consumption is normal; an energy consumption level greater than 3 indicates an energy consumption anomaly.
9. The method for determining abnormal energy consumption based on carbon consumption index as claimed in claim 1, wherein the step S5 is further represented as:
s5.1: analyzing the distribution conditions of the high-carbon-consumption industry and the new energy industry in the area to be detected according to the judged energy consumption level in the step 4;
s5.2: and adjusting the industrial structure in the area to be detected according to the industrial distribution condition obtained by analysis.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110334633.6A CN113177686A (en) | 2021-03-29 | 2021-03-29 | Energy consumption abnormity judgment method based on carbon consumption index |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110334633.6A CN113177686A (en) | 2021-03-29 | 2021-03-29 | Energy consumption abnormity judgment method based on carbon consumption index |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113177686A true CN113177686A (en) | 2021-07-27 |
Family
ID=76922506
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110334633.6A Pending CN113177686A (en) | 2021-03-29 | 2021-03-29 | Energy consumption abnormity judgment method based on carbon consumption index |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113177686A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114154871A (en) * | 2021-12-02 | 2022-03-08 | 特斯联科技集团有限公司 | Building carbon emission analysis system based on big data processing |
| CN115982631A (en) * | 2023-03-20 | 2023-04-18 | 深圳市森辉智能自控技术有限公司 | Workshop energy application monitoring and early warning system based on data analysis |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102521714A (en) * | 2011-12-29 | 2012-06-27 | 国网信息通信有限公司 | Method and device for constructing KPI (key performance indicator) hierarchical model and energy consumption assessing method and system |
| CN105976105A (en) * | 2016-04-29 | 2016-09-28 | 广州绿石碳资产管理有限公司 | Method and device for managing carbon emission |
| CN109409637A (en) * | 2018-08-29 | 2019-03-01 | 国网江苏省电力有限公司苏州供电分公司 | A kind of urban energy data management and operational monitoring method |
| CN110084506A (en) * | 2019-04-23 | 2019-08-02 | 兰州环境能源交易中心有限公司 | Low-carbon analysis and assessment system |
-
2021
- 2021-03-29 CN CN202110334633.6A patent/CN113177686A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102521714A (en) * | 2011-12-29 | 2012-06-27 | 国网信息通信有限公司 | Method and device for constructing KPI (key performance indicator) hierarchical model and energy consumption assessing method and system |
| CN105976105A (en) * | 2016-04-29 | 2016-09-28 | 广州绿石碳资产管理有限公司 | Method and device for managing carbon emission |
| CN109409637A (en) * | 2018-08-29 | 2019-03-01 | 国网江苏省电力有限公司苏州供电分公司 | A kind of urban energy data management and operational monitoring method |
| CN110084506A (en) * | 2019-04-23 | 2019-08-02 | 兰州环境能源交易中心有限公司 | Low-carbon analysis and assessment system |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114154871A (en) * | 2021-12-02 | 2022-03-08 | 特斯联科技集团有限公司 | Building carbon emission analysis system based on big data processing |
| CN115982631A (en) * | 2023-03-20 | 2023-04-18 | 深圳市森辉智能自控技术有限公司 | Workshop energy application monitoring and early warning system based on data analysis |
| CN115982631B (en) * | 2023-03-20 | 2023-07-25 | 深圳市森辉智能自控技术有限公司 | Workshop energy application monitoring and early warning system based on data analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lindman et al. | Wind power learning rates: A conceptual review and meta-analysis | |
| CN113592134B (en) | Electric power carbon emission evaluation system and method based on energy data | |
| CN113177686A (en) | Energy consumption abnormity judgment method based on carbon consumption index | |
| Sabia et al. | Energy saving in wastewater treatment plants: A methodology based on common key performance indicators for the evaluation of plant energy performance, classification and benchmarking | |
| CN116128167B (en) | Distributed photovoltaic power generation analysis method based on cloud computing real-time monitoring | |
| CN116341988B (en) | Urban energy carbon emission monitoring system based on double-carbon targets | |
| CN114240086A (en) | Carbon emission monitoring method and device, storage medium and processor | |
| CN115600798A (en) | Urban intelligent energy management method based on double-carbon platform | |
| CN116362584A (en) | Economic analysis method based on user side energy storage capacity configuration | |
| CN112132481A (en) | Comprehensive evaluation method for regional energy efficiency | |
| CN116739368A (en) | Industrial park carbon emission level monitoring and evaluating method based on energy big data | |
| Dong et al. | Improving the accuracy of wind speed statistical analysis and wind energy utilization in the Ningxia Autonomous Region, China | |
| CN114879619A (en) | Digital workshop energy optimization method and system | |
| CN116542430B (en) | Multi-dimensional water carbon emission intelligent analysis method and system | |
| CN116596196A (en) | Carbon emission checking method and system | |
| CN116433440A (en) | Data autoregressive enhanced carbon emission measuring and calculating method, system and electronic equipment | |
| Ionescu et al. | Energy effectiveness-new energy performance indicator to optimize the industrial energy consumptions | |
| CN115511230A (en) | Electric energy substitution potential analysis and prediction method | |
| CN114662563A (en) | Industrial electricity non-invasive load decomposition method based on gradient lifting algorithm | |
| CN113642778A (en) | Power demand prediction framework considering multiple dimensions and multiple factors | |
| CN111178671A (en) | Comprehensive energy system energy efficiency improving method based on multi-energy detection parameters | |
| CN112288285B (en) | Photovoltaic power station string attenuation rate evaluation method based on generalized extreme value distribution | |
| Raza et al. | Analysis of Sectoral Energy Demand in Pakistan | |
| CN111429041B (en) | Cross-border renewable resource life cycle energy consumption assessment method | |
| Hannum | Effect of natural gas prices on renewable portfolio standard impacts |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210727 |
|
| RJ01 | Rejection of invention patent application after publication |