CN109409637A - A kind of urban energy data management and operational monitoring method - Google Patents
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Abstract
A kind of pair of urban energy data are managed the method with monitoring.It includes excavating to urban energy data, establishes urban energy data hierarchy administrative model；By choosing evaluation index, application level analytic approach establishes metrics evaluation model.Effect of the present invention: complete multi-energy data management system can be constructed, and its function can be increased in application layer according to the needs of energy sector than more fully excavating multi-energy data type.In turn, to build international energy model city as target, the Quantization Index System that can objectively evaluate urban energy state of development is provided, is changed for urban energy and reasonable planning proposal is provided.
Description
Technical field
The invention belongs to energy big data applied technical fields, more particularly to a kind of urban energy data management and operation
Monitoring method.
Background technique
It is proposed in " international energy, which is changed, develops model city " target, China urban energy, which is changed, gradually deeply to push away
Into this puts forward new requirements multi-energy data management and operational monitoring system.Existing multi-energy data management and operational monitoring
System cannot be considered in terms of various multi-energy datas, only investigate energy development level in the industry mostly, obtained data result cannot
Comprehensively and objectively reflect city entirety energy development situation, in addition, choose evaluation index when, still concentrate concern energy supply can
By property, the problems such as energy scale, Energy Intensity, it is not able to satisfy the new need of energy revolution " innovation, green, efficient, open, shared "
It asks.Therefore, it is necessary to innovate multi-energy data management system and multi-energy data appraisement system, but still lack effective method at present.
Summary of the invention
To solve the above-mentioned problems, the purpose of the present invention is to provide a kind of urban energy data managements and operational monitoring side
Method.
In order to achieve the above object, urban energy data management provided by the invention and operational monitoring method include in order
The following steps of progress:
Step 1) is changed according to international energy and develops model's city requirement, and urban energy data run monitoring system is established,
Including multi-energy data management system and multi-energy data appraisement system: the multi-energy data management system includes data acquisition module
Block, data memory module and data application module；Wherein data acquisition module is for acquiring urban energy data；Data store mould
Block carries out classification storage to the urban energy data that data acquisition module uploads；Data application module is according to energy enterprise or political affairs
Mansion department application demand calls urban energy data from data memory module, and carries out analytical calculation, for urban energy
Development level is changed to be evaluated；Multi-energy data appraisement system specifically includes following 4 sub-indicators: a supply cleans level
Index, the horizontal index of b consumer electricalization, c service the horizontal index of wisdomization, and d utilizes efficient horizontal index；
Step 2), to each sub-indicator is analyzed in multi-energy data appraisement system in step 1), determine it is each subitem refer to
Target core index；
The meaning of the core index of each sub-indicator in step 3), foundation step 2), from multi-energy data management system
Required multi-energy data is transferred in data memory module；Multi-energy data includes urban and rural residents year domestic load, the whole society year
Electricity consumption total amount, energy services platform share rate, intelligent electric meter coverage rate, year energy consumption total amount, year clean energy resource consumption figure, titanium dioxide
Total carbon emission, city's GDP total amount, city year power consumption total amount and final energy consumption total amount；
Step 4) evaluates energy revolution development level with the multi-energy data transferred according to above-mentioned core index, really
Make energy revolution development index.
In step 1), the data of the data collecting module collected include energy class data and social economy's class number
According to energy class data specifically include: a electric power data, b coal data, c fuel data, d Natural gas data；Social economy's class number
According to specifically including: a society data, b economic data, c policies and regulations data.
It is described to each sub-indicator is analyzed in multi-energy data appraisement system in step 1) in step 2), it determines
The step of core index of each sub-indicator, is as follows:
Step 2.1), which is listed, can reflect that energy supply cleans horizontal index, and by expert estimation, it is highest to choose score
Two as reflection energy supply clean horizontal core index；Core index specifically includes: clean energy resource consumption figure accounts for energy
Source consumption proportion, per GDP CO2 emissions；
Step 2.2), which is listed, can reflect that it is highest to choose score by expert estimation for the electrified horizontal index of energy-consuming
Two as the electrified horizontal core index of reflection energy-consuming；Core index specifically includes: electric energy accounts for final energy consumption
Ratio, living standard of urban and rural population electricity consumption account for power consumption specific gravity；
Step 2.3) lists the index that can reflect energy services wisdomization level, and by expert estimation, it is highest to choose score
Two core index as reflection energy services wisdomization level；Core index specifically includes: energy services platform shares rate,
Intelligent electric meter coverage rate；
Step 2.4), which is listed, can reflect that it is highest to choose score by expert estimation for the efficient horizontal index of energy source configuration
Two as the efficient horizontal core index of reflection energy source configuration；Core index specifically includes: per Unit GDP Energy Consumption, per GDP
Power consumption.
In step 4), it is described according to above-mentioned core index and the multi-energy data transferred to energy revolution development level into
The step of row is evaluated, and determines energy revolution development index is as follows:
Step 4.1) determines the power of each sub-indicator and each core index in step 2) in step 1) using analytic hierarchy process (AHP)
Weight, steps are as follows:
4.1a, all core index are compared to each other two-by-two, are obtained for the relatively important of a certain sub-indicator of upper level
Property, using 1-9 scaling law development of judgment matrix B；
4.1b: Mode of Level Simple Sequence and consistency check are carried out to judgment matrix
Mode of Level Simple Sequence can be attributed to the characteristic root and feature vector problem for calculating judgment matrix, i.e., to judgment matrix B, meter
Calculation meets BW=λmaxThe Maximum characteristic root λ of WmaxAnd characteristic vector W, and the component w of characteristic vector WiIt is i-th of sub-indicator
Relative weighting；For test and judge matrix consistency, need to calculate coincident indicator CI=(λmax- n)/(n-1), n is judgement
Order of matrix number, judgment matrix has crash consistency when coincident indicator CI=0, and coincident indicator CI is bigger, and consistency is got over
Difference；In order to which whether test and judge matrix has good uniformity, need coincident indicator CI and Aver-age Random Consistency Index
RI is compared, and is denoted as CR=CI/RI, and as CR < 0.1, judgment matrix has good uniformity, otherwise will be to judging square
Battle array is adjusted；
4.1c calculates core index relative weighting
The relative weighting of calculated each sub-indicator in 4.1b are as follows:
In formulaIt representsThe relative weighting of corresponding x-th of sub-indicator, x=1,2,3,4；
The corresponding core index of each sub-indicator is respectively relative to the relative weighting of same sub-indicator:
In formula,It representsIt indicates in xth item sub-indicator i-th
Relative weighting of the core index relative to same sub-indicator, x=1,2,3,4, i=1,2；
Then relative weighting of each core index relative to other all core index are as follows:
In formula, wxiIt is corresponding i-th of the core index of xth item sub-indicator relative to the opposite of other all core index
Weight, x=1,2,3,4, i=1,2；
Step 4.2) is according to energy revolution demand for development, from selecting step 2 in the multi-energy data that step 3) is transferred) in the energy
The reference value of each core index of sub-indicator in data evaluation system, is then normalized reference value:
When core index data are the bigger the better,
When core index data are the smaller the better,
SiIt is the reference value of some core index；BiIt is the current value of some core index, Min is the selected city core
Minimum value in index is divided by 1.05；Max is maximum value in the core index of selected city multiplied by 1.05, when selected city
When being one, it divided by 1.05, Max is its own multiplied by 1.05 that Min, which is its own,；
Value in relative weighting and step 4.2) in step 4.3) foundation step 4.1) after each core index normalization adds
Power calculates each sub-indicator development level, and referred to as energy revolution subitem development index, calculation formula is as follows:
Wherein, AxFor xth item energy revolution subitem development index；BxiIt is in step 4.2) i-th in xth item sub-indicator
Value after core index normalization；wxiIt is the weight of the core index；The item for the core index that m is included for the sub-indicator
Number, takes m=2, x=1,2 herein, and 3,4, i=1,2；
Step 4.4) according to energy revolution each in step 4.3) itemize development index weighted calculation energy revolution development index,
Aggregate level is changed for describing urban energy, calculation formula is as follows:
Wherein: DI is energy revolution development index, AxIt is xth item energy revolution subitem development index in step 4.3)；
It is the relative weighting of xth item sub-indicator；U is the total item of the sub-indicator, here, u=4, x=1,2,3,4.
Urban energy data management provided by the invention and operational monitoring method have the following beneficial effects: can compared with it is complete
Multi-energy data type is excavated to face, constructs complete multi-energy data management system, and can exist according to the needs of energy sector
Application layer increases its function.In turn, to build international energy model city as target, urban energy development can be objectively evaluated by providing
The Quantization Index System of situation is changed for urban energy and provides reasonable planning proposal.
Detailed description of the invention
Fig. 1 is urban energy data management provided by the invention and operational monitoring method flow diagram.
Fig. 2 is multi-energy data schematic diagram of management system structure provided by the invention.
Fig. 3 is 2013-2016 Nian Mou city's energy revolution subitem development index situation of change.
Fig. 4 is the city 2013-2016 Nian Mou energy revolution development index situation of change.
Specific embodiment
In the following with reference to the drawings and specific embodiments to urban energy data management provided by the invention and operational monitoring method
It is described in detail.
As shown in Figure 1, urban energy data management provided by the invention and operational monitoring method include carrying out in order
The following steps:
Step 1) is changed according to international energy and develops model's city requirement, and urban energy data run monitoring system is established,
Including multi-energy data management system and multi-energy data appraisement system: the international energy change development model city, which refers to, to be met
The new city of " innovation is coordinated, is green, open, shared " idea of development, it is desirable that energy-consuming clean and effective, energy management are flat
Platform is intelligently open.The multi-energy data management system includes data acquisition module, data memory module and data application module；
Wherein data acquisition module is for acquiring urban energy data, and according to multi-energy data source difference, the data of acquisition include the energy
Class data and social economy's class data, energy class data specifically include: a electric power data, b coal data, c fuel data, d are natural
Destiny evidence；Social economy's class data specifically include: a society data, b economic data, c policies and regulations data；Data memory module
Classification storage is carried out to the urban energy data that data acquisition module uploads；Data application module is according to energy enterprise or government
Department's application demand calls urban energy data from data memory module, and carries out analytical calculation, for becoming to urban energy
Leather development level is evaluated；Multi-energy data appraisement system specifically includes following 4 sub-indicators: a supply cleans level and refers to
Mark, the horizontal index of b consumer electricalization, c service the horizontal index of wisdomization, and d utilizes efficient horizontal index；
Step 2), to each sub-indicator is analyzed in multi-energy data appraisement system in step 1), determine it is each subitem refer to
Target core index；
The meaning of the core index of each sub-indicator in step 3), foundation step 2), from multi-energy data management system
Required multi-energy data is transferred in data memory module；It is changed towards international energy and develops model city demand, need to transfer
Multi-energy data include that urban and rural residents' year domestic load, the whole society year electricity consumption total amount, energy services platform share rate, intelligence electricity
Table coverage rate, year energy consumption total amount, year clean energy resource consumption figure, CO2 emission total amount, city's GDP total amount, city year power consumption
Total amount and final energy consumption total amount, for calculating core index value；
Step 4) evaluates energy revolution development level with the multi-energy data transferred according to above-mentioned core index, really
Make energy revolution development index.
It is described to each sub-indicator is analyzed in multi-energy data appraisement system in step 1) in step 2), it determines
The step of core index of each sub-indicator, is as follows:
Step 2.1), which is listed, can reflect that energy supply cleans horizontal index, and by expert estimation, it is highest to choose score
Two as reflection energy supply clean horizontal core index；In the present invention, core index specifically includes: clean energy resource
Consumption figure accounts for energy-consuming ratio, per GDP CO2 emissions；
Step 2.2), which is listed, can reflect that it is highest to choose score by expert estimation for the electrified horizontal index of energy-consuming
Two as the electrified horizontal core index of reflection energy-consuming；In the present invention, core index specifically includes: electric energy accounts for end
Energy-consuming ratio is held, living standard of urban and rural population electricity consumption accounts for power consumption specific gravity；
Step 2.3) lists the index that can reflect energy services wisdomization level, and by expert estimation, it is highest to choose score
Two core index as reflection energy services wisdomization level；In the present invention, core index specifically includes: energy services
Platform shares rate, intelligent electric meter coverage rate；
Step 2.4), which is listed, can reflect that it is highest to choose score by expert estimation for the efficient horizontal index of energy source configuration
Two as the efficient horizontal core index of reflection energy source configuration；In the present invention, core index specifically includes: per GDP
Energy consumption, per GDP power consumption；
In step 4), it is described according to above-mentioned core index and the multi-energy data transferred to energy revolution development level into
The step of row is evaluated, and determines energy revolution development index is as follows:
Step 4.1) determines the power of each sub-indicator and each core index in step 2) in step 1) using analytic hierarchy process (AHP)
Weight, steps are as follows:
4.1a, all core index are compared to each other two-by-two, are obtained for the relatively important of a certain sub-indicator of upper level
Property, using 1-9 scaling law development of judgment matrix B.Wherein, the meaning of 1-9 scale is as shown in table 1:
1 judgment matrix scale of table
| Scale | Scale is explained |
| 1 | aiAnd ajIt is of equal importance |
| 3 | aiCompare ajIt slightly shows important |
| 5 | aiCompare ajIt is obvious important |
| 7 | aiCompare ajIt is extremely important |
| 9 | aiCompare ajIt is of crucial importance |
| 2,4,6,8 | The median of above-mentioned judgment criteria |
| aji=1/aij | aiCompare ajInessential degree |
4.1b: Mode of Level Simple Sequence and consistency check are carried out to judgment matrix
Mode of Level Simple Sequence refers to associated with it according to the grade for judgment matrix calculating index a certain for upper level
The weight of each index importance order.Mode of Level Simple Sequence can be attributed to the characteristic root and feature vector problem for calculating judgment matrix,
I.e. to judgment matrix B, calculating meets BW=λmaxThe Maximum characteristic root λ of WmaxAnd characteristic vector W, and the component w of characteristic vector Wi
It is the relative weighting of i-th of sub-indicator.For test and judge matrix consistency, need to calculate coincident indicator CI=
(λmax- n)/(n-1), n is the order of judgment matrix, and judgment matrix has crash consistency when coincident indicator CI=0, unanimously
Property index CI is bigger, and consistency is poorer.In order to which whether test and judge matrix has good uniformity, need coincident indicator CI
It is compared with Aver-age Random Consistency Index RI, is denoted as CR=CI/RI, as CR < 0.1, judgment matrix has good consistent
Property, otherwise judgment matrix will be adjusted.The Aver-age Random Consistency Index RI of 1-9 rank judgment matrix is as shown in table 2:
The Aver-age Random Consistency Index RI of 2 1-9 rank judgment matrix of table
| Order | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| RI | 0 | 0 | 0.58 | 0.9 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 |
4.1c calculates core index relative weighting
(supply cleans horizontal index to calculated each sub-indicator, and the horizontal index of consumer electricalization services intelligence in 4.1b
The horizontal index of intelligentization utilizes efficient horizontal index) relative weighting are as follows:
In formulaIt representsThe relative weighting of corresponding x-th of sub-indicator, x=1,2,3,4.
The corresponding core index of each sub-indicator is respectively relative to the relative weighting of same sub-indicator:
In formula,It representsIt indicates in xth item sub-indicator i-th
Relative weighting of the core index relative to same sub-indicator, x=1,2,3,4, i=1,2.
Then relative weighting of each core index relative to other all core index are as follows:
In formula, wxiIt is corresponding i-th of the core index of xth item sub-indicator relative to the opposite of other all core index
Weight, x=1,2,3,4, i=1,2.
Step 4.2) is according to energy revolution demand for development, from selecting step 2 in the multi-energy data that step 3) is transferred) in the energy
The reference value of each core index of sub-indicator in data evaluation system.Specifically, reference value reflects the core index
The higher level at home and abroad reached, is then normalized reference value:
When core index data are the bigger the better,
When core index data are the smaller the better,
SiIt is the reference value of some core index；BiIt is the current value of some core index, Min is the selected city core
Minimum value in index is divided by 1.05；Max be maximum value in the core index of selected city multiplied by 1.05 (when selected city
When being one, it divided by 1.05, Max is its own multiplied by 1.05) that Min, which is its own,.
Value in relative weighting and step 4.2) in step 4.3) foundation step 4.1) after each core index normalization adds
Power calculates each sub-indicator development level, and referred to as energy revolution subitem development index, calculation formula is as follows:
Wherein, AxFor xth item energy revolution subitem development index；BxiIt is in step 4.2) i-th in xth item sub-indicator
Value after core index normalization；wxiIt is the weight of the core index；The item for the core index that m is included for the sub-indicator
Number, takes m=2, x=1,2 herein, and 3,4, i=1,2.
Step 4.4) according to energy revolution each in step 4.3) itemize development index weighted calculation energy revolution development index,
Aggregate level is changed for describing urban energy, calculation formula is as follows:
Wherein: DI is energy revolution development index, AxIt is xth item energy revolution subitem development index in step 4.3)；
It is the relative weighting of xth item sub-indicator；U is the total item of the sub-indicator, here, u=4, x=1,2,3,4.
Specific embodiment
Below with reference to example, the present invention is described in further detail.
2013-2016 energy revolution development in certain city is analyzed using the method for the present invention.
Step 1) establishes multi-energy data operational monitoring system, which includes: comprising data acquisition module, data storage mould
The multi-energy data management system of block and data application module, investigate energy supply clean horizontal, energy-consuming it is electrified it is horizontal,
Energy services wisdom level and the efficient horizontal multi-energy data appraisement system of energy source configuration.
Step 2) determines the core index of each sub-indicator
Step 2.1), which is listed, can reflect that energy supply cleans horizontal index, by expert estimation, choose highest scoring
Two as reflection energy supply clean horizontal core index, as shown in table 3.
3 energy supply of table cleans horizontal index marking result
As shown in Table 3, which includes: that clean energy resource consumption figure accounts for energy-consuming ratio, per GDP carbon dioxide
Discharge amount.Specifically:
Clean energy resource consumption figure accounts for energy-consuming ratio=year clean energy resource consumption figure/, and consume energy in year total amount
Per GDP CO2 emissions=CO2 emission total amount/city's GDP total amount
Step 2.2), which is listed, can reflect that it is highest to choose score by expert estimation for the electrified horizontal index of energy-consuming
Two core index as the electrified level of reflection energy-consuming, as shown in table 4.
The electrified horizontal index marking result of 4 energy-consuming of table
As shown in Table 4, which includes: that electric energy accounts for final energy consumption ratio, and living standard of urban and rural population electricity consumption accounts for electricity
Specific gravity can be consumed.
Specifically:
Electric energy accounts for final energy consumption ratio=city year power consumption total amount/final energy consumption total amount
Living standard of urban and rural population electricity consumption accounts for the power consumption specific gravity=urban and rural residents year domestic load/whole society year electricity consumption total amount
Step 2.3) lists the index that can reflect energy services wisdomization level, and by expert estimation, it is highest to choose score
Two core index as reflection energy services wisdomization level, as shown in table 5.
The horizontal index marking result of 5 energy services wisdomization of table
As shown in Table 5, which includes: that energy services platform shares rate, intelligent electric meter coverage rate, the two indexs
Electric power enterprise can be inquired or relevant departments' data obtain.
Step 2.4), which is listed, can reflect that it is highest to choose score by expert estimation for the efficient horizontal index of energy source configuration
Two core index as the efficient level of reflection energy source configuration, as shown in table 6.
The efficient horizontal index marking result of 6 energy source configuration of table
As shown in Table 6, which includes: per Unit GDP Energy Consumption, per GDP power consumption.
Specifically:
Per Unit GDP Energy Consumption=final energy consumption total amount/city's GDP total amount
Per GDP power consumption=city year power consumption total amount/city's GDP total amount
Meaning of the step 3) according to the corresponding core index of sub-indicator each in multi-energy data appraisement system in step 2), from
Required data, including urban and rural residents year domestic load are transferred in the data memory module of multi-energy data management system, entirely
Social year electricity consumption total amount, energy services platform share rate, intelligent electric meter coverage rate, and consume energy in year total amount, year clean energy resource consumption figure,
CO2 emission total amount, city's GDP total amount, city year power consumption total amount, final energy consumption total amount, for calculating core index
Value.
Step 4) evaluates energy revolution development level with the multi-energy data transferred according to evaluation index, determines the energy
The step of changing development index is as follows:
Step 4.1) determines step 1) and each index in multi-energy data appraisement system in step 2) using analytic hierarchy process (AHP)
Weight.Weights are as shown in table 7.
The weight of each index in 7 multi-energy data appraisement system of table
Step 4.2) is according to energy revolution demand for development, from selecting step 2 in the multi-energy data transferred in step 3)) in energy
The reference value of each core index of sub-indicator in source data appraisement system, as shown in table 8.
8 core index reference value of table
Then reference value is normalized, obtains data after each core index normalization of certain city 2013-2016,
As shown in table 9.
Each core index normalization data of certain city of table 9 2013-2016
Step 4.3) evaluates each sub-indicator development level: adding according to the value after core index normalization each in step 4.2)
Power calculates each sub-indicator development level, referred to as energy revolution subitem development index.Fig. 3 is that 2013-2016 Nian Mou city's energy becomes
Leather subitem development index situation of change.
As can be seen that 2013-2016 energy services wisdom level in the city is continuously improved, energy supply cleans water
It is flat basicly stable with the electrified horizontal holding of energy-consuming, but the efficient level of energy source configuration is due to per Unit GDP Energy Consumption and unit
GDP power consumption is continuously improved and declines, so the city should put forth effort to improve the efficient level of energy source configuration.
Step 4.4) evaluates urban energy and changes overall development level, calculates energy revolution development index.Fig. 4 is 2013-
2016 city Nian Mou energy revolution development index situations of change.
Constantly rise as can be seen that development index is changed in the urban energy, illustrates that urban energy development level is constantly mentioning
It is high.
The above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, although referring to examples detailed above to this
Invention is described in detail, and those of ordinary skill in the art can still carry out a specific embodiment of the invention
Modification perhaps equivalent replacement these without departing from any modification of spirit and scope of the invention or equivalent replacement, application to
Within the claims of the invention criticized.
The method provided by the invention urban energy data being managed with monitoring, with urban energy data management system
Based on, by selection evaluation index, multi-energy data appraisement system is established, it can be than more fully excavating multi-energy data type.
The present invention can increase its function in application layer according to the needs of energy sector.The present invention is to build international energy model city
Target provides the Quantization Index System that can objectively evaluate urban energy state of development, changes for urban energy and provides reasonable rule
It draws and suggests.
Claims (4)
1. a kind of urban energy data management and operational monitoring method, it is characterised in that: the urban energy data management with
Operational monitoring method includes the following steps carried out in order:
Step 1) is changed according to international energy and develops model's city requirement, and urban energy data run monitoring system is established, including
Multi-energy data management system and multi-energy data appraisement system: the multi-energy data management system includes data acquisition module, number
According to memory module and data application module；Wherein data acquisition module is for acquiring urban energy data；Data memory module pair
The urban energy data that data acquisition module uploads carry out classification storage；Data application module is according to energy enterprise or portion, government
Door application demand calls urban energy data from data memory module, and carries out analytical calculation, for changing to urban energy
Development level is evaluated；Multi-energy data appraisement system specifically includes following 4 sub-indicators: a supply cleans horizontal index,
The horizontal index of b consumer electricalization, c service the horizontal index of wisdomization, and d utilizes efficient horizontal index；
Step 2), to each sub-indicator is analyzed in multi-energy data appraisement system in step 1), determine each sub-indicator
Core index；
The meaning of the core index of each sub-indicator in step 3), foundation step 2), from the data of multi-energy data management system
Required multi-energy data is transferred in memory module；Multi-energy data includes urban and rural residents year domestic load, the whole society year electricity consumption
Total amount, energy services platform share rate, intelligent electric meter coverage rate, year energy consumption total amount, year clean energy resource consumption figure, carbon dioxide row
Put total amount, city's GDP total amount, city year power consumption total amount and final energy consumption total amount；
Step 4) evaluates energy revolution development level with the multi-energy data transferred according to above-mentioned core index, determines
Energy revolution development index.
2. urban energy data management according to claim 1 and operational monitoring method, it is characterised in that: in step 1)
In, the data of the data collecting module collected include energy class data and social economy's class data, and energy class data are specific
It include: a electric power data, b coal data, c fuel data, d Natural gas data；Social economy's class data specifically include: a society number
According to, b economic data, c policies and regulations data.
3. urban energy data management according to claim 1 and operational monitoring method, it is characterised in that: in step 2)
In, it is described to each sub-indicator is analyzed in multi-energy data appraisement system in step 1), determine the core of each sub-indicator
The step of heart index, is as follows:
Step 2.1), which is listed, can reflect that energy supply cleans horizontal index, by expert estimation, choose score highest two
Horizontal core index is cleaned as reflection energy supply；Core index specifically includes: clean energy resource consumption figure accounts for the energy and disappears
Take ratio, per GDP CO2 emissions；
Step 2.2), which is listed, can reflect that the electrified horizontal index of energy-consuming chooses score highest two by expert estimation
As the electrified horizontal core index of reflection energy-consuming；Core index specifically includes: electric energy accounts for final energy consumption ratio,
Living standard of urban and rural population electricity consumption accounts for power consumption specific gravity；
Step 2.3) lists the index that can reflect energy services wisdomization level, by expert estimation, chooses score highest two
Core index as reflection energy services wisdomization level；Core index specifically includes: energy services platform shares rate, intelligence
Ammeter coverage rate；
Step 2.4), which is listed, can reflect that the efficient horizontal index of energy source configuration chooses score highest two by expert estimation
As the efficient horizontal core index of reflection energy source configuration；Core index specifically includes: per Unit GDP Energy Consumption, per GDP electricity
Consumption.
4. urban energy data management according to claim 1 and operational monitoring method, it is characterised in that: in step 4)
In, it is described that energy revolution development level is evaluated with the multi-energy data transferred according to above-mentioned core index, determine energy
It is as follows that the step of development index, is changed in source:
Step 4.1) determines the weight of each sub-indicator and each core index in step 2) in step 1), step using analytic hierarchy process (AHP)
It is rapid as follows:
4.1a, all core index are compared to each other two-by-two, obtain for the relative importance of a certain sub-indicator of upper level, adopts
With 1-9 scaling law development of judgment matrix B；
4.1b: Mode of Level Simple Sequence and consistency check are carried out to judgment matrix
Mode of Level Simple Sequence can be attributed to the characteristic root and feature vector problem for calculating judgment matrix, i.e., to judgment matrix B, calculate full
Sufficient BW=λmaxThe Maximum characteristic root λ of WmaxAnd characteristic vector W, and the component w of characteristic vector WiIt is the phase of i-th of sub-indicator
To weight；For test and judge matrix consistency, need to calculate coincident indicator CI=(λmax- n)/(n-1), n is judgment matrix
Order, judgment matrix has crash consistency when coincident indicator CI=0, and coincident indicator CI is bigger, and consistency is poorer；For
Whether test and judge matrix has good uniformity, needs to carry out coincident indicator CI and Aver-age Random Consistency Index RI
Compare, be denoted as CR=CI/RI, as CR < 0.1, judgment matrix has good uniformity, otherwise will carry out to judgment matrix
Adjustment；
4.1c calculates core index relative weighting
The relative weighting of calculated each sub-indicator in 4.1b are as follows:
In formulaIt representsThe relative weighting of corresponding x-th of sub-indicator, x=1,2,3,4；
The corresponding core index of each sub-indicator is respectively relative to the relative weighting of same sub-indicator:
In formula,It representsIndicate i-th of core in xth item sub-indicator
Relative weighting of the index relative to same sub-indicator, x=1,2,3,4, i=1,2；
Then relative weighting of each core index relative to other all core index are as follows:
In formula, wxiIt is opposite power of corresponding i-th of the core index of xth item sub-indicator relative to other all core index
Weight, x=1,2,3,4, i=1,2；
Step 4.2) is according to energy revolution demand for development, from selecting step 2 in the multi-energy data that step 3) is transferred) in multi-energy data
The reference value of each core index of sub-indicator in appraisement system, is then normalized reference value:
When core index data are the bigger the better,
When core index data are the smaller the better,
SiIt is the reference value of some core index；BiIt is the current value of some core index, Min is the selected city core index
In minimum value divided by 1.05；Max is maximum value in the core index of selected city multiplied by 1.05, when selected city is one
When a, it divided by 1.05, Max is its own multiplied by 1.05 that Min, which is its own,；
Value in relative weighting and step 4.2) in step 4.3) foundation step 4.1) after each core index normalization weights meter
Each sub-indicator development level is calculated, referred to as energy revolution subitem development index, calculation formula is as follows:
Wherein, AxFor xth item energy revolution subitem development index；BxiIt is i-th core in xth item sub-indicator in step 4.2)
Value after index normalization；wxiIt is the weight of the core index；The item number for the core index that m is included for the sub-indicator,
This takes m=2, x=1,2, and 3,4, i=1,2；
Step 4.4) is used for according to energy revolution each in step 4.3) subitem development index weighted calculation energy revolution development index
It describes urban energy and changes aggregate level, calculation formula is as follows:
Wherein: DI is energy revolution development index, AxIt is xth item energy revolution subitem development index in step 4.3)；It is xth
The relative weighting of item sub-indicator；U is the total item of the sub-indicator, here, u=4, x=1,2,3,4.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111859045A (en) * | 2020-07-31 | 2020-10-30 | 生态环境部环境规划院 | Method and accounting system for rapidly accounting carbon dioxide emission of industries and industries |
| CN112580937A (en) * | 2020-11-30 | 2021-03-30 | 国网上海市电力公司 | Urban energy development monitoring method based on energy structure analysis |
| CN112884347A (en) * | 2021-03-11 | 2021-06-01 | 清华大学 | Urban energy balance management system and construction method thereof |
| CN113177686A (en) * | 2021-03-29 | 2021-07-27 | 国网浙江省电力有限公司湖州供电公司 | Energy consumption abnormity judgment method based on carbon consumption index |
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2018
- 2018-08-29 CN CN201810994457.7A patent/CN109409637A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111859045A (en) * | 2020-07-31 | 2020-10-30 | 生态环境部环境规划院 | Method and accounting system for rapidly accounting carbon dioxide emission of industries and industries |
| CN112580937A (en) * | 2020-11-30 | 2021-03-30 | 国网上海市电力公司 | Urban energy development monitoring method based on energy structure analysis |
| CN112884347A (en) * | 2021-03-11 | 2021-06-01 | 清华大学 | Urban energy balance management system and construction method thereof |
| CN113177686A (en) * | 2021-03-29 | 2021-07-27 | 国网浙江省电力有限公司湖州供电公司 | Energy consumption abnormity judgment method based on carbon consumption index |
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