CN112365080A - Energy source resilience effect prediction method and computer readable storage medium - Google Patents

Energy source resilience effect prediction method and computer readable storage medium Download PDF

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CN112365080A
CN112365080A CN202011321840.XA CN202011321840A CN112365080A CN 112365080 A CN112365080 A CN 112365080A CN 202011321840 A CN202011321840 A CN 202011321840A CN 112365080 A CN112365080 A CN 112365080A
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energy
period
total
energy consumption
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李沛
陈晖�
陈政
王刚
何耿生
黄国日
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Energy Development Research Institute of China Southern Power Grid Co Ltd
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Energy Development Research Institute of China Southern Power Grid Co Ltd
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    • 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
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    • 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
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    • G06Q10/067—Enterprise or organisation modelling
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    • 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
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Abstract

The invention provides an energy rebound effect prediction method, which comprises the following steps: acquiring department labor force, department capital and department effective energy service; constructing a department economic total output model according to department labor force, department capital and department effective energy service; calculating a contribution value of the improvement of the energy efficiency of the department to the increase of the output according to the total economic output model of the department; multiplying and decomposing the energy consumption change according to an LMDI decomposition method to generate an energy consumption change factor; and calculating the energy resilience effect and the change trend thereof according to the contribution value of the department energy efficiency improvement on the output increase and the energy consumption change factor. The energy source resilience effect model based on the input-output table provided by the invention improves the characteristics that the existing model research is mostly concentrated in high energy consumption industries and lacks the transverse comparison among different industries of national economy and the longitudinal comparison and analysis in different periods, so as to provide reference for making an industry policy which is beneficial to industrial structure optimization and energy conservation and emission reduction.

Description

Energy source resilience effect prediction method and computer readable storage medium
Technical Field
The invention belongs to the technical field of information, and particularly relates to an energy rebound effect prediction method and a computer readable storage medium.
Background
The improvement of energy efficiency is the first energy-saving policy choice for dealing with the problem of energy safety because of having more cost advantage and economic benefit than the development of new energy. The improvement of energy efficiency in the economic development of China produces an energy rebound effect, which is widely accepted by the academic world, however, the following problems are strictly demonstrated by the fresh research: firstly, China improves energy efficiency, saves energy, enlarges economic scale due to substitution effect and income effect, generates new energy demand, and the energy rebound effect generated by the method is competitive with great magnitude, and the energy efficiency is improved to the end, so that the energy consumption is increased: and secondly, selecting an industry policy for saving energy and reducing consumption according to the energy rebound effect and the industry heterogeneity of comprehensive energy consumption.
Scholars at home and abroad make a great deal of research on the energy rebound effect. From the demonstration method, the existing methods for measuring and calculating the energy rebound effect mainly comprise three types: firstly, the energy rebound effect is calculated by simulating the influence of the improvement of the energy efficiency on the future overall economy and energy consumption through a general equilibrium model: secondly, the method is estimated through the metering relation between energy consumption and economic growth, and the method is commonly used for measuring and calculating the energy rebound effect at the national, regional or industrial level: thirdly, the influence of energy price change on a consumption structure is described through a demand system model, commodity cost reduction caused by improving energy efficiency and the influence of the commodity cost reduction on demand are analyzed, and the energy rebound effect generated by energy efficiency change is measured, but the three methods have less research on the energy rebound effect in a specific industry.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method for predicting an energy rebound effect, which is used for predicting the energy rebound effect in a specific industry.
One embodiment of the invention provides an energy rebound effect prediction method, which comprises the following steps:
acquiring department labor force in the first time, department capital in the first time and effective energy service of the department in the first time;
constructing a total department economic output model according to the department labor force in the first time, the department capital in the first time and the department effective energy service in the first time;
calculating a contribution value of the improvement of the energy efficiency of the department to the increase of the output according to the total economic output model of the department;
multiplying and decomposing the energy consumption change according to an LMDI decomposition method to generate an energy consumption change factor; wherein, the energy consumption variation factors include: economic scale factors, industrial structure factors and energy intensity factors;
and calculating the energy resilience effect and the change trend thereof according to the contribution value of the department energy efficiency improvement on the output increase and the energy consumption change factor.
Further, before constructing the department gross economic output model according to the department labor force in the first time, the department capital in the first time and the department efficient energy service in the first time, the method further comprises the following steps:
acquiring the energy use efficiency of departments in the first time and the energy physical quantity consumed by the departments in the first time;
and constructing a department effective energy service calculation model in the first time according to the department energy utilization efficiency in the first time and the department energy consumption physical quantity in the first time.
Further, the department effective energy service calculation model in the first time is as follows:
Ujt＝θjtEjt (1)
wherein, UjtFor efficient energy service during the period t, thetajtJ energy efficiency for the department of the period t, EjtIs the amount of energy substance consumed by department j during period t.
Further, the department economic total output model is:
Yjt＝f(Ljt,Kjt,Ujt)+εjt (2)
wherein, YjtIs the economic total output of department j in the period t, LjtLabor force for department j during period t, KjtCapital, U, for time t division jjtFor efficient energy service during the period t, epsilonjtF is a functional relationship for the error term.
Further, before calculating the contribution value of the department energy efficiency improvement to the yield increase according to the department economic total yield model, the method further comprises the following steps:
taking logarithm of the total economic output model of the department to obtain:
lnYjt＝αjtlnLjt+βjtlnKjt+γjt(lnθjt+lnEjt)+εjt (3)
and (3) carrying out derivation on the total economic output model of the department after logarithm taking to obtain:
Figure BDA0002793113040000031
wherein, YjtFor the total economic output of j in the t period, alphajtFor the flexibility of the output of department j to labor, LjtIs labor in time t department j, betajtElasticity of capital for yield of department j, KjtCapital, γ, for j in the t-period divisionjtFlexibility to serve the production of efficient energy for department j, θjtFor the department j of the period t, the energy use efficiency,Ejtthe amount of energy substance, epsilon, consumed by department j during the period tjtIs an error term.
Further, the method comprises the step of calculating a contribution value of the improvement of energy efficiency of the department to the increase of the yield according to the total economic yield model of the department, and calculating by the following formula:
Figure BDA0002793113040000032
wherein σjtContribution to yield increase for department j energy efficiency improvement, gammajtFlexibility to serve the production of efficient energy for department j, θjtJ energy efficiency, Y, for the department of the t periodjtIs the total economic output of the department j in the period t.
Further, the multiplicative decomposition of the energy consumption change according to the LMDI decomposition method to generate the energy consumption change factor includes:
decomposing the total energy consumption to obtain:
Figure BDA0002793113040000041
wherein E represents the total energy consumption of China; ejRepresenting department j energy consumption; y represents the total output of China; y isjRepresents department j yields; i represents the energy intensity of China; i isjRepresenting department j energy intensity; sjRepresents the proportion of department j output in total output;
obtaining various effects which cause energy consumption change according to the total energy consumption after decomposition:
Figure BDA0002793113040000042
wherein E istFor the total energy consumption of period t, EτFor the period tau total energy consumption, Dt,τAs a total effect of the overall energy consumption change,
Figure BDA0002793113040000043
in order to achieve the effect of economy of scale,
Figure BDA0002793113040000044
in order to have an industrial structural effect,
Figure BDA0002793113040000045
is an energy intensity effect.
Further, the method for predicting the energy rebound effect further comprises the following steps:
order to
Figure BDA0002793113040000046
For the expected energy saving amount caused by the increase of energy efficiency from t period to tau period of department j, i.e. the decrease of energy intensity,
Figure BDA0002793113040000047
the increase of energy consumption brought by the increase of the overall economic scale, namely the increase of output from the t period to the tau period of the department j,
Figure BDA0002793113040000048
for the increase of energy consumption caused by the increase of energy efficiency, i.e. the decrease of energy intensity, of department j from the period t to the period tau, then:
Figure BDA0002793113040000049
Figure BDA00027931130400000410
Figure BDA00027931130400000411
wherein the content of the first and second substances,
Figure BDA00027931130400000412
for the economic-scale effect of department j,
Figure BDA00027931130400000413
in order to be an energy intensity effect,
Figure BDA00027931130400000414
total energy consumption of department j time t, σjtAnd improving the energy efficiency of the department j to increase the contribution value of the output.
Further, the energy rebound effect is measured and calculated according to the contribution value of the department energy efficiency improvement on the output increase and the energy consumption variation factor, and the calculation is carried out through the following formula:
Figure BDA0002793113040000051
wherein the content of the first and second substances,
Figure BDA0002793113040000052
the energy rebound effect caused by the improvement of the energy efficiency of the department j from the period t to the period tau,
Figure BDA0002793113040000053
for the department j, the increase of energy consumption caused by the increase of energy efficiency from the t period to the tau period, namely the decrease of energy intensity,
Figure BDA0002793113040000054
for the expected energy saving amount caused by the increase of energy efficiency, i.e. the decrease of energy intensity, from the t period to the tau period of department j, σjtFor department j the contribution value of energy efficiency improvement to yield increase,
Figure BDA0002793113040000055
for the economic-scale effect of department j,
Figure BDA0002793113040000056
total energy consumption for time t of department j.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, where when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute any one of the energy rebound effect prediction methods.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
one embodiment of the invention provides an energy rebound effect prediction method, which comprises the following steps: acquiring department labor force in the first time, department capital in the first time and effective energy service of the department in the first time; constructing a total department economic output model according to the department labor force in the first time, the department capital in the first time and the department effective energy service in the first time; calculating a contribution value of the improvement of the energy efficiency of the department to the increase of the output according to the total economic output model of the department; multiplying and decomposing the energy consumption change according to an LMDI decomposition method to generate an energy consumption change factor; wherein, the energy consumption variation factors include: economic scale factors, industrial structure factors and energy intensity factors; and calculating the energy resilience effect and the change trend thereof according to the contribution value of the department energy efficiency improvement on the output increase and the energy consumption change factor. The energy source resilience effect model based on the input-output table provided by the invention improves the characteristics that the existing model research is mostly concentrated in high energy consumption industries and lacks the transverse comparison among different industries of national economy and the longitudinal comparison and analysis in different periods, so as to provide reference for making an industry policy which is beneficial to industrial structure optimization and energy conservation and emission reduction.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method for predicting energy rebound effect according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for predicting energy rebound according to another embodiment of the present invention;
FIG. 3 is a flowchart of a method for predicting energy rebound effect according to another embodiment of the present invention;
FIG. 4 is a flowchart illustrating a method for predicting energy rebound according to another embodiment of the present invention;
fig. 5 is a general block diagram of a method for constructing a supply and demand side response model of Guangdong province based on an energy technology model according to an embodiment of the present invention;
fig. 6 is a block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
A first aspect.
Referring to fig. 1-4, an embodiment of the invention provides a method for predicting an energy rebound effect, including:
and S10, acquiring department labor force in the first time, department capital in the first time and department effective energy service in the first time.
In a specific embodiment, before constructing the total departmental economic production model according to the departmental workforce at the first time, the departmental capital at the first time, and the departmental efficient energy service at the first time, the S20 further includes:
and S11, acquiring the department energy use efficiency in the first time and the energy physical quantity consumed by the department in the first time.
And S12, constructing a department effective energy service calculation model in the first time according to the department energy use efficiency in the first time and the department energy consumption physical quantity in the first time.
In a specific embodiment, the department efficient energy service calculation model in the first time is:
Ujt＝θjtEjt (1)
wherein, UjtFor efficient energy service during the period t, thetajtJ energy efficiency for the department of the period t, EjtIs the amount of energy substance consumed by department j during period t.
And S20, constructing a department economic total output model according to the department labor force in the first time, the department capital in the first time and the department effective energy service in the first time.
In one embodiment, the department total economic production model is:
Yjt＝f(Ljt,Kjt,Ujt)+εjt (2)
wherein, YjtIs the economic total output of department j in the period t, LjtLabor force for department j during period t, KjtCapital, U, for time t division jjtIs an effective energy source in the t periodService epsilonjtF is a functional relationship for the error term.
In a specific embodiment, before calculating the contribution value of the department energy efficiency improvement to the yield increase according to the department total economic production model, the step S30 further includes:
s21, taking logarithm of the total economic output model of the department to obtain:
lnYjt＝αjtlnLjt+βjtlnKjt+γjt(lnθjt+lnEjt)+εjt (3)
s22, deriving the logarithm department economic total output model to obtain:
Figure BDA0002793113040000081
wherein, YjtFor the total economic output of j in the t period, alphajtFor the flexibility of the output of department j to labor, LjtIs labor in time t department j, betajtElasticity of capital for yield of department j, KjtCapital, γ, for j in the t-period divisionjtFlexibility to serve the production of efficient energy for department j, θjtJ energy efficiency for the department of the period t, EjtThe amount of energy substance, epsilon, consumed by department j during the period tjtIs an error term.
And S30, calculating the contribution value of the improvement of the energy efficiency of the department to the increase of the output according to the economic total output model of the department.
In a specific embodiment, the S30, calculating the contribution value of the department energy efficiency improvement to the yield increase according to the department total economic yield model, is calculated by the following formula:
Figure BDA0002793113040000091
wherein σjtContribution to yield increase for department j energy efficiency improvement, gammajtYield for department jElasticity of energy efficient services, thetajtJ energy efficiency, Y, for the department of the t periodjtIs the total economic output of the department j in the period t.
S40, multiplying and decomposing the energy consumption change according to an LMDI (Log average Dies Index) decomposition method to generate an energy consumption change factor; wherein, the energy consumption variation factors include: economic scale factors, industrial structure factors and energy intensity factors.
In a specific embodiment, the S40, decomposing the energy consumption variation multiplicatively according to the LMDI decomposition method to generate the energy consumption variation factor, includes:
s41, decomposing the total energy consumption to obtain:
Figure BDA0002793113040000092
wherein E represents the total energy consumption of China; ejRepresenting department j energy consumption; y represents the total output of China; y isjRepresents department j yields; i represents the energy intensity of China; i isjRepresenting department j energy intensity; sjRepresents the proportion of department j output in total output;
s42, obtaining various effects causing energy consumption change according to the total energy consumption after decomposition:
Figure BDA0002793113040000101
wherein E istFor the total energy consumption of period t, EτFor the period tau total energy consumption, Dt,τAs a total effect of the overall energy consumption change,
Figure BDA0002793113040000102
in order to achieve the effect of economy of scale,
Figure BDA0002793113040000103
in order to have an industrial structural effect,
Figure BDA0002793113040000104
is an energy intensity effect.
In one embodiment, the method comprises the steps of
Figure BDA0002793113040000105
For the expected energy saving amount caused by the increase of energy efficiency from t period to tau period of department j, i.e. the decrease of energy intensity,
Figure BDA0002793113040000106
the increase of energy consumption brought by the increase of the overall economic scale, namely the increase of output from the t period to the tau period of the department j,
Figure BDA0002793113040000107
for the increase of energy consumption caused by the increase of energy efficiency, i.e. the decrease of energy intensity, of department j from the period t to the period tau, then:
Figure BDA0002793113040000108
Figure BDA0002793113040000109
Figure BDA00027931130400001010
wherein the content of the first and second substances,
Figure BDA00027931130400001011
for the economic-scale effect of department j,
Figure BDA00027931130400001012
in order to be an energy intensity effect,
Figure BDA00027931130400001013
total energy consumption of department j time t, σjtDepartment j energy efficiencyThe contribution to yield increase is improved.
And S50, calculating the energy rebound effect and the change trend thereof according to the contribution value of the energy efficiency improvement of the department to the output increase and the energy consumption change factor.
In a specific embodiment, the calculating the energy rebound effect according to the contribution value of the department energy efficiency improvement on the yield increase and the energy consumption variation factor is calculated by the following formula:
Figure BDA00027931130400001014
wherein the content of the first and second substances,
Figure BDA00027931130400001015
the energy rebound effect caused by the improvement of the energy efficiency of the department j from the period t to the period tau,
Figure BDA0002793113040000111
for the department j, the increase of energy consumption caused by the increase of energy efficiency from the t period to the tau period, namely the decrease of energy intensity,
Figure BDA0002793113040000112
for the expected energy saving amount caused by the increase of energy efficiency, i.e. the decrease of energy intensity, from the t period to the tau period of department j, σjtFor department j the contribution value of energy efficiency improvement to yield increase,
Figure BDA0002793113040000113
for the economic-scale effect of department j,
Figure BDA0002793113040000114
total energy consumption for time t of department j.
The energy source resilience effect model based on the input-output table provided by the invention improves the characteristics that the existing model research is mostly concentrated in high energy consumption industries and lacks the transverse comparison among different industries of national economy and the longitudinal comparison and analysis in different periods, so as to provide reference for making an industry policy which is beneficial to industrial structure optimization and energy conservation and emission reduction.
In one embodiment, please refer to fig. 5.
FIG. 5 is a general block diagram of a construction method of a supply and demand side response model of Guangdong province based on an energy technology model. As shown in fig. 5, first, an energy input/output table is prepared based on the chinese input/output table and the energy statistical data. And then, constructing a department production model based on the Cabudawser production function. Then, the factor of energy consumption variation is decomposed into an economic scale factor, an industrial structure factor and an energy intensity factor by adopting an LMDI decomposition method. And finally, measuring and calculating the energy source resilience effect and the change trend of the energy source resilience effect in various industries in China at different periods.
The method comprises the following specific steps:
s101, compiling an energy input-output table based on the Chinese input-output table and the energy statistical data:
specifically, in step S101, according to statistical data such as "chinese input-output table" and "chinese energy statistics yearbook" in corresponding year, 42 departments and 149 departments are grouped into 23 departments (18 non-energy departments and 5 energy departments) according to 2017 national economic industry classification (GB/T4754 plus 2017) and according to research needs. The energy input and output table is an extension of the traditional value type input and output table, and is characterized in that a non-energy department has valuable flow, and an energy department has not only valuable flow but also physical flow, so that the use condition of energy in each department and each industry can be known, and the energy input and output table is an effective tool for analyzing energy problems.
TABLE 1 energy input-output table style
Figure BDA0002793113040000121
The specific programming method is as follows: first, Z is obtained from the original value type input-output tableij、Fi、 Xi、Xj. Secondly, make the middle partThe energy production and processing industry (physical quantity) is increased by dividing the energy department into an energy department and a non-energy department, and E is obtained from the energy statistics yearbookj、EFAnd E. For the non-energy sector, input of energy products (E)j) Equal to the terminal energy consumption of the department; for energy sector, input of energy products (E)j) Equal to the sum of the terminal energy consumption and the processing conversion input of the department.
For the non-energy department, the energy department invests in the processing conversion of the non-energy department (Z) because there is no energy processing conversionEE) Is equal to zero; for the energy department, the energy department's conversion of processing into the energy department (Z)EE) The ratio of the energy processing conversion input amount of the department to the input amount of the energy product is multiplied by the value amount of the energy product used by the energy department. In order to measure the output elasticity of the energy service, a row of energy reward is added in the third quadrant, and the value of the energy reward is as follows: the output of the energy department-the energy processing conversion input (value amount).
The worker reward is known from the added value of the original value type input-output table, the fixed asset depreciation and the business surplus are the capital reward, and the net production tax can be considered as the income created by the labor and the capital together, wherein the net production tax is divided into the worker reward and the capital reward according to the proportion of the worker reward, the fixed asset depreciation and the business surplus.
S102, constructing a department production model based on the Cabudawser production function.
Specifically, for step S102, a production model of the department j in the t period is constructed based on the kobudow grulas production function, and in order to research the contribution of the energy efficiency change to economic growth, the energy use efficiency θ is introduced into the production modeljtIt demonstrates the efficiency of energy conversion into an efficient energy service that contributes to production activities:
Yjt＝f(Ljt,Kjt,Ujt)+εjt (1)
wherein: y isjtIs the economic total output of department j in the period t, LjtLabor force for department j during period t, KjtCapital, U, for time t division jjtFor efficient energy service during the period t, epsilonjtIs an error term.
Ujt＝θjtEjt (2)
Wherein E isjtThe amount of energy substance, θ, consumed by department j during period tjtThe energy utilization efficiency of the department j in the period t is reflected, and the energy utilization efficiency not only refers to the physical conversion efficiency, but also takes the economic efficiency into account. Taking logarithm of formula (1) at the same time to obtain formula (3):
lnYjt＝αjtlnLjt+βjtlnKjt+γjt(lnθjt+lnEjt)+εjt (3)
the two sides of the formula (3) are derived with respect to time t to obtain
Figure BDA0002793113040000141
Wherein alpha isjtFor the flexibility of the yield of department j to labour, betajtElasticity of capital for yield of department j, γjtFlexibility to serve the production of efficient energy for department j.
Under the condition of completely competing market, and simultaneously, assuming that the return of production scale of the department j is unchanged, the elasticity of the output of the department j to the three factors of labor, capital and effective energy service is respectively equal to the income shares of the labor, the capital and the effective energy service, namely the occupation ratio of the labor return, the capital return and the energy return in the added value in the energy input-output table.
Therefore, the contribution of the energy efficiency improvement of the t-period department j to the yield increase can be calculated according to the formula (5):
Figure BDA0002793113040000142
wherein, thetajtIs not variable at macro-economic level and is used for estimation
Figure BDA0002793113040000143
Construction of energy efficiency index EEIjt,EEIjtReflects the change of energy efficiency of department j with time, and is therefore available
Figure BDA0002793113040000144
As
Figure BDA0002793113040000145
Estimated value of (a):
EEIj0＝1
Figure BDA0002793113040000146
s103, multiplicatively decomposing the energy consumption change by adopting an LMDI decomposition method, and dividing the factors causing the energy consumption change into three parts: economic scale factors, industrial structure factors and energy intensity factors.
Specifically, for step S103, from the national level, the total energy consumption of our country is decomposed:
Figure BDA0002793113040000151
wherein E represents the total energy consumption of China; ejRepresenting department j energy consumption; y represents the total output of China; y isjRepresents department j yields; i represents the energy intensity of China; i isjRepresenting department j energy intensity; sjRepresents the proportion of department j production in total production.
According to equation (7), the use of LMDI decomposition results in various effects that lead to changes in energy consumption:
Figure BDA0002793113040000152
wherein E istFor the total energy consumption of period t, EτFor the period tau total energy consumption, Dt,τAs a total effect of the overall energy consumption change,
Figure BDA0002793113040000153
in order to achieve the effect of economy of scale,
Figure BDA0002793113040000154
in order to have an industrial structural effect,
Figure BDA0002793113040000155
is an energy intensity effect. Respectively obtaining the total output proportion of the output of each department, the energy consumption of each department in the period t and the period tau and the energy intensity data of each department
Figure BDA0002793113040000156
Figure BDA0002793113040000157
Figure BDA0002793113040000158
Figure BDA0002793113040000159
Wherein the content of the first and second substances,
Figure BDA00027931130400001510
weight for LMDI decomposition:
Figure BDA00027931130400001511
since the analysis is performed on an industry level basis, the method can be used
Figure BDA00027931130400001512
And (3) simplification:
Figure BDA0002793113040000161
Figure BDA0002793113040000162
Figure BDA0002793113040000163
and S104, measuring and calculating the energy source resilience effect and the change trend of the energy source resilience effect in various industries in China at different periods.
Specifically, for step S104, let
Figure BDA0002793113040000164
For the expected energy saving amount caused by the increase of energy efficiency from t period to tau period of department j, i.e. the decrease of energy intensity,
Figure BDA0002793113040000165
the increase of energy consumption brought by the increase of the overall economic scale, namely the increase of output from the t period to the tau period of the department j,
Figure BDA0002793113040000166
for the increase of energy consumption caused by the increase of energy efficiency, i.e. the decrease of energy intensity, of department j from the period t to the period tau, then:
Figure BDA0002793113040000167
Figure BDA0002793113040000168
Figure BDA0002793113040000169
then, from time t to time τ, the energy rebound effect caused by the improvement of the energy efficiency of department j is:
Figure BDA00027931130400001610
a second aspect.
The present invention provides an electronic device, including:
a processor, a memory, and a bus;
the bus is used for connecting the processor and the memory;
the memory is used for storing operation instructions;
the processor is configured to call the operation instruction, and the executable instruction causes the processor to perform an operation corresponding to the energy rebound effect prediction method according to the first aspect of the present application.
In an alternative embodiment, an electronic device is provided, as shown in fig. 6, the electronic device 5000 shown in fig. 6 includes: a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are coupled, such as via a bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. It should be noted that the transceiver 5004 is not limited to one in practical application, and the structure of the electronic device 5000 is not limited to the embodiment of the present application.
The processor 5001 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 5001 may also be a combination of processors implementing computing functionality, e.g., a combination comprising one or more microprocessors, a combination of DSPs and microprocessors, or the like.
Bus 5002 can include a path that conveys information between the aforementioned components. The bus 5002 may be a PCI bus or EISA bus, etc. The bus 5002 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus.
The memory 5003 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 5003 is used for storing application program codes for executing the present solution, and the execution is controlled by the processor 5001. The processor 5001 is configured to execute application program code stored in the memory 5003 to implement the teachings of any of the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like.
In a third aspect.
The present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for energy rebound effect prediction as set forth in the first aspect of the present application.
Yet another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, which, when run on a computer, enables the computer to perform the corresponding content in the aforementioned method embodiments.

Claims (10)

1. An energy rebound effect prediction method is characterized by comprising the following steps:
acquiring department labor force in the first time, department capital in the first time and effective energy service of the department in the first time;
constructing a total department economic output model according to the department labor force in the first time, the department capital in the first time and the department effective energy service in the first time;
calculating a contribution value of the improvement of the energy efficiency of the department to the increase of the output according to the total economic output model of the department;
multiplying and decomposing the energy consumption change according to an LMDI decomposition method to generate an energy consumption change factor; wherein, the energy consumption variation factors include: economic scale factors, industrial structure factors and energy intensity factors;
and calculating the energy resilience effect and the change trend thereof according to the contribution value of the department energy efficiency improvement on the output increase and the energy consumption change factor.
2. The method of claim 1, wherein the step of constructing the total departmental economic production model based on the departmental labor force at the first time, the departmental capital at the first time, and the departmental efficient energy service at the first time further comprises:
acquiring the energy use efficiency of departments in the first time and the energy physical quantity consumed by the departments in the first time;
and constructing a department effective energy service calculation model in the first time according to the department energy utilization efficiency in the first time and the department energy consumption physical quantity in the first time.
3. The method according to claim 2, wherein the calculation model of the department-effective energy service in the first time period is:
Ujt＝θjtEjt (1)
wherein, UjtFor efficient energy service during the period t, thetajtJ energy efficiency for the department of the period t, EjtIs the amount of energy substance consumed by department j during period t.
4. The method according to claim 2, wherein the total department economic output model is:
Yjt＝f(Ljt,Kjt,Ujt)+εjt (2)
wherein, YjtIs the economic total output of department j in the period t, LjtLabor force for department j during period t, KjtCapital, U, for time t division jjtFor efficient energy service during the period t, epsilonjtF is a functional relationship for the error term.
5. The method according to claim 4, wherein before calculating the contribution of department energy efficiency improvement to yield increase according to the department gross economic output model, the method further comprises:
taking logarithm of the total economic output model of the department to obtain:
ln Yjt＝αjtln Ljt+βjtln Kjt+γjt(lnθjt+ln Ejt)+εjt (3)
and (3) carrying out derivation on the total economic output model of the department after logarithm taking to obtain:
Figure FDA0002793113030000021
wherein, YjtFor the total economic output of j in the t period, alphajtFor the flexibility of the output of department j to labor, LjtIs labor in time t department j, betajtElasticity of capital for yield of department j, KjtCapital, γ, for j in the t-period divisionjtFlexibility to serve the production of efficient energy for department j, θjtJ energy efficiency for the department of the period t, EjtThe amount of energy substance, epsilon, consumed by department j during the period tjtIs an error term.
6. The method according to claim 4, wherein the value of the contribution of the department energy efficiency improvement to the yield increase is calculated according to the department total economic yield model, and is calculated by the following formula:
Figure FDA0002793113030000031
wherein σjtContribution to yield increase for department j energy efficiency improvement, gammajtFlexibility to serve the production of efficient energy for department j, θjtJ energy efficiency, Y, for the department of the t periodjtIs the total economic output of the department j in the period t.
7. The method for predicting the energy rebound effect as set forth in claim 1, wherein the multiplicatively decomposing the energy consumption change according to the LMDI decomposition method to generate the energy consumption change factor comprises:
decomposing the total energy consumption to obtain:
Figure FDA0002793113030000032
wherein E represents the total energy consumption of China; ejRepresenting department j energy consumption; y represents the total output of China; y isjRepresents department j yields; i represents the energy intensity of China; i isjRepresenting department j energy intensity; sjRepresents the proportion of department j output in total output;
obtaining various effects which cause energy consumption change according to the total energy consumption after decomposition:
Figure FDA0002793113030000033
wherein E istFor the total energy consumption of period t, EτFor the period tau total energy consumption, Dt,τTotal effect of total change in total energy consumption，
Figure FDA0002793113030000034
In order to achieve the effect of economy of scale,
Figure FDA0002793113030000035
in order to have an industrial structural effect,
Figure FDA0002793113030000036
is an energy intensity effect.
8. The method of claim 7, further comprising:
order to
Figure FDA0002793113030000041
For the expected energy saving amount caused by the increase of energy efficiency from t period to tau period of department j, i.e. the decrease of energy intensity,
Figure FDA0002793113030000042
the increase of energy consumption brought by the increase of the overall economic scale, namely the increase of output from the t period to the tau period of the department j,
Figure FDA0002793113030000043
for the increase of energy consumption caused by the increase of energy efficiency, i.e. the decrease of energy intensity, of department j from the period t to the period tau, then:
Figure FDA0002793113030000044
Figure FDA0002793113030000045
Figure FDA0002793113030000046
wherein the content of the first and second substances,
Figure FDA0002793113030000047
for the economic-scale effect of department j,
Figure FDA0002793113030000048
in order to be an energy intensity effect,
Figure FDA0002793113030000049
total energy consumption of department j time t, σjtAnd improving the energy efficiency of the department j to increase the contribution value of the output.
9. The method according to claim 7, wherein the energy rebound effect is estimated based on the contribution of the department energy efficiency improvement to the yield increase and the energy consumption variation factor, and is calculated by the following formula:
Figure FDA00027931130300000410
wherein the content of the first and second substances,
Figure FDA00027931130300000411
the energy rebound effect caused by the improvement of the energy efficiency of the department j from the period t to the period tau,
Figure FDA00027931130300000412
for the department j, the increase of energy consumption caused by the increase of energy efficiency from the t period to the tau period, namely the decrease of energy intensity,
Figure FDA00027931130300000413
for the expected energy saving amount caused by the increase of energy efficiency, i.e. the decrease of energy intensity, from the t period to the tau period of department j, σjtContribution value to yield increase for department j energy efficiency improvement，
Figure FDA00027931130300000414
For the economic-scale effect of department j,
Figure FDA00027931130300000415
total energy consumption for time t of department j.
10. A computer-readable storage medium, comprising a stored computer program, wherein the computer program when executed controls an apparatus in which the computer-readable storage medium is located to perform the method for predicting the energy rebound effect according to any one of claims 1 to 9.
CN202011321840.XA 2020-11-23 2020-11-23 Energy source resilience effect prediction method and computer readable storage medium Pending CN112365080A (en)

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CN106779157A (en) * 2016-11-18 2017-05-31 中铁第勘察设计院集团有限公司 The Forecasting Methodology of Regional Energy consumption demand
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106169101A (en) * 2016-01-13 2016-11-30 国家电网公司 A kind of Energy Demand Forecast method based on STRUCTURE DECOMPOSITION
CN106779157A (en) * 2016-11-18 2017-05-31 中铁第勘察设计院集团有限公司 The Forecasting Methodology of Regional Energy consumption demand
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