Energy transformation influence assessment method and system based on multi-factor analysis

Abstract

The invention relates to an energy transformation influence assessment method and system based on multi-factor analysis, and the method comprises the steps: obtaining a result after the execution of energy transformation in a to-be-assessed region and the caused influence, and determining influence factors under the economic, environmental and technical dimensions as original data; preprocessing the original data, and classifying and merging the processed data according to dimensions; according to the data set corresponding to each dimension, constructing an economic influence evaluation model corresponding to each dimension, outputting economic influence, environmental influence and technical influence of energy transformation on the to-be-evaluated region, outputting a model result, and constructing a comprehensive evaluation model; and outputting the comprehensive influence of the energy transformation on the to-be-evaluated region according to the comprehensive evaluation model. According to the technical scheme, the influence of energy transformation on multiple dimensions of economy, environment and technology is comprehensively considered through multiple models, so that a scientific and objective evaluation result is provided.

Description

Technical Field

[0001] The present application relates to the field of energy transformation technology, and in particular to an energy transformation impact assessment method and system based on multi-factor analysis. Background Art

[0002] With the intensification of the global energy crisis and the improvement of environmental protection awareness, energy transformation has become an important issue for governments and enterprises. Energy transformation not only involves the adjustment of energy structure, but also involves complex factors in multiple aspects such as economy, society and environment. Therefore, an energy transformation impact assessment method that can comprehensively consider multiple factors is needed to scientifically and objectively evaluate the effect and impact of energy transformation.

[0003] At present, although there are some energy transition impact assessment methods and technologies, most of them focus on a single factor or a single level of assessment, lacking comprehensiveness and systematicness. For example, some methods only focus on the economic effects of energy transition, while ignoring social and environmental factors; some methods only focus on the adjustment of energy structure, but lack comprehensive consideration of technology, policy, market and other aspects in the process of energy transition. Summary of the invention

[0004] In order to at least overcome to some extent the problem that the energy transition impact assessment methods in related technologies lack comprehensiveness and systematicness, the present application provides an energy transition impact assessment method and system based on multi-factor analysis.

[0005] The scheme of this application is as follows:

[0006] According to a first aspect of an embodiment of the present application, a method for evaluating the impact of energy transformation based on multi-factor analysis is provided, comprising:

[0007] Obtain the results and impacts of energy transformation in the region to be assessed, and identify the influencing factors in economic, environmental and technical dimensions as raw data;

[0008] Preprocessing the original data, and classifying and merging the processed data according to dimensions;

[0009] According to the data set corresponding to the economic dimension, an economic impact assessment model based on multivariate linear regression is constructed, and the economic impact of energy transformation on the area to be assessed is output through the economic impact assessment model;

[0010] According to the data set corresponding to the environmental dimension, an environmental impact assessment model based on STIRPAT is constructed, and the environmental impact of energy transformation on the area to be assessed is output through the environmental impact assessment model;

[0011] According to the data set corresponding to the technical dimension, a technical impact assessment model based on CE3METLA is constructed, and the technical impact of energy transformation on the assessed area is output through the technical impact assessment model;

[0012] Constructing a comprehensive assessment model based on the output results of the economic impact assessment model, the environmental impact assessment model and the technical impact assessment model;

[0013] The comprehensive assessment model outputs the comprehensive impact of energy transformation on the region to be assessed.

[0014] Preferably, preprocessing the raw data includes:

[0015] Use the Z-scor method to detect outliers on the original data:

[0016]

[0017] Among them, Z is an outlier, X is a single observation, μ is the mean of the sample where the observation is located, and σ is the standard deviation of the sample.

[0018] Preferably, preprocessing the raw data further includes:

[0019] Use Newton interpolation function to fill the detected abnormal values, and use Newton interpolation to fit the curve so that the interpolation polynomial and the fitted function have the same function value and high-order derivative value at the known points;

[0020] The Newton interpolation function is:

[0021]

[0022] Among them, P n (x) is the Newton interpolation function, f[x0,x1,…,x n ] is the original function f(x) with respect to x0,x1,…,x n The x-order difference quotient of

[0023] P n The relationship between (x) and the original function f(x) is:

[0024] f(x)=P n (x)+R n (x);

[0025] Among them, R n (x) is the remainder.

[0026] Preferably, preprocessing the raw data further includes:

[0027] To standardize:

[0028]

[0029] Among them, x ij is the jth observed value of the ith influencing factor, zx ij is the jth observation value of the i-th influencing factor after standardization, is the mean value of the i-th influencing factor, σ i is the variance of the i-th influencing factor.

[0030] Preferably, an economic impact assessment model based on multiple linear regression is constructed according to the data set corresponding to the economic dimension, including:

[0031] The economic impact assessment model based on multiple linear regression is:

[0032]

[0033] Among them, x1, x2, …, x m are all independent variables that affect the dependent variable y, β1,…,β m are the correlation coefficients corresponding to each independent variable, β0 is the intercept term, and ε is the error term;

[0034] The least squares method is used to estimate the parameters β0, β1, …, β m , select the estimated value make When j = 0, 1, 2, ..., m, the sum of squared errors is the smallest;

[0035] The sum of squared errors is:

[0036]

[0037] Where Q is the sum of squared errors;

[0038] make

[0039] have to

[0040] After sorting, it is transformed into a normal system of equations:

[0041]

[0042] Convert the normal equations into matrix form:

[0043] X T Xβ=X T Y;

[0044] When the matrix X has full column rank, X T X is a reversible square matrix, and the solution of the normal equations is:

[0045]

[0046] Will Substituting back into the original model we get an estimate of y:

[0047]

[0048] Preferably, an environmental impact assessment model based on STIRPAT is constructed according to the data set corresponding to the environmental dimension, including:

[0049] Constructing an environmental impact assessment model based on STIRPAT:

[0050] ln(I)=ln(a)+β1ln(P)+β2ln(A)+β3ln(T)+β0;

[0051] Where I is the environmental impact, P is the population size, A is the per capita affluence, T is the energy transition situation, β0 is a constant term, β1, β2, β3 are parameters, and ∈ is an error term;

[0052] The least squares method is used to estimate the parameters β0, β1, …, β m , select the estimated value make When j = 0, 1, 2, ..., m, the sum of squared errors is the smallest;

[0053] The sum of squared errors is:

[0054]

[0055] Where Q is the sum of squared errors;

[0056] make

[0057] have to

[0058] After sorting, it is transformed into a normal system of equations:

[0059]

[0060] Convert the normal equations into matrix form:

[0061] X T Xβ=X T Y;

[0062] When the matrix X has full column rank, X T X is a reversible square matrix, and the solution of the normal equations is:

[0063]

[0064] Will Substituting back into the original model we get an estimate of y:

[0065] ln(I)=ln(a)+β1ln(P)+β2ln(A)+β3ln(T)+β0.

[0066] Preferably, a technology impact assessment model based on CE3METLA is constructed according to the data set corresponding to the technology dimension, including:

[0067] The production process is represented by the Cobb-Douglas production function; the variables in the Cobb-Douglas production function include: capital, labor and energy;

[0068] Energy input is incorporated as an additional variable into the Cobb-Douglas production function to construct a technology impact assessment model:

[0069] Y=A·E γ ·K α ·L β ;

[0070] Among them, E is energy input, Y is total output, A is technology level, K is total capital input; L is total labor input, α, β, γ represent the output elasticity coefficients of energy input;

[0071] Through multiple energy technology substitution evolution mechanisms and endogenous energy technology progress mechanisms, the competition and substitution between different energy technologies are simulated;

[0072] Through the multi-equation Logistic technology diffusion technology impact assessment model, the technology impact assessment model can represent the competition and complementary relationship between different energy technologies in the energy system, as well as the time evolution and energy structure transformation change rules;

[0073] Identify technical variables that affect energy systems;

[0074] For each technical variable, a Logistic growth model is constructed to describe its growth and saturation phenomenon during the market penetration process;

[0075] The Logistic model is:

[0076]

[0077] Among them, T i is the market penetration rate of the i-th technology, r i is the growth rate of the i-th technology, K i is the market saturation of the ith technology.

[0078] Preferably, a comprehensive assessment model is constructed based on the output results of the economic impact assessment model, the environmental impact assessment model and the technical impact assessment model, including:

[0079] Determine the evaluation indicators;

[0080] According to the evaluation indicators, a comprehensive evaluation model is constructed based on the analytic hierarchy process;

[0081] The comprehensive evaluation model includes: a target layer, a criterion layer and an indicator layer;

[0082] The comprehensive evaluation model establishes a judgment matrix of the criterion layer relative to the target layer, and a judgment matrix of the indicator layer relative to the criterion layer based on the expert scoring results; calculates the score of each criterion layer according to the combined weights and actual data, and outputs the comprehensive impact of energy transformation on the assessed area based on the scores of each criterion layer.

[0083] Preferably, the evaluation indicators include:

[0084] economic dimension, environmental dimension and technological dimension;

[0085] The evaluation indicators under the economic dimension include at least: GDP growth rate, energy consumption elasticity coefficient and energy investment return rate;

[0086] The evaluation indicators under the environmental dimension include at least: carbon emissions, air quality index and proportion of renewable energy consumption;

[0087] The evaluation indicators under the technical dimension include at least: the number of energy technology patents, the adoption rate of new energy technologies and the proportion of R&D investment.

[0088] According to a second aspect of an embodiment of the present application, there is provided an energy transition impact assessment system based on multi-factor analysis, comprising:

[0089] Processor and memory;

[0090] The processor and the memory are connected via a communication bus:

[0091] Wherein, the processor is used to call and execute the program stored in the memory;

[0092] The memory is used to store a program, and the program is at least used to execute an energy transformation impact assessment method based on multi-factor analysis as described in any one of the above items.

[0093] The technical solution provided by this application may have the following beneficial effects:

[0094] The energy transformation impact assessment method based on multi-factor analysis in the present application includes: obtaining the results and impacts of energy transformation in the area to be assessed, and determining the influencing factors in the economic, environmental and technical dimensions as the original data; preprocessing the original data, and classifying and merging the processed data according to the dimensions; constructing an economic impact assessment model based on multivariate linear regression according to the data set corresponding to the economic dimension, and outputting the economic impact of energy transformation on the area to be assessed through the economic impact assessment model; constructing an environmental impact assessment model based on STIRPAT according to the data set corresponding to the environmental dimension, and outputting the environmental impact of energy transformation on the area to be assessed through the environmental impact assessment model; constructing a technical impact assessment model based on CE3METLA according to the data set corresponding to the technical dimension, and outputting the technical impact of energy transformation on the area to be assessed through the technical impact assessment model; constructing a comprehensive assessment model according to the output results of the economic impact assessment model, the environmental impact assessment model and the technical impact assessment model; and outputting the comprehensive impact of energy transformation on the area to be assessed according to the comprehensive assessment model.

[0095] In this technical solution, multiple models are used to comprehensively consider the impact of energy transformation on multiple dimensions such as economy, environment and technology, so as to provide scientific and objective evaluation results.

[0096] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0098] Figure 1 It is a flowchart of an energy transformation impact assessment method based on multi-factor analysis provided by an embodiment of the present application;

[0099] Figure 2 It is a flowchart of another energy transformation impact assessment method based on multi-factor analysis provided by an embodiment of the present application;

[0100] Figure 3 It is a structural diagram of an energy transformation impact assessment system based on multi-factor analysis provided by an embodiment of the present application.

[0101] Reference numerals: processor-21; memory-22. DETAILED DESCRIPTION

[0102] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0103] Embodiment 1

[0104] Figure 1 This is a flow chart of an energy transition impact assessment method based on multi-factor analysis provided by an embodiment of the present application, with reference to Figure 1 , an energy transition impact assessment method based on multi-factor analysis, including:

[0105] S11: Obtain the results and impacts of energy transformation in the region to be assessed, and determine the influencing factors in the economic, environmental and technical dimensions as raw data;

[0106] S12: preprocessing the original data, and classifying and merging the processed data according to dimensions;

[0107] S13: Based on the data set corresponding to the economic dimension, an economic impact assessment model based on multivariate linear regression is constructed, and the economic impact of energy transformation on the assessed region is output through the economic impact assessment model;

[0108] S14: Based on the data set corresponding to the environmental dimension, an environmental impact assessment model based on STIRPAT is constructed, and the environmental impact of energy transformation on the assessed area is output through the environmental impact assessment model;

[0109] S15: Based on the data set corresponding to the technical dimension, a technical impact assessment model based on CE3METLA is constructed, and the technical impact of energy transformation on the assessed area is output through the technical impact assessment model;

[0110] S16: Construct a comprehensive assessment model based on the output results of the economic impact assessment model, the environmental impact assessment model and the technical impact assessment model;

[0111] S17: Output the comprehensive impact of energy transformation on the assessed region based on the comprehensive assessment model.

[0112] It should be noted that this technical solution takes into account the results of regional energy transformation and its impact, which involves technical, economic, environmental and other aspects. Therefore, the results and impacts of energy transformation in the evaluated region are obtained, and the influencing factors in the economic, environmental and technical dimensions are determined as the original data.

[0113] Specifically, the influencing factors under the economic dimension include: GDP, energy consumption level, per capita disposable income, etc.; the influencing factors under the environmental dimension include: carbon emissions, air quality, etc.; the influencing factors under the technological dimension include: industrial structure, R&D investment, number of patents per capita, etc.

[0114] It should be noted that the original data is preprocessed, refer to Figure 2 ,include:

[0115] Use the Z-scor method to detect outliers on the original data:

[0116]

[0117] Among them, Z is an outlier, X is a single observation, μ is the mean of the sample where the observation is located, and σ is the standard deviation of the sample.

[0118] In specific practice, the Z-scor threshold is set to 3, that is, when the Z-scor value of a data point exceeds 3, the data point is considered to be an outlier.

[0119] Preprocessing of raw data also includes:

[0120] Use Newton interpolation function to fill the detected abnormal values, and use Newton interpolation to fit the curve so that the interpolation polynomial and the fitted function have the same function value and high-order derivative value at the known points;

[0121] The Newton interpolation function is:

[0122]

[0123] Among them, P n (x) is the Newton interpolation function, f[x0,x1,…,x n ] is the original function f(x) with respect to x0,x1,…,x n The n-order difference quotient of

[0124] P n The relationship between (x) and the original function f(x) is:

[0125] f(x)=P n (x)+R n (x);

[0126] Among them, R n (x) is the remainder.

[0127] Preprocessing of raw data also includes:

[0128] To standardize:

[0129]

[0130] Among them, x ij is the jth observed value of the ith influencing factor, zx ij is the jth observation value of the i-th influencing factor after standardization, is the mean value of the i-th influencing factor, σ i is the variance of the i-th influencing factor.

[0131] In this technical solution, a corresponding impact assessment model is constructed for the data set corresponding to each dimension.

[0132] According to the data set corresponding to the economic dimension, an economic impact assessment model based on multivariate linear regression is constructed, including:

[0133] The economic impact assessment model based on multiple linear regression is:

[0134]

[0135] Among them, x1, x2, …, x m are all independent variables that affect the dependent variable y, β1,…,β m are the correlation coefficients corresponding to each independent variable, β0 is the intercept term, and ε is the error term;

[0136] The least squares method is used to estimate the parameters β0, β1, …, β m , select the estimated value make When j = 0, 1, 2, ..., m, the sum of squared errors is the smallest;

[0137] The sum of squared errors is:

[0138]

[0139] Where Q is the sum of squared errors;

[0140] make

[0141] have to

[0142] After sorting, it is transformed into a normal system of equations:

[0143]

[0144] Convert the normal equations into matrix form:

[0145] X T Xβ=X T Y;

[0146] When the matrix X has full column rank, X TX is a reversible square matrix, and the solution of the normal equations is:

[0147]

[0148] Will Substituting back into the original model we get an estimate of y:

[0149]

[0150] The STIRPAT model is a random parameter model used to assess the impact of factors such as population (P), affluence (A), and technology (T) on environmental pressure (I). The vector autoregression model is a statistical model used to capture the linear relationship between multiple time series to analyze the impact of one variable on another.

[0151] According to the data sets corresponding to the environmental dimensions, an environmental impact assessment model based on STIRPAT is constructed, including:

[0152] Constructing an environmental impact assessment model based on STIRPAT:

[0153] ln(I)=ln(a)+β1ln(P)+β2ln(A)+β3ln(T)+β0;

[0154] Where I is the environmental impact, P is the population size, A is the per capita affluence, T is the energy transition situation, β0 is a constant term, β1, β2, β3 are parameters, and ∈ is an error term;

[0155] In specific practice, I represents environmental impact, such as carbon emissions or air quality; P represents population size; A represents per capita wealth, which is represented by GDP per capita; T represents energy transformation, including the utilization rate and proportion of clean energy, and the application of new energy technologies.

[0156] The least squares method is used to estimate the parameters β0, β1, …, β m , select the estimated value make When j = 0, 1, 2, ..., m, the sum of squared errors is the smallest;

[0157] The sum of squared errors is:

[0158]

[0159] Where Q is the sum of squared errors;

[0160] make

[0161] have to

[0162] After sorting, it is transformed into a normal system of equations:

[0163]

[0164] Convert the normal equations into matrix form:

[0165] X T Xβ=X T Y;

[0166] When the matrix X has full column rank, X T X is a reversible square matrix, and the solution of the normal equations is:

[0167]

[0168] Will Substituting back into the original model we get an estimate of y:

[0169] ln(I)=ln(a)+β1ln(P)+β2ln(A)+β3ln(T)+β0.

[0170] The CE3METLA model is a comprehensive evaluation model that can simulate the relationship between macroeconomics, energy structure, and technological status. The core of the CE3METLA model is a dynamic intertemporal optimization model based on the theory of endogenous economic growth, which takes into account the policy-driven Logistic multiple technology diffusion mechanism.

[0171] The CE3METLA model consists of an economic module, an energy module and a technology diffusion module.

[0172] The economic module is responsible for representing the production process using the Cobb-Douglas production function;

[0173] The variables in the Cobb-Douglas production function include: capital, labor, and energy;

[0174] Energy input is incorporated as an additional variable into the Cobb-Douglas production function to construct a technology impact assessment model:

[0175] Y=A·E γ ·K α ·L β ;

[0176] Among them, E is energy input, Y is total output, A is technology level, K is total capital input; L is total labor input, α, β, γ represent the output elasticity coefficients of energy input;

[0177] The energy module is responsible for simulating the competition and substitution between different energy technologies through multiple energy technology substitution evolution mechanisms and endogenous energy technology progress mechanisms;

[0178] The technology diffusion module is responsible for using the multi-equation Logistic technology diffusion technology impact assessment model to make the technology impact assessment model represent the competition and complementary relationship between different energy technologies in the energy system, as well as the time evolution and energy structure transformation change rules;

[0179] Identify the technological variables that affect the energy system, such as renewable energy technologies (solar, wind), traditional energy technologies (coal, oil), and energy efficiency technologies;

[0180] For each technical variable, a Logistic growth model is constructed to describe its growth and saturation phenomenon during the market penetration process;

[0181] The logistic model is:

[0182]

[0183] Among them, T i is the market penetration rate of the i-th technology, r i is the growth rate of the i-th technology, K i is the market saturation of the ith technology.

[0184] It should be noted that the comprehensive assessment model is constructed based on the output results of the economic impact assessment model, the environmental impact assessment model and the technical impact assessment model, including:

[0185] Determine the evaluation indicators;

[0186] According to the evaluation indicators and based on the analytic hierarchy process, a comprehensive evaluation model is constructed;

[0187] The comprehensive evaluation model includes: target layer, criterion layer and indicator layer;

[0188] Based on the expert scoring results, the comprehensive evaluation model establishes a judgment matrix of the criterion layer relative to the target layer, and a judgment matrix of the indicator layer relative to the criterion layer; according to the combined weights and actual data, the score of each criterion layer is calculated, and the comprehensive impact of energy transformation on the assessed area is output by combining the scores of each criterion layer.

[0189] In this technical solution, a comprehensive assessment model is constructed based on the output results of the above-mentioned impact assessment models.

[0190] First determine the evaluation indicators:

[0191] Economic impact: GDP growth rate, energy consumption elasticity coefficient, energy investment return rate, etc.

[0192] Environmental impact: carbon emissions, air quality index, proportion of renewable energy consumption, etc.

[0193] Technological impact: number of energy technology patents, adoption rate of new energy technologies, proportion of R&D investment, etc.

[0194] Then build an evaluation model

[0195] Based on the analytic hierarchy process, a comprehensive evaluation model is constructed to evaluate the impact of energy transformation on the economy, environment, and technology. The evaluation model is divided into three layers: target layer, criterion layer, and indicator layer. Through expert scoring, a judgment matrix of the criterion layer relative to the target layer and a judgment matrix of the indicator layer relative to the criterion layer are established. According to the combined weights and actual data, the score of each criterion layer is calculated, and then these scores are combined to obtain the comprehensive effect score of energy transformation.

[0196] The energy transformation impact assessment method based on multi-factor analysis in this embodiment includes: obtaining the results and impacts of energy transformation in the area to be assessed, and determining the influencing factors in the economic, environmental and technical dimensions as original data; preprocessing the original data, and classifying and merging the processed data according to the dimensions; constructing an economic impact assessment model based on multivariate linear regression according to the data set corresponding to the economic dimension, and outputting the economic impact of energy transformation on the area to be assessed through the economic impact assessment model; constructing an environmental impact assessment model based on STIRPAT according to the data set corresponding to the environmental dimension, and outputting the environmental impact of energy transformation on the area to be assessed through the environmental impact assessment model; constructing a technical impact assessment model based on CE3METLA according to the data set corresponding to the technical dimension, and outputting the technical impact of energy transformation on the area to be assessed through the technical impact assessment model; constructing a comprehensive assessment model according to the output results of the economic impact assessment model, the environmental impact assessment model and the technical impact assessment model; and outputting the comprehensive impact of energy transformation on the area to be assessed according to the comprehensive assessment model.

[0197] In this technical solution, multiple models are used to comprehensively consider the impact of energy transformation on multiple dimensions such as economy, environment and technology, so as to provide scientific and objective evaluation results.

[0198] Embodiment 2

[0199] Figure 3 This is a schematic diagram of a structure of an energy transformation impact assessment system based on multi-factor analysis provided by an embodiment of the present application, referring to Figure 3 , an energy transition impact assessment system based on multi-factor analysis, including:

[0200] Processor 21 and memory 22;

[0201] The processor 21 and the memory 22 are connected via a communication bus:

[0202] The processor 21 is used to call and execute the program stored in the memory 22;

[0203] The memory 22 is used to store a program, and the program is used to execute at least one of the energy transformation impact assessment methods based on multi-factor analysis in the above embodiment.

[0204] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0205] It should be noted that, in the description of this application, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0206] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0207] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0208] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0209] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0210] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0211] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0212] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for assessing the impact of energy transition based on multi-factor analysis, characterized in that: include: Obtain the results and impacts of energy transformation in the region to be assessed, and identify the influencing factors in economic, environmental and technical dimensions as raw data; Preprocessing the original data, and classifying and merging the processed data according to dimensions; According to the data set corresponding to the economic dimension, an economic impact assessment model based on multivariate linear regression is constructed, and the economic impact of energy transformation on the area to be assessed is output through the economic impact assessment model; According to the data set corresponding to the environmental dimension, an environmental impact assessment model based on STIRPAT is constructed, and the environmental impact of energy transformation on the area to be assessed is output through the environmental impact assessment model; According to the data set corresponding to the technical dimension, a technical impact assessment model based on CE3METLA is constructed, and the technical impact of energy transformation on the assessed area is output through the technical impact assessment model; Constructing a comprehensive assessment model based on the output results of the economic impact assessment model, the environmental impact assessment model and the technical impact assessment model; The comprehensive assessment model outputs the comprehensive impact of energy transformation on the region to be assessed.

2. The method according to claim 1, characterized in that Preprocessing the raw data includes: Use the Z-scor method to detect outliers on the original data: Among them, Z is an outlier, X is a single observation, μ is the mean of the sample where the observation is located, and σ is the standard deviation of the sample.

3. The method according to claim 2, characterized in that Preprocessing the raw data further includes: Use Newton interpolation function to fill the detected abnormal values, and use Newton interpolation to fit the curve so that the interpolation polynomial and the fitted function have the same function value and high-order derivative value at the known points; The Newton interpolation function is: Among them, P n (x) is the Newton interpolation function, f[x0,x1,…,x n ] is the original function f(x) with respect to x0,x1,…,x n The n-order difference quotient of P n The relationship between (x) and the original function f(x) is: x(x)=P n (x)+R n (x); Among them, R n (x) is the remainder.

4. The method according to claim 3, characterized in that Preprocessing the raw data further includes: To standardize: Among them, x ij is the jth observed value of the ith influencing factor, zx ij is the jth observation value of the i-th influencing factor after standardization, is the mean value of the i-th influencing factor, σ i is the variance of the i-th influencing factor.

5. The method according to claim 1, characterized in that: According to the data set corresponding to the economic dimension, an economic impact assessment model based on multivariate linear regression is constructed, including: The economic impact assessment model based on multiple linear regression is: Among them, x1, x2, …, x m are all independent variables that affect the dependent variable y, β1,…,β m are the correlation coefficients corresponding to each independent variable, β0 is the intercept term, and ε is the error term; The least squares method is used to estimate the parameters β0, β1, …, β m , select the estimated value make When , the sum of squared errors is minimum; The sum of squared errors is: Where Q is the sum of squared errors; make have to After sorting, it is transformed into a normal system of equations: Convert the normal equations into matrix form: X T Xβ=X T Y; When the matrix X has full column rank, X T X is a reversible square matrix, and the solution of the normal equations is: Will Substituting back into the original model we get an estimate of y:

6. The method according to claim 1, characterized in that According to the data sets corresponding to the environmental dimensions, an environmental impact assessment model based on STIRPAT is constructed, including: Constructing an environmental impact assessment model based on STIRPAT: ln(I)=ln(a)+β1ln(P)+β2ln(A)+β3ln(T)+β0; Where l is the environmental impact, P is the population size, A is the per capita affluence, T is the energy transition situation, β0 is a constant term, β1, β2, β3 are parameters, and ∈ is an error term; The least squares method is used to estimate the parameters β0, β1, …, β m , select the estimated value make When , the sum of squared errors is minimum; The sum of squared errors is: Where Q is the sum of squared errors; make have to After sorting, it is transformed into a normal system of equations: Convert the normal equations into matrix form: X T Xβ=X T Y; When the matrix X has full column rank, X T X is a reversible square matrix, and the solution of the normal equations is: Will Substituting back into the original model we get an estimate of y: ln(I)=ln(a)+β1ln(P)+β2ln(A)+β3ln(T)+β0.

7. The method according to claim 1, characterized in that According to the data set corresponding to the technical dimension, a technical impact assessment model based on CE3METLA is constructed, including: The production process is represented by the Cobb-Douglas production function; the variables in the Cobb-Douglas production function include: capital, labor and energy; Energy input is incorporated as an additional variable into the Cobb-Douglas production function to construct a technology impact assessment model: Y=A·E γ ·K α ·L β ; Among them, E is energy input, Y is total output, A is technology level, K is total capital input; L is total labor input, α, β, γ represent the output elasticity coefficients of energy input; Through multiple energy technology substitution evolution mechanisms and endogenous energy technology progress mechanisms, the competition and substitution between different energy technologies are simulated; Through the multi-equation Logistic technology diffusion technology impact assessment model, the technology impact assessment model can represent the competition and complementary relationship between different energy technologies in the energy system, as well as the time evolution and energy structure transformation change rules; Identify technical variables that affect energy systems; For each technical variable, a Logistic growth model is constructed to describe its growth and saturation phenomenon during the market penetration process; The Logistic model is: Among them, T i is the market penetration rate of the i-th technology, r i is the growth rate of the i-th technology, K i is the market saturation of the ith technology.

8. The method according to claim 1, characterized in that Based on the output results of the economic impact assessment model, the environmental impact assessment model and the technical impact assessment model, a comprehensive assessment model is constructed, including: Determine the evaluation indicators; According to the evaluation indicators, a comprehensive evaluation model is constructed based on the analytic hierarchy process; The comprehensive evaluation model includes: a target layer, a criterion layer and an indicator layer; The comprehensive evaluation model establishes a judgment matrix of the criterion layer relative to the target layer, and a judgment matrix of the indicator layer relative to the criterion layer based on the expert scoring results; calculates the score of each criterion layer according to the combined weights and actual data, and outputs the comprehensive impact of energy transformation on the assessed area based on the scores of each criterion layer.

9. The method according to claim 8, characterized in that The evaluation indicators include: economic dimension, environmental dimension and technological dimension; The evaluation indicators under the economic dimension include at least: GDP growth rate, energy consumption elasticity coefficient and energy investment return rate; The evaluation indicators under the environmental dimension include at least: carbon emissions, air quality index and proportion of renewable energy consumption; The evaluation indicators under the technical dimension include at least: the number of energy technology patents, the adoption rate of new energy technologies and the proportion of R&D investment.

10. An energy transition impact assessment system based on multi-factor analysis, characterized in that: include: Processor and memory; The processor and the memory are connected via a communication bus: Wherein, the processor is used to call and execute the program stored in the memory; The memory is used to store a program, and the program is at least used to execute an energy transformation impact assessment method based on multi-factor analysis as described in any one of claims 1-9.

Images