Regional energy structure transformation planning method and system considering social cost, and computer storage medium

Abstract

The invention provides a regional energy structure transformation planning method and system considering social cost and a computer storage medium, and relates to the technical field of energy transformation. The method comprises the following steps: acquiring current year data and historical year data of energy consumption varieties in a region according to statistical data; historical cost functions of the carbon emission factor, the energy consumption and the energy utilization efficiency are obtained through fitting of historical year data, the cost and the energy conservation and carbon reduction benefits are comprehensively considered, and the energy transformation social cost of the future year is calculated; setting a comprehensive discount rate and a carbon dioxide emission intensity annual average decline rate limit value in a research planning period; and obtaining an optimal path of regional future energy transformation based on nonlinear programming optimization. According to the method, path analysis is carried out on regional energy transformation from top to bottom from energy consumption of various varieties, so that the trouble of diversity of the national economy industry and data acquisition difficulty on medium-and-long-term energy transformation path planning is reduced.

Description

Technical Field

[0001] The present application relates to the field of energy transformation technology, and more specifically, to a method, system and computer storage medium for regional energy structure transformation planning taking into account social costs. Background Art

[0002] Energy transformation includes transformation on the energy supply side, transmission side and demand side, covering aspects such as new energy development, transmission and distribution network construction, terminal electrification transformation and equipment energy efficiency improvement.

[0003] Starting from the aspects of macroeconomics, policy planning, technological development and energy supply and demand, various types of energy-environment models are generally constructed to predict the trend and structure of regional or industrial energy consumption and greenhouse gas emissions, including three main types of top-down, bottom-up and hybrid models. Commonly used models include CGE model, LEAP model, EPS model and POLES model, etc. Each model has its own unique scope of application and applicable conditions.

[0004] On the one hand, existing analysis techniques often have more complex models and require more historical data as support, especially bottom-up models and hybrid models. Some of the data are difficult to obtain statistically and require extensive experience as support to analyze a more reasonable development path for regional energy structure transformation.

[0005] On the other hand, existing technologies often lack a macroeconomic evaluation perspective, or the economic evaluation is limited to energy development costs, without considering the energy-saving economic benefits and carbon reduction externality benefits during the life cycle, and lack the perspective of overall social costs in benefit evaluation. Summary of the invention

[0006] The purpose of the embodiments of the present application is to provide a regional energy structure transformation planning method, system and computer storage medium that takes into account social costs, so as to conduct a top-down path analysis of regional energy transformation based on the consumption of various types of energy, so as to reduce the diversity of national economic industries and the difficulty of data acquisition for medium- and long-term energy transformation path planning.

[0007] In a first aspect, the present invention provides a method for regional energy structure transformation planning taking into account social costs, the method comprising the following steps:

[0008] S1: Obtain the data of energy consumption types in the region for the current year based on statistical data;

[0009] S2: Obtain historical annual data in the region based on statistical data;

[0010] S3: Take historical annual data to fit the historical cost functions of carbon emission factor, energy consumption and energy efficiency;

[0011] S4: Based on the historical cost function and the data of the current year, the social cost of energy transformation in future years is calculated by comprehensively considering the cost and energy conservation and carbon reduction benefits;

[0012] S5: Set limits on the comprehensive discount rate and the average annual decline rate of carbon dioxide emission intensity during the research planning period;

[0013] S6: Based on nonlinear programming optimization, the optimal path for future regional energy transformation is obtained.

[0014] In an optional implementation, in S1, the data for the current year includes the current annual price, the utilization efficiency for the current year, and the carbon emission factor for the current year, wherein the utilization efficiency for the current year is for:

[0015]

[0016] In the formula, is the terminal consumption of energy type n in the current year t0, It is the social reference quantity for that year.

[0017] In an optional implementation, in S2, the historical annual data includes the historical annual energy investment cost and the historical annual energy utilization efficiency η, the historical annual energy variety consumption Q and the historical annual carbon emission factor θ, wherein the historical annual energy investment cost includes supply-side investment S, transmission-side investment T and demand-side investment D.

[0018] In an optional implementation, in S3, the supply-side investment S and the historical annual carbon emission factor θ can be fitted to obtain the supply-side historical cost function:

[0019]

[0020] in, is the historical cost of the supply side in the current year t0, and is the investment fitting coefficient corresponding to the supply-side energy variety n;

[0021] The transmission side investment T and the historical annual energy consumption Q are fitted to obtain the transmission side historical cost function:

[0022]

[0023] in, is the historical cost of the transmission side in the current year t0, and is the investment fitting coefficient corresponding to the energy type n on the transmission side;

[0024] The historical cost function of the demand side can be obtained by fitting the demand side investment D with the historical annual energy efficiency η:

[0025]

[0026] in, is the historical cost of the demand side in the current year t0, and is the fitting coefficient corresponding to the energy type n on the demand side.

[0027] In an alternative embodiment, in S4, the social cost of energy transition TC in year t within the planned study period t for:

[0028]

[0029] in:

[0030]

[0031]

[0032] Where N is the number of energy consumption types in the region, is the transformation cost of the supply side in year t, is the transformation cost of the transmission side in year t, is the transformation cost of the demand side in year t, is the social energy carbon cost in year t, is the price of energy type n in year t, is the social reference quantity of energy type n in year t, is the utilization efficiency of energy type n in year t, CP(t) is the carbon price in year t, is the carbon emission factor of energy type n in year t.

[0033] In an optional implementation, in S4, the calculation formula of the social energy carbon cost SC is as follows:

[0034] SC=EC+CC

[0035]

[0036] CC=CE·CP

[0037]

[0038] Among them, EC is the total energy cost, CC is the total carbon dioxide emission externality loss, Q n is the consumption of energy type n, P n is the price of energy type n, q n is the social reference quantity of energy type n, η nis the utilization efficiency of energy type n, CE is carbon emissions, CP is carbon price, θ n is the carbon emission factor of energy type n.

[0039] In an optional implementation, in S4, the supply-side transformation cost is:

[0040]

[0041] in, is the transformation cost of the supply side in year t, is the carbon emission factor of supply-side energy type n in year t;

[0042] The cost of the transmission side transformation is:

[0043]

[0044] in, is the transformation cost of the transmission side in year t, is the consumption of energy type n on the transmission side in year t;

[0045] The cost of demand-side transformation is:

[0046]

[0047] in, is the transformation cost of the demand side in year t, is the utilization efficiency of energy type n on the demand side in year t.

[0048] In an optional embodiment, in S4, the future year cost function is the historical cost function with a time factor added:

[0049]

[0050] in, They are the time factor coefficients of the supply side, transmission side and demand side respectively.

[0051] In a second aspect, the present invention provides a regional energy structure transformation planning system taking into account social costs, the system comprising:

[0052] The current year energy data analysis unit is used to obtain the current year data of energy consumption types in the region based on statistical data;

[0053] The historical annual energy transformation key function fitting unit is used to obtain historical annual data in the region based on statistical data, and to fit the historical annual data to obtain the historical cost functions of carbon emission factors, energy consumption and energy efficiency;

[0054] The social cost assessment unit for energy transformation in future years is used to calculate the social cost of energy transformation in future years based on the historical cost function and the data of the current year, taking into account the cost and energy-saving and carbon-reduction benefits;

[0055] The optimal energy transformation path planning unit is used to set the limits of the comprehensive discount rate and the average annual decline rate of carbon dioxide emission intensity during the research planning period, and to derive the optimal path for future regional energy transformation based on nonlinear programming optimization.

[0056] In a third aspect, the present invention provides a computer storage medium storing a computer program, which implements the steps of any one of the methods in the aforementioned embodiments when the computer program is executed by a processor.

[0057] The beneficial effects of the regional energy structure transformation planning method, system and computer storage medium taking into account social costs provided by the embodiments of the present invention include:

[0058] Based on comprehensive consideration of data availability and planning operability, a set of regional energy structure transformation planning methods that take into account social costs and are easy to implement in a programmatic manner is proposed. From the perspective of social costs, the energy transformation path is evaluated from the perspective of full life cycle economic evaluation factors such as energy transformation cost investment on the supply side, transmission side and demand side, energy conservation and carbon reduction benefits within the planned year, etc. The optimal development path of regional energy transformation is sought through nonlinear programming methods. Compared with existing traditional methods, a more comprehensive economic evaluation perspective is considered, forming a more implementable digital planning model for energy transformation. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0060] Figure 1 A flow chart of a regional energy structure transformation planning method taking into account social costs provided in an embodiment of the present application;

[0061] Figure 2 A block diagram of the composition of a regional energy structure transformation planning system taking into account social costs provided in an embodiment of the present application.

[0062] Icons: 1-Energy data analysis unit for the current year; 2-Key function fitting unit for energy transformation in historical years; 3-Social cost assessment unit for energy transformation in future years; 4-Optimal path planning unit for energy transformation. DETAILED DESCRIPTION

[0063] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0064] Figure 1 A flow chart of a regional energy structure transformation planning method (hereinafter referred to as “method”) taking into account social costs provided in an embodiment of the present application. Specifically, the method includes the following steps:

[0065] S1: Obtain the current year data of energy consumption types in the region based on statistical data.

[0066] Among them, the data for the current year include the current annual price, the utilization efficiency of the current year and the carbon emission factor of the current year.

[0067] Among them, energy consumption types include primary fossil energy (such as coal, oil, gas, etc.), secondary energy types (such as electricity, heat and hydrogen, etc.). The current year price and the carbon emission factor of the year can be directly obtained based on statistical data. The utilization efficiency of the year is the energy consumption divided by the social reference amount. The social reference amount can be a statistical quantity that can represent the macro-development factors of the society, such as regional gross domestic product (GDP) or regional population. From the statistical data, it can be obtained that the terminal consumption of energy type n in the current year t0 is The social reference volume for that year was Its utilization efficiency in that year is for:

[0068]

[0069] S2: Obtain historical annual data in the region based on statistical data.

[0070] Among them, historical annual data include historical annual energy investment costs and historical annual energy utilization efficiency, historical annual energy variety consumption and historical annual carbon emission factors.

[0071] Specifically, the historical annual energy investment cost includes supply-side investment S, transmission-side investment T and demand-side investment D.

[0072] In the historical year series [t 0-k t 0-k+1 t 0-k+2 …t0], the supply-side investment S, transmission-side investment T, demand-side investment D, historical annual energy consumption Q, historical annual energy utilization efficiency η and historical annual carbon emission factor θ of various energy types corresponding to each year are obtained.

[0073] S3: Take historical annual data to fit the historical cost function of carbon emission factor, energy consumption and energy utilization efficiency.

[0074] Specifically, the supply-side investment S and the historical annual carbon emission factor θ can be fitted to obtain the supply-side historical cost function:

[0075]

[0076] in, is the historical cost of the supply side in the current year t0, and is the investment fitting coefficient corresponding to the supply-side energy variety n.

[0077] The transmission side investment T and the historical annual energy consumption Q are fitted to obtain the transmission side historical cost function:

[0078]

[0079] in, is the historical cost of the transmission side in the current year t0, and is the investment fitting coefficient corresponding to the energy type n on the transmission side.

[0080] The historical cost function of the demand side can be obtained by fitting the demand side investment D with the historical annual energy efficiency η:

[0081]

[0082] in, is the historical cost of the demand side in the current year t0, and is the fitting coefficient corresponding to the energy type n on the demand side.

[0083] S4: Based on the historical cost function and current year data, taking into account the costs and energy-saving and carbon-reduction benefits, calculate the social cost of energy transformation in future years.

[0084] Specifically, it is assumed that there are N types of energy consumer goods in the region. The social cost of energy transformation is equal to the supply-side transformation cost plus the transmission-side transformation cost plus the demand-side transformation cost plus the social energy-carbon cost after the transformation, minus the social energy-carbon cost if there is no transformation.

[0085] Among them, the cost of supply-side transformation is:

[0086]

[0087] in, is the transformation cost of the supply side in year t, is the carbon emission factor of supply-side energy type n in year t.

[0088] The cost of the transmission side transformation is:

[0089]

[0090] in, is the transformation cost of the transmission side in year t, is the consumption of energy type n on the transmission side in year t.

[0091] The cost of demand-side transformation is:

[0092]

[0093] in, is the transformation cost of the demand side in year t, is the utilization efficiency of energy type n on the demand side in year t.

[0094] The future year cost function adds a time factor to the historical cost function to introduce the impact of future uncertainty, that is:

[0095]

[0096] in, They are the time factor coefficients of the supply side, transmission side and demand side respectively.

[0097] The social energy carbon cost SC is the total energy cost EC plus the total carbon dioxide emission externality loss CC, that is:

[0098] SC=EC+CC

[0099]

[0100] CC=CE·CP

[0101]

[0102] Among them, Q n is the consumption of energy type n, P n is the price of energy type n, q n is the social reference quantity of energy type n, η n is the utilization efficiency of energy type n, CE is carbon emissions, CP is carbon price, θ n is the carbon emission factor of energy type n.

[0103] Therefore, the social cost of energy transition in year t within the planning study period is TC t for:

[0104]

[0105] in:

[0106]

[0107] in, is the social energy carbon cost in year t, is the price of energy type n in year t, is the social reference quantity of energy type n in year t, is the utilization efficiency of energy type n in year t, CP(t) is the carbon price in year t, is the carbon emission factor of energy type n in year t.

[0108] S5: Set limits on the comprehensive discount rate and the average annual decline rate of carbon dioxide emission intensity during the research planning period.

[0109] Specifically, the comprehensive discount rate is set to μ, and the annual average decline rate limit of carbon dioxide emission intensity (CE / GDP) is set to ε, where GDP is the gross regional product.

[0110] S6: Based on nonlinear programming optimization, the optimal path for future regional energy transformation is obtained.

[0111] Specifically, the optimal path refers to the path that meets the annual average decline rate limit of carbon dioxide emission intensity within the research planning period [t0, t m ] is a transformation path with the lowest social cost of energy transformation. Its calculation method meets the following nonlinear programming conditions:

[0112]

[0113]

[0114] Among them, CE (t) is the total energy cost in year t, GDP (t) is the gross regional product in year t.

[0115] Please refer to Figure 2 Based on the same inventive concept, the embodiment of the present application also provides a regional energy structure transformation planning system taking into account social costs (hereinafter referred to as: system), the system includes a current year energy data analysis unit 1, a historical year energy transformation key function fitting unit 2, a future year energy transformation social cost assessment unit 3 and an energy transformation optimal path planning unit 4.

[0116] Specifically, the current year energy data analysis unit 1 is used to obtain the current year data of energy consumption types in the region based on statistical data for subsequent analysis. In other words, the current year energy data analysis unit 1 is used to execute S1 in the above method.

[0117] The historical annual energy transformation key function fitting unit 2 is used to obtain historical annual data in the region based on statistical data, and to fit the historical annual data to obtain the historical cost functions of carbon emission factors, energy consumption, and energy utilization efficiency for subsequent analysis. In other words, the historical annual energy transformation key function fitting unit 2 is used to execute S2 and S3 in the above method.

[0118] The future year energy transition social cost assessment unit 3 is used to calculate the future year energy transition social cost based on the historical cost function and the current year data, taking into account the cost and energy saving and carbon reduction benefits. In other words, the future year energy transition social cost assessment unit 3 is used to execute S4 in the above method.

[0119] The energy transformation optimal path planning unit 4 is used to set the comprehensive discount rate and the annual average decline rate limit of carbon dioxide emission intensity within the research planning period, and obtain the optimal path for regional future energy transformation based on nonlinear programming optimization. In other words, the energy transformation optimal path planning unit 4 is used to execute S5 and S6 in the above method.

[0120] This embodiment also provides a computer program product or a computer program, which includes computer instructions stored in a computer storage medium. A processor of an electronic device reads the computer instructions from the computer storage medium, and when the processor executes the computer instructions, a regional energy structure transformation planning method taking into account social costs is implemented.

[0121] The method, system and computer storage medium for regional energy structure transformation planning taking into account social costs provided in this embodiment have the following beneficial effects:

[0122] 1. Starting from various energy consumption types, conduct a top-down analysis of regional energy transformation paths to reduce the difficulties caused by the diversity of national economic industries and the difficulty of data acquisition in mid- and long-term energy transformation path planning.

[0123] 2. Based on the energy investment data of historical years (supply side, transmission side and demand side) and energy utilization conditions (energy consumption, energy utilization efficiency and carbon emission factor), a nonlinear programming method for energy transformation costs in future years is generated.

[0124] 3. From the perspective of social cost, that is, considering the initial investment cost of energy transformation, as well as the energy-saving benefits and carbon emission externality gains and losses, the future energy transformation costs can be evaluated from a more comprehensive social perspective.

[0125] Therefore, the embodiment of the present invention proposes a regional energy structure transformation planning method that takes into account social costs and is easy to implement in a programmatic manner based on comprehensive consideration of data availability and planning operability, and conducts economic optimization from the perspective of overall social costs. Compared with existing traditional methods, it considers a more comprehensive economic evaluation perspective and forms a more implementable digital planning model for energy transformation.

[0126] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0127] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0128] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0129] It should be noted that if the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially be embodied in the form of a software product, or in other words, the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM) random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0130] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0131] The above are only embodiments of the present application and are not intended to limit the scope of protection of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the scope of protection of the present application.

Claims

1. A regional energy structure transformation planning method taking into account social costs, characterized in that: The method comprises the following steps: S1: Obtain the data of energy consumption types in the region for the current year based on statistical data; S2: Obtain historical annual data in the region based on statistical data; S3: Taking the historical annual data, respectively, fitting the historical cost functions of carbon emission factor, energy consumption and energy efficiency; S4: Based on the historical cost function and the current year data, taking into account the cost and energy-saving and carbon-reduction benefits, calculate the social cost of energy transformation in future years; S5: Set limits on the comprehensive discount rate and the average annual decline rate of carbon dioxide emission intensity during the research planning period; S6: Based on nonlinear programming optimization, the optimal path for future regional energy transformation is obtained.

2. The regional energy structure transformation planning method taking into account social costs according to claim 1 is characterized in that: In S1, the data for the current year include the current annual price, the utilization efficiency of the current year and the carbon emission factor of the current year, among which the utilization efficiency of the current year is for: In the formula, is the terminal consumption of energy type n in the current year t0, It is the social reference quantity for that year.

3. The regional energy structure transformation planning method taking into account social costs according to claim 2 is characterized in that: In S2, the historical annual data includes the historical annual energy investment cost and the historical annual energy utilization efficiency η, the historical annual energy variety consumption Q and the historical annual carbon emission factor θ, wherein the historical annual energy investment cost includes supply-side investment S, transmission-side investment T and demand-side investment D.

4. The regional energy structure transformation planning method taking into account social costs according to claim 3 is characterized in that: In S3, the supply-side investment S and the historical annual carbon emission factor θ can be fitted to obtain the supply-side historical cost function: in, is the historical cost of the supply side in the current year t0, and is the investment fitting coefficient corresponding to the supply-side energy variety n; The transmission side investment T and the historical annual energy consumption Q are fitted to obtain the transmission side historical cost function: in, is the historical cost of the transmission side in the current year t0, and is the investment fitting coefficient corresponding to the energy type n on the transmission side; The historical cost function of the demand side can be obtained by fitting the demand side investment D with the historical annual energy efficiency η: in, is the historical cost of the demand side in the current year t0, and is the fitting coefficient corresponding to the energy type n on the demand side.

5. The regional energy structure transformation planning method taking into account social costs according to claim 4 is characterized in that: In S4, the social cost of energy transition in year t within the planned study period TC t for: in: Where N is the number of energy consumption types in the region, is the transformation cost of the supply side in year t, is the transformation cost of the transmission side in year t, is the transformation cost of the demand side in year t, is the social carbon cost in year t, is the price of energy type n in year t, is the social reference quantity of energy type n in year t, is the utilization efficiency of energy type n in year t, CP (t) is the carbon price in year t, is the carbon emission factor of energy type n in year t.

6. The regional energy structure transformation planning method taking into account social costs according to claim 5 is characterized in that: In S4, the calculation formula of social energy carbon cost SC is as follows: SC=EC+CC CC=CE·CP Among them, EC is the total energy cost, CC is the total carbon dioxide emission externality loss, Q n is the consumption of energy type n, P n is the price of energy type n, q n is the social reference quantity of energy type n, η n is the utilization efficiency of energy type n, CE is carbon emissions, CP is carbon price, θ n is the carbon emission factor of energy type n.

7. The regional energy structure transformation planning method taking into account social costs according to claim 6 is characterized in that: In S4, the cost of supply-side transformation is: in, is the transformation cost of the supply side in year t, is the carbon emission factor of supply-side energy type n in year t; The cost of transmission side transformation is: in, is the transformation cost of the transmission side in year t, is the consumption of energy type n on the transmission side in year t; The cost of demand-side transformation is: in, is the transformation cost of the demand side in year t, is the utilization efficiency of energy type n on the demand side in year t.

8. The regional energy structure transformation planning method taking into account social costs according to claim 7 is characterized in that: In S4, the future year cost function is the historical cost function with a time factor added: in, They are the time factor coefficients of the supply side, transmission side and demand side respectively.

9. A regional energy structure transformation planning system taking into account social costs, characterized in that: The system comprises: The current year energy data analysis unit (1) is used to obtain the current year data of energy consumption types in the region based on statistical data; The historical annual energy transformation key function fitting unit (2) is used to obtain historical annual data in the region based on statistical data, and to fit the historical annual data to obtain the historical cost functions of carbon emission factor, energy consumption and energy utilization efficiency; The social cost assessment unit for energy transition in future years (3) is used to calculate the social cost of energy transition in future years based on the historical cost function and the data of the current year, taking into account the cost and energy conservation and carbon reduction benefits; The optimal energy transformation path planning unit (4) is used to set the limits of the comprehensive discount rate and the average annual decline rate of carbon dioxide emission intensity within the research planning period, and to derive the optimal path for the region's future energy transformation based on nonlinear programming optimization.

10. A computer storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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