Layout scheme determination method, system, device, medium and product of wind power equipment

Abstract

The application discloses a kind of layout scheme determination method, system, equipment, medium and product of wind power equipment, belong to wind power equipment layout planning technical field, the method is: obtaining at least two candidate layout schemes, and obtaining material demand matrix and emission factor matrix;Each candidate layout scheme includes target equipment data and transaction equipment data of wind power equipment in each region;For each candidate layout scheme, according to target equipment data and transaction equipment data, determine life cycle matrix in combination with material flow analysis technology;Material demand matrix, emission factor matrix and life cycle matrix are operated on matrix, and the total carbon emission corresponding to each candidate layout scheme is obtained;According to all total carbon emissions, select the candidate layout scheme with the minimum total carbon emission as the target layout scheme, therefore, by implementing the present application, the precise calculation of carbon emissions can be realized, and the reliability of layout decision is improved.

Description

Technical Field

[0001] This invention relates to the field of wind power equipment layout planning technology, and in particular to a method, system, equipment, medium and product for determining the layout scheme of wind power equipment. Background Technology

[0002] While wind power generation does not generate direct carbon emissions during operation, its equipment consumes significant amounts of resources such as steel, concrete, and electricity throughout its entire lifecycle, including manufacturing, construction, operation, maintenance, and recycling, indirectly generating substantial carbon emissions. With the continued growth of global wind power capacity, accurately assessing the carbon emissions throughout the entire lifecycle of wind power is crucial for formulating carbon reduction policies and optimizing the wind power industry layout.

[0003] Currently, existing methods calculate the difference in the number of wind power equipment between adjacent years based on the number of equipment in each region under different layout schemes, to obtain the net increase in equipment. Then, based on the net increase in equipment and the fixed emission factors of wind power equipment and materials in each region, the total carbon emissions corresponding to each layout scheme are calculated, and the layout scheme with the lowest carbon emissions is selected as the target scheme to achieve layout optimization.

[0004] However, existing methods calculate total carbon emissions based solely on net new equipment. On the one hand, this net new equipment cannot reflect the actual production volume of the equipment, resulting in a serious underestimation of carbon emissions during the production stage. On the other hand, it also ignores carbon emissions generated in other life cycle stages, leading to inaccurate calculation of total carbon emissions and thus affecting the reliability of layout optimization decisions. Summary of the Invention

[0005] This invention provides a method, system, equipment, medium, and product for determining the layout scheme of wind power equipment. It can solve the problem that the existing technology ignores the real material flow at each stage of the life cycle, resulting in inaccurate calculation of total carbon emissions and failure to truly reflect the differences in carbon emissions between different layout schemes.

[0006] This invention provides a method for determining the layout scheme of wind power equipment, including: At least two candidate layout schemes are obtained, and a material demand matrix and an emission factor matrix are obtained. The material demand matrix is ​​used to characterize the demand of each material at each life cycle stage, and the emission factor matrix is ​​used to characterize the carbon emission intensity of each material in each region at each life cycle stage. Each candidate layout scheme includes target equipment data and traded equipment data of wind power equipment in each region. For each of the candidate layout schemes, a lifecycle matrix is ​​determined based on the target equipment data and the transaction equipment data, combined with material flow analysis technology. The lifecycle matrix is ​​used to characterize the equipment data of the wind power equipment at each stage of its lifecycle. Matrix operations are performed on the material demand matrix, the emission factor matrix, and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme; Based on the total carbon emissions mentioned above, the candidate layout scheme with the minimum total carbon emissions is selected as the target layout scheme.

[0007] The embodiments of this invention comprehensively consider the demand of different materials at each stage of their life cycle and the differences in carbon emission intensity of different materials in different regions, making carbon emission assessment more comprehensive and accurate, and avoiding the one-sidedness of assessment based on a single factor. By comparing multiple schemes and selecting the best one, the optimal layout scheme for carbon emissions can be selected from many candidate schemes, providing a scientific basis for decision-making for the low-carbon development of the wind power industry and improving the reliability of layout optimization decisions.

[0008] Furthermore, the step of determining the lifecycle matrix based on the target device data and the transaction device data, combined with material flow analysis technology, specifically involves: The target equipment data is input into a preset lifespan distribution model to obtain retired equipment data; Based on the material conservation principle of wind power equipment, and combining the target equipment data and the decommissioned equipment data, the data for new equipment is determined; Based on the equipment data constraints of wind power equipment, the newly added equipment data and the transaction equipment data are inverted and calculated to obtain the production equipment data. The target equipment data, the newly added equipment data, the retired equipment data, and the production equipment data are respectively mapped to each stage of the wind power equipment's life cycle to obtain the life cycle matrix.

[0009] By employing material flow analysis technology, the material flow of wind power equipment throughout its entire lifecycle—from production, new installations, operation to decommissioning—is fully tracked, ensuring the integrity, closed-loop nature, and logical consistency of the lifecycle data. Utilizing the law of conservation of mass creates inherent mathematical constraints between equipment data at each stage, avoiding data inconsistencies or logical contradictions and improving the reliability of the assessment results. Furthermore, by obtaining production equipment data through inversion calculations, the difficulty of directly obtaining production stage data is overcome, filling data gaps and achieving complete coverage of the entire lifecycle.

[0010] Further, the step of inputting the target equipment data into a preset lifespan distribution model to obtain decommissioned equipment data specifically involves: Obtain historical data on newly added equipment in various regions and years; The historical newly added equipment data is input into the lifespan distribution model to calculate the equipment retirement probability in each region and year based on the operating time of the wind power equipment. The retirement equipment data is obtained by weighted summing of the equipment retirement probabilities for the corresponding years of the candidate layout scheme for all the newly installed capacity in the historical years.

[0011] This probabilistic processing of historical new equipment data based on the lifespan distribution model can accurately reflect the decommissioning patterns of wind power equipment at different operating years. Compared with simply estimating decommissioning based on the design lifespan, it is more in line with the actual decommissioning situation and greatly improves the accuracy of decommissioned equipment data. By introducing two dimensions of refinement, namely region and year, it can capture the differences in decommissioning probability caused by factors such as policy, maintenance level, and wind resource differences in different regions, making the prediction of decommissioned equipment data more refined and regionalized, and applicable to complex scenarios with multi-regional layouts.

[0012] Furthermore, the acquisition of the material demand matrix specifically involves: Obtain the average equipment capacity data of the wind power equipment in various regions and years around the world. Based on the average equipment capacity data, a query is performed in the preset material matrix to obtain the material demand matrix, wherein the preset material matrix is ​​used to characterize the demand of each equipment for each material under different capacities.

[0013] By pre-setting a material matrix, the material requirements of each device under different capacities are standardized. This allows for quick retrieval of the material requirement matrix simply by inputting the average device capacity data, avoiding the tedious process of compiling a material list for each device and significantly improving data processing efficiency. Since device capacity is a key factor affecting material requirements, querying based on capacity can accurately reflect the differences in material requirements between devices with different capacities, avoiding estimation bias caused by uniform averaging.

[0014] Furthermore, the method also includes: Obtain dynamic power carbon emission factors and non-power stationary carbon emission intensity for each region, year, and material; The carbon emission intensity of electricity for each region and material in each year is determined based on the dynamic carbon emission factor. The carbon emission intensity of each material in each region and year is determined based on the electricity carbon emission intensity and the non-electric stationary carbon emission intensity, thus obtaining the emission factor matrix.

[0015] By introducing a dynamic electricity carbon emission factor, the carbon emission assessment results are made time-dynamic, avoiding the assessment distortion caused by using a fixed emission factor. The carbon emission sources are divided into two major categories: electricity and non-electricity. After processing them separately and then combining them, the classification is more scientific and reasonable, and can reflect the different influencing factors of different emission sources.

[0016] Further, the matrix operation performed on the material demand matrix, the emission factor matrix, and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme is specifically as follows: The material demand matrix and the emission factor matrix are multiplied element-wise to obtain the component material carbon emission matrix for each component at each life cycle stage. The carbon emission matrix of the component material is multiplied by the life cycle matrix to obtain the carbon emission matrix for each life cycle stage. The carbon emission matrices of each life cycle stage are summed to obtain the total carbon emission matrix, which is used to characterize the carbon emissions of each region in each year throughout the entire life cycle. The total carbon emissions are obtained by summing all the carbon emissions based on the total carbon emission matrix.

[0017] This matrix operation method is computationally efficient and easily parallelized, enabling rapid evaluation of a large number of candidate layout schemes and meeting the computational needs for comparing multiple schemes in practical engineering.

[0018] Another embodiment of the present invention provides a layout scheme determination system for wind power equipment, including: a data acquisition module, a data calculation module, a carbon emission calculation module, and a scheme determination module; The data acquisition module is used to acquire at least two candidate layout schemes and to acquire a material demand matrix and an emission factor matrix. The material demand matrix is ​​used to characterize the demand of each material at each life cycle stage, and the emission factor matrix is ​​used to characterize the carbon emission intensity of each material in each region at each life cycle stage. Each candidate layout scheme includes target equipment data and traded equipment data of wind power equipment in each region. The data calculation module is used to determine a life cycle matrix for each candidate layout scheme based on the target equipment data and the transaction equipment data, combined with material flow analysis technology. The life cycle matrix is ​​used to characterize the equipment data of the wind power equipment at each stage of its life cycle. The carbon emission calculation module is used to perform matrix operations on the material demand matrix, the emission factor matrix and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme. The scheme determination module is used to select the candidate layout scheme with the smallest total carbon emissions as the target layout scheme based on all the total carbon emissions.

[0019] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of the wind power equipment layout scheme determination method of the present invention.

[0020] Another embodiment of the present invention also provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform the steps of the wind power equipment layout scheme determination method of the present invention.

[0021] Another embodiment of the present invention also provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps of the wind power equipment layout scheme determination method as described in any one aspect. Attached Figure Description

[0022] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating a method for determining the layout scheme of wind power equipment according to an embodiment of the present invention; Figure 2 This is a material flow life cycle stage decomposition diagram provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a layout scheme determination system for wind power equipment provided in an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0026] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0027] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0028] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0029] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0030] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0031] See Figure 1To address the problem that existing technologies neglect the actual material flow during the life cycle stages, leading to inaccurate calculations of total carbon emissions and failing to accurately reflect the carbon emission differences between different layout schemes, an embodiment of the present invention provides a method for determining the layout scheme of wind power equipment, comprising: Step 101: Obtain at least two candidate layout schemes and obtain a material demand matrix and an emission factor matrix, wherein the material demand matrix is ​​used to characterize the demand of each material at each life cycle stage, and the emission factor matrix is ​​used to characterize the carbon emission intensity of each material in each region at each life cycle stage; each candidate layout scheme includes target equipment data and traded equipment data of wind power equipment in each region.

[0032] It should be noted that, as Figure 2 As shown, the complete process of the wind power equipment industry chain is provided, including the raw material production stage, equipment production stage, construction and installation stage, operation and maintenance stage, and recycling and disposal stage. Among them, the raw material production stage is the upstream link of the equipment production stage. In this invention, its material consumption and carbon emissions are included in the carbon emission accounting of the equipment production stage. Under the framework of the layout optimization method provided by this invention, the life cycle stages include the equipment production stage, construction and installation stage, operation and maintenance stage, and recycling and disposal stage.

[0033] Among them, target equipment data refers to the planned installed capacity of wind power equipment in each region in the candidate layout scheme. Transaction equipment data refers to the planned allocation of resources between regions in the candidate layout scheme to meet the planned installed capacity demand of each region, that is, the planned supply relationship between regions in the scheme.

[0034] In this step, multiple candidate layout schemes are obtained from direct user input via an input device; or multiple candidate layout schemes are obtained from optimization algorithms. These optimization algorithms include random generation algorithms, genetic algorithms, particle swarm optimization, simulated annealing, etc. The optimization algorithms generate multiple layout schemes that satisfy preset constraints (such as maximum installed capacity limits for each region, total investment cost limits, etc.) by randomly sampling or iteratively searching in the solution space. Each scheme includes target equipment data for wind power equipment in each region and transaction equipment data between regions. A preset material matrix is ​​obtained from a preset database. This preset material matrix records the unit demand of various major materials (such as steel, copper, aluminum, rare earth, etc.) under different equipment types and capacities. Based on the equipment capacity data for each region in the candidate layout schemes, the preset material matrix is ​​queried to obtain the demand for each material in each region and year, forming a material demand matrix. Dynamic power carbon emission factors for each region and year are obtained from the power planning database, and non-power stationary carbon emission intensity for each material in each region is obtained from the industrial statistics database. The power carbon emission factors are converted into the power carbon emission intensity of each material in each region, and then combined with the corresponding non-power stationary carbon emission intensity to obtain the comprehensive carbon emission intensity of each material in each region at each life cycle stage, forming an emission factor matrix.

[0035] Step 102: For each of the candidate layout schemes, based on the target equipment data and the transaction equipment data, and combined with material flow analysis technology, determine the life cycle matrix, wherein the life cycle matrix is ​​used to characterize the equipment data of the wind power equipment at each life cycle stage.

[0036] Among them, material flow analysis technology is a method for tracking the input, output and inventory of matter in a specific system. It is used to quantify the entire process of matter entering a specific system from nature, flowing and transforming at various stages, and finally returning to nature.

[0037] In this step, the installed capacity and number of wind turbines are used as the basic elements of material flow to construct a full life-cycle material balance model from production, new installation, operation to decommissioning. This model is based on the law of conservation of mass, which states that the total amount of mass entering a certain stage is equal to the sum of the total amount of mass output in that stage and the change in stock. Based on this model, the installed capacity and number of turbines for each candidate layout scheme are calculated to obtain equipment data for the production, new installation, operation, and decommissioning stages of wind turbines, and these data are organized into a life-cycle matrix according to a unified data structure. Furthermore, the flow of each component in the power generation equipment at each stage of its life cycle is obtained to obtain the component-level life-cycle matrix A. c,t,r The components include blades, rotors, towers, gearboxes, generators, etc., with a lifecycle matrix A. c,t,r Represented as: ; in, a cq,ti,rj Representation Component c q In the year t i ,area r j Flow rate (unit: unit or MW).

[0038] Step 103: Perform matrix operations on the material demand matrix, the emission factor matrix, and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme; In this step, the material demand matrix and the emission factor matrix are first multiplied together to obtain the carbon emission intensity matrix of each component at each life cycle stage. Then, the carbon emission intensity matrix is ​​multiplied by the equipment data of the corresponding stage in the life cycle matrix, that is, the number of equipment at each stage is multiplied by the unit carbon emission intensity of the corresponding stage to obtain the carbon emission amount of each life cycle stage. Finally, the carbon emission amounts of all life cycle stages are summed to obtain the total carbon emission of the candidate layout scheme over the entire life cycle.

[0039] Step 104: Based on all the total carbon emissions, select the candidate layout scheme with the smallest total carbon emissions as the target layout scheme.

[0040] In this step, due to significant differences in emission factors across different regions and the varying patterns of equipment activity levels with changes in installed capacity at different lifecycle stages, the total carbon emissions calculated through the aforementioned matrix operations will also change when the installed capacity for each region is set to different values. The total carbon emissions corresponding to each candidate layout scheme are then compared, and the scheme with the lowest value is selected as the target layout scheme, thereby minimizing carbon emissions from wind power equipment layout throughout its entire lifecycle. This target layout scheme includes the optimal installed capacity allocation scheme for wind power equipment in each region and the equipment trading scheme.

[0041] As an example of an embodiment of the present invention, the step of determining the lifecycle matrix based on the target device data and the transaction device data, combined with material flow analysis technology, specifically involves: The target equipment data is input into a preset lifespan distribution model to obtain retired equipment data; Based on the material conservation principle of wind power equipment, and combining the target equipment data and the decommissioned equipment data, the data for new equipment is determined; Based on the equipment data constraints of wind power equipment, the newly added equipment data and the transaction equipment data are inverted and calculated to obtain the production equipment data. The target equipment data, the newly added equipment data, the retired equipment data, and the production equipment data are respectively mapped to each stage of the wind power equipment's life cycle to obtain the life cycle matrix.

[0042] Among them, the lifespan distribution model is a pre-constructed mathematical model used to describe the retirement pattern of wind power equipment. This model is built based on the historical operation data and retirement statistics of wind power equipment and can reflect the retirement probability distribution of equipment under different operating years.

[0043] In this embodiment, the lifetime distribution model can adopt the Weibull distribution model (which conforms to the characteristic that wind turbine lifetimes are "mostly concentrated around the average lifetime"). The probability of decommissioning the newly installed capacity in each historical year in year y can be determined based on the Weibull distribution model, and then the amount of decommissioning can be determined based on the decommissioning probability. Based on material flow analysis technology, a stock-flow conservation system for wind power equipment is established, defining the core dynamic variable: stock (S... y ) represents the cumulative installed capacity (in MW) of the region over y years, i.e., data on decommissioned equipment, characterizing the intensity of activities during the operation and maintenance phase; inflow (I y ) represents the region's newly installed capacity (unit: MW) in year y, i.e., new equipment data, characterizing the intensity of activity during the construction phase; outflow (O y Let be the decommissioning capacity of wind turbines in the region in year y (unit: MW), i.e., the data on decommissioned equipment, representing the intensity of activities during the recovery phase. All three satisfy the law of conservation of mass, expressed as: ; The cumulative installed capacity for the previous year can be obtained from data released by the Global Wind Energy Council (GWEC). Based on the material conservation principle of wind power equipment, the data of newly added equipment is obtained through inversion solution. .

[0044] Because there is a lack of unified and transparent global statistics on wind power equipment manufacturing, this embodiment uses a regional trade flow matrix to invert production equipment data. Specifically, a trade matrix for wind power equipment is defined. ,in, The equipment capacity (in MW) exported from region i to region j; diagonal elements Let be the self-generated and self-consumed equipment capacity (unit: MW) of region i; this matrix satisfies the following constraints: ; ; Based on transaction equipment data and new installed capacity Solve for the diagonal elements of the matrix The actual equipment output in each region was derived. .

[0045] The target equipment data, new equipment data, decommissioned equipment data, and production equipment data are mapped to each stage of the wind power equipment's lifecycle to obtain the lifecycle matrix. Specifically, the target equipment data... Mapping to the activity level of the operation and maintenance phase; adding the new device data Mapping to the activity level of the construction phase; transferring the decommissioned equipment data Mapping activity levels to the recycling phase; transferring production equipment data The activity levels are mapped to the equipment production stage. The activity level data for each stage are organized according to component type and region to obtain the lifecycle matrix.

[0046] As an example of an embodiment of the present invention, the step of inputting the target equipment data into a preset lifespan distribution model to obtain decommissioned equipment data specifically involves: Obtain historical data on newly added equipment in various regions and years; The historical newly added equipment data is input into the lifespan distribution model to calculate the current equipment decommissioning probability in each region based on the operating time of the wind power equipment. The retired equipment data is obtained by weighted summing of the current equipment retirement probabilities corresponding to the new installation volume in all the historical years.

[0047] In this embodiment, the probability density function f(t) of the Weibull distribution model represents the instantaneous decommissioning probability of the wind turbine after t years of operation, and the cumulative distribution function F(t) represents the cumulative decommissioning probability after t years of operation, as shown in the following formula: ; ; Where t represents the wind turbine's operating time (in years); k represents the shape parameter; and η represents the scale parameter (representing the wind turbine's average operating life).

[0048] The number of demobilizations in a certain region in year y ( The formula is: ) is the weighted sum of the decommissioning probabilities of all historical new installations in year y. ; in, Let F(t) represent the newly installed capacity in year yt; F(t) - F(t-1) represent the annual decommissioning probability of the wind turbine after t years of operation.

[0049] As an example of an embodiment of the present invention, the acquisition of the material demand matrix specifically includes: Obtain the average equipment capacity data of the wind power equipment in various regions; Based on the average equipment capacity data, a query is performed in the preset material matrix to obtain the material demand matrix, wherein the preset material matrix is ​​used to characterize the demand of each equipment for each material under different capacities.

[0050] In this embodiment, the average equipment capacity data is the average single-unit capacity of each region in the candidate layout scheme, and the average single-unit capacity of each region and each year constitutes the wind turbine size matrix S. t,r , is represented as: ; Among them, S ti, rj Indicates the year t i Region r j The average single-unit capacity of wind turbines (unit: MW); n is the year number, and k is the region number.

[0051] A lifecycle inventory analysis is performed on wind turbines of different size classes to collect material input data for each component in the entire wind power equipment at different size classes, forming a standardized material consumption database. Based on this standardized material consumption database, a pre-defined material matrix at the component level is generated. The average equipment capacity data is matched with each size class in the pre-defined material matrix to determine the size class to which the average equipment capacity belongs. The unit material consumption of each component at that size class throughout its lifecycle is then read to obtain the material requirement matrix Q. c,s,m , is represented as: ; in, q cq,su,mp Representation Component c q In size s u Below are the materials m p Consumption (unit: tons of material / unit or tons of material / MW). u This refers to discrete fan size classifications.

[0052] As an example of an embodiment of the present invention, the method further includes: Obtain the current electricity carbon emission factor and non-electric stationary carbon emission intensity for each region and material; Determine the carbon emission intensity of electricity for each material in each region based on the current electricity carbon emission factor; The carbon emission intensity of each material in each region is determined based on the electricity carbon emission intensity and the non-electric stationary carbon emission intensity, thus obtaining the emission factor matrix.

[0053] In this embodiment, baseline emission factors for typical industrial substances in various regions are extracted from authoritative global LCA databases (including Gabi Professional and Ecoinvent databases). For regions where precise matching is not possible, default values ​​from the Other World (RoW) are used to supplement the dataset, forming an initial emission factor dataset covering the entire globe. Current electricity carbon emission factors are obtained from regional power structure data published by organizations such as the International Energy Agency (IEA), representing the carbon dioxide emissions generated per unit of electricity consumed in the target year (unit: tons). For high-emission contributors, key materials such as steel, iron, aluminum, resin, and concrete were selected. The emission factors of each material were decomposed into two parts: electricity-related and non-electricity stationary. The non-electricity stationary part was calculated by subtracting electricity-related emissions from the baseline emission factor and was treated as a time invariant in subsequent years. The electricity carbon emission intensity of each material in each region was determined based on the current electricity carbon emission factor. The electricity dynamic part was dynamically generated based on the product of the unit electricity consumption of the material production and the annual electricity carbon emission factor of the region. The carbon emission intensity of each material in each region was determined based on the electricity carbon emission intensity and the non-electricity stationary carbon emission intensity, resulting in the emission factor matrix EF. m,t,r , is represented as: ; in, ef mp,ti,rj Material m p In the year t i ,area r j Carbon emission intensity (unit: tons) (Unit materials) p This represents the number of material types.

[0054] As an example of an embodiment of the present invention, the step of performing matrix operations on the material demand matrix, the emission factor matrix, and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme is specifically as follows: The material demand matrix and the emission factor matrix are multiplied element-wise to obtain the component material carbon emission matrix for each component at each life cycle stage. The carbon emission matrix of the component material is multiplied by the life cycle matrix to obtain the carbon emission matrix for each life cycle stage. The carbon emission matrices of each life cycle stage are summed to obtain the total carbon emission matrix, which is used to characterize the carbon emissions of each region throughout the entire life cycle. The total carbon emissions are obtained by summing all the carbon emissions based on the total carbon emission matrix.

[0055] In this embodiment, the material demand matrix Q is... c,s,m With emission factor matrix Perform element-wise multiplication and multiply by the component-level lifecycle matrix A. c,t,r Perform matrix multiplication to obtain the carbon emission matrix of a single component at each stage of its life cycle. E c,t,r , is represented as: ; in, Hadamard product (element-level multiplication) is used to calculate the carbon emissions of materials. The calculation results are in millions of tons. .

[0056] The total carbon emissions matrix over the entire life cycle is as follows: ; Therefore, by using matrix operations to achieve spatiotemporal coupling of three key dynamic factors, the accuracy and practicality of global wind power carbon footprint assessment can be significantly improved.

[0057] Furthermore, to overcome the geographical attribution bias of carbon emissions caused by cross-border trade in components, after determining the life cycle matrix based on target equipment data and traded equipment data, a step to correct carbon emission attribution is also included. Specifically, for key components such as towers and generators, the net export volume of key components in each region is calculated based on the import and export trade data of such components in each region. The corrected formula is: ,in, For carbon emissions, Let k be the net export volume of this component in region k. This refers to the emission factor per unit capacity of the components. Through the above correction, the carbon emissions at the whole turbine level are broken down and adjusted at the component level. On the one hand, this solves the problem of cross-border flow of components that cannot be covered by whole turbine trade data. On the other hand, it realizes the transformation from "accounting at the place of production" to "accounting at the place of final use," so that the carbon emission accounting results of the wind power industry in various regions more accurately reflect their actual consumption responsibility and avoid carbon leakage caused by trade activities.

[0058] like Figure 3 As shown, based on the above-mentioned method embodiments, an embodiment of the present invention provides a wind power equipment layout scheme determination system 300, including: a data acquisition module 301, a data calculation module 302, a carbon emission calculation module 303, and a scheme determination module 304; The data acquisition module 301 is used to acquire at least two candidate layout schemes and to acquire a material demand matrix and an emission factor matrix. The material demand matrix is ​​used to characterize the demand of each material at each life cycle stage, and the emission factor matrix is ​​used to characterize the carbon emission intensity of each material in each region at each life cycle stage. Each candidate layout scheme includes target equipment data and traded equipment data of wind power equipment in each region. The data calculation module 302 is used to determine a life cycle matrix for each candidate layout scheme based on the target equipment data and the transaction equipment data, combined with material flow analysis technology. The life cycle matrix is ​​used to characterize the equipment data of the wind power equipment at each life cycle stage. The carbon emission calculation module 303 is used to perform matrix operations on the material demand matrix, the emission factor matrix and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme. The scheme determination module 304 is used to select the candidate layout scheme with the smallest total carbon emissions as the target layout scheme based on all the total carbon emissions.

[0059] Furthermore, the data calculation module 302 is also used for: The target equipment data is input into a preset lifespan distribution model to obtain retired equipment data; Based on the material conservation principle of wind power equipment, and combining the target equipment data and the decommissioned equipment data, the data for new equipment is determined; Based on the equipment data constraints of wind power equipment, the newly added equipment data and the transaction equipment data are inverted and calculated to obtain the production equipment data. The target equipment data, the newly added equipment data, the retired equipment data, and the production equipment data are respectively mapped to each stage of the wind power equipment's life cycle to obtain the life cycle matrix.

[0060] Further, the step of inputting the target equipment data into a preset lifespan distribution model to obtain decommissioned equipment data specifically involves: Obtain historical data on newly added equipment in various regions and years; The historical newly added equipment data is input into the lifespan distribution model to calculate the current equipment decommissioning probability in each region based on the operating time of the wind power equipment. The retired equipment data is obtained by weighted summing of the current equipment retirement probabilities corresponding to the new installation volume in all the historical years.

[0061] Furthermore, the data acquisition module 301 is also used for: Obtain the average equipment capacity data of the wind power equipment in various regions; Based on the average equipment capacity data, a query is performed in the preset material matrix to obtain the material demand matrix, wherein the preset material matrix is ​​used to characterize the demand of each equipment for each material under different capacities.

[0062] Furthermore, system 300 is also used for: Obtain the current electricity carbon emission factor and non-electric stationary carbon emission intensity for each region and material; Determine the carbon emission intensity of electricity for each material in each region based on the current electricity carbon emission factor; The carbon emission intensity of each material in each region is determined based on the electricity carbon emission intensity and the non-electric stationary carbon emission intensity, thus obtaining the emission factor matrix.

[0063] Furthermore, the carbon emission calculation module 303 is also used for: The material demand matrix and the emission factor matrix are multiplied element-wise to obtain the component material carbon emission matrix for each component at each life cycle stage. The carbon emission matrix of the component material is multiplied by the life cycle matrix to obtain the carbon emission matrix for each life cycle stage. The carbon emission matrices of each life cycle stage are summed to obtain the total carbon emission matrix, which is used to characterize the carbon emissions of each region throughout the entire life cycle. The total carbon emissions are obtained by summing all the carbon emissions based on the total carbon emission matrix.

[0064] It is understood that the above system embodiments correspond to the method embodiments of the present invention, and can implement all the implementation methods of any of the above method embodiments of the present invention, which will not be repeated here.

[0065] It should be noted that the system embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the system embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0066] Based on the above embodiments of the wind power equipment layout scheme determination method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the wind power equipment layout scheme determination method of any of the above embodiments of the present invention, which will not be described in detail here.

[0067] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0068] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0069] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0070] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the wind power equipment layout scheme determination method described in any of the above-described method embodiments of the present invention, which will not be repeated here.

[0071] Based on the above-described method embodiments, this invention further provides a computer program / program product, which is stored in a storage medium and executed by at least one processor to implement the wind power equipment layout scheme determination method described in any of the above-described method embodiments, which will not be elaborated further here.

[0072] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0073] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for determining the layout scheme of wind power equipment, characterized in that, include: At least two candidate layout schemes are obtained, and a material demand matrix and an emission factor matrix are obtained. The material demand matrix is ​​used to characterize the demand of each material at each life cycle stage, and the emission factor matrix is ​​used to characterize the carbon emission intensity of each material in each region at each life cycle stage. Each candidate layout scheme includes target equipment data and traded equipment data of wind power equipment in each region. For each of the candidate layout schemes, a lifecycle matrix is ​​determined based on the target equipment data and the transaction equipment data, combined with material flow analysis technology. The lifecycle matrix is ​​used to characterize the equipment data of the wind power equipment at each stage of its lifecycle. Matrix operations are performed on the material demand matrix, the emission factor matrix, and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme; Based on the total carbon emissions mentioned above, the candidate layout scheme with the minimum total carbon emissions is selected as the target layout scheme.

2. The method for determining the layout scheme of wind power equipment as described in claim 1, characterized in that, The step of determining the lifecycle matrix based on the target device data and the transaction device data, combined with material flow analysis technology, specifically involves: The target equipment data is input into a preset lifespan distribution model to obtain retired equipment data; Based on the material conservation principle of wind power equipment, and combining the target equipment data and the decommissioned equipment data, the data for new equipment is determined; Based on the equipment data constraints of wind power equipment, the newly added equipment data and the transaction equipment data are inverted and calculated to obtain the production equipment data. The target equipment data, the newly added equipment data, the retired equipment data, and the production equipment data are respectively mapped to each stage of the wind power equipment's life cycle to obtain the life cycle matrix.

3. The method for determining the layout scheme of wind power equipment as described in claim 2, characterized in that, The step of inputting the target equipment data into a preset lifespan distribution model to obtain decommissioned equipment data specifically involves: Obtain historical data on newly added equipment in various regions and years; The historical newly added equipment data is input into the lifespan distribution model to calculate the current equipment decommissioning probability in each region based on the operating time of the wind power equipment. The retired equipment data is obtained by weighted summing of the current equipment retirement probabilities corresponding to the new installation volume in all the historical years.

4. The method for determining the layout scheme of wind power equipment as described in claim 1, characterized in that, The acquisition of the material requirement matrix specifically involves: Obtain the average equipment capacity data of the wind power equipment in various regions; Based on the average equipment capacity data, a query is performed in the preset material matrix to obtain the material demand matrix, wherein the preset material matrix is ​​used to characterize the demand of each equipment for each material under different capacities.

5. The method for determining the layout scheme of wind power equipment as described in claim 1, characterized in that, The method further includes: Obtain the current electricity carbon emission factor and non-electric stationary carbon emission intensity for each region and material; Determine the carbon emission intensity of electricity for each material in each region based on the current electricity carbon emission factor; The carbon emission intensity of each material in each region is determined based on the electricity carbon emission intensity and the non-electric stationary carbon emission intensity, thus obtaining the emission factor matrix.

6. The method for determining the layout scheme of wind power equipment as described in claim 1, characterized in that, The matrix operation on the material demand matrix, the emission factor matrix, and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme is specifically as follows: The material demand matrix and the emission factor matrix are multiplied element-wise to obtain the component material carbon emission matrix for each component at each life cycle stage. The carbon emission matrix of the component material is multiplied by the life cycle matrix to obtain the carbon emission matrix for each life cycle stage. The carbon emission matrices of each life cycle stage are summed to obtain the total carbon emission matrix, which is used to characterize the carbon emissions of each region throughout the entire life cycle. The total carbon emissions are obtained by summing all the carbon emissions based on the total carbon emission matrix.

7. A system for determining the layout scheme of wind power equipment, characterized in that, include: The system includes a data acquisition module, a data calculation module, a carbon emission calculation module, and a scheme determination module. The data acquisition module is used to acquire at least two candidate layout schemes and to acquire a material demand matrix and an emission factor matrix. The material demand matrix is ​​used to characterize the demand of each material at each life cycle stage, and the emission factor matrix is ​​used to characterize the carbon emission intensity of each material in each region at each life cycle stage. Each candidate layout scheme includes target equipment data and traded equipment data of wind power equipment in each region. The data calculation module is used to determine a life cycle matrix for each candidate layout scheme based on the target equipment data and the transaction equipment data, combined with material flow analysis technology. The life cycle matrix is ​​used to characterize the equipment data of the wind power equipment at each stage of its life cycle. The carbon emission calculation module is used to perform matrix operations on the material demand matrix, the emission factor matrix and the life cycle matrix to obtain the total carbon emissions corresponding to each candidate layout scheme. The scheme determination module is used to select the candidate layout scheme with the smallest total carbon emissions as the target layout scheme based on all the total carbon emissions.

8. A terminal device, characterized in that, The method includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, it implements the method for determining the layout scheme of wind power equipment as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the layout scheme determination method for wind power equipment as described in any one of claims 1-6.

10. A computer program product, characterized in that, include: Computer instructions, when executed by a processor, implement the steps in the method for determining the layout scheme of wind power equipment as described in any one of claims 1 to 6.

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