Zero-carbon power supply station full-life-cycle carbon emission accounting and effect evaluation method, system and device and medium

Abstract

The invention discloses a zero-carbon power supply station full-life-cycle carbon emission accounting and effect evaluation method, system and device and a medium, and belongs to the technical field of carbon emission management, and the method comprises the steps: guaranteeing complete coverage through defining physical and logic accounting boundaries, achieving the credible collection and evidence storage of carbon emission data based on the multi-source monitoring and block chain technology, and achieving the real-time analysis of the carbon emission. A multi-method system integrating full-life-cycle analysis and dynamic carbon factor correction is adopted to achieve accurate accounting, an evaluation system covering multi-dimensional indexes is constructed, graded evaluation is conducted through stepped rating, and finally an improved scheme is formed. According to the method, through physical and logic double-boundary division and combination of a hierarchical decoupling model, the full-scene emission source of the power supply station is defined, and the accounting error of cross-regional power transmission carbon emission is reduced; through fusion of a full life cycle analysis method and a dynamic correction mechanism, accurate quantitative accounting of carbon emission is realized.

Description

Technical Field

[0001] This invention relates to the field of carbon emission management technology, specifically to a method, system, equipment, and medium for carbon emission accounting and effectiveness evaluation throughout the entire life cycle of a zero-carbon power supply station. Background Technology

[0002] Traditional accounting relies on manual reporting or low-frequency data collection, lacking intelligent monitoring methods for power supply station scenarios. Data collection dimensions are missing: data related to clean power, such as distributed photovoltaic and energy storage charging and discharging losses, are not included in the collection scope, making it impossible to quantify the carbon reduction effect of clean energy substitution. Data credibility is insufficient: there is no data traceability and anti-tampering mechanism, and activity data (such as fuel consumption and office energy consumption) are prone to human error, affecting the validity of accounting results.

[0003] Existing carbon emission accounting standards (such as the "Guidelines for Enterprise Greenhouse Gas Emission Accounting Methods and Reporting for Power Generation Facilities") only focus on enterprise-level or industry-level granularity and do not clearly define the accounting boundaries for the dual attributes of power supply stations ("building + power service"): At the physical boundary level, special emission sources such as mobile sources (maintenance vehicles) and ancillary facilities (charging piles, emergency generators) under the jurisdiction of power supply stations are not defined, which can easily lead to omissions or duplications in the accounting scope; At the logical boundary level, the carbon emission allocation for cross-regional power transmission adopts the "average electric carbon factor method", which does not take into account the dynamic changes of regional power grid flow, and the accounting error is as high as 50% or more, making it impossible to accurately trace the indirect carbon emission responsibility of purchased electricity.

[0004] Existing technologies have not established a closed-loop logic of "accounting-evaluation-optimization". The specific problem is that the accounting results are only used for carbon emission statistics and cannot directly support the evaluation of the effectiveness of zero-carbon construction, nor can they output targeted technical optimization solutions, resulting in low application value of accounting data. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention provides a method, system, equipment and medium for carbon emission accounting and effectiveness evaluation of the entire life cycle of zero-carbon power supply stations.

[0006] Therefore, the technical problem solved by this invention is that: the invention aims to solve the technical problems of traditional methods, such as: excessive error due to fuzzy accounting boundaries; scattered and unreliable data sources; single and unspecific evaluation dimensions; and disconnected management links that make it difficult to form a closed loop.

[0007] To address the aforementioned technical problems, this invention provides the following technical solution: a method for carbon emission accounting and effectiveness evaluation throughout the entire life cycle of a zero-carbon power supply station, comprising, The dual boundaries for carbon emission accounting are defined by dividing the physical boundaries into logical boundaries.

[0008] The system collects direct and indirect carbon emission data and auxiliary data in real time through monitoring equipment, and performs credible processing and data storage on the direct and indirect carbon emission data and auxiliary data.

[0009] The power supply station is divided into different life cycle stages. For each stage, life cycle analysis method, fuel emission factor method, measurement method and carbon emission flow theory are integrated for calculation. The emission factor is dynamically corrected based on the real-time carbon intensity data of the regional power grid.

[0010] An evaluation index system was constructed, the weight of each evaluation index was determined based on a multi-criteria decision analysis method, and the evaluation results were graded based on a tiered rating standard.

[0011] Based on the accounting and evaluation results, optimization solutions covering the energy supply side, end-user energy side, and management side are output for indicators that have not met the standards.

[0012] As a preferred embodiment of the method for carbon emission accounting and effectiveness evaluation throughout the entire life cycle of a zero-carbon power supply station as described in this invention, the step of defining the dual boundaries of carbon emission accounting by dividing physical boundaries into logical boundaries includes: The physical boundaries for carbon emission accounting are defined based on the geographical jurisdiction and asset ownership of the power supply station.

[0013] Based on a multi-level coupled accounting model, a logical boundary is established that includes direct carbon emissions and indirect carbon emissions.

[0014] The calculation of indirect carbon emissions adopts a formula that integrates the fixed carbon factor of the primary power grid and the dynamic carbon factor of the regional power grid.

[0015] As a preferred embodiment of the method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle as described in this invention, the process of making direct and indirect carbon emission data and auxiliary data credible and storing evidence includes, The collected direct and indirect carbon emission data and auxiliary data are standardized using a local data processor.

[0016] Standardized direct and indirect carbon emission data, as well as auxiliary data, will be stored on the blockchain using blockchain technology.

[0017] As a preferred embodiment of the method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle as described in this invention, the method of dividing the power supply station into different life cycle stages includes: The implicit carbon emissions from the production process of building materials for power supply stations are accounted for during the building materials production stage.

[0018] During the construction phase, calculate the carbon emissions corresponding to the energy consumption of construction machinery and transportation.

[0019] The direct and indirect carbon emissions of the power supply station during its operation and maintenance phase are accounted for.

[0020] The carbon emissions from building demolition and equipment scrapping and recycling processes are calculated during the demolition and recycling phase.

[0021] As a preferred embodiment of the zero-carbon power supply station life-cycle carbon emission accounting and effectiveness evaluation method described in this invention, the method of calculating emissions at different stages by integrating life-cycle analysis methods, fuel emission factor methods, measured methods, and carbon emission flow theory, and dynamically correcting emission factors based on real-time carbon intensity data of the regional power grid, includes: Life cycle analysis was used to calculate carbon emissions based on the ISO 14040 standard during the building materials production, construction, and demolition / recycling phases.

[0022] During the operation and maintenance phase, the fuel emission factor method, the measured method, and the carbon emission flow theory are used simultaneously for collaborative accounting and cross-validation.

[0023] During the calculation process, real-time carbon intensity data from the regional power grid is incorporated to dynamically correct and update the accounting factors for indirect carbon emissions monthly.

[0024] The beneficial effects of this preferred technical solution are that by applying life cycle analysis methods to the building materials, construction and demolition stages, and combining the fuel factor method, measured method and carbon emission flow theory in the operation stage for multi-method collaborative verification, accurate accounting of the entire life cycle from construction to demolition is achieved. At the same time, by introducing real-time carbon intensity data of the regional power grid and dynamically correcting the accounting factors monthly, the timeliness and accuracy of indirect carbon emission accounting in the operation stage are improved.

[0025] As a preferred embodiment of the zero-carbon power supply station life-cycle carbon emission accounting and effectiveness evaluation method described in this invention, the following steps are included: constructing an evaluation index system, determining the weight of each evaluation index based on a multi-criteria decision analysis method, and classifying the evaluation results based on a tiered rating standard. Construct a multi-dimensional evaluation index system for the effectiveness of zero-carbon construction, covering energy supply, end-use energy consumption, system operation, accounting quality, digital management, economic benefits, and social impact.

[0026] By employing a multi-criteria decision analysis method, the correlation and weight of evaluation indicators at each level are determined through comprehensive expert judgment.

[0027] Based on a pre-set tiered rating standard, the effectiveness of zero-carbon construction in power supply stations is divided into three levels: basic, advanced, and zero-carbon.

[0028] The beneficial effects of this preferred technical solution are as follows: by constructing a multi-dimensional evaluation index system covering energy supply, end-user energy consumption, system operation, accounting quality, digital management, economic benefits, and social impact, it comprehensively reflects the overall effectiveness of zero-carbon construction of power supply stations; by using a multi-criteria decision analysis method to comprehensively determine the index weights based on expert judgment, it enhances the scientificity and objectivity of the evaluation; and by dividing the effectiveness into three levels—basic, advanced, and zero-carbon—based on a tiered rating standard, it provides a clear improvement ladder and benchmarking targets for power supply stations at different construction stages, thereby improving the guidance and operability of the evaluation results.

[0029] As a preferred embodiment of the zero-carbon power supply station life-cycle carbon emission accounting and performance evaluation method described in this invention, the optimized scheme for outputting non-compliant indicators covering the energy supply side, end-user energy consumption side, and management side includes: On the energy supply side, adjustments should be made to the layout of photovoltaic modules and the charging and discharging strategies of energy storage systems should be optimized.

[0030] For end-user energy consumption, we will promote the electrification of maintenance vehicles and implement energy-saving renovations of buildings.

[0031] On the management side, we will improve the functions of the carbon management platform and strengthen carbon business training for employees.

[0032] The beneficial effects of this preferred technical solution are that by conducting targeted analysis of the non-compliant indicators and outputting specific and feasible optimization solutions from the energy supply side, the end-user energy side, and the management side respectively, it realizes a closed-loop management of the entire chain from energy structure optimization and energy efficiency improvement to management system improvement, thereby systematically promoting the continuous reduction of carbon emissions from power supply stations and substantial progress in zero-carbon construction.

[0033] This invention provides a system for calculating and evaluating the carbon emissions of a zero-carbon power supply station throughout its entire life cycle.

[0034] To address the aforementioned technical problems, this invention provides the following technical solution: a zero-carbon power supply station full life cycle carbon emission accounting and effectiveness evaluation system, comprising: a boundary and model management module, a carbon-energy flow collaborative monitoring and credible evidence storage module, a full life cycle dynamic accounting engine, a multi-dimensional intelligent evaluation and grading module, and an optimization decision and scheme generation module.

[0035] The boundary and model management module defines the dual boundaries for carbon emission accounting by dividing physical boundaries into logical boundaries.

[0036] The carbon-energy flow collaborative monitoring and credible evidence storage module collects direct and indirect carbon emission data and auxiliary data in real time through monitoring equipment, and performs credible processing and evidence storage on the direct and indirect carbon emission data and auxiliary data.

[0037] The full life cycle dynamic accounting engine divides the power supply station into different life cycle stages, integrates life cycle analysis methods, fuel emission factor method, actual measurement method and carbon emission flow theory to perform accounting for different stages, and dynamically corrects the emission factor based on the real-time carbon intensity data of the regional power grid.

[0038] The multidimensional intelligent assessment and grading module constructs an assessment index system, determines the weight of each assessment index based on a multi-criteria decision analysis method, and grades the assessment results based on a tiered rating standard.

[0039] Based on the accounting and evaluation results, optimization solutions covering the energy supply side, end-user energy side, and management side are output for indicators that do not meet the standards.

[0040] The present invention provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the method for calculating and evaluating the carbon emissions of a zero-carbon power supply station throughout its entire life cycle.

[0041] The present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method for calculating and evaluating the carbon emissions of a zero-carbon power supply station throughout its entire life cycle.

[0042] The beneficial effects of this invention are as follows: By dividing the physical and logical boundaries and combining them with a hierarchical decoupling model, this invention defines the emission sources of power supply stations across all scenarios and reduces the calculation error of carbon emissions from cross-regional power transmission; by integrating a full life cycle analysis method and a dynamic correction mechanism, it achieves accurate quantitative accounting of carbon emissions; by constructing an indicator system and a tiered rating mechanism covering technical, economic, and social dimensions, it provides a highly adaptable and guiding zero-carbon assessment path for power supply stations at different construction stages; by deploying a carbon-energy flow collaborative monitoring system and integrating blockchain evidence storage technology, it achieves real-time collection and reliable management of multi-source data, ensuring data quality and traceability from the source. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 The above is a flowchart of a method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle, provided as an embodiment of the present invention.

[0045] Figure 2This is a schematic diagram of a scheme module for a zero-carbon power supply station's full life-cycle carbon emission accounting and effectiveness evaluation system, provided as an embodiment of the present invention. Detailed Implementation

[0046] To make the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0047] Example 1, referring to Figure 1 This is one embodiment of the present invention, which provides a method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle, including: S1. Define the dual boundaries for carbon emission accounting by dividing the physical boundaries into logical boundaries.

[0048] S2. Collect direct and indirect carbon emission data and auxiliary data in real time through monitoring equipment, and perform credibility processing and evidence storage on the direct and indirect carbon emission data and auxiliary data.

[0049] S3. Divide the power supply station into different life cycle stages, and calculate the emission factors by integrating life cycle analysis methods, fuel emission factor method, actual measurement method and carbon emission flow theory for different stages. Dynamically correct the emission factors based on the real-time carbon intensity data of the regional power grid.

[0050] S4. Construct an evaluation index system, determine the weight of each evaluation index based on the multi-criteria decision analysis method, and classify the evaluation results based on the tiered rating standard.

[0051] S5. Based on the accounting and evaluation results, output optimization solutions covering the energy supply side, end-user energy side and management side for indicators that have not met the standards.

[0052] This invention defines the scope of carbon emission accounting for power supply stations and reduces accounting errors in cross-regional power transmission by constructing a dual-boundary model of physical and logical decoupling. Relying on carbon-energy flow collaborative monitoring and blockchain evidence storage technology, it achieves real-time acquisition and tamper-proof storage of multi-source data, ensuring data quality and credibility. It employs a full-lifecycle multi-method fusion accounting and dynamic carbon factor correction mechanism to improve the accuracy and timeliness of carbon emission quantification. It establishes a multi-dimensional indicator system and a tiered hierarchical evaluation method, providing a path for evaluating the effectiveness of zero-carbon construction for power supply stations. Finally, based on the accounting and evaluation results, it outputs targeted optimization solutions, forming a closed-loop technology system encompassing "monitoring-accounting-evaluation-optimization."

[0053] Example 2, an embodiment of the present invention, provides a method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle, based on the previous embodiment, including: In S1, defining the dual boundaries for carbon emission accounting by dividing the physical boundaries into logical boundaries includes steps A1-A3: A1. Delineate the physical boundaries for carbon emission accounting based on the geographical jurisdiction and asset ownership of the power supply station.

[0054] Specifically, the physical boundary delineation is as follows: the coverage includes fixed facilities (substations, office buildings, charging piles, emergency generators), mobile sources (maintenance vehicles, repair vehicles), external power access links and ancillary facilities (canteens, dormitories) under the jurisdiction of the power supply station, based on the geographical jurisdiction of the power supply station, excluding public energy consumption shared by the power grid company headquarters or municipal units.

[0055] A2. Based on a multi-level coupled accounting model, establish a logical boundary that includes direct carbon emissions and indirect carbon emissions.

[0056] A3. The calculation of indirect carbon emissions adopts a calculation formula that integrates the fixed carbon factor of the primary power grid and the dynamic carbon factor of the regional power grid.

[0057] In the embodiments of this application, the multi-level coupling accounting model in A2 is a hierarchical decoupling model. Specifically, it includes adopting a hierarchical decoupling model. The core idea of ​​the hierarchical decoupling model originates from the research on accurate hierarchical and zonal accounting of large-scale power grids in the field of power grid carbon emission accounting. Previous studies have addressed the problem of large errors in carbon emission accounting for provincial and above power grids by proposing a power supply carbon emission factor calculation model that takes into account the hierarchical and zonal decoupling of large-scale power grids. This research divides the power grid into 500kV and above (primary grid), 220kV and below decouplingable areas (secondary grid), and 220kV and below non-decoupling areas (tertiary grid). By calculating the power exchange and the proportion of various types of power generation in each level of the power grid step by step, it solves the error problem caused by the traditional unified carbon emission factor estimation. Its core logic is to decompose the carbon flow path of the complex power grid through hierarchical division and accurately match the energy structure of different levels of power grids. This provides a core technical reference for the design of the hierarchical decoupling model for the power supply station scenario in this patent. However, existing research focuses on medium and large-scale power grids at the provincial and regional levels, failing to adapt to the characteristics of power supply stations with "small granularity and multiple emission sources in various scenarios." This invention addresses this by optimizing the scenario-based approach, specifically dividing power supply station carbon emissions into direct carbon emissions (consumption of fossil fuels and electricity production) and indirect carbon emissions (purchased electricity). Specifically, indirect carbon emissions from primary power grids (national / provincial) are calculated using a fixed carbon factor, while regional power grids (municipal / county) dynamically allocate carbon emissions based on power flow data. The calculation formula is as follows: in, Indirect carbon emissions from purchased electricity For purchased electricity, To fix carbon factors for primary power grids, For the regional power grid dynamic carbon factor, This represents the proportion of electricity generated by the primary power grid.

[0058] In one optional implementation, the multi-level coupled accounting model can be a chain-like allocation model based on hierarchical decomposition of responsibilities. Specifically, it includes: first, calculating the baseline indirect carbon emissions carried by purchased electricity based on the annual average carbon emission intensity of the national or provincial power grid; then, obtaining real-time or day-ahead power flow data and corresponding carbon flow density distribution of the power grid (city / county level) where the power supply station is located; tracing the power load of the power supply station to specific power generation units (such as thermal power, wind power, photovoltaic, etc.) within the regional power grid based on the power flow tracing algorithm; and decomposing the baseline carbon emissions into two parts based on the tracing results: one part corresponds to the carbon emissions avoided by the actual power supply of clean energy within the regional power grid, which is deducted; the other part corresponds to the additional carbon emissions generated by the power supply of fossil energy units within the regional power grid, which is dynamically accumulated based on their actual power generation carbon intensity.

[0059] In another optional implementation, the multi-level coupled accounting model can also be a dynamic coupled estimation model based on data fusion and machine learning. Specific implementation details include: constructing a dataset containing multi-dimensional features such as power grid hierarchy, historical electricity generation, power generation structure, and meteorological factors; training a dynamic coupling function using machine learning algorithms, with inputs including purchased electricity from power supply stations, time, and real-time operating status of the regional power grid, and outputting a coupled and corrected comprehensive carbon emission factor; the goal of training this model is to minimize the error between the estimation results and simulation results based on detailed physical models or high-precision measured data. In actual accounting, the trained coupling function is directly called, combined with real-time input data, to output an integrated carbon factor that integrates the influence of fixed factors from the upper-level power grid and the dynamic characteristics of the regional power grid, used for one-step calculation of indirect carbon emissions.

[0060] In the embodiments of this application, the trust processing and evidence storage in S2, namely blockchain technology on-chain evidence storage, specifically includes generating data packets with timestamps, data fingerprints and unique identifiers from standardized carbon emission data preprocessed by the edge computing gateway, and calling the blockchain smart contract to synchronously write the hash value and key metadata of the data packets into the distributed ledger, thereby ensuring that all data operations are traceable and tamper-proof, and that the consistency of the data can be verified through the consensus mechanism.

[0061] In one alternative implementation, trusted processing and evidence storage can be achieved through a private blockchain or consortium blockchain architecture. Specifically, this includes: deploying blockchain nodes locally at the power supply station or within the power grid company; uploading pre-processed data to the blockchain via a standardized interface; automatically completing data verification, hash calculation, and block packaging through pre-built smart contracts; and having multiple business nodes participating in consensus jointly maintain the ledger.

[0062] In another alternative implementation, trusted processing and evidence storage can also be achieved by combining with a public blockchain platform. Specifically, this includes submitting the hash value and digest information of the data to a credible public blockchain network for evidence storage via an API interface, while storing the complete data in a local or cloud-based secure database, forming a lightweight trusted evidence storage solution that combines "on-chain evidence storage and off-chain storage," which has both data security and system scalability.

[0063] Furthermore, the credibility processing and verification of direct and indirect carbon emission data and auxiliary data in S2 includes steps B1-B2: B1. Standardize the collected direct and indirect carbon emission data and auxiliary data through a local data processor.

[0064] B2. Standardized direct and indirect carbon emission data and auxiliary data will be stored on the blockchain using blockchain technology.

[0065] In this application embodiment, the local data processor in B1, i.e., the edge computing gateway, is specifically responsible for real-time processing of raw monitoring data at the data source. Its specific implementation details include: deploying key energy nodes at the power supply station site (such as power distribution rooms, next to photovoltaic inverters, and in charging pile group control cabinets) to receive raw data streams from heterogeneous sensors such as smart meters, carbon meters, and vehicle terminals; filtering out invalid data such as communication anomalies and instantaneous peaks through built-in data cleaning algorithms; formatting and standardizing the data according to a preset unified data model; and extracting key features (such as time period, device ID, energy consumption value, and carbon emission equivalent) to form lightweight standardized data packets for subsequent transmission and storage.

[0066] In one alternative implementation, the local data processor can be an embedded industrial gateway device that has a built-in multi-protocol adapter module (supporting Modbus, DL / T645, MQTT, etc.), a lightweight edge computing unit, and a security encryption chip. It can perform data protocol parsing, preliminary aggregation calculation, and data desensitization on-site, and securely push the processed data to the upper-level system or blockchain node through wired or 5G wireless networks.

[0067] In another alternative implementation, the local data processor can also be an edge computing software platform deployed on the local server or industrial control computer of the power supply station. This platform runs in a virtualized or containerized form, integrating functions such as data access, stream processing, rule engine and local storage. It can process business logic (such as multi-source data correlation analysis and preliminary real-time carbon emission estimation) and supports docking with blockchain evidence storage services through API.

[0068] Furthermore, the division of the power supply station into different life cycle stages in S3 includes steps C1-C4: C1. Calculate the implicit carbon emissions of the power supply station's building materials production process during the building materials production stage.

[0069] C2. Calculate the carbon emissions corresponding to the energy consumption of construction machinery and transportation during the construction phase.

[0070] C3. Calculate the direct and indirect carbon emissions of the power supply station during its operation and maintenance phase.

[0071] C4. Calculate the carbon emissions of building demolition and equipment scrapping and recycling processes during the demolition and recycling phase.

[0072] Furthermore, step S3 involves calculating emissions at different stages using integrated life cycle analysis methods, fuel emission factor methods, measured methods, and carbon emission flow theory, and dynamically correcting emission factors based on real-time carbon intensity data from the regional power grid, including steps D1-D3: D1. Use life cycle analysis methods to calculate carbon emissions based on ISO 14040 standards during the building material production, construction, and demolition / recycling phases.

[0073] D2. For the operation and maintenance phase, the fuel emission factor method, the measured method and the carbon emission flow theory are used simultaneously for collaborative accounting and cross-validation.

[0074] Specifically, in, For the j-th type of fuel consumption, As a fuel emission factor, Let k be the electricity consumption of the branch. Here, m represents the number of fuel types corresponding to direct emissions, and p represents the number of electricity-consuming branches. This indicates direct carbon emissions. Indicates indirect carbon emissions. This represents the total carbon emissions.

[0075] D3. During the accounting process, real-time carbon intensity data of the regional power grid is introduced to dynamically correct and update the accounting factors for indirect carbon emissions monthly.

[0076] Specifically, this includes adjusting the emission factor monthly based on real-time carbon intensity data from the regional power grid, and adjusting the coefficient. The deviation rate between the regional power grid carbon emission intensity and the benchmark value is used to ensure that the accounting results are consistent with reality.

[0077] In this embodiment, the multi-criteria decision analysis method in S4 employs the expert trust propagation-decision laboratory analysis method to determine the indicator weights. Specifically, experts from multiple related fields such as carbon management, power systems, and building energy conservation are invited to independently score the indicators based on their judgments of the mutual influence relationships among the indicators within the indicator system. The scoring results of all experts are collected and weighted by trust level to generate a comprehensive direct influence matrix. Based on this matrix, the decision laboratory analysis method (DEMATEL) is used to calculate the influence degree, affected degree, centrality (representing the importance of the indicator in the system), and causality (distinguishing whether the indicator is a driving factor or a result factor) of each indicator. Finally, the centrality values ​​of each indicator are normalized to determine the final weight of the indicator in the comprehensive evaluation.

[0078] The core calculation process of DEMATEL is as follows: 1. Construction of the basic matrix: Direct Influence Matrix X: Expert scores determine the degree of direct influence between indicators ( : 0 = no effect, 1 = weak, 2 = medium, 3 = strong.

[0079] Normalized matrix: (Eliminating dimensions) 2. Specific formula: Comprehensive Impact Matrix: (I is the identity matrix) Impact level: (Total impact of indicator i on other indicators) Degree of impact: (Indicator j is affected by the total influence of other indicators) Centrality (Importance): (The higher the value, the more important it is) Cause degree: ( ) is the cause indicator. (As an outcome indicator) 3. Weight Determination: Indicator weight = Centrality Normalization ( ) in, This indicates the degree of direct influence of indicator i on indicator j. This represents the total degree of "direct influence + indirect influence" of indicator i on indicator j. The value in the i-th row and j-th column is the total degree of influence. .

[0080] In one optional implementation, the multi-criteria decision analysis method can be the analytic hierarchy process (AHP). Specific implementation details include: establishing a hierarchical structure based on the constructed multi-dimensional evaluation index system; inviting experts to determine the importance of each index at the same level relative to the criteria at the next higher level through pairwise comparisons, and constructing a judgment matrix; performing a consistency check on the judgment matrix, and if the check passes, calculating its eigenvector as the local weight of the index at that level; finally, synthesizing the local weights of the indicators at each level from top to bottom to obtain the comprehensive weight of all bottom-level indicators relative to the overall goal.

[0081] In another optional implementation, the multi-criteria decision analysis method can also be a game theory-based subjective and objective weighting method. Specific implementation details include: first, using objective weighting methods, such as the entropy weighting method or the CRITIC method, to calculate the objective weights of each indicator based on historical evaluation data of the power supply station or industry benchmark data; second, using subjective weighting methods, such as the aforementioned expert scoring method or the Delphi method, to determine the subjective weights of each indicator; then, constructing a game model with the objective of minimizing the deviation between subjective and objective weights, and obtaining a set of optimal combination coefficients by solving the model; finally, using these combination coefficients to linearly weight the subjective and objective weights to obtain the optimal combination weights that take into account both expert experience and data patterns.

[0082] Furthermore, in S4, the construction of the evaluation index system, the determination of the weight of each evaluation index based on the multi-criteria decision analysis method, and the classification of the evaluation results based on the tiered rating standard include steps E1-E3: E1. Construct a multi-dimensional evaluation index system for the effectiveness of zero-carbon construction, covering energy supply, end-use energy, system operation, accounting quality, digital management, economic benefits, and social impact.

[0083] The details are shown in Table 1: Table 1 Evaluation Index System

[0084] E2. Through multi-criteria decision analysis, the correlation and weight of evaluation indicators at all levels are determined by combining expert judgments.

[0085] E3. Based on the pre-set tiered rating standards, the effectiveness of zero-carbon construction of power supply stations is divided into three levels: basic, advanced, and zero-carbon.

[0086] Specifically, the evaluation results will be divided into three levels: Basic level: Meets the core indicators (photovoltaic self-sufficiency rate ≥30%, carbon accounting error rate ≤15%), and carbon emission intensity is reduced by ≥20% compared to the benchmark.

[0087] Advanced level: Meets all secondary indicators, carbon emission intensity is reduced by ≥40% compared to the benchmark, and renewable energy accounts for ≥50%.

[0088] Zero-carbon level: Net zero carbon emissions throughout the entire life cycle, with remaining carbon emissions neutralized through green electricity, carbon offsetting, and other means, and meeting the assessment standards for 12 consecutive months.

[0089] The specific details are shown in Table 2. Table 2. Tiered Rating Criteria for Zero-Carbon Power Supply Stations

[0090] Furthermore, the optimization solutions in S5 for non-compliant indicators covering the energy supply side, end-user energy side, and management side include F1-F3: F1. On the energy supply side, adjust the layout of photovoltaic modules and optimize the charging and discharging strategies of energy storage systems.

[0091] F2. For end-user energy consumption, promote the electrification of maintenance vehicles and implement building energy-saving renovations.

[0092] F3. For the management side, improve the functions of the carbon management platform and strengthen employee carbon business training.

[0093] Example 3 is an embodiment of the present invention, which provides a method for carbon emission accounting and effectiveness evaluation of the entire life cycle of a zero-carbon power supply station. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0094] Boundary delineation: The physical boundary covers the Sino-German Power Supply Station office building (2000㎡), charging piles (10 units), maintenance vehicles (8 vehicles), and the 35kV substation; within the logical boundary, the primary power grid's electricity share β=0.6, with a fixed carbon factor. Regional power grid dynamic carbon factor ; Data Collection: 12 smart meters and 8 vehicle energy consumption terminals were deployed to collect real-time data from January to June 2024, including purchased electricity. The photovoltaic power generation is 30 MWh, and the fuel consumption of the maintenance vehicle is 500 L.

[0095] Calculation results: Direct carbon emissions: .

[0096] Indirect carbon emissions: .

[0097] Total carbon emissions during operation: After correction, the accuracy is improved to 92% compared to the traditional calculation method (error 18%).

[0098] Example 4, refer to Figure 2 This is one embodiment of the present invention, which provides a zero-carbon power supply station full life cycle carbon emission accounting and effectiveness evaluation system, including: a boundary and model management module, a carbon-energy flow collaborative monitoring and credible evidence storage module, a full life cycle dynamic accounting engine, a multi-dimensional intelligent evaluation and classification module, and an optimization decision and scheme generation module.

[0099] The boundary and model management module defines the dual boundaries for carbon emission accounting by dividing physical boundaries into logical boundaries.

[0100] The carbon-energy flow collaborative monitoring and credible evidence storage module collects direct and indirect carbon emission data and auxiliary data in real time through monitoring equipment, and performs credible processing and evidence storage on the direct and indirect carbon emission data and auxiliary data.

[0101] The full life cycle dynamic accounting engine divides the power supply station into different life cycle stages, integrates life cycle analysis methods, fuel emission factor method, actual measurement method and carbon emission flow theory to perform accounting for different stages, and dynamically corrects the emission factor based on the real-time carbon intensity data of the regional power grid.

[0102] The multidimensional intelligent assessment and grading module constructs an assessment index system, determines the weight of each assessment index based on a multi-criteria decision analysis method, and grades the assessment results based on a tiered rating standard.

[0103] Based on the accounting and evaluation results, optimization solutions covering the energy supply side, end-user energy side, and management side are output for indicators that have not met the standards.

[0104] This embodiment also provides an electronic device applicable to a method for calculating and evaluating the carbon emissions throughout the entire life cycle of a zero-carbon power supply station, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the method for calculating and evaluating the carbon emissions throughout the entire life cycle of a zero-carbon power supply station as proposed in the above embodiment.

[0105] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a method for calculating and evaluating the carbon emissions of a zero-carbon power supply station throughout its entire life cycle, as proposed in the above embodiment.

[0106] The storage medium proposed in this embodiment and the method for calculating and evaluating the carbon emissions of a zero-carbon power supply station throughout its entire life cycle proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0107] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0108] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for carbon emission accounting and effectiveness evaluation throughout the entire life cycle of a zero-carbon power supply station, characterized in that: include, Defining the dual boundaries of carbon emission accounting by dividing physical boundaries into logical boundaries; The monitoring equipment collects direct and indirect carbon emission data and auxiliary data in real time, and performs credible processing and storage on the direct and indirect carbon emission data and auxiliary data. The power supply station is divided into different life cycle stages. For each stage, life cycle analysis method, fuel emission factor method, measurement method and carbon emission flow theory are integrated to calculate the emission factors. The emission factors are dynamically corrected based on the real-time carbon intensity data of the regional power grid. An evaluation index system was constructed, the weight of each evaluation index was determined based on a multi-criteria decision analysis method, and the evaluation results were graded based on a tiered rating standard. Based on the accounting and evaluation results, optimization solutions covering the energy supply side, end-user energy side, and management side are output for indicators that have not met the standards.

2. The method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle as described in claim 1, characterized in that: The method of defining the dual boundaries for carbon emission accounting by dividing physical boundaries into logical boundaries includes, The physical boundaries for carbon emission accounting are defined based on the geographical jurisdiction and asset ownership of the power supply station. Based on a multi-level coupled accounting model, a logical boundary is established that includes direct carbon emissions and indirect carbon emissions; The calculation of indirect carbon emissions adopts a formula that integrates the fixed carbon factor of the primary power grid and the dynamic carbon factor of the regional power grid.

3. The method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle as described in claim 2, characterized in that: The process of making direct and indirect carbon emission data and auxiliary data credible and storing evidence includes... The collected direct and indirect carbon emission data and auxiliary data are standardized using a local data processor. Standardized direct and indirect carbon emission data, as well as auxiliary data, will be stored on the blockchain using blockchain technology.

4. The method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle as described in claim 3, characterized in that: The classification of different life cycle stages of power supply stations includes, The implicit carbon emissions from the production process of building materials for power supply stations are accounted for during the building materials production stage. During the construction phase, calculate the carbon emissions corresponding to the energy consumption of construction machinery and transportation. During the operation and maintenance phase, calculate the direct and indirect carbon emissions of the power supply station during its operation period. The carbon emissions from the demolition and recycling process are calculated during the demolition and recycling phase.

5. The method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle as described in claim 4, characterized in that: The calculations, which integrate life cycle analysis methods, fuel emission factor methods, measured methods, and carbon emission flow theory for different stages, and dynamically adjust emission factors based on real-time carbon intensity data of the regional power grid, include: Life cycle analysis is used in the building material production stage, construction stage and demolition and recycling stage to calculate carbon emissions based on the ISO14040 standard. During the operation and maintenance phase, the fuel emission factor method, the measured method, and the carbon emission flow theory are used simultaneously for collaborative accounting and cross-validation. During the calculation process, real-time carbon intensity data from the regional power grid is incorporated to dynamically correct and update the accounting factors for indirect carbon emissions monthly.

6. The method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle as described in claim 4, characterized in that: The construction of the evaluation index system includes determining the weight of each evaluation index based on a multi-criteria decision analysis method, and classifying the evaluation results based on a tiered rating standard. Construct a multi-dimensional evaluation index system for the effectiveness of zero-carbon construction, covering energy supply, end-use energy, system operation, accounting quality, digital management, economic benefits, and social impact; By using a multi-criteria decision analysis method, the correlation and weight of evaluation indicators at all levels are determined by integrating expert judgments. Based on a pre-set tiered rating standard, the effectiveness of zero-carbon construction in power supply stations is divided into three levels: basic, advanced, and zero-carbon.

7. The method for carbon emission accounting and effectiveness evaluation of a zero-carbon power supply station throughout its entire life cycle as described in claim 4, characterized in that: The optimization schemes for outputting non-compliant indicators covering the energy supply side, end-user energy side, and management side include: On the energy supply side, adjustments should be made to the layout of photovoltaic modules and optimization of the charging and discharging strategies for energy storage systems. For end-user energy consumption, we will promote the electrification of maintenance vehicles and implement energy-saving renovations of buildings. On the management side, we will improve the functions of the carbon management platform and strengthen carbon business training for employees.

8. A system for calculating and evaluating the carbon emissions throughout the entire life cycle of a zero-carbon power supply station, employing the method for calculating and evaluating the carbon emissions throughout the entire life cycle of a zero-carbon power supply station as described in any one of claims 1 to 7, characterized in that, include: The module includes a boundary and model management module, a carbon-energy flow collaborative monitoring and credible evidence storage module, a full life cycle dynamic accounting engine, a multi-dimensional intelligent assessment and classification module, and an optimization decision-making and scheme generation module. The boundary and model management module defines the dual boundaries for carbon emission accounting by dividing physical boundaries into logical boundaries. The carbon-energy flow collaborative monitoring and credible evidence storage module collects direct and indirect carbon emission data and auxiliary data in real time through monitoring equipment, and performs credible processing and evidence storage on the direct and indirect carbon emission data and auxiliary data. The full life cycle dynamic accounting engine divides the power supply station into different life cycle stages, integrates life cycle analysis methods, fuel emission factor method, actual measurement method and carbon emission flow theory for different stages, and dynamically corrects the emission factor based on the real-time carbon intensity data of the regional power grid. The multidimensional intelligent assessment and grading module constructs an assessment index system, determines the weight of each assessment index based on a multi-criteria decision analysis method, and grades the assessment results based on a tiered rating standard. Based on the accounting and evaluation results, optimization solutions covering the energy supply side, end-user energy side, and management side are output for indicators that do not meet the standards.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method for calculating and evaluating the carbon emissions of a zero-carbon power supply station throughout its entire life cycle, as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for calculating and evaluating the carbon emissions of a zero-carbon power supply station throughout its entire life cycle, as described in any one of claims 1 to 7.

Images