Low-carbon performance evaluation index determination method based on full life cycle transformer substation infrastructure project

Abstract

The invention discloses a low-carbon performance evaluation index determination method based on a full life cycle transformer substation infrastructure project, and a 110 kv transformer substation infrastructure project carbon emission accounting method based on a life cycle theory. Constructing a low-carbon performance evaluation index system of the capital construction project of the 110kV transformer substation in the whole life cycle based on a correlation analysis method; a full-life-cycle 110kV transformer substation capital construction project low-carbon performance evaluation model is provided by considering the influence of multiple factors. In combination with the weight of the low-carbon performance evaluation indexes of the 110kv transformer substation infrastructure project, COPRAS is selected to comprehensively consider the information of multiple indexes, and the score ranking of each scheme is calculated to provide a decision basis for a decision maker. Based on a correlation analysis method, a multi-dimensional low-carbon performance evaluation index system is constructed from the four stages of design, construction, operation, scrapping and planning of the whole life cycle, and the low-carbon performance of the 110kV transformer substation infrastructure project can be effectively evaluated. Meanwhile, various factors are fully considered, uncertainty factors are processed through a fuzzy comprehensive evaluation method, and the optimal compromise scheme is found through a COPRAS method.

Description

Technical Field

[0001] The present invention belongs to the technical field of carbon emission reduction management in the electric power industry, and specifically provides a method for determining low-carbon performance evaluation indicators for substation infrastructure projects based on the entire life cycle. Background Art

[0002] The power system is a complex network, in which the 110kv substation is an important part of the power transmission and transformation system. Its infrastructure projects include civil engineering, electrical equipment installation, transmission line construction, etc., which will produce certain carbon emissions. Therefore, the low-carbon performance review of the 110kv substation infrastructure project has become a starting point for optimizing the power system and promoting energy transformation, so as to comprehensively promote the transformation of power grid construction towards a smart, low-carbon and green direction.

[0003] In this context, combining the characteristics of 110kV substation infrastructure projects, building an evaluation index system that can reflect both the low-carbon effect of the project construction process and the environmental benefits, and achieving a win-win situation for economic and environmental development, has become an urgent problem to be solved. Traditional evaluation methods often lack consideration of the specific operating environment of 110kV substations, making it difficult to fully reflect the actual contribution of low-carbon technologies.

[0004] This invention fully combines the existing domestic problems and, starting from the actual needs of the power industry, proposes a key indicator measurement technology for low-carbon performance evaluation of 110kV substation infrastructure projects based on the entire life cycle. This technology not only takes into account the energy efficiency and environmental impact of the project design phase, but also integrates multiple dimensions such as material selection during the construction process, energy efficiency improvement during the operation phase, and resource recovery during the scrapping phase, providing a comprehensive and scientific low-carbon evaluation tool. Through this method, it can effectively guide the low-carbon transformation and optimization of operation strategies of 110kV substations and promote the sustainable development of the power industry. Summary of the invention

[0005] In response to the above problems, the present invention proposes a method for determining low-carbon performance evaluation indicators for substation infrastructure projects based on the entire life cycle. Through careful consideration of the entire life cycle, the carbon emission sources at each stage are comprehensively sorted out, laying the foundation for accurately calculating the carbon emissions of 110kV substation infrastructure projects. Based on the correlation analysis method, starting from the four stages of design, construction, operation, scrapping and preparation for the entire life cycle, a multi-dimensional low-carbon performance evaluation index system is constructed, which can effectively evaluate the low-carbon performance of 110kV substation infrastructure projects. At the same time, when proposing a low-carbon performance evaluation model for 110kV substation infrastructure projects throughout the life cycle, various factors are fully considered, and the uncertainty factors are handled through the fuzzy comprehensive evaluation method. The COPRAS method finds the best compromise solution to provide a scientific basis and decision-making support for the low-carbon transformation and sustainable development of substations.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] The method for determining low-carbon performance evaluation indicators for substation infrastructure projects based on the entire life cycle includes the following steps:

[0008] 1) Carbon emission accounting method for 110kv substation infrastructure projects based on life cycle theory;

[0009] 2) Based on the correlation analysis method, a low-carbon performance evaluation index system for 110kV substation infrastructure projects throughout the entire life cycle is established;

[0010] 3) Considering the influence of multiple factors, a low-carbon performance evaluation model for 110kV substation infrastructure projects throughout the life cycle was proposed;

[0011] 4) Combined with the weights of the low-carbon performance evaluation indicators of the 110kv substation infrastructure project, the selection of COPRAS can comprehensively consider the information of multiple indicators and provide a basis for decision makers by calculating the score ranking of each plan.

[0012] As a further improvement of the present invention, the step 1) calculates the carbon footprint of the 110kv substation infrastructure project using the life cycle method through four steps:

[0013] (1) Identify the various stages in the product or service life cycle and the emission sources at each stage;

[0014] (2) Query and determine the carbon footprint factor;

[0015] (3) Collect product or service data and calculate carbon footprint;

[0016] (4) Analysis of carbon footprint calculation results;

[0017] The carbon footprint of each stage of the 110kv substation infrastructure project cycle is the sum of the usage of all emission sources in this stage multiplied by their emission factors, that is:

[0018] CF i =∑(AD ij ×EF ij ) (1)

[0019] Among them, AD ij is the usage of the jth emission source in the i-th stage, in kg, m3 or kW·h; EF ij is the carbon footprint factor of the jth emission source in the i-th phase; CF i is the total carbon footprint of the product or service in stage i.

[0020] As a further improvement of the present invention, the step 2) constructs a low-carbon performance evaluation index for 110kV substation infrastructure projects based on a correlation analysis method, which is expressed as:

[0021]

[0022] Where r is the indicator correlation coefficient; They are the average values ​​of the two indicators respectively. The two indicators that failed the correlation test can be used as independent indicators. For the two indicators with relatively high correlation, they are selected according to the above principles and one of them is retained. The indicators are simplified according to this method respectively, and finally the indicators obtained by correlation analysis can be obtained.

[0023] As a further improvement of the present invention, the step 2) constructs the low-carbon performance evaluation index of the 110kV substation infrastructure project based on the correlation analysis method, and determines the evaluation index system from the design evaluation stage, construction evaluation stage, operation evaluation stage, and scrapping and preparation stage:

[0024]

[0025]

[0026] As a further improvement of the present invention, the step 2) constructs a low-carbon performance evaluation index system for 110kV substation infrastructure projects over the entire life cycle based on the correlation analysis method, considers the actual operation data of the 110kV substation infrastructure projects on the basis of the traditional subjective indicator weight perception method, and establishes a weight perception method based on subjective and objective factors. In the established weight perception method based on subjective and objective factors, the actual operation data of the 110kV substation infrastructure projects is considered on the basis of the traditional subjective indicator weight perception method, and a weight perception method based on the combination of subjective and objective factors is established, which can be expressed as:

[0027]

[0028] where θ 1 is the expert preference coefficient of the ordinal relation analysis method, θ 2 is the expert preference coefficient of grey relational analysis; α j is the subjective weight of the evaluation index by ordinal relationship analysis method; β j It is the objective weight of the evaluation indexes by grey relational analysis method.

[0029] As a further improvement of the present invention, the step 2) establishes a method based on subjective and objective factors combined weight perception method in which the subjective weight of the evaluation index is calculated according to the following method: The specific steps are as follows:

[0030] Step 1: Determine the indicator sequence, select evaluation indicators to conduct a comprehensive evaluation of the object to be evaluated, and the evaluator selects the most important indicator from the indicators, and the corresponding weight is recorded as; then continue to select the most important indicator from the remaining indicators, and so on; until all indicators are selected, a sequence of indicators ranked by relative importance is formed, and the corresponding indicator weight is;

[0031] Step 2: Determine the relative importance ratio of the indicators. The relative importance ratio of the indicators determines the indicator weight. It is obtained after discussion by all evaluators. The calculation formula of the relative importance ratio is:

[0032]

[0033] Step 3: Calculate the weight of the nth indicator. The calculation formula is:

[0034]

[0035] Step 4: Calculate the weights of all indicators according to the relative importance ratio r j , determine the weights of other n-1 indicators;

[0036] α j-1 =r j α j (5)

[0037] Step 5: Determine the weight coefficient of each indicator to the total target layer, set α pq is the weight coefficient of the qth indicator under the pth criterion layer in the indicator system in the total target layer, α p is the weight coefficient of the pth criterion layer in the total target layer; α (p) q is the weight coefficient of the qth indicator in the pth criterion layer, then:

[0038] α pq =α p ×α (p) q (6).

[0039] As a further improvement of the present invention, the step 2) establishes a method based on the perception of the combined weights of subjective and objective factors, and the objective weights of the evaluation indicators are calculated by the grey correlation analysis method according to the following method:

[0040] Step 1: Determine the system main behavior reference sequence X 0 Comparison sequence X with system-related factors 1 ;

[0041] X 0 (k)=(x 0 (1),x 0 (2),…,x 0(n)) (7)

[0042] X i (k)=(x i (1),x i (2),…,x i (n)) (i=1,2,…m) (8)

[0043] Step 2: Since the physical meanings of different factors in the system are different, the dimensions of their data are also different, making it difficult to draw correct conclusions when making comparisons. Therefore, it is necessary to normalize the data and convert the data into a pure digital sequence to facilitate calculation and comparative analysis, and to classify the sequence data into a range.

[0044]

[0045] Step 3: Calculate the correlation coefficient:

[0046]

[0047] Where ρ is the resolution coefficient, the value range is [0,1], and it is generally taken as 0.5;

[0048] Step 4: Calculate the correlation:

[0049]

[0050] Sorting is performed according to the magnitude of the factor correlation, reflecting the strength of the relationship between the comparison sequence and the reference sequence.

[0051] As a further improvement of the present invention, step 3) considers the influence of multiple factors and proposes a low-carbon performance evaluation model for 110kV substation infrastructure projects. The specific steps are as follows:

[0052] Step 1: Establish a corresponding first-level evaluation indicator set, which means that there are three evaluation indicators in the first-level evaluation indicators, which correspond to energy efficiency indicators, economic indicators and environmental indicators respectively. On the basis of the first-level indicator set, establish a second-level indicator set, that is, each first-level indicator corresponds to several second-level indicators. On the basis of the second-level indicator set, establish a third-level indicator set, that is, each second-level indicator corresponds to several third-level indicators.

[0053] Step 2: Create a review level set V = (V 1 ,V 2 ,V 3 ,V 4 ) = (excellent, good, average, poor), the invited experts make judgments on the questions corresponding to each indicator in the questionnaire according to the actual situation of each evaluated project, and then select appropriate comments in the comment level;

[0054] Step 3: Establish an evaluation index weight set based on the combined weight;

[0055] Step 4: Establish a fuzzy judgment matrix, the specific form is shown in R below:

[0056]

[0057] Among them, r ij =μ R (U i ,V j ), r∈[1,n] is the membership of the i-th factor U to the j-th comment level V. For each three-level factor U ij You can use an R i , then the secondary factor U i The fuzzy relation matrix on the V domain is R i =(B 1 ,B 2 ,B 3 ,…,B i ) T ;

[0058] Relationship Matrix R i The element B in i Yes ij and r ij pass After fuzzy transformation, the first-level evaluation vector is obtained. After processing, the fuzzy evaluation result B=W of the first-level factor is obtained. i ·R i =(b 1 ,b 2 ,…,b i );

[0059] Step 5: Repeat the above calculation process, use the first-level judgment result as the second-level indicator membership, calculate the comprehensive evaluation result vector of the previous level indicator, and after determining the fuzzy relationship matrix and weight set of each layer, perform fuzzy evaluation in different levels. Through the hierarchical evaluation and then comprehensive method, the fuzzy comprehensive evaluation result of project U is finally obtained, and then according to the maximum membership principle, the comment level corresponding to the maximum value in the set is selected as the final project evaluation result;

[0060] Step 6: Calculate the final project evaluation results through normalization Get the low carbon performance of each project.

[0061] As a further improvement of the present invention, step 4) combines the weights of the low-carbon performance evaluation indicators of the 110kv substation infrastructure project, selects COPRAS to comprehensively consider the information of multiple indicators, and calculates the score ranking of each scheme, as follows:

[0062] Step 1: Evaluate the low-carbon performance plan of each 110kv substation infrastructure project under different indicators, and the obtained decision matrix is ​​recorded as:

[0063]

[0064] Where: x ij For the indicator C j Under this condition, the evaluation value of the low-carbon performance scheme of the i-th 110kv substation infrastructure project is i , if C j ∈J 1 If it is a benefit indicator, then x ij The larger the value of C is, the better the low-carbon performance of the 110kv substation project is; on the contrary, if C j ∈J 2 Cost-based indicators, then x ij The larger the value is, the worse the low-carbon performance of the 110kv substation project is;

[0065] Step 2: Normalize it to get the normalized decision matrix, as shown below:

[0066]

[0067] Step 3: Calculate the weighted normalized decision matrix, calculate the weighted normalized decision matrix R = (r ij ) m×n ;

[0068] r ij =y ij × j i=1,2,…,mj=1,2,…,n (17)

[0069] Step 4: Low Carbon Performance Plan A for 110kv Substation Infrastructure Project i The benefit indicators in the

[0070]

[0071] Where: Obviously, The larger the value, the better the solution A i better; better

[0072] Step 5: Determine the comprehensive cost value for cost-based indicators

[0073]

[0074] Where: Obviously, The smaller the value, the better the solution A i better; better

[0075] Step 6: Calculate its comprehensive evaluation value

[0076]

[0077] Where: Obviously, Q i The larger the value, the lower the carbon performance of 110kv substation infrastructure project A i If a 110kv substation infrastructure project low-carbon performance plan has the largest comprehensive evaluation value, Q i Then the low-carbon performance solution for the 110kv substation infrastructure project should be the best choice;

[0078] Step 7: Calculate the effectiveness of the low-carbon performance solution for each 110kv substation infrastructure project

[0079]

[0080] Where: Compared with the prior art, the present invention has the following beneficial effects:

[0081] In response to the above problems, the present invention proposes a key indicator measurement technology for low-carbon performance evaluation of 110kV substation infrastructure projects based on the entire life cycle, and constructs an evaluation indicator system from four stages: design evaluation stage, construction evaluation stage, operation evaluation stage, and scrapping and preparation stage.

[0082] The low-carbon performance evaluation system for 110kv substation infrastructure projects constructed by the present invention covers all aspects of the entire life cycle of 110kV substation infrastructure projects. Through careful consideration of the design, construction, operation, scrapping and preparation stages, as well as comprehensive evaluation of multi-dimensional indicators such as energy efficiency, material selection, environmental impact, economic benefits, and technological innovation, the low-carbon performance in each project can be comprehensively and accurately quantified. The weight perception method based on subjective and objective factors is adopted, combined with a variety of scientific methods such as G1 method, gray correlation analysis method, fuzzy comprehensive evaluation method and COPRAS method, which effectively overcomes the limitations of a single evaluation method. The present invention helps relevant departments to deeply understand the logical relationship between their production factors and energy conservation and emission reduction, so as to optimize power transmission and distribution equipment in a targeted manner. Through the low-carbon performance evaluation of substation electrical design and other aspects, the company is encouraged to select efficient transformers, switchgear, etc., reduce the energy loss of equipment, and more importantly, contribute to saving energy, reducing pollution, and achieving sustainable development for the society. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 This is a research framework diagram of the low-carbon performance evaluation model and its application method based on the 110kV substation infrastructure project of the present invention;

[0084] Figure 2 This is the carbon footprint of a 110kV substation infrastructure project of the present invention. DETAILED DESCRIPTION

[0085] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments:

[0086] A key indicator determination technology for low-carbon performance evaluation of 110kV substation infrastructure projects based on the entire life cycle is proposed. According to the applicable scope of each carbon footprint calculation method, the life cycle method is suitable for analyzing and calculating the carbon footprint of substation infrastructure projects. The application of the life cycle method to calculate the carbon footprint of a product or service mainly goes through four steps: (1) determine the various stages and emission sources of the product or service life cycle; (2) query and determine the carbon footprint factor; (3) collect product or service data and calculate the carbon footprint; (4) analyze the carbon footprint calculation results. The carbon footprint of each stage of the product or service life cycle is the sum of the usage of all emission sources in this stage multiplied by their emission factors, that is:

[0087] CF i =∑(AD ij ×EF ij ) (1)

[0088] Where: AD ij EF is the usage of the jth emission source in the i-th stage, in kg, m3 or kW·h, etc.; ij is the carbon footprint factor of the jth emission source in the i-th phase; CF i is the total carbon footprint of the product or service in stage i.

[0089] Since there are many factors to be considered in the construction of evaluation indicators, the relationship between evaluation indicators is relatively complex, and there is inevitably a certain correlation between the preliminary indicators. If these related indicators are directly used in the 110kV substation infrastructure low-carbon performance evaluation indicator system, it will cause the amplification of some benefits and affect the rationality of the comprehensive evaluation results. Therefore, it is necessary to simplify the preliminary indicators and eliminate highly correlated indicators. The correlation analysis method does not reconstruct the indicators, which can ensure that the significance of the indicators does not change, and is suitable for the 110kV substation low-carbon performance evaluation indicator system. The correlation analysis method requires a correlation analysis matrix. The closer the absolute value of the correlation coefficient of the two indicator data is to 1, the stronger the correlation is.

[0090] Assume there are S evaluation indicators S 1 ,S 2 ,…,S m These m indicators are divided into k categories:

[0091] Each row above represents a type of indicator. For the indicators in each row, a correlation analysis matrix is ​​made. The closer the absolute value of the correlation coefficient of two indicator data is to 1, the stronger the correlation is. The range of the correlation coefficient r is used to judge the degree of correlation between the two indicators: r = 0, indicating no correlation at all; 0 < |r| < 0.3, indicating basically no correlation; 0.3 < |r| < 0.5, indicating low correlation; 0.5 < |r| < 0.8, indicating significant correlation; 0.8 < |r| < 1, indicating high correlation; r = 1, indicating complete correlation.

[0092]

[0093] in, are the average values ​​of the two indicators respectively. The correlation matrix is:

[0094]

[0095] The correlation coefficient r ij In the above example, the two indicators that failed the correlation test can be used as independent indicators. For the two indicators with high correlation, one of them can be selected according to the above principle. The k types of indicators are simplified according to this method, and finally the indicators obtained by correlation analysis can be obtained.

[0096] In the low-carbon performance review of 110kV substation infrastructure projects, building a review index system is a key step to ensure that the review results are scientific, objective and comprehensive. By dividing the entire life cycle of 110kv substation infrastructure projects, the four stages of 110kv substation infrastructure projects are comprehensively considered, including the design evaluation stage, construction evaluation stage, operation evaluation stage, and scrapping and preparation stage, and the main dimensions of the review index system are determined, such as energy efficiency, carbon emissions, environmental impact, economic benefits, and technological innovation. These indicators comprehensively review the low-carbon and green nature of infrastructure projects, and provide important support for the carbon verification of the project. The main contents are as follows:

[0097] (1) Design evaluation stage

[0098] 1) Advancedness

[0099] ① Overall layout design

[0100] The master plan design focuses on the overall layout of the substation infrastructure project, including the reasonable distribution of buildings, equipment, roads and green spaces. In the low-carbon performance review, the master plan design needs to consider how to optimize the layout to reduce material use, reduce energy consumption, and improve the efficiency of construction and operation. For example, reduce the length of cables through reasonable equipment layout, or use natural light and ventilation to reduce dependence on artificial lighting and air conditioning.

[0101] ②HVAC design

[0102] HVAC design involves the heating, ventilation and air conditioning systems within the substation. In the low-carbon review, this indicator needs to assess whether the design of the HVAC system can effectively use energy and reduce greenhouse gas emissions. This may include the use of efficient insulation materials, energy-saving HVAC equipment, and the use of renewable energy (such as geothermal energy) to provide some or all of the required heating and cooling.

[0103] ③Electrical design

[0104] Electrical design is the core part of the design of substation infrastructure projects, including the selection and configuration of transformers, switchgear, protection and control systems, etc. In the low-carbon performance review, electrical design needs to consider how to improve energy utilization, reduce power loss, and ensure system reliability and safety through efficient electrical equipment and advanced control technology.

[0105] 2) Innovation

[0106] ④Concept innovation

[0107] Concept innovation refers to the use of new ideas, technologies and materials in the design process to achieve low-carbon goals. This may include adopting modular design to reduce resource consumption during construction, or using smart technology to optimize substation operations and maintenance. Concept innovation helps promote substation design in a more environmentally friendly and efficient direction.

[0108] ⑤Technological innovation

[0109] Technological innovation involves applying new technologies in substation design and operation to improve energy efficiency and reduce carbon emissions. This may include using advanced monitoring and diagnostic tools to optimize equipment performance, or adopting new energy storage technologies to balance grid loads and increase the utilization of renewable energy.

[0110] 3) Effectiveness

[0111] ⑥Social benefits

[0112] Social benefits focus on the positive impact of substation design and operation on society. In the low-carbon performance review, this indicator needs to review how substation infrastructure projects promote local economic development, provide employment opportunities, and improve social welfare by reducing environmental pollution and improving energy security.

[0113] (2) Construction evaluation stage

[0114] 1) Green construction management

[0115] ① Management system

[0116] This indicator review project has a comprehensive management system to ensure the achievement of low-carbon goals. This includes but is not limited to energy management system, environmental management system and quality management system. An effective management system should be able to monitor and reduce energy consumption, ensure that environmental protection measures are implemented during construction and operation, and evaluate and control possible environmental impacts.

[0117] ②Inspection data completeness

[0118] The completeness of inspection data is the key to ensuring project quality. In the low-carbon performance review, it is necessary to check all relevant inspection data, including design documents, construction drawings, material certification, equipment certification, etc., to ensure that low-carbon standards are followed during the design and construction process. This helps avoid rework due to incomplete data, thereby reducing resource waste.

[0119] 2) Environmental protection and safety

[0120] ① Setting of environmental protection signs

[0121] The setting of environmental protection signs helps to remind all relevant personnel to pay attention to environmental protection measures. The review needs to evaluate whether environmental protection signs are set up in conspicuous locations in the substation and whether these signs can clearly convey environmental protection information, such as waste classification, energy conservation and emission reduction, etc.

[0122] ②Soil and water conservation

[0123] Soil and water conservation is an important part of substation infrastructure construction. The review needs to examine whether the project has effective soil and water conservation measures, such as vegetation coverage to prevent soil erosion and the design of drainage systems, to ensure that the construction process will not cause adverse effects on the surrounding environment.

[0124] ③ Vehicles meet the standards

[0125] Vehicle emissions are one of the important factors affecting air quality. In the low-carbon performance review, it is necessary to assess whether all construction and operation vehicles meet national or local emission standards, and whether there are measures to reduce vehicle use, such as encouraging the use of electric or hybrid vehicles.

[0126] ④ Incineration regulations

[0127] Incineration activities may produce harmful gases and particulate matter, causing environmental pollution. The review needs to check that there are strict incineration regulations and that these regulations are effectively enforced to reduce air pollution.

[0128] ⑤Environmental restoration measures

[0129] Environmental restoration is an important task after substation construction. The review requires that the project has a detailed environmental restoration plan, including vegetation restoration, soil improvement, etc., to ensure that the environment after construction can be restored to its natural state as soon as possible.

[0130] 3) Resource conservation and recycling

[0131] ①Material quality

[0132] High-quality materials not only improve the safety and durability of the substation, but also reduce the frequency of maintenance and replacement, thereby reducing overall carbon emissions. The review needs to check whether the materials used meet environmental protection and quality standards, as well as whether recyclable or renewable materials are used.

[0133] ② Regulations on waste recycling

[0134] Waste material recycling can effectively reduce the impact of waste on the environment and improve the utilization rate of resources. The review needs to assess whether the project has waste material recycling plans and facilities, and whether these plans have been effectively implemented.

[0135] ③SF6 recycling situation

[0136] SF6 is a potent greenhouse gas that is widely used in high-voltage switchgear. The review needs to assess whether the substation has SF6 gas recovery and treatment mechanisms and whether these mechanisms can effectively reduce SF6 emissions.

[0137] ④Inspection situation

[0138] Strict inspection is the key to ensure the implementation of low-carbon performance standards. The review needs to check that all design and construction links have undergone rigorous inspections, including material inspections, equipment inspections, and construction quality inspections.

[0139] ⑤Energy-saving electrical

[0140] Energy-saving electrical technology is an effective means to reduce the energy consumption of substations. The review needs to evaluate whether the electrical system of the substation design adopts energy-saving technologies, such as high-efficiency transformers, energy-saving lighting and intelligent control systems.

[0141] ⑥Construction energy utilization rate

[0142] The energy efficiency during the construction process directly affects the carbon emissions of the project. The review needs to examine the energy efficiency during the construction process, including the selection of construction machinery and the energy consumption of temporary facilities.

[0143] ⑦Transportation distance

[0144] The transportation distance of materials and equipment is an important factor affecting carbon emissions. The review needs to assess whether the project has taken measures to reduce the transportation distance, such as choosing nearby suppliers or optimizing logistics routes.

[0145] ⑧Energy-saving measures for temporary buildings

[0146] Energy-saving measures for temporary buildings can help reduce energy consumption during construction. During the review, it is necessary to check whether temporary buildings use energy-saving materials and equipment, such as insulation materials and energy-saving lighting.

[0147] 4) Technological innovation

[0148] ①Green technology project establishment

[0149] The application of green technology helps to improve the environmental performance of substations. The review needs to assess whether the project adopts green technology, such as solar power generation, rainwater collection system, green building materials, etc.

[0150] ②Information construction

[0151] Information construction technology, such as BIM (Building Information Modeling), can optimize the design and construction process and improve resource utilization efficiency. The review needs to assess whether the project uses information technology to improve construction efficiency, reduce material waste, and optimize construction progress.

[0152] (3) Operational evaluation stage

[0153] 1) Coordination

[0154] ①Humanities satisfaction

[0155] This indicator evaluates the coordination of substation infrastructure projects in terms of nature, history and geography, as well as its impact on surrounding communities. Humanistic satisfaction not only involves the exterior design of substation infrastructure projects and their harmony with the surrounding environment, but also includes respect for local cultural heritage and natural landscapes. High humanistic satisfaction means that the construction and operation of the substation are widely accepted and supported by community residents, which helps to enhance social harmony and stability.

[0156] ② (Nature, history, region, etc.) coordination

[0157] The coordination index focuses on the degree of integration between the substation and the surrounding environment, including architectural style, color matching, landscape design, etc. Good coordination can reduce interference with the lives of surrounding residents, enhance the social image of the substation, and help gain public understanding and support.

[0158] 2) Environment and resources

[0159] ③ Air pollution control

[0160] This indicator measures the impact of substation infrastructure projects on air quality during operation, especially the emission control of pollutants such as PM2.5, SO2, and NOx. Effective air pollution control measures can help reduce the negative impact of substation infrastructure projects on air quality and protect public health.

[0161] ④Solid waste pollution control

[0162] The solid waste pollution control index evaluates whether the solid waste generated during the operation of the substation infrastructure project (such as waste materials generated by equipment replacement) is properly handled. This includes the classification, recycling, reuse and final safe disposal of waste.

[0163] ⑤ Resource utilization

[0164] Resource utilization index focuses on the efficiency of the use of resources (such as water, electricity, materials, etc.) during the operation of substation infrastructure projects. High resource utilization means that the substation can effectively reduce resource consumption, reduce operating costs, and reduce the impact on the environment.

[0165] ⑥SF6 gas emissions

[0166] SF6 is a potent greenhouse gas widely used in high-voltage electrical equipment. This indicator assesses the emissions of SF6 gas during substation operation and measures to reduce emissions, such as using low-SF6 or SF6-free equipment.

[0167] ⑦ Green coverage rate of substation

[0168] The green coverage index measures the degree of greening inside and around the substation. A high green coverage helps improve the microclimate, absorb carbon dioxide, provide ecological habitats, and also improve the aesthetics of the substation.

[0169] ⑧ Carbon emissions from substation buildings

[0170] The building carbon emission indicator focuses on the carbon emissions of the substation infrastructure project itself, including the carbon emissions during the production, transportation and construction of building materials. Assessing this indicator will help promote the adoption of low-carbon building materials and construction methods.

[0171] 3) Economical

[0172] ⑨Operation cost estimation

[0173] The operating cost estimation indicator involves all costs of the substation infrastructure project during operation, including energy consumption, maintenance costs, equipment replacement costs, etc. By estimating and optimizing operating costs, the economic efficiency and sustainability of the substation infrastructure project can be improved.

[0174] ⑩Internal Return

[0175] The internal rate of return indicator measures the direct economic benefits brought by the operation of substation infrastructure projects, such as electricity sales revenue, energy saving benefits, etc. A high internal rate of return indicates that the substation infrastructure project has strong operating efficiency and profitability, which helps to support its long-term operation and development.

[0176] (4) Decommissioning and construction stage

[0177] 1) Building Demolition

[0178] ① Artificial carbon emission

[0179] This indicator focuses on the carbon emissions directly generated by manual work during the demolition and construction process. This includes the energy consumed when using tools, equipment and machinery, as well as the resulting exhaust emissions. During the review, measures to reduce carbon emissions in manual work will be considered, such as optimizing work processes and using low-emission tools.

[0180] ② Mechanical carbon removal

[0181] The Machinery Carbon Emissions Index measures the carbon emissions caused by the use of machinery and equipment during the demolition and construction process. This includes the operation of equipment such as excavators, cranes, generators, etc. The review will consider the use of high-efficiency, low-emission machinery and equipment, as well as measures to reduce machinery usage time and improve efficiency.

[0182] ③Energy carbon emissions

[0183] Energy carbon emission indicators involve the energy consumed and carbon emissions generated during the entire demolition and construction process. This includes the use of energy such as electricity and fuel. During the review, the efficiency of energy use, the use of renewable energy, and energy-saving measures to reduce overall energy consumption and carbon emissions will be evaluated.

[0184] ④Green demolition method

[0185] This indicator focuses on the environmental friendliness of the methods used when dismantling old substations. Green demolition methods aim to minimize damage to the environment, reduce waste generation, and increase the recycling rate of materials. The review will consider whether these methods are adopted, such as orderly demolition and classified recycling.

[0186] 2) Waste transportation

[0187] ⑤ Manual transportation

[0188] The manual transportation indicator measures the carbon emissions generated by manual transportation of materials and equipment during the demolition and construction process. During the review, consideration will be given to optimizing transportation routes and methods, reducing unnecessary manual transportation, and taking measures to improve the efficiency of manual transportation.

[0189] ⑥Vehicle transportation

[0190] The vehicle transportation indicator involves the carbon emissions generated by the use of vehicles to transport materials and equipment during the demolition and construction process. The review will assess whether measures have been taken to reduce the use of vehicles, such as reasonable transportation plans, the use of energy-saving or electric vehicles, etc.

[0191] 3) Waste disposal

[0192] ⑦Landfill

[0193] The Landfill Indicator looks at whether waste generated from demolition is disposed of in landfills. The assessment will consider measures taken to reduce waste generation and whether environmentally friendly waste management methods are used, such as waste separation, recycling and reuse.

[0194] ⑧Reuse

[0195] The reuse indicator measures how much materials and equipment are reused during the demolition and construction process. The review will consider whether a reuse plan is in place and whether measures are taken to promote the reuse of materials and equipment, thereby reducing resource consumption and waste generation.

[0196] ⑨Recyclable

[0197] The recyclability indicator focuses on how much materials and equipment can be recycled during the demolition and construction process. The review will assess whether measures have been taken to increase the recycling rate of materials, such as selecting recyclable materials and establishing a recycling system.

[0198] On the other hand, the principle adopted by the present invention is to encourage 110kV substation infrastructure projects to adopt more environmentally friendly production methods, promote the consumption of renewable energy and the application of clean energy technology, and promote the green transformation of the power industry by comprehensively considering the carbon emissions of the low-carbon performance of 110kV substation infrastructure projects, the implementation effect of energy-saving and emission reduction measures, and economic benefits. The subjective and objective weights of the indicators are determined by the G1 method and the gray correlation analysis method. The main process of the weight method calculation is as follows:

[0199] 1) G1 method to determine subjective weight

[0200] Assume that n evaluation indicators are selected to conduct a comprehensive evaluation of the object to be reviewed, and the reviewer selects the most important indicator X from the n indicators. 1 , the corresponding weight is denoted as α 1 ; Then continue to select the most important indicators from the remaining n-1 indicators, and so on; until all indicators are selected, a sequence of indicators ranked by relative importance is formed (X 1 ,X 2 ,...,X n )The corresponding indicator weight is (α 1 ,α 2 ,...,α n ).

[0201] The relative importance ratio of indicators j The relative importance ratio r determines the weight of the indicator, which is determined by discussion among all reviewers. j The calculation is shown in formula (3).

[0202]

[0203] The calculation of the nth indicator weight is shown in formula (4).

[0204]

[0205] According to the relative importance ratio r j , determine the weights of the other n-1 indicators, see formula (5).

[0206] α j-1 =r j α j (5)

[0207] Let α pq is the weight coefficient of the qth indicator under the pth criterion layer in the indicator system in the total target layer, α p is the weight coefficient of the pth criterion layer in the total target layer; α (p) q is the weight coefficient of the qth indicator in the pth criterion layer, then:

[0208] α pq =α p ×α (p) q (6)

[0209] The ordinal relationship analysis method uses experts to rank the importance of indicators and rationally weight the importance of adjacent indicators, which is highly subjective and arbitrary.

[0210] 2) Grey correlation analysis method to determine objective weights

[0211] Determine the system main behavior reference sequence X 0 Comparison sequence X with system-related factors 1 .

[0212] X 0 (k)=(x 0 (1),x 0 (2),…,x 0 (n)) (7)

[0213] X i (k)=(x i (1),x i (2),…,x i (n)) (i=1,2,…m) (8)

[0214] Since the physical meanings of different factors in the system are different, the dimensions of their data are also different, making it difficult to draw correct conclusions when comparing. Therefore, it is necessary to normalize (dimensionless) the data and convert the data into a pure digital sequence for calculation and comparative analysis. The data of the sequence is classified into a range.

[0215]

[0216] Calculate the correlation coefficient:

[0217]

[0218] Where ρ is the resolution coefficient, which ranges from [0,1] and is generally 0.5.

[0219] Calculate the correlation:

[0220]

[0221] Sorting is performed according to the magnitude of the factor correlation, reflecting the strength of the relationship between the comparison sequence and the reference sequence.

[0222] 3) Comprehensive weight acquisition method

[0223] Determination of combination weighting: (1) Use the G1 method to subjectively weight the evaluation indicators. (2) Use the grey correlation analysis method to objectively weight the indicators. (3) Combine the weights of (1) and (2) to determine the combination weight. (4) Select the expert preference coefficient to perform dynamic combination weighting and determine the linear combination weight.

[0224]

[0225] Combining the above two aspects, Figure 1 The above process, based on the fuzzy comprehensive evaluation method and COPRAS method, can quantify the low-carbon performance of the 110kV substation infrastructure project.

[0226] The fuzzy comprehensive evaluation method is a method that uses the principle of fuzzy transformation to analyze the object to be evaluated and then obtain its comprehensive evaluation. It is mainly divided into two steps: the first step is to judge according to the influence of a single factor, and the second step is to consider the influence of all factors for a comprehensive evaluation.

[0227] First, determine the evaluation index factor set, factor set (U = (u 1 ,u 2 ,…,u i )) refers to various factors that can affect the evaluation object (u i ).

[0228] Generally speaking, each factor has different importance. In order to express their importance, for each factor u i Assign the corresponding weight w i , then the weight set w i It can be expressed as: W = (w 1 ,w 2 ,…,w i ).

[0229] The evaluation level set (V) is composed of various evaluation result elements (v i ), that is, V=(v 1 ,v 2 ,…,v i ).

[0230] The fuzzy relationship matrix is ​​an evaluation of each independent factor in the factor set U, and its purpose is to calculate the degree of membership of each evaluation object to each element in the evaluation conclusion. First, the fuzzy evaluation matrix R is used to represent the fuzzy relationship of each indicator factor from the evaluation indicator factor set U to the comment level set V. The evaluation expert group is organized to evaluate and score each indicator factor, and the fuzzy relationship matrix is ​​constructed as follows:

[0231]

[0232] The R of the i-th row i It represents the membership of the evaluated factor i to each comment in the comment set, and the jth column represents the degree to which the evaluated factor takes the jth comment in the comment set.

[0233] The fuzzy relationship matrix can only reflect the impact of a single factor on the evaluation object. If you want to accurately judge an object, you also need to make a comprehensive analysis based on the weight set and the influence of various factors to make an accurate judgment. After calculating the weight set W and the fuzzy relationship matrix R, you can use the fuzzy comprehensive evaluation method to conduct the evaluation.

[0234]

[0235] Where: B is the fuzzy comprehensive evaluation result, b j is the membership degree of the evaluation object to the jth level in the comment set.

[0236] Combined with the weights of the low-carbon performance evaluation indicators of the 110kv substation infrastructure project, the selection of COPRAS can comprehensively consider the information of multiple indicators and provide decision makers with a scientific and reliable basis for decision-making by calculating the score ranking of each plan.

[0237] Low Carbon Performance Solution A for 110kv Substation Infrastructure Project i The benefit indicators in the

[0238]

[0239] Where: Obviously, The larger the value, the better the solution A iSecondly, for cost-based indicators, determine their comprehensive cost value

[0240]

[0241] Where: Obviously, The smaller the value, the better the solution A i Then, calculate its comprehensive evaluation value:

[0242]

[0243] Where: Obviously, Q i The larger the value, the lower the carbon performance of 110kv substation infrastructure project A i If a low-carbon performance plan for a 110kv substation infrastructure project has the largest comprehensive evaluation value, Q i Therefore, the low-carbon performance solution for the 110kv substation infrastructure project should be the best choice.

[0244] Calculate the effectiveness of the low-carbon performance solution for each 110kv substation infrastructure project:

[0245]

[0246] Where:

[0247] From the results, it can be seen that the utility of each 110kv substation infrastructure project low-carbon performance plan ranges from 0 to 100%, and the utility of the optimal 110kv substation infrastructure project low-carbon performance plan is 100%. In the process of selecting the low-carbon performance plan for the 110kv substation infrastructure project, Q i The optimal low-carbon performance level of each 110kv substation infrastructure project low-carbon performance plan is used to determine the best 110kv substation infrastructure project low-carbon performance plan selection strategy. The specific process is as follows: First, for each U i Sort them from large to small, let's record them as U (1) ≥U (2) ≥…≥U (m) This order is the priority order of low-carbon performance solutions for 110kv substation infrastructure projects, that is, U (1) Corresponding low-carbon performance plan for 110kv substation infrastructure project.

[0248] Finally, let F i is the membership degree of the evaluation level of the ith scheme obtained by the fuzzy comprehensive evaluation method, C iis the comprehensive evaluation value of the i-th scheme obtained by the COPRAS method, α and β are the weight coefficients of the two methods, which are used to adjust the relative importance of the two evaluation methods in the final evaluation. The comprehensive evaluation result T i It can be calculated by the following formula:

[0249] T i =αF i +βC i (19)

[0250] In the formula, the values ​​of α and β are usually determined according to the actual situation and the decision maker's preference, and satisfy α + β = 1. In this way, the comprehensive evaluation result T i The membership degree F of the fuzzy comprehensive evaluation method is integrated i and the evaluation value C of the COPRAS method i , provides a balanced evaluation result, which takes into account both the fuzziness and uncertainty of the evaluation object and the optimal solution in multi-objective decision-making. Decision experts can adjust α and β according to the characteristics of the evaluation objectives and evaluation indicators to ensure that the evaluation results are more in line with the needs.

[0251] The present invention is further described below in conjunction with examples. The following examples are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the protection scope of the present application.

[0252] This paper takes 50 typical 110kv substation infrastructure projects as examples, calculates the carbon footprint of each project and the possible carbon reduction benefits, quantifies the low-carbon performance of the infrastructure projects throughout their life cycle, and conducts an evaluation. Figure 1 As shown, a low-carbon performance review model based on a 110kV substation infrastructure project and its application method include the following steps:

[0253] Step 1: Calculation of the carbon footprint of a 110kv substation infrastructure project. The first stage is the preparation (materialization) stage, which includes all carbon emissions caused by the production of building materials and all carbon emissions generated from the production site to the construction site; the second stage is the construction stage, which includes the carbon emissions generated by all construction machinery; the third stage is the operation stage, which includes the impact of energy and water consumed in the daily operation of the building; the fourth stage is the scrapping stage, which includes carbon emissions during the demolition stage. According to the carbon emission factor method, the carbon footprint data of a 110kV substation infrastructure project at each stage are obtained as follows: Figure 2 shown.

[0254] Step 2: Use the correlation coefficient method to simplify the low-carbon performance evaluation index system of the 110kv substation infrastructure project and eliminate the coupling relationship between the indicators. Calculate the correlation coefficients between the secondary indicators, and judge the correlation between the indicators based on the correlation coefficients between the indicators in the table. For two indicators with smaller absolute values ​​of correlation coefficients, they can be used as independent indicators; for indicators with larger absolute values ​​of correlation coefficients, only one of them needs to be retained. Set the threshold of the absolute value of the correlation coefficient to 0.9.

[0255] Step 3: Use the G1 method to calculate the subjective weight of the indicator system. Comprehensively evaluate the first-level evaluation indicators, and select the most important indicator X from all indicators by 4 reviewers. 1 , the corresponding weight is denoted as α 1 ; Then continue to select the most important indicators from the remaining indicators until all indicators are selected, forming an indicator sequence ranked by relative importance (X 1 ,X 2 ,X 3 )The corresponding indicator weight is (α 1 ,α 2 ,α 3 ). The index sequence ranked by relative importance (X 1 ,X 2 ,X 3 ) corresponds to (A 1 ,A 2 ,A 3 )Indicator weight is (α 1 ,α 2 ,α 3 ).

[0256] Step 4: Determine the relative importance ratio of the indicators, which is obtained after discussion among the four evaluators.

[0257] Step 5: Calculate the final indicator weight.

[0258] Step 6: Calculate the weights of all indicators according to the relative importance ratio r j , determine the weights of other indicators.

[0259] Step 7: Similarly, calculate the secondary indicators under the primary indicators.

[0260] Step 8: Determine the relative importance of all factors at a certain level to the overall goal, starting from the highest level to the lowest level. pq =α p ×α (p) q, the weight of the first-level indicator is multiplied by the weight of the second-level indicator below it to obtain the subjective weight of each indicator.

[0261] Step 9: Obtain the objective weight of carbon emission reduction contribution rate assessment index based on grey correlation analysis method.

[0262] Step 10: Based on the calculation results of subjective weights and objective weights, the combined weights of the low-carbon performance review indicators of the 110kv substation infrastructure project are obtained according to the formula.

[0263] Step 11: Based on the combined weight value, the fuzzy comprehensive evaluation method and COPRAS method are used to obtain the low-carbon performance of each infrastructure project.

[0264] Step 12: Based on the above information and industry standards, 20 experts were invited to score each evaluation indicator based on the actual project data. This project sets four levels of comments for each indicator, namely V = (V 1 ,V 2 ,V 3 ,V 4 )=(excellent, good, average, poor). 20 experienced personnel evaluate the index system, and each expert grades each indicator of the index layer. Due to the fuzziness of the index, the number of times each person scores the index can be combined to obtain the degree of membership of the index to a certain comment level. The proportion of the comment levels of the 20 people who agree with each indicator is taken as the degree of membership, so as to establish a single-factor fuzzy comprehensive evaluation matrix.

[0265] Step 13: According to the calculation of the membership model, the membership matrix of indicators at all levels can be obtained.

[0266] Step 14: Through fuzzy comprehensive evaluation Hi=Ci×V(i=1,2,3) can get the final score.

[0267] Step 15: Calculate by normalization Get the fuzzy comprehensive evaluation method score.

[0268] Step 16: Determine the comprehensive benefit value of the benefit indicators in the low-carbon performance plan of the 110kv substation infrastructure project through the COPRAS method.

[0269] Step 17: Determine the comprehensive cost value of cost-type indicators through the COPRAS method.

[0270] Step 18: Calculate its comprehensive evaluation value.

[0271] Step 19: Calculate the effectiveness of the low carbon performance solution for each 110kv substation infrastructure project

[0272] Step 20: Construct a comprehensive model to integrate the results of the fuzzy comprehensive evaluation method and the COPRAS method to obtain a comprehensive low-carbon performance review result, T i =αF i +βCi .

[0273] Step 21: A low-carbon performance review was conducted on 50 typical 110kV substation infrastructure projects. The low-carbon performance score of each project was obtained by applying the fuzzy comprehensive evaluation method and COPRAS method.

[0274] Among these projects, Case 3, the 110 kV Boyi Digital Twin Substation project in Lingang area, stood out with its highest score. The low-carbon performance review results of the Shanghai Lingang 110 kV Boyi Digital Twin Substation infrastructure project show that the project has demonstrated excellent low-carbon practices in all stages of design, construction, operation, decommissioning and preparation. This achievement is due to the project team's in-depth understanding and application of low-carbon technologies, as well as its continued commitment to environmental protection and resource conservation.

[0275] The above description is only a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any modification or equivalent change made based on the technical essence of the present invention still falls within the scope of protection required by the present invention.

Claims

1. A method for determining low-carbon performance evaluation indicators for substation infrastructure projects based on the entire life cycle, characterized by: The following steps are involved: 1) Carbon emission accounting method for 110kv substation infrastructure projects based on life cycle theory; 2) Based on the correlation analysis method, a low-carbon performance evaluation index system for 110kV substation infrastructure projects throughout the entire life cycle is established; 3) Considering the influence of multiple factors, a low-carbon performance evaluation model for 110kV substation infrastructure projects throughout the life cycle was proposed; 4) Combined with the weights of the low-carbon performance evaluation indicators of the 110kv substation infrastructure project, the selection of COPRAS can comprehensively consider the information of multiple indicators and provide a basis for decision makers by calculating the score ranking of each plan.

2. The method for determining low-carbon performance evaluation indicators of substation infrastructure projects based on the entire life cycle according to claim 1 is characterized by: The step 1) life cycle method is used to calculate the carbon footprint of the 110kv substation infrastructure project through four steps: (1) Identify the various stages in the product or service life cycle and the emission sources at each stage; (2) Query and determine the carbon footprint factor; (3) Collect product or service data and calculate carbon footprint; (4) Analysis of carbon footprint calculation results; The carbon footprint of each stage of the 110kv substation infrastructure project cycle is the sum of the usage of all emission sources in this stage multiplied by their emission factors, that is: CF i =∑(AD ij ×EF ij ) (1) Among them, AD ij is the usage of the jth emission source in the i-th stage, in kg, m3 or kW·h; EF ij is the carbon footprint factor of the jth emission source in the i-th phase; CF i is the total carbon footprint of the product or service in stage i.

3. The method for determining low-carbon performance evaluation indicators of substation infrastructure projects based on the entire life cycle according to claim 1 is characterized by: The step 2) constructs a low-carbon performance evaluation index for 110kV substation infrastructure projects based on the correlation analysis method, which is expressed as: Where r is the indicator correlation coefficient; They are the average values ​​of the two indicators respectively. The two indicators that failed the correlation test can be used as independent indicators. For the two indicators with relatively high correlation, they are selected according to the above principles, and one of them is retained. The indicators are simplified according to this method respectively, and finally the indicators obtained by correlation analysis can be obtained.

4. The method for determining low-carbon performance evaluation indicators of substation infrastructure projects based on the entire life cycle according to claim 1 is characterized by: In the step 2), the low-carbon performance evaluation index of the 110kV substation infrastructure project is constructed based on the correlation analysis method, and the evaluation index system is determined from the design evaluation stage, construction evaluation stage, operation evaluation stage, and scrapping and preparation stage:

5. The method for determining low-carbon performance evaluation indicators of substation infrastructure projects based on the entire life cycle according to claim 1 is characterized by: The step 2) constructs a low-carbon performance evaluation index system for 110kV substation infrastructure projects over the entire life cycle based on the correlation analysis method, considers the actual operation data of 110kV substation infrastructure projects on the basis of the traditional subjective indicator weight perception method, and establishes a weight perception method based on subjective and objective factors. In the weight perception method based on subjective and objective factors, the actual operation data of 110kV substation infrastructure projects is considered on the basis of the traditional subjective indicator weight perception method, and a weight perception method based on the combination of subjective and objective factors is established, which can be expressed as: Among them, θ1 is the expert preference coefficient of the ordinal relation analysis method, θ2 is the expert preference coefficient of the grey relation analysis method; α j is the subjective weight of the evaluation index by ordinal relationship analysis method; β j It is the objective weight of the evaluation index by grey relational analysis method.

6. The method for determining low-carbon performance evaluation indicators of substation infrastructure projects based on the entire life cycle according to claim 5 is characterized by: The step 2) establishes the order relationship analysis method based on the subjective and objective factors combined weight perception method to calculate the subjective weight of the evaluation index according to the following method: The specific steps are as follows: Step 1: Determine the indicator sequence, select evaluation indicators to conduct a comprehensive evaluation of the object to be evaluated, and the evaluator selects the most important indicator from the indicators, and the corresponding weight is recorded as; then continue to select the most important indicator from the remaining indicators, and so on; until all indicators are selected, a sequence of indicators ranked by relative importance is formed, and the corresponding indicator weight is; Step 2: Determine the relative importance ratio of the indicators. The relative importance ratio of the indicators determines the indicator weight. It is obtained after discussion by all evaluators. The calculation formula of the relative importance ratio is: Step 3: Calculate the weight of the nth indicator. The calculation formula is: Step 4: Calculate the weights of all indicators according to the relative importance ratio r j , determine the weights of other n-1 indicators; α j-1 ＝r j α j (5) Step 5: Determine the weight coefficient of each indicator to the total target layer, set α pq is the weight coefficient of the qth indicator under the pth criterion layer in the indicator system in the total target layer, α p is the weight coefficient of the pth criterion layer in the total target layer; α (p) q is the weight coefficient of the qth indicator in the pth criterion layer, then: α pq ＝α p ×α (p) q (6)。 7. The method for determining low-carbon performance evaluation indicators of substation infrastructure projects based on the entire life cycle according to claim 5 is characterized by: The step 2) establishes a method based on the perception of the combined weights of subjective and objective factors, and the objective weights of the evaluation indicators are calculated by the grey correlation analysis method according to the following method: Step 1: Determine the system main behavior reference sequence X0 and the comparison sequence X1 of system related factors; X0(k)=(x0(1),x0(2),…,x0(n)) (7) X i (k)=(x i (1),x i (2),…,x i (n)) (i=1,2,…m) (8) Step 2: Since the physical meanings of different factors in the system are different, the dimensions of their data are also different, making it difficult to draw correct conclusions when making comparisons. Therefore, it is necessary to normalize the data and convert the data into a pure digital sequence to facilitate calculation and comparative analysis, and to classify the sequence data into a range. Step 3: Calculate the correlation coefficient: Where ρ is the resolution coefficient, the value range is [0,1], and it is generally taken as 0.5; Step 4: Calculate the correlation: Sorting is performed according to the magnitude of the factor correlation, reflecting the strength of the relationship between the comparison sequence and the reference sequence.

8. The method for determining low-carbon performance evaluation indicators of substation infrastructure projects based on the entire life cycle according to claim 1 is characterized by: Step 3) Considering the influence of multiple factors, a low-carbon performance review model for 110kV substation infrastructure projects is proposed. The specific steps are as follows: Step 1: Establish a corresponding first-level evaluation indicator set, which means that there are three evaluation indicators in the first-level evaluation indicators, which correspond to energy efficiency indicators, economic indicators and environmental indicators respectively. On the basis of the first-level indicator set, establish a second-level indicator set, that is, each first-level indicator corresponds to several second-level indicators. On the basis of the second-level indicator set, establish a third-level indicator set, that is, each second-level indicator corresponds to several third-level indicators. Step 2: Establish a comment level set V = (V1, V2, V3, V4) = (excellent, good, average, poor). The invited experts make judgments on the questions corresponding to each indicator in the questionnaire based on the actual situation of each evaluated project, and then select appropriate comments in the comment level; Step 3: Establish an evaluation index weight set based on the combined weight; Step 4: Establish a fuzzy judgment matrix, the specific form is shown in R below: Among them, r ij =μ R (U i ,V j ), r∈[1,n] is the membership of the i-th factor U to the j-th comment level V. For each three-level factor U ij You can use an R i , then the secondary factor U i The fuzzy relation matrix on the V domain is R i =(B1,B2,B3,…,B i ) T ; Relationship Matrix R i The element B in i Yes ij and r ij pass After fuzzy transformation, the first-level evaluation vector is obtained. After processing, the fuzzy evaluation result B=W of the first-level factor is obtained. i ·R i =(b1,b2,…,b i ); Step 5: Repeat the above calculation process, use the first-level judgment result as the second-level indicator membership, calculate the comprehensive evaluation result vector of the previous level indicator, and after determining the fuzzy relationship matrix and weight set of each layer, perform fuzzy evaluation in different levels. Through the hierarchical evaluation and then comprehensive method, the fuzzy comprehensive evaluation result of project U is finally obtained, and then according to the maximum membership principle, the comment level corresponding to the maximum value in the set is selected as the final project evaluation result; Step 6: Calculate the final project evaluation results through normalization Get the low carbon performance of each project.

9. The method for determining low-carbon performance evaluation indicators of substation infrastructure projects based on the entire life cycle according to claim 1 is characterized by: Step 4) Combined with the weights of the low-carbon performance evaluation indicators of the 110kv substation infrastructure project, COPRAS is selected to comprehensively consider the information of multiple indicators and calculate the score ranking of each scheme, as follows: Step 1: Evaluate the low-carbon performance plan of each 110kv substation infrastructure project under different indicators, and the obtained decision matrix is ​​recorded as: Where: x ij For the indicator C j Under this condition, the evaluation value of the low-carbon performance scheme of the i-th 110kv substation infrastructure project is i , if C j ∈J1 benefit-type indicator, then x ij The larger the value of C is, the better the low-carbon performance of the 110kv substation project is; on the contrary, if C j ∈J2 cost type index, then x ij The larger the value is, the worse the low-carbon performance of the 110kv substation project is; Step 2: Normalize it to get the normalized decision matrix, as shown below: Step 3: Calculate the weighted normalized decision matrix, calculate the weighted normalized decision matrix R = (r ij ) m×n ; r ij =y ij ×w j i=1,2,…,m j=1,2,…,n (17) Step 4: Low Carbon Performance Plan A for 110kv Substation Infrastructure Project i The benefit indicators in the Where: Obviously, The larger the value, the better the solution A i better; better Step 5: Determine the comprehensive cost value for cost-based indicators Where: Obviously, The smaller the value, the better the solution A i better; better Step 6: Calculate its comprehensive evaluation value Where: Obviously, Q i The larger the value, the lower the carbon performance of 110kv substation infrastructure project A i If a 110kv substation infrastructure project low-carbon performance plan has the largest comprehensive evaluation value, Q i Then the low-carbon performance solution for the 110kv substation infrastructure project should be the best choice; Step 7: Calculate the effectiveness of the low-carbon performance solution for each 110kv substation infrastructure project Where:

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