Multi-dimensional evaluation method based on building energy consumption management

Abstract

The invention relates to a multi-dimensional evaluation method based on building energy consumption management, and the method comprises the following steps: S1, building energy consumption behavior indexes which comprise a human factor, a machine factor, a material factor and a method factor; s2, establishing an energy consumption comprehensive index evaluation system by using an energy consumption analysis method; and S3, by taking the energy consumption influence factor as a first-level index and the energy consumption behavior index as a second-level index, establishing a comprehensive evaluation index based on energy consumption to comprehensively evaluate each energy consumption behavior index in the energy consumption comprehensive index evaluation system. Compared with the prior art, through the systematic energy consumption index establishment and evaluation system, the energy consumption condition of the building can be comprehensively known, main energy consumption sources can be identified, and corresponding energy-saving improvement measures can be formulated, so that the overall energy efficiency management level is improved.

Description

Technical Field

[0001] The present invention relates to the field of building energy-saving transformation, and in particular to a multi-dimensional evaluation method based on building energy consumption management. Background Art

[0002] Against the backdrop of global energy conservation and emission reduction, building energy management has become an important part of modern building management. Building energy management involves monitoring, analyzing and optimizing the energy use of various equipment in buildings to reduce energy consumption and lower operating costs. Related technical fields include energy management systems (EMS), smart building technology, and Internet of Things (IoT) technology. With the development of information technology, intelligent and data-based energy management methods have gradually been introduced, promoting the scientific, refined and automated management of building energy consumption. However, traditional energy management methods still have certain limitations and are difficult to fully meet the growing energy-saving needs of modern buildings.

[0003] Traditional building energy management usually relies on manual collection and analysis of energy consumption data, using methods such as simple energy audits and regular energy consumption assessments. These methods are often based on speculation based on past experience and lack systematic data support. In addition, traditional technologies mainly rely on single indicators or static indicators for evaluation, resulting in a one-sided understanding of energy consumption behavior and an inability to conduct in-depth analysis of the various factors that affect energy consumption. In the research process, traditional technologies often use questionnaires, interviews, and other methods. The results are easily affected by subjective factors, and the accuracy and comprehensiveness of the data are low. Therefore, traditional energy management methods cannot adapt to the increasingly complex management needs of building energy consumption. The overall energy management process is Figure 1 shown.

[0004] The energy consumption analysis methods of traditional technologies lack scientificity and systematicity, and fail to fully reflect the actual energy consumption of buildings, resulting in the formulation of energy consumption improvement measures often being based on inaccurate data. Secondly, traditional methods are difficult to achieve a comprehensive evaluation of energy consumption behavior, and cannot fully consider the influence of multiple factors such as people, machines, materials, and methods, which makes managers lack a comprehensive perspective when formulating energy-saving strategies. Finally, the traditional energy consumption cost analysis mechanism lacks market considerations and cannot effectively guide users to choose high-efficiency equipment, which affects the promotion and implementation of energy-saving measures. Therefore, in order to overcome the shortcomings of traditional technologies, a more systematic, scientific and operational building energy consumption management method is urgently needed to improve the level of energy efficiency management and promote sustainable development. Summary of the invention

[0005] The purpose of the present invention is to provide a multi-dimensional evaluation method based on building energy consumption management in order to overcome at least one of the defects of the above-mentioned prior art.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] A multi-dimensional evaluation method based on building energy consumption management includes the following steps:

[0008] S1. Establish energy consumption behavior indicators, wherein the energy consumption behavior indicators include human factors, machine factors, material factors and legal factors; the human factors include working days, non-working days, and employees' energy consumption habits on working days; the machine factors include energy efficiency of energy-consuming equipment, replacement of energy-consuming equipment, and energy consumption of energy-consuming equipment; the material factors include energy consumption of lighting and energy consumption of equipment; the legal factors include management regulations, energy management system, energy consumption management requirements, and incentive measures;

[0009] S2. Use energy consumption analysis methods to establish a comprehensive energy consumption index evaluation system;

[0010] S3. Taking energy consumption influencing factors as the primary indicators and energy consumption behavior indicators as the secondary indicators, establish a comprehensive evaluation index based on energy consumption to comprehensively evaluate various energy consumption behavior indicators in the energy consumption comprehensive indicator evaluation system, wherein the energy consumption influencing factors include building area type factors, regional building area factors, energy consumption time factors of energy consuming units, number of personnel per unit building area factors, equipment energy efficiency factors, building operation time factors, air conditioning energy consumption factors, lighting energy consumption factors, lighting and air conditioning simultaneous use factors, lighting and air conditioning simultaneous use time factors per unit building area, power equipment energy consumption factors, power use time factors per unit building area, power equipment energy efficiency factors, elevator energy consumption factors, and elevator use time factors per unit building area.

[0011] Furthermore, in S1, the energy consumption behavior index is established through survey analysis, energy consumption data analysis and energy consumption cost analysis.

[0012] Among them, the investigation and analysis is to conduct energy consumption investigation, and clarify the basic data of various energy consumption through investigation methods; the energy consumption data analysis is to combine the energy consumption data of each system, analyze the energy consumption through sub-item management, clarify the factors affecting energy consumption, and analyze the energy consumption proportion of each system; the energy consumption cost analysis is to obtain the energy consumption cost according to the investigation and analysis results, combined with the market mechanism, according to the sub-item management method, establish the corresponding energy-saving transformation price system, and determine the expenses that users should bear for using the corresponding energy-saving services.

[0013] Furthermore, the survey method is a questionnaire survey, telephone survey or on-site survey, and the basic data of the survey include energy consumption areas, departments, building areas, lighting and electrical equipment, power equipment, refrigeration equipment, fire-fighting equipment, office equipment types, as well as lighting, air-conditioning, power operation modes, equipment switching time, working hours, and air-conditioning and lighting working modes.

[0014] Furthermore, in S2, the energy consumption analysis method includes any one or more of cluster analysis, association rules, and classification tree algorithm.

[0015] Among them, when the energy consumption analysis method is cluster analysis, different energy consumption types are identified by cluster analysis of historical energy consumption data. When the energy consumption analysis method is association rules, the correlation between different energy consumption factors is mined, and some factors are analyzed to have a significant impact on a certain energy consumption, so as to provide energy-saving suggestions and guidance for users. When the energy consumption analysis method is a classification tree algorithm, an energy consumption classification prediction model can be constructed based on historical energy consumption data and classification labels, which is used to predict the energy consumption category of a certain time period or a certain area in the future and formulate targeted energy consumption management strategies.

[0016] Furthermore, in S3, the factors affecting energy consumption are analyzed by a comprehensive evaluation method, and the comprehensive evaluation method includes the following steps: calculating the total value of each evaluation index, performing dimensionless processing, calculating each weight value, and multiplying it with the normalized index matrix to obtain a weighted index matrix; finally, calculating the comprehensive evaluation value of the index, ranking it, and obtaining a multi-dimensional quantitative assessment carbon saving index.

[0017] Furthermore, in S3, the energy consumption behavior indicators are analyzed by a multi-indicator evaluation method, which is a greenhouse gas inventory method. This method performs weighted summation of direct and indirect emissions of energy consumption, combined with carbon emission factors and carbon equivalent coefficients, to obtain emission indicators for various types of energy-consuming equipment.

[0018] Compared with the prior art, the present invention has the following advantages:

[0019] (1) Improve energy efficiency management: Through the establishment and evaluation of a systematic energy consumption index system, we can fully understand the energy consumption of the building, identify the main sources of energy consumption, and formulate corresponding energy-saving improvement measures, thereby improving the overall energy efficiency management level.

[0020] (2) Promoting energy-saving transformation: The establishment of energy consumption cost analysis and energy-saving price system provides users with a basis for selecting energy-saving equipment, encourages users to adopt high-efficiency equipment, helps promote the implementation of energy-saving transformation, and reduces operating costs.

[0021] (3) Scientific decision support: The application of multi-dimensional evaluation methods (such as hierarchical analysis method, comprehensive evaluation method, etc.) makes the evaluation results more scientific and objective, providing data support for management in formulating energy management strategies and helping to make more reasonable decisions.

[0022] (4) Quantified carbon emission management: The greenhouse gas inventory method can accurately calculate the carbon emissions of a building, which helps managers understand greenhouse gas emissions, provides a basis for further implementation of carbon emission reduction measures, and promotes sustainable development.

[0023] (5) Enhance user awareness: Research and analysis and the establishment of energy consumption behavior indicators make it clear how personnel, management, and equipment are used, increase users’ attention to energy efficiency management, and help create a good atmosphere for energy conservation and emission reduction.

[0024] (6) Optimizing resource allocation: By analyzing the various factors that affect energy consumption, we can rationally optimize resource allocation to ensure that energy consumption and operating costs are minimized while meeting usage needs.

[0025] Enhance enterprise competitiveness: After implementing energy-saving and emission-reduction measures, enterprises can not only reduce operating costs, but also improve their corporate image and enhance their competitiveness in the market, which is in line with society's expectations for environmental protection.

[0026] Continuous improvement mechanism: By establishing a feedback mechanism and continuous improvement measures, managers can continuously optimize energy management plans based on evaluation results, forming a virtuous cycle and continuously improving energy efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is the energy consumption management flow chart of the present invention;

[0028] Figure 2 It is the energy consumption behavior indicator structure diagram of the present invention;

[0029] Figure 3 It is a flow chart of the energy consumption analysis method of the present invention;

[0030] Figure 4 is a flow chart of carbon emission calculation of the present invention;

[0031] Figure 5 It is a comprehensive evaluation flow chart of the evaluation indicators of the present invention; DETAILED DESCRIPTION

[0032] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.

[0033] Example

[0034] like Figure 2 As shown, the energy consumption behavior indicator is established as follows:

[0035] Energy consumption behavior indicators include human factors, machine factors, material factors and legal factors. The human factors are working days, non-working days, and the energy consumption habits of employees on working days; the machine factors include the energy efficiency of energy-consuming equipment, replacement of energy-saving equipment, and inspection factors of energy consumption; the material factors include energy consumption factors such as lighting and equipment; the legal factors include management regulations, energy management system, energy consumption management requirements, and incentive measures.

[0036] like Figure 3 As shown in the figure, the energy consumption analysis method includes using statistical means to form an energy consumption database through enterprise energy consumption report statistics, energy consumption system data statistics, online monitoring data statistics, and energy consumption data matching with building area, energy consumption area and energy consumption department; analyzing energy consumption through data mining, using cluster analysis, grouping users, and extracting typical energy consumption user models based on the aggregation of typical energy consumption, combined with energy consumption location, energy consumption area, energy consumption equipment type, and energy consumption time; for different types of users, using association rules and classification tree algorithms, mining various factors affecting energy consumption, and evaluating the degree of influence, sorting from high to low according to the degree of influence of each factor on energy consumption, and determining the main factors affecting energy consumption. According to the statistical analysis of user electricity consumption, typical association rules are used to compare high and low user electricity consumption, establish rules, and extract the main factors affecting energy consumption.

[0037] Energy consumption cost analysis: Investigate energy consumption and equipment conditions, adopt an equipment cost price system for energy-consuming equipment, classify prices according to different equipment energy efficiency levels, determine the price differences of different energy-efficient equipment, and guide users to take energy-saving measures and encourage high-energy-saving equipment. The multi-index evaluation method includes one of the following: hierarchical analysis method, fuzzy comprehensive evaluation method, comprehensive index method, entropy value method, and grey correlation analysis method.

[0038] Factors influencing energy consumption include building area type factors, regional building area factors, energy consumption time factors of energy-consuming units, number of people per unit building area factors, equipment energy efficiency factors, building operating time factors, air-conditioning energy consumption factors, lighting energy consumption factors, simultaneous use of lighting and air-conditioning factors, simultaneous use time factors of lighting and air-conditioning per unit building area, power equipment energy consumption factors, power use time factors per unit building area, power equipment energy efficiency factors, elevator energy consumption factors, elevator use time factors per unit building area, other energy consumption factors per unit building area, other related energy equipment use factors, time factors of other related energy equipment per unit building area, management factors, other related management factors, other related incentive factors, and other energy management factors.

[0039] Energy consumption indicators include electricity consumption, water resource consumption, gas consumption, and other energy consumption. Electricity consumption includes lighting consumption, air conditioning consumption, power consumption, and special consumption; water resource consumption includes cooling water consumption and domestic water consumption; gas consumption includes heating gas consumption and hot water gas consumption; and other energy consumption includes energy consumption of specific equipment.

[0040] like Figure 5 As shown, the comprehensive evaluation method includes the following steps:

[0041] Step 1: Calculate the total value of each evaluation indicator;

[0042] Step 2: Use dimensionless data processing method to obtain the normalized indicator matrix;

[0043] Step 3: Solve the judgment matrix by the eigenvector method, calculate the weight vector W of each component, and multiply it with the normalized indicator matrix to obtain the weighted indicator matrix;

[0044] Step 4: Calculate the comprehensive evaluation value of the index;

[0045] Step 5: Rank according to the comprehensive score of the indicators and sort the rankings.

[0046] In step 1, for the positive index, the larger its value, the better the evaluation effect, and for the negative index, the smaller its value, the better the evaluation effect; in step 2, different indexes are normalized by dimensionless processing, and the dimensionless processing formula is:

[0047] For positive indicators (the larger the evaluation value, the better), you can use:

[0048] Among them, x i ' j is the dimensionless value, x ij is the original index value, max(x ij ) is the maximum value in the column.

[0049] For the reverse indicator (the smaller the evaluation value, the better), you can use:

[0050] Among them, min(x ij ) is the minimum value in the column.

[0051] In step 4, the comprehensive evaluation value C of the index is calculated by the following formula:

[0052] C = X·W;

[0053] Where: X is the normalized indicator matrix; W is the weight vector, W = (ω 1 ,ω 2 ,…,ωm ) T ,ω i Represents the weight of the i-th indicator.

[0054] For each evaluation object (row vector), its comprehensive evaluation value C is calculated by matrix multiplication:

[0055] That is, the weighted sum of all indicators.

[0056] The multi-dimensional evaluation method based on building energy consumption management also includes the following steps: using energy influencing factors as primary indicators and energy consumption indicators as secondary indicators to establish comprehensive evaluation indicators based on energy consumption.

[0057] like Figure 4 As shown, based on the carbon emission and energy consumption indicators, combined with the greenhouse gas inventory method, the carbon emission indicators are calculated; the greenhouse gas inventory method includes the following steps:

[0058] Step 1: Calculate the direct emissions indicators of energy consumption;

[0059] Step 2: Calculate indirect emissions caused by energy consumption;

[0060] Step 3: Multiply direct emissions and other emission indicators by the carbon equivalent coefficient to convert them into carbon dioxide equivalents, and obtain the greenhouse gas inventory by summing them up.

[0061] The energy sources include natural gas, fuel oil, diesel and electricity purchased by power grid enterprises, among which the carbon equivalent coefficient of complete combustion of each cubic meter of natural gas is 49.1g CO 2 / kwh, the carbon equivalent coefficient of complete combustion of each liter of fuel oil is 33.4gCO 2 / kwh; the carbon equivalent coefficient of complete combustion of each liter of diesel is 37.1g CO 2 / kwh, the carbon equivalent coefficient of each kilowatt-hour of complete combustion is 112.4g CO 2 / kwh; the total carbon emissions are calculated using the formula: N = E + P

[0062] Where: N: Total carbon emissions (unit: kg CO 2 e), E: direct emissions (unit: kg CO 2 e), P: process emissions (unit: kg CO 2 e)

[0063] Direct emissions calculation formula

[0064] For each energy source j, its direct emissions E j It can be calculated by the following formula:

[0065] Ej =Q j ·δ j , where: Q j : Energy consumption of energy j (unit: kg / kWh), δ j : Carbon equivalent factor of energy j (unit: kg CO 2 e / (kg / kWh)

[0066] The carbon emission factors of different energy sources are as follows:

[0067] Natural gas: δ gas =1.44kgCO2e / (kg / kWh);

[0068] Fuel oil: δ oil =1.78kgCO2e / (kg / kWh);

[0069] Diesel: δ diesel =2.4kgCO2e / (kg / kWh);

[0070] Electricity: δ electric =0.983kgCO2e / (kg / kWh).

[0071] The final carbon emissions formula is: Among them, j represents different types of energy, specifically natural gas, fuel oil, diesel and electricity.

[0072] The first-level indicators include excellent, good, qualified and unqualified; Energy consumption equipment indicator evaluation level: The first-level indicators include excellent, qualified and unqualified; The energy consumption equipment indicators include air-conditioning equipment, power equipment, lighting equipment, and elevators; The indicator evaluation levels are: The second-level indicator evaluation levels include: Class A, Class B, and Class C; The second-level indicators include: Air-conditioning equipment evaluation method: Air-conditioning equipment is divided into three levels, A, B, and C, according to energy efficiency. Each level of air-conditioning equipment has a corresponding energy consumption range; After energy saving, the energy consumption range of air-conditioning equipment should be lowered by one level. If the energy consumption is higher than the highest energy consumption range of its corresponding level, it is unqualified; Power equipment and lighting equipment: The evaluation levels are divided according to relevant regulations; Elevator equipment evaluation method: Elevator equipment is classified and evaluated according to the "Energy Design Standard for Super High-rise Buildings" (GB 50501-2005), with Class A equipment scoring 90 and Class B equipment scoring 80; Lighting equipment evaluation: According to the energy-saving certification, the score is 90; Carbon emissions indicators are qualified.

[0073] Specific implementation case: Energy consumption management and carbon emission assessment of an office building

[0074] Background: A large office building with a construction area of ​​20,000 square meters, equipped with office areas, conference rooms, rest areas and supporting facilities. The annual energy consumption of the office building mainly comes from air conditioning, lighting and power equipment. It is planned to reduce energy consumption and carbon emissions through energy management.

[0075] 1. Establish energy consumption behavior indicators

[0076] Energy consumption behavior indicators include:

[0077] Human factors: working days, non-working days, and employees’ energy usage habits during working days.

[0078] Mechanical factors: energy efficiency of energy-consuming equipment, replacement of energy-consuming equipment, and energy consumption of energy-consuming equipment.

[0079] Material factors: Reasonably adjust the energy consumption of lighting and equipment, and ensure that lights are turned off in areas where lighting is not needed.

[0080] Legal factors: Develop energy management systems and set up incentives to encourage employees to participate in energy-saving activities.

[0081] 2. Energy consumption analysis method

[0082] Data Collection:

[0083] Through the survey, we can obtain energy consumption data of various equipment in the building, including:

[0084] Air conditioning system: Annual electricity consumption is 200,000 kWh

[0085] Lighting system: Annual electricity consumption is 100,000 kWh

[0086] Power equipment: Annual electricity consumption is 50,000kWh

[0087] Energy consumption database establishment:

[0088] Statistical methods are used to match the above data with building area, energy consumption area, etc. to establish an energy consumption database.

[0089] Data mining:

[0090] Conduct cluster analysis to analyze typical energy user models and identify the usage time and areas of high-energy consumption equipment (such as air conditioning and lighting).

[0091] 3. Energy consumption cost analysis

[0092] Formulate pricing system:

[0093] According to the cost of equipment with different energy efficiency levels, the following is determined through research:

[0094] Energy efficiency ratings of high-efficiency air conditioners and their prices at $80,000

[0095] Energy efficiency rating of a regular air conditioner and its price is 60,000 yuan

[0096] 4. Multi-index evaluation method

[0097] Comprehensive evaluation method implementation steps:

[0098] Step 1: Calculate the total value of each evaluation indicator:

[0099] Air conditioning energy consumption: 200,000kWh

[0100] Lighting energy consumption: 100,000kWh

[0101] Power equipment energy consumption: 50,000kWh

[0102] Step 2: Dimensionless processing to obtain a normalized indicator matrix.

[0103] Step 3: Use the eigenvector method to calculate the weight vector W and multiply it with the normalized indicator matrix to obtain the weighted indicator matrix.

[0104] Step 4: Calculate the comprehensive evaluation value C of the indicator and obtain the comprehensive score.

[0105] Step 5: Rank based on the overall scores and identify priority areas for improvement.

[0106] 5. Carbon emissions assessment

[0107] Greenhouse gas inventory method:

[0108] Step 1: Calculate direct air conditioning emissions:

[0109] Direct emissions = air conditioning electricity consumption × carbon equivalent coefficient

[0110] =200,000kWh×112.4gCO2 / kWh=22,480kgCO2

[0111] Step 2: Calculate emissions from lighting and power equipment in the same way.

[0112] Step 3: Add up all direct emissions to get the total carbon emissions of the office building.

[0113] 6. Improvement measures and suggestions

[0114] Based on the evaluation results, improvement measures are proposed:

[0115] Replacing air conditioning equipment with high-efficiency models is expected to reduce energy consumption by 15%.

[0116] Optimize the lighting system and implement intelligent control to further reduce energy consumption.

[0117] Strengthen energy-saving training for employees, improve their energy-saving awareness, and form a good energy-saving culture.

[0118] in conclusion

[0119] Through the above implementation cases, the energy consumption and carbon emissions of a certain office building can be effectively evaluated, providing a scientific basis for subsequent energy-saving renovation and management decisions. At the same time, the established indicator system and analysis method can be extended and applied to the energy consumption management of other buildings.

[0120] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. A multidimensional evaluation method based on building energy consumption management, characterized in that: The steps include: S1. Establish energy consumption behavior indicators, wherein the energy consumption behavior indicators include human factors, machine factors, material factors and legal factors; the human factors include working days, non-working days, and employees' energy consumption habits on working days; the machine factors include energy efficiency of energy-consuming equipment, replacement of energy-consuming equipment, and energy consumption of energy-consuming equipment; the material factors include energy consumption of lighting and energy consumption of equipment; the legal factors include management regulations, energy management system, energy consumption management requirements, and incentive measures; S2. Use energy consumption analysis methods to establish a comprehensive energy consumption index evaluation system; S3. Taking energy consumption influencing factors as the primary indicators and energy consumption behavior indicators as the secondary indicators, establish a comprehensive evaluation index based on energy consumption to comprehensively evaluate various energy consumption behavior indicators in the energy consumption comprehensive indicator evaluation system, wherein the energy consumption influencing factors include building area type factors, regional building area factors, energy consumption time factors of energy consuming units, number of personnel per unit building area factors, equipment energy efficiency factors, building operation time factors, air conditioning energy consumption factors, lighting energy consumption factors, lighting and air conditioning simultaneous use factors, lighting and air conditioning simultaneous use time factors per unit building area, power equipment energy consumption factors, power use time factors per unit building area, power equipment energy efficiency factors, elevator energy consumption factors, and elevator use time factors per unit building area.

2. According to claim 1, a multi-dimensional evaluation method based on building energy consumption management is characterized in that: In S1, the energy consumption behavior index is established through research analysis, energy consumption data analysis and energy consumption cost analysis.

3. The multi-dimensional evaluation method based on building energy consumption management according to claim 2 is characterized in that: The survey and analysis is to conduct an energy consumption survey and clarify the basic data of various energy consumption through survey methods; the energy consumption data analysis is to combine the energy consumption data of each system, analyze the energy consumption through sub-item management, clarify the factors affecting energy consumption, and analyze the energy consumption proportion of each system; the energy consumption cost analysis is to obtain the energy consumption cost based on the survey and analysis results, combined with the market mechanism, and through the sub-item management method, establish a corresponding energy-saving transformation price system, and determine the expenses that users should bear for using corresponding energy-saving services.

4. The multi-dimensional evaluation method based on building energy consumption management according to claim 3 is characterized in that: The survey method is questionnaire survey, telephone survey or on-site survey. The basic data of the survey include energy consumption area, department, building area, lighting and electrical equipment, power equipment, refrigeration equipment, fire-fighting equipment, office equipment types, as well as lighting, air-conditioning, power operation modes, equipment switching time, working hours, and air-conditioning and lighting working modes.

5. The multi-dimensional evaluation method based on building energy consumption management according to claim 1 is characterized in that: In S2, the energy consumption analysis method includes any one or more of cluster analysis, association rules, and classification tree algorithm.

6. A multi-dimensional evaluation method based on building energy consumption management according to claim 4, characterized in that: When the energy consumption analysis method is cluster analysis, different energy consumption types are identified by performing cluster analysis on historical energy consumption data.

7. The multi-dimensional evaluation method based on building energy consumption management according to claim 4 is characterized in that: When the energy consumption analysis method is an association rule, the association relationship between different energy consumption factors is mined, and it is analyzed that certain factors have a significant impact on a certain energy consumption, so as to provide energy-saving suggestions and guidance to users.

8. The multi-dimensional evaluation method based on building energy consumption management according to claim 4 is characterized in that: When the energy consumption analysis method is a classification tree algorithm, an energy consumption classification prediction model can be constructed based on historical energy consumption data and classification labels to predict the energy consumption category of a certain time period or a certain area in the future and formulate targeted energy consumption management strategies.

9. The multi-dimensional evaluation method based on building energy consumption management according to claim 1 is characterized in that: In S3, the factors affecting energy consumption are analyzed by a comprehensive evaluation method, which includes the following steps: calculating the total value of each evaluation index, performing dimensionless processing, calculating each weight value, multiplying it with the normalized index matrix, and obtaining a weighted index matrix; finally, calculating the comprehensive evaluation value of the index, ranking it, and obtaining a multi-dimensional quantitative assessment carbon saving index.

10. The multi-dimensional evaluation method based on building energy consumption management according to claim 1 is characterized in that: In S3, the energy consumption behavior indicators are analyzed by a multi-indicator evaluation method, which is a greenhouse gas inventory method. This method uses direct and indirect emissions of energy consumption, combined with carbon emission factors and carbon equivalent coefficients, to perform weighted summation to obtain emission indicators for various types of energy-consuming equipment.

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