Green low-carbon energy service management system

Abstract

The invention discloses a green low-carbon energy consumption service management system, which belongs to the technical field of energy consumption management and comprises a platform end and a user end. The platform end is used and managed by a platform party and comprises a monitoring analysis module; the monitoring analysis module is used for performing monitoring reserve analysis, setting a plurality of energy consumption estimation models and configuring corresponding energy consumption estimation models for the user side; the user side comprises a monitoring module, a display module and an energy-saving analysis module; the monitoring module is used for monitoring energy consumption data of each energy consumption device in an enterprise in real time, and merging and classifying the energy consumption devices to obtain a plurality of representative classifications and independent devices; monitoring equipment is arranged according to the representative classification and the independent equipment; performing real-time energy consumption monitoring on the representative classification and the independent equipment according to the energy consumption estimation model to obtain energy consumption monitoring data of the energy consumption equipment; the display module is used for monitoring and displaying; and the energy-saving analysis module is used for performing real-time energy-saving analysis according to the energy consumption simulation model to obtain a corresponding emission reduction scheme.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy management, and in particular is a green and low-carbon energy service management system. Background Art

[0002] As energy demand continues to increase, developing green and low-carbon energy, improving energy efficiency, and reducing carbon emissions have become the goals and pursuits of current social development; traditional energy management systems often have problems such as high energy consumption, large carbon emissions, and insufficient intelligence, which cannot meet the current society's urgent needs for energy conservation, emission reduction, and sustainable development. In recent years, with the rapid development of information technology and the improvement of intelligence, green and low-carbon energy service management systems have gradually become possible. By integrating advanced sensor technology, Internet of Things technology, big data analysis technology, etc., the system can achieve real-time monitoring, intelligent analysis, and efficient management of energy consumption. In addition, with the continuous innovation and application of green and low-carbon technologies, such as the use of clean energy and the promotion of energy-saving and efficiency-enhancing technologies, it also provides strong technical support for the development of green and low-carbon energy service management systems.

[0003] However, despite the huge potential and market prospects of the green and low-carbon energy service management system, there are still some challenges and problems in the market. For example, there may be compatibility issues between devices of different brands and models, especially when enterprises add new devices later.

[0004] Based on this, in order to solve the green and low-carbon energy service management needs of enterprises, the present invention provides a green and low-carbon energy service management system. Summary of the invention

[0005] In order to solve the problems existing in the above solutions, the present invention provides a green and low-carbon energy service management system.

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

[0007] A green and low-carbon energy service management system, comprising a platform end and a user end;

[0008] The platform end is used and managed by the platform party, including a monitoring and analysis module;

[0009] The monitoring and analysis module is used to perform monitoring and reserve analysis, identify the monitoring scope of the platform, and generate and update the reserve equipment list in real time according to the monitoring scope; set up several energy consumption estimation models according to the reserve equipment list, and update the energy consumption estimation model according to the update of the reserve equipment list; configure the corresponding energy consumption estimation model for the user end.

[0010] The user terminal includes a monitoring module, a display module and an energy-saving analysis module;

[0011] The monitoring module is used to monitor the energy consumption data of each energy-consuming device in the enterprise in real time, obtain the list of energy-consuming devices in the enterprise, merge and classify the energy-consuming devices in the list of energy-consuming devices, obtain a number of representative classifications and independent devices; and deploy monitoring devices according to the representative classifications and independent devices;

[0012] Real-time energy consumption monitoring is performed on representative classifications and independent equipment according to the energy consumption estimation model to obtain energy consumption monitoring data of the energy-consuming equipment.

[0013] Furthermore, the method for setting the energy-consuming equipment list includes:

[0014] Acquire enterprise information, and generate a potential device list according to the enterprise information, wherein the potential device list is used to count corresponding potential device information;

[0015] A device calibration model is established, and the expression of the device calibration model is:

[0016]

[0017] Where: (si, FLi) is the input data, si represents the potential device information of the corresponding potential device in the potential device list, i represents the potential device, i=1, 2, ..., n, n is the number of the corresponding potential devices in the potential device list; FLi represents the verification material of the corresponding potential device; si→FLi means that the corresponding potential device information and the verification material are associated and verified; the output data is the device calibration value SP(si, FLi), and the device calibration value is 1 or 0;

[0018] Collect calibration material data according to the potential device list; analyze the potential device list and calibration material data through the device calibration model to obtain the device calibration value of the corresponding potential device information;

[0019] The potential equipment information with equipment calibration value of 1 is integrated to establish a list of energy-consuming equipment.

[0020] Furthermore, the method for merging and classifying the energy-consuming equipment in the list of energy-consuming equipment includes:

[0021] Define independent devices, where independent devices refer to energy-consuming devices that perform energy consumption monitoring independently; identify the energy-consuming device list according to the independent device definition, obtain corresponding independent device information, and mark the non-independent device information in the energy-consuming device list as candidate information;

[0022] The energy connection mode corresponding to the selected information is obtained, and the selected information is merged according to the energy connection mode to obtain a plurality of unit classifications; and a representative classification is determined according to the unit classifications.

[0023] Furthermore, the method for merging the selected information according to the energy connection mode includes:

[0024] Obtain unit classification standards; establish a unit judgment model, the expression of the unit judgment model is:

[0025]

[0026] Where: (LK, DB) is the input data, LK is the energy connection mode of the two candidate information for the corresponding combined analysis, DB is the unit classification standard; LK→DB means that LK meets the unit classification standard; the output data is the unit judgment value DP(LK, DB), and the unit judgment value is 1 or 0;

[0027] By analyzing the unit judgment model, the unit judgment values ​​between the corresponding candidate information are obtained, and the corresponding candidate information with the unit judgment value 1 is allocated to the same unit classification; and so on, until all the candidate information is allocated.

[0028] Furthermore, the method of determining the representative classification according to the unit classification includes:

[0029] Setting a merging upper limit; performing a merging simulation on the unit classification based on the merging upper limit to obtain a number of merging schemes to be selected;

[0030] An energy consumption simulation model is set according to the unit classification; historical energy consumption data of the enterprise is obtained, and a verification data set is set according to the historical energy consumption data and the energy consumption simulation model, wherein the verification data set includes a simulated usage mode and energy consumption of the corresponding energy-consuming equipment;

[0031] Performing energy consumption monitoring simulation on the candidate merging scheme according to the verification data set and the energy consumption simulation model to obtain a scheme simulation result of the candidate merging scheme, wherein the scheme simulation result is composed of energy consumption simulation errors of corresponding energy-consuming equipment;

[0032] The candidate merging schemes are screened according to the simulation results of the schemes, a target merging scheme is determined, and the unit classifications are merged according to the target merging scheme to obtain several representative classifications.

[0033] Furthermore, the method for screening the merger schemes to be selected according to the scheme simulation results includes:

[0034] The energy-consuming devices in the energy-consuming device list are marked as j, where j=1, 2, ..., m, and m is the number of energy-consuming devices in the energy-consuming device list;

[0035] According to the simulation results of the scheme, the energy consumption simulation error of the corresponding energy-consuming equipment is identified, which is marked as WCj; the energy consumption of the energy-consuming equipment is identified, which is marked as MHj;

[0036] The screening value of the corresponding candidate merger solution is calculated according to the screening formula. The screening formula is:

[0037]

[0038] Where: SA is the screening value; βj represents the weight coefficient of the corresponding energy-consuming equipment, which is set by the platform according to user needs;

[0039] The candidate merge solution with the smallest screening value is selected as the target merge solution.

[0040] Furthermore, the method for monitoring energy consumption of representative classifications according to the energy consumption estimation model includes:

[0041] Acquire representative energy consumption data corresponding to representative classification in real time; identify energy-consuming equipment corresponding to the representative classification, and acquire the operating status of the energy-consuming equipment in real time; integrate the operating status and energy-consuming equipment information of each energy-consuming equipment corresponding to the representative classification into representative analysis data;

[0042] The representative analysis data and the representative energy consumption data are analyzed by the energy estimation model to obtain the energy consumption monitoring data of the energy-using equipment in the representative classification.

[0043] The display module is used to perform monitoring and display, obtain an energy consumption simulation model, and dynamically display the energy consumption monitoring data of the energy-consuming equipment according to the energy consumption simulation model;

[0044] The energy-saving analysis module is used to perform real-time energy-saving analysis according to the energy consumption simulation model, obtain corresponding emission reduction plans, and display the emission reduction plans to users.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] By monitoring energy consumption in real time, the system can promptly detect energy waste and excessive carbon emissions, and take corresponding energy-saving measures and emission reduction strategies. This will help reduce the company's energy consumption and carbon emissions and achieve the goal of energy conservation and emission reduction. At the same time, in order to adapt to the changes in the company's energy-consuming equipment and technological development, intelligent monitoring of energy-consuming equipment is achieved through intelligent monitoring, solving the problem of inflexibility and inconvenience of existing energy consumption monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0049] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] like Figure 1 As shown, a green and low-carbon energy service management system includes a platform end and a user end;

[0051] The platform end is used and managed by the platform party, including a monitoring and analysis module;

[0052] The monitoring and analysis module is used to perform monitoring and reserve analysis, identify the monitoring scope of the platform, which is the scope of various enterprises that the platform needs to serve, and generate and update the reserve equipment list in real time according to the monitoring scope. The reserve equipment list includes information on various energy-consuming equipment that can monitor energy consumption;

[0053] The platform sets up several energy consumption estimation models according to the reserve equipment list, and updates the corresponding energy consumption estimation models according to the update of the reserve equipment list, so that the corresponding energy consumption estimation models can meet the monitoring of the corresponding updated energy-consuming equipment; the energy consumption estimation model is used to analyze the operating status of several energy-consuming equipment, the energy-consuming equipment information and the overall energy consumption monitoring data, and determine the energy consumption monitoring data of each energy-consuming equipment; and mark the corresponding equipment application scope for the energy consumption estimation model; configure the corresponding energy consumption estimation model for the corresponding user terminal, and when the user terminal updates a new energy-consuming equipment, analyze whether it is within the equipment application scope. When it is not within the equipment application scope, the platform will update the model.

[0054] The user terminal is used by users and includes a monitoring module, a display module and an energy-saving analysis module;

[0055] The monitoring module is used to monitor the energy consumption data of various energy-consuming equipment in the enterprise in real time, and obtain the energy-consuming equipment list of the enterprise. The energy-consuming equipment list is used to count the various energy-consuming equipment information in the enterprise, such as equipment type, power, production period and other related information;

[0056] The energy-consuming equipment in the energy-consuming equipment list is combined and classified to obtain a number of representative classifications and independent equipment; monitoring equipment is arranged according to the representative classifications and independent equipment, which is equivalent to setting one monitoring equipment for one independent equipment and one monitoring equipment for one representative classification;

[0057] According to the energy consumption estimation model, real-time energy consumption monitoring is performed on representative classifications and independent equipment to obtain energy consumption monitoring data of corresponding energy-consuming equipment.

[0058] In one embodiment, the list of energy-consuming devices can be set by the user according to actual conditions.

[0059] In one embodiment, a method for setting the energy-consuming device list includes:

[0060] Obtain enterprise information, including enterprise type, business scope, location and other related information; retrieve various energy-consuming equipment that may be used by the enterprise in real time based on the enterprise information and mark them as potential equipment. Specifically, various energy-consuming equipment that may be used by similar enterprises can be summarized, such as searching and matching based on big data analysis technology to form a potential equipment list;

[0061] Establish an equipment calibration model, which is used to analyze the potential equipment information in the potential equipment list to determine whether it is the energy-consuming equipment of the enterprise; the expression of the equipment calibration model is:

[0062]

[0063] Where: (si, FLi) is the input data, si represents the potential equipment information of the corresponding potential equipment in the potential equipment list, i represents the potential equipment, i=1, 2, ..., n, n is the number of corresponding potential equipment in the potential equipment list; FLi represents the verification material of the corresponding potential equipment, the verification material can be the enterprise's confirmation record of the corresponding potential equipment, or it can be the monitoring data within the enterprise, and then the monitoring data is used to identify whether there is such equipment, and then determine the detailed equipment information, so as to reduce the enterprise's confirmation workload; si→FLi means that the corresponding potential equipment information and the verification material are associated and verified; the output data is the equipment calibration value SP(si, FLi), and the equipment calibration value is 1 or 0;

[0064] Obtain corresponding calibration material data according to the potential device list, where the calibration material data is the integrated data of a plurality of calibration materials; analyze the potential device list and calibration material data through the device calibration model to obtain the device calibration value of the corresponding potential device information;

[0065] The potential equipment information with equipment calibration value of 1 is integrated to establish a list of energy-consuming equipment; and the list of energy-consuming equipment can be updated subsequently according to the above method.

[0066] In one embodiment, a method for merging and classifying corresponding energy-consuming devices in a list of energy-consuming devices includes:

[0067] Define independent devices. Independent devices refer to energy-consuming devices that monitor energy consumption independently. The specific determination is based on user needs. According to the definition of independent devices, the energy-consuming device list is identified to obtain the corresponding independent device information, and the non-independent device information in the energy-consuming device list is marked as candidate information.

[0068] Obtain the energy connection mode corresponding to the selected information, such as computer A, computer B, and computer C are all connected through socket A; merge the selected information according to the obtained energy connection mode to obtain several unit classifications, that is, determine the unit classification according to the lowest monitoring node, and generally merge according to the energy connection mode corresponding to a single line, such as computer A, computer B, and computer C are all connected through socket A, then computer A, computer B, and computer C are merged into one unit classification;

[0069] Determine the representative classification based on the unit classification; each unit classification may correspond to one representative classification, or multiple unit classifications that can be merged may be merged into one representative classification based on user needs, and the merging standard is that energy consumption can be uniformly monitored; the specific classification is determined based on user needs.

[0070] In one embodiment, the method for merging the selected information according to the energy connection mode includes:

[0071] Obtain unit classification standards. Unit classification standards are set by the platform according to user needs, such as defining unit classification standards according to lines, sockets, etc.;

[0072] A unit judgment model is established. The unit judgment model is used to judge whether the energy connection mode of the corresponding candidate information meets the unit classification standard. The expression of the unit judgment model is:

[0073]

[0074] Where: (LK, DB) is the input data, LK is the energy connection mode of the two candidate information for the corresponding combined analysis, DB is the unit classification standard; LK→DB means that LK meets the unit classification standard; the output data is the unit judgment value DP(LK, DB), and the unit judgment value is 1 or 0;

[0075] Through the unit judgment model, the unit judgment value between the corresponding candidate information is obtained, and the corresponding candidate information with unit judgment value 1 is assigned to the same unit category; and so on, until all the candidate information is assigned. When users add new energy-consuming equipment in the future, they can also be intelligently assigned to the corresponding unit category.

[0076] In one embodiment, the method for determining a representative classification according to a unit classification includes:

[0077] Set the merging upper limit. The merging upper limit is set by the platform to limit the number of energy-consuming devices and the overall energy consumption upper limit corresponding to the representative classification. When there are too many energy-consuming devices or the overall energy consumption is too large, the energy consumption accuracy of each energy-consuming device in the representative classification will be reduced. It is mainly set according to the estimated accuracy corresponding to the historical merging records. It is generally set manually by the platform staff, and can also be set in combination with existing intelligent analysis technology;

[0078] Based on the merging upper limit, each unit classification is merged and simulated to determine various merging schemes, that is, each representative classification corresponding to each merging scheme meets the merging upper limit requirement; for example, each unit classification is randomly combined, and then selected by the merging upper limit to determine various merging schemes, which are marked as candidate merging schemes;

[0079] Energy consumption simulation models are set up according to the classification of each unit. The energy consumption simulation model is used to display the connection relationship and energy consumption relationship of each energy-consuming device. It can be established based on existing modeling technology to form a visual data model, such as using lines to represent lines and using simple blocks to represent corresponding energy-consuming devices and monitoring devices. The platform party sets it up according to the actual situation of the user;

[0080] Obtain the historical energy consumption data of the enterprise. The historical energy consumption data is the historical usage of each energy-consuming equipment in the enterprise; set up a verification data set based on the historical energy consumption data and the energy consumption simulation model. The verification data set includes the simulated usage mode and energy consumption of each energy-consuming equipment, that is, use the historical energy consumption data and the energy consumption simulation model to set up the simulated usage mode of each energy-consuming equipment. Generally, the self-simulated usage mode is set according to the situation with the highest probability of use, such as computer A and computer B are used from 9 to 12, and computer A is used from 12 to 13:30, and computer B is not used; the energy consumption is to simulate the use according to the simulated usage mode and detect the corresponding energy consumption. It can also be counted based on historical data with clear energy consumption; the platform can simulate the usage and energy consumption of various equipment on the spot to form a material library, which will be matched according to the energy-consuming equipment and the simulated usage mode, and integrated into a verification data set; the most accurate is to conduct simulated monitoring in the enterprise, use the usage mode as the simulated usage mode, and record the corresponding energy consumption; there are many ways to set up the verification data set;

[0081] Perform energy consumption monitoring simulation on the selected merged scheme according to the verification data set and the energy consumption simulation model to obtain the energy consumption simulation error of each energy-consuming device; that is, use it according to the simulated use method in the verification data, monitor it according to the subsequent energy consumption monitoring method, obtain the monitored energy consumption of the corresponding energy-consuming equipment, compare it with the energy consumption in the verification data set, and determine the energy consumption simulation error; integrate it into the scheme simulation result;

[0082] The merging schemes to be selected are screened according to the scheme simulation results, and the target merging scheme is determined, such as presetting the weight coefficients of various energy-consuming equipment, and then screening is performed according to the scheme simulation results. Other methods can also be used to screen according to the scheme simulation results.

[0083] The unit classifications are merged according to the target merging scheme to form representative classifications.

[0084] In one embodiment, a method for real-time energy consumption monitoring of representative categories according to an energy consumption estimation model includes:

[0085] The energy consumption monitoring data corresponding to the representative classification is obtained in real time and marked as representative energy consumption data, that is, the total energy consumption monitoring data of each energy-consuming device corresponding to the representative classification;

[0086] Identify the energy-consuming equipment corresponding to the representative classification, and obtain the operating status of the energy-consuming equipment in real time, such as whether it is running, the gear it is in during operation, etc. The operating status is collected according to the actual energy-consuming equipment. It can be obtained by using video monitoring, installing corresponding sensors, etc., or input by enterprise staff. For some smart devices, the corresponding operating status can be directly accessed; integrate the operating status of the energy-consuming equipment and the energy-consuming equipment information of the representative classification into representative analysis data;

[0087] The representative analysis data and representative energy consumption data are analyzed through the energy consumption estimation model to determine the energy consumption monitoring data of each energy-consuming equipment in the representative classification; that is, the energy consumption proportion of each energy-consuming equipment is estimated using the operating status and energy-consuming equipment information, and then the representative energy consumption data is divided according to the energy consumption proportion to form the energy consumption monitoring data of the corresponding energy-consuming equipment.

[0088] The display module is used for monitoring and displaying, obtaining an energy consumption simulation model, and dynamically displaying energy consumption monitoring data of corresponding energy-consuming equipment according to the energy consumption simulation model; for example, displaying its working status according to the energy consumption monitoring data and displaying corresponding energy consumption data.

[0089] The energy-saving analysis module is used to perform real-time energy-saving analysis according to the energy consumption simulation model, obtain corresponding emission reduction plans, and display the emission reduction plans to users.

[0090] In one embodiment, after the actual energy consumption data is determined according to the energy consumption simulation model, it can be analyzed according to the existing energy conservation and emission reduction analysis method to set an emission reduction plan.

[0091] For example, deep learning algorithms such as neural networks and convolutional neural networks can be used to build intelligent models, and intelligent analysis can be performed through the successfully trained intelligent models to generate emission reduction plans.

[0092] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0093] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A green and low-carbon energy service management system, characterized in that: Including platform side and user side; The platform end is used and managed by the platform party, including a monitoring and analysis module; The monitoring and analysis module is used to perform monitoring and reserve analysis, identify the monitoring scope of the platform, and generate and update the reserve equipment list in real time according to the monitoring scope; set a number of energy consumption estimation models according to the reserve equipment list, and update the energy consumption estimation model according to the update of the reserve equipment list; configure the corresponding energy consumption estimation model for the user terminal; The user terminal includes a monitoring module, a display module and an energy-saving analysis module; The monitoring module is used to monitor the energy consumption data of each energy-consuming device in the enterprise in real time, obtain the list of energy-consuming devices in the enterprise, merge and classify the energy-consuming devices in the list of energy-consuming devices, obtain a number of representative classifications and independent devices; and deploy monitoring devices according to the representative classifications and independent devices; Performing real-time energy consumption monitoring on representative classifications and independent devices according to the energy consumption estimation model to obtain energy consumption monitoring data of the energy-consuming devices; The display module is used to perform monitoring and display, obtain an energy consumption simulation model, and dynamically display the energy consumption monitoring data of the energy-consuming equipment according to the energy consumption simulation model; The energy-saving analysis module is used to perform real-time energy-saving analysis according to the energy consumption simulation model, obtain corresponding emission reduction plans, and display the emission reduction plans to users.

2. A green and low-carbon energy service management system according to claim 1, characterized in that: Methods for setting the energy-consuming equipment list include: Acquire enterprise information, and generate a potential device list according to the enterprise information, wherein the potential device list is used to count corresponding potential device information; A device calibration model is established, and the expression of the device calibration model is: Where: (si, FLi) is the input data, si represents the potential device information of the corresponding potential device in the potential device list, i represents the potential device, i=1, 2, ..., n, n is the number of the corresponding potential devices in the potential device list; FLi represents the verification material of the corresponding potential device; si→FLi means that the corresponding potential device information and the verification material are associated and verified; the output data is the device calibration value SP(si, FLi), and the device calibration value is 1 or 0; Collect calibration material data according to the potential device list; analyze the potential device list and calibration material data through the device calibration model to obtain the device calibration value of the corresponding potential device information; The potential equipment information with equipment calibration value of 1 is integrated to establish a list of energy-consuming equipment.

3. A green and low-carbon energy service management system according to claim 2, characterized in that: The methods for combining and classifying the energy-consuming equipment in the list of energy-consuming equipment include: Define independent devices, where independent devices refer to energy-consuming devices that perform energy consumption monitoring independently; identify the energy-consuming device list according to the independent device definition, obtain corresponding independent device information, and mark the non-independent device information in the energy-consuming device list as candidate information; The energy connection mode corresponding to the selected information is obtained, and the selected information is merged according to the energy connection mode to obtain a plurality of unit classifications; and a representative classification is determined according to the unit classifications.

4. A green and low-carbon energy service management system according to claim 3, characterized in that: Methods for combining selected information according to energy connection methods include: Obtain unit classification standards; establish a unit judgment model, the expression of the unit judgment model is: Where: (LK, DB) is the input data, LK is the energy connection mode of the two candidate information for the corresponding combined analysis, DB is the unit classification standard; LK→DB means that LK meets the unit classification standard; the output data is the unit judgment value DP(LK, DB), and the unit judgment value is 1 or 0; By analyzing the unit judgment model, the unit judgment values ​​between the corresponding candidate information are obtained, and the corresponding candidate information with the unit judgment value 1 is allocated to the same unit classification; and so on, until all the candidate information is allocated.

5. A green and low-carbon energy service management system according to claim 4, characterized in that: Methods for determining representative classifications based on unit classifications include: Setting a merging upper limit; performing a merging simulation on the unit classification based on the merging upper limit to obtain a number of merging schemes to be selected; An energy consumption simulation model is set according to the unit classification; historical energy consumption data of the enterprise is obtained, and a verification data set is set according to the historical energy consumption data and the energy consumption simulation model, wherein the verification data set includes a simulated usage mode and energy consumption of the corresponding energy-consuming equipment; Performing energy consumption monitoring simulation on the candidate merging scheme according to the verification data set and the energy consumption simulation model to obtain a scheme simulation result of the candidate merging scheme, wherein the scheme simulation result is composed of energy consumption simulation errors of corresponding energy-consuming equipment; The candidate merging schemes are screened according to the simulation results of the schemes, a target merging scheme is determined, and the unit classifications are merged according to the target merging scheme to obtain several representative classifications.

6. A green and low-carbon energy service management system according to claim 5, characterized in that: Methods for screening the merger plans to be selected based on the simulation results include: The energy-consuming devices in the energy-consuming device list are marked as j, where j=1, 2, ..., m, and m is the number of energy-consuming devices in the energy-consuming device list; According to the simulation results of the scheme, the energy consumption simulation error of the corresponding energy-consuming equipment is identified, which is marked as WCj; the energy consumption of the energy-consuming equipment is identified, which is marked as MHj; The screening value of the corresponding candidate merger solution is calculated according to the screening formula. The screening formula is: Where: SA is the screening value; βj represents the weight coefficient of the corresponding energy-consuming equipment; The candidate merge solution with the smallest screening value is selected as the target merge solution.

7. A green and low-carbon energy service management system according to claim 1, characterized in that: Methods for monitoring energy consumption of representative categories based on energy consumption estimation models include: Acquire representative energy consumption data corresponding to representative classification in real time; identify energy-consuming equipment corresponding to the representative classification, and acquire the operating status of the energy-consuming equipment in real time; integrate the operating status and energy-consuming equipment information of each energy-consuming equipment corresponding to the representative classification into representative analysis data; The representative analysis data and the representative energy consumption data are analyzed by the energy estimation model to obtain the energy consumption monitoring data of the energy-using equipment in the representative classification.

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