Equipment state evaluation method based on energy data

Abstract

The invention discloses an equipment state evaluation method based on energy data, which overcomes the problems that a user cannot obtain effective information from energy data and cannot accurately evaluate the equipment state in the prior art, and comprises the following steps: collecting energy data, and preprocessing the collected energy data; according to a preset energy data archiving model, matching the collected energy data to obtain an energy holographic archive, and establishing an energy data asset tree and a data processing rule; based on the energy holographic archive, extracting equipment indexes according to energy consumption characteristics, and constructing an energy holographic archive index system; and evaluating the equipment state according to the index system. By establishing the holographic file and extracting the equipment indexes according to the energy consumption characteristics, the user can more comprehensively understand and utilize the energy data, the accurate evaluation of the equipment state is realized, and more comprehensive and accurate information support is provided for the development of the equipment.

Description

Technical Field

[0001] The present invention relates to the field of big data computing and energy application technology, and in particular to an equipment status evaluation method based on energy data. Background Art

[0002] In recent years, my country's new energy industries such as wind power and photovoltaics have developed rapidly, energy data has continued to increase, and the number of companies and entities including energy stations has continued to increase. There is no indicator management system that can meet the construction of a multi-level centralized control center. Moreover, energy assessment is an important prerequisite for accurately evaluating the status of energy-consuming equipment and rationally planning and utilizing resources. It can fully understand the development status, energy usage status and development potential of different energy sources in regions or enterprises; at the same time, it can also provide a scientific and accurate basis for the implementation of low-carbon development and the realization of dual-carbon goals in the whole society. However, most of the existing technologies rely on manual management of energy data, which greatly increases the time for data processing and reduces the efficiency of energy data processing. It makes it impossible for users to obtain effective information from a large amount of energy data to judge the status of equipment, which affects the user's management and optimization of energy.

[0003] In the existing technology, energy data is often used to construct an energy indicator system, and the equipment status is evaluated through the energy indicator system. However, the energy indicator system is usually constructed based on the experience and knowledge of experts, which will lead to the evaluation indicator constructors to pursue the comprehensiveness of the indicator system and attempt to include all influencing factors into the indicator system, resulting in too many indicators and redundancy between indicators. This situation will not only affect the judgment of experts, but also lead to an unreasonable indicator system, distorted indicator structure, and distort the real information in terms of direction and quantity, affecting the authenticity of the evaluation object results. Summary of the invention

[0004] The purpose of the present invention is to solve the problem in the prior art that there is a large amount of energy data, users are unable to obtain effective information from the energy data, and cannot accurately evaluate the equipment status. A method for evaluating the equipment status based on energy data is provided. By establishing a holographic archive and extracting equipment indicators according to energy consumption characteristics, users can more comprehensively understand and utilize energy data, realize the evaluation of the equipment status, and provide more comprehensive and accurate information support for the development of the equipment; and energy data can be updated in real time, completely releasing the manual pressure caused by the huge amount of energy data and the complex format, and freeing up a lot of manual time.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: A method for evaluating equipment status based on energy data, characterized in that it comprises the following steps: S1: Collect energy data and pre-process the collected energy data; S2: Match the collected energy data according to the preset energy data matching model to obtain the initial energy holographic file; S3: Establish energy data asset trees and data processing rules for different types of industries; S4: For each energy data asset tree, extract equipment indicators according to energy consumption characteristics, establish an indicator system, calculate indicator data based on energy data, and generate an indicator data flow diagram; S5: Evaluate the equipment status based on the obtained indicator system and indicator data.

[0006] The device status assessment method based on energy data provided by the present invention establishes an energy holographic archive for energy data, then establishes the number of energy data assets and data processing rules, extracts equipment indicators according to energy consumption characteristics for each energy data under the energy data asset tree, completes the construction of the indicator system, calculates indicator data according to energy data, generates an indicator data flow diagram, and further displays energy data and device status in the initial energy holographic archive, so that users can more comprehensively understand and use energy holographic archives, provide more comprehensive and accurate information support for the development of equipment, and can update energy data in real time. The number of indicators is reasonable, the indicator structure is real, and the distribution of energy data is comprehensively and clearly displayed.

[0007] Preferably, step S4 includes: generating an indicator data flow diagram according to the hierarchical relationship between the indicators, and determining the indicator data upstream and downstream of the current indicator data based on the indicator data flow direction and the indicator data tracing direction, the indicator data flow direction is the direction of increasing hierarchy, and the indicator data tracing direction is the direction of decreasing hierarchy.

[0008] Preferably, the establishment of the energy data asset tree includes: constructing different types of energy data asset trees according to the energy holographic archive, in each type of energy data asset tree, the site is used as the first-level tree, the distribution room is used as the second-level tree, and the energy-consuming equipment is used as the third-level tree.

[0009] The energy consumed by the energy-consuming equipment and the index data are used as a four-level tree.

[0010] Preferably, step S1 includes: acquiring original energy data sent by different users, and performing data cleaning and filtering on the original energy data, and then normalizing the cleaned original energy data according to preset standards, and performing association and completion processing on related energy data in the normalized original energy data to form initial asset data and establish an initial energy database.

[0011] Preferably, a data threshold of each indicator is determined to determine whether the indicator data obtained based on the energy data is within the threshold range. If not, an alarm is issued.

[0012] Preferably, the energy data matching model has built-in data classification rules and matching rules.

[0013] The data classification rules include equipment type, industry type, region, and asset type, and the matching rules include region matching rules, time matching rules, and importance matching rules.

[0014] As a preference, for industrial enterprises, equipment indicators are extracted from power distribution rooms, electrical equipment and process production lines according to energy consumption characteristics.

[0015] Preferably, in the energy data asset tree, each device can only be attached to one energy data asset tree.

[0016] Preferably, the energy consumption characteristics include real-time data change trends, abnormal energy consumption data and energy performance parameters.

[0017] Preferably, the normalization processing of the original energy data includes: adding device ID and time to the energy data; and normalizing the energy data with inconsistent time description or field type.

[0018] Therefore, the present invention has the following beneficial effects: The energy holographic archive contains energy generated by different enterprises and different equipment. The initial energy holographic archive is obtained by matching the pre-processed raw energy data. For different types of industries in the initial energy holographic archive, the number of energy data assets and data processing rules are established. Each energy data asset tree contains a large amount of energy data. Finally, for the energy data under each energy data asset tree, according to the energy consumption characteristics, the equipment indicators are extracted, the indicator system construction is completed, the indicator data is calculated according to the energy data, and the indicator data flow diagram is generated. The energy data and equipment status are further displayed in the initial energy holographic archive, so that users can more comprehensively understand and use the energy holographic archive, and provide more comprehensive and accurate information support for the development of equipment. In addition, it can update energy data in real time, completely release the manual pressure caused by the huge amount of energy data and complex format, liberate a lot of manual time, and also avoid the huge workload of multiple platforms with the same function and docking, thereby greatly reducing the time of data processing and improving the processing efficiency of energy data. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flowchart of the steps of the equipment status assessment method based on energy data in the present invention. DETAILED DESCRIPTION

[0020] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments: Embodiment 1: This embodiment provides a method for evaluating equipment status based on energy data, such as Figure 1 As shown, the operation process is as follows: Step 1, collect energy data and pre-process the collected energy data; Step 2, match the collected energy data according to the preset energy data matching model to obtain the initial energy holographic file; Step 3, for different types of industries, establish energy data asset trees and data processing rules; Step 4, for each energy data asset tree, extract equipment indicators according to energy consumption characteristics, establish an indicator system, calculate indicator data based on energy data, and generate an indicator data flow diagram.

[0021] The device status assessment method based on energy data provided in this embodiment first obtains the original energy data sent by different users and pre-processes the original energy data. Because the energy holographic archive contains energy generated by different enterprises and different equipment, it is necessary to match the pre-processed original energy data to obtain the initial energy holographic archive. For different types of industries in the initial energy holographic archive, the number of energy data assets and data processing rules are established, and each energy data asset tree contains a large amount of energy data. Finally, for the energy data under each energy data asset tree, according to the energy consumption characteristics, the equipment indicators are extracted, the indicator system construction is completed, the indicator data is calculated according to the energy data, and the indicator data flow diagram is generated, and the energy data and equipment status are further displayed in the initial energy holographic archive, so that users can more comprehensively understand and use the energy holographic archive, and provide more comprehensive and accurate information support for the development of equipment. And it can update energy data in real time, completely release the manual pressure caused by the huge amount of energy data and complex format, liberate a lot of manual time, and also avoid the huge workload of multiple platforms with the same function and docking, thereby greatly reducing the time of data processing and improving the processing efficiency of energy data.

[0022] The technical scheme and technical effects of the present invention will be further described below through specific examples. The following examples are explanations of the present invention and the present invention is not limited to the following examples.

[0023] The current energy data processing method can no longer meet the needs of digital management, and the weaknesses in external mechanism output, content information, and data management are gradually becoming apparent. Therefore, this embodiment provides a device status assessment method based on energy data to solve the following technical problems: (1) With the continuous development of the energy industry, the amount and types of energy data are increasing, and it is impossible to process energy data in a timely manner and obtain effective information from energy data in a timely manner.

[0024] (2) The link from data collection to data application is too long, making it difficult to obtain first-hand data. It is becoming increasingly difficult to ensure the integrity, timeliness, and accuracy of the data.

[0025] (3) Solve the existing problems of data collection and management not being unified, and energy data resources being difficult to apply widely and effectively.

[0026] Specifically, Figure 1 As shown, a method for evaluating equipment status based on energy data includes the following steps: Step 1: Collect energy data and pre-process the collected energy data.

[0027] Obtain the original energy data sent by different users, and perform data cleaning and data filtering on these original energy data.

[0028] Energy data includes real-time parameters such as three-phase voltage, three-phase current, power, power factor, instantaneous flow, pressure, temperature, etc., as well as total electricity consumption at peak, flat and valley times, forward and reverse active and reactive electricity, water consumption, gas consumption, etc. It is specifically divided into energy production data, energy supply network operation data, user comprehensive energy load data, and comprehensive energy market data.

[0029] Data cleaning deletes or corrects inaccurate information in the original energy data set, including deleting duplicate information, correcting errors, processing invalid values ​​and missing values, etc. It prevents erroneous or problematic data from entering the calculation process to ensure data accuracy and consistency. Through data cleaning, analysis problems caused by erroneous information can be avoided, the time and cost of re-analysis can be reduced, and important decisions can be avoided based on erroneous information, thereby reducing business risks.

[0030] ‌Deleting duplicate information is also called data deduplication‌, which is used to remove duplicate records in a data set.

[0031] ‌Handling missing values‌: To fill in the missing values ​​in the original energy data, you can use interpolation, mean, median, mode and other methods.

[0032] ‌Handling outliers‌: Detecting and handling outliers in raw energy data can either remove or replace them.

[0033] The cleaned raw energy data is then normalized according to preset standards, and the related energy data in the normalized raw energy data are associated and supplemented to form initial asset data and establish an initial energy database.

[0034] The normalization of raw energy data includes: Data normalization: Standardize data formats into a consistent format.

[0035] Data conversion: Convert the format of data to facilitate processing and analysis. In this embodiment, it includes adding device ID and time to energy data and normalizing energy data with inconsistent time description or field type.

[0036] Step 2: Match the collected energy data according to the preset energy data matching model to obtain the initial energy holographic file.

[0037] Holographic archives refer to the creation of detailed archives for individuals or entities by integrating multi-dimensional data. This application uses energy data to create energy holographic archives. Holographic archives have powerful and flexible data retrieval and analysis functions. Through holographic archives, energy data of different regions, industries and equipment can be queried.

[0038] Therefore, it is necessary to first classify and match the energy data, and match the energy data to the corresponding industries, stations, distribution rooms, and energy-consuming equipment.

[0039] In this embodiment, the energy data processed in the first step are matched one by one by using a preset energy data matching model. The energy data matching model has built-in data classification rules and matching rules. The data classification rules include equipment type, industry type, region, and energy data type. The matching rules include regional matching rules, time matching rules, and importance matching rules.

[0040] By matching all energy data, the initial energy holographic archive is obtained.

[0041] In this embodiment, the initial energy file also includes industry type, equipment information, etc. For example, for the initial energy file of buildings in a certain area, the initial energy file includes all buildings in the area, and is classified and counted according to labels such as building type, area, street, and green building, and the number of buildings of each type is intuitively displayed. The energy data of each building is matched under the building list. For the initial energy file of industrial enterprises in a certain area, the initial energy file includes all enterprises in the area, including company profiles, contact information, operating conditions, etc. The energy data of each enterprise / industry is matched under the enterprise / industry list.

[0042] Step 3: For different types of industries, establish energy data asset trees and data processing rules.

[0043] In the initial energy holographic file obtained in the second step, although the energy data has been preliminarily classified, it is still difficult to obtain the equipment status directly from the energy data and to manage the energy subsequently. Therefore, for the classified energy data presented in the initial energy holographic file, energy data asset trees of different types (buildings, industrial enterprises, green energy, etc.) are established to further manage the energy data.

[0044] In this embodiment, the data asset tree includes three levels. The first level is the physical site (including the site name and site ID), such as a specific enterprise / industry or a building. The second level is the distribution room (including the distribution room name, distribution room ID and distribution room account number). The third level is the energy-consuming equipment (including the equipment name and equipment ID). The third level equipment includes the energy data generated by the energy-consuming equipment.

[0045] Based on the above operations, an energy data asset tree is obtained, which can be queried in the holographic archive, allowing users to understand the energy status of the equipment in real time.

[0046] When establishing an energy data asset tree, each device can only be attached to one energy data asset tree.

[0047] Step 4: For each energy data asset tree, extract equipment indicators based on energy consumption characteristics, establish an indicator system, calculate indicator data based on energy data, and generate an indicator data flow diagram.

[0048] Through the energy data of the equipment, users can understand the status of the equipment, but it is far from enough to use the energy data to further evaluate the equipment. Therefore, it is necessary to establish an indicator system to facilitate the evaluation of equipment status and production energy consumption, promote low-carbon construction and development, and realize a green economic cycle.

[0049] Specific: For industrial enterprises, equipment indicators are extracted from power distribution rooms, power equipment and process production lines according to energy consumption characteristics. The process production line is mainly for industrial production. When generating products, the energy consumption of a single product during production can help users better calculate production costs, reasonably adjust the production quantity of a single product, and improve the efficiency of single product production. Energy consumption characteristics include real-time data change trends, production energy consumption data (such as real-time and historical energy consumption information of each production product, production workshop, shift and important production links), abnormal energy consumption data (operation of energy-consuming equipment in operation, shutdown, standby, ready, fault, and overload states) and energy performance parameters (ratios of energy data, statistical models, engineering models, etc.), power quality (such as voltage, current harmonic distortion rate, voltage imbalance rate, voltage deviation rate, line loss, pipe network loss), etc.

[0050] Furthermore, for green projects, due to the different characteristics of various energy projects such as photovoltaics, energy storage, hydropower, wind power, and charging piles, common indicators are extracted from production processes, grid-connected equipment, and operating systems; for buildings, the characteristics of energy operation of various public buildings are summarized, and indicator models are extracted from power distribution, lighting, HVAC, power and other systems.

[0051] In this embodiment, the established indicator system is based on the energy data asset tree, and a site-distribution room-equipment hierarchical model is established to obtain evaluation indicators for each site, each distribution room, and each device. The evaluation indicators are classified into equipment indicator level, distribution room indicator level, and site indicator level. The indicators in the distribution room indicator level can be used to calculate the indicators in the site indicator level, and the indicators in the equipment indicator level can be used to calculate the indicators in the distribution room indicator level. The indicator data flow direction is the direction of increasing levels, and the indicator data traceability direction is the direction of decreasing levels.

[0052] An indicator data flow diagram is generated according to the hierarchical relationship between each indicator, and the indicator data upstream and downstream of the current indicator data are determined based on the indicator data flow direction and the indicator data traceability direction.

[0053] Determine the data threshold of each indicator, and judge whether the indicator data obtained based on the energy data is within the threshold range. If not, use the pop-up window of the holographic archive to alarm. According to the alarm indicators, you can intuitively understand the equipment failure problem, which is convenient for staff to maintain in time. At the same time, according to the indicator data, you can understand the equipment dynamics in real time, which is also convenient for users to adjust the equipment, thereby optimizing the entire energy structure and realizing efficient utilization and optimization of energy.

[0054] The device status assessment method based on energy data provided in this embodiment can achieve the following beneficial effects: Through energy data, we can accurately grasp the energy consumption information of industrial enterprises in the park, ensure the implementation of the government's industrial policies on new energy development, demand-side management, energy conservation, environmental protection and safety, support the management needs of people's livelihood, finance, taxation and other fields, and improve the management level of industrial enterprises in the park. At the same time, through online monitoring and analysis and mining of energy data, we can also timely, accurately and comprehensively discover the equipment asset management, energy load optimization, price package selection problems and improvement space in the energy use process of industrial enterprises in the park, so as to help continuously improve the safety, economy, quality and environmental protection level of energy use of industrial enterprises. According to the problems that need to be solved and the needs that need to be met by industrial enterprises in the park, we can integrate the resources of various equipment, hardware, software and service suppliers to form a sound comprehensive energy service manufacturer alliance. At the same time, we can accurately promote the opportunities of comprehensive energy service projects through the portraits of enterprises and service providers, promote transaction matching through financial products, and let users get cost-effective comprehensive energy services. At the same time, it helps government management departments to carry out more effective energy management and optimization of industrial enterprises, and improve the competitiveness and sustainable development capabilities of industrial enterprises.

[0055] Embodiment 2: This embodiment provides a method for evaluating equipment status based on energy data, which further optimizes the solution in the first embodiment.

[0056] This embodiment takes the energy data of industrial enterprises as an example, and based on the characteristics of energy consumption of industrial enterprises, extracts equipment indicator models from power distribution rooms, energy-consuming equipment, and process production lines, and establishes a data asset tree and data processing rules that are only applicable to industrial enterprises.

[0057] After establishing this set of energy holographic archive indicator system, the energy data in the energy holographic archive can be updated in real time, thereby updating the equipment indicators, and the user can grasp the equipment dynamics in real time, conduct equipment management, and detect equipment failures in a timely manner.

[0058] In order to facilitate data management and processing, a data management interface is developed to support data import, export, addition, modification, query and other functions. Finally, the project can implement the interface call of the application layer to facilitate the energy management and optimization of industrial enterprises. These interfaces can include real-time data query, alarm and early warning, energy consumption analysis and optimization, etc., to help government management departments to more effectively manage and optimize the energy of industrial enterprises and improve the competitiveness and sustainable development capabilities of enterprises.

[0059] It is also possible to import and export indicator data, and export configuration templates in Excel format. According to the template prompts, you can configure indicator codes, indicator names, database table names, measuring point names and other related information, which can be directly imported into the system. The system can automatically identify configuration anomalies and pop up prompts for abnormal problems and how to deal with them.

[0060] Embodiment three: This embodiment provides a system for constructing an energy holographic archive indicator system based on big data, which is used to implement an equipment status assessment method based on energy data in Embodiment 1.

[0061] A system for constructing an energy holographic archive index system based on big data includes an energy data acquisition module, an energy holographic archive and an energy holographic archive management module. The energy data acquisition module is connected to the energy holographic archive, and the energy holographic archive is connected to the energy holographic archive management module. The three modules cooperate with each other to realize an equipment status evaluation method based on energy data in Embodiment 1. It helps government management departments to conduct more effective energy management and optimization of industrial enterprises, and improve the competitiveness and sustainable development capabilities of industrial enterprises.

[0062] Specifically, the energy data acquisition module, including a current sensor and a voltage sensor, can collect energy data and pre-process the collected energy data.

[0063] Furthermore, the energy data acquisition module normalizes, processes abnormal data, and performs standardized management on the collected signals through sensing equipment and data collectors, and effectively integrates energy data including energy production data, energy supply network operation data, user comprehensive energy load data, comprehensive energy market data, etc. through a real-time and reliable communication network.

[0064] In this embodiment, the energy data transmission adopts the MTQQ protocol, which can work in an environment with small bandwidth and poor network connection quality, thereby realizing reliable transmission of energy data. At the same time, the MTQQ protocol supports security mechanisms such as authentication and encryption, and can also adapt to various application scenarios and support different types of message transmission, realize encrypted transmission of energy data, and ensure the security of energy data.

[0065] The holographic archive displays all industries in the region in a classified manner, dividing the industries into industrial enterprises, construction industry, and green energy. Each industry type includes different sites, each site includes different distribution rooms, and each distribution room includes different equipment. Each process generates energy data. The energy data collected by the energy data acquisition module is matched to the corresponding sites, distribution rooms, and equipment to obtain a holographic archive, which is convenient for users to view the data.

[0066] The holographic archive includes an indicator system construction module. The indicator system construction module extracts equipment indicators based on the collected energy data and the energy holographic archive according to the energy consumption characteristics to construct an indicator system.

[0067] The indicator system construction module has a built-in indicator library, which includes the indicator name, indicator item ID, indicator generation time, indicator value, database table name, device name and device ID represented by the indicator, indicator level, indicator data flow direction, indicator data traceability direction, indicator data update frequency, indicator data algorithm logic, upper and lower limits of indicator data, and whether the indicator status is enabled.

[0068] The energy holographic archive management module can realize the import of energy data, the import, export, addition, modification and query of energy data asset trees, and the import, export, modification, addition and query of indicator data flow diagrams.

[0069] For example, for industrial enterprises, based on the characteristics of energy consumption of industrial enterprises, equipment indicator models are extracted from distribution rooms, energy-consuming equipment, and process production lines to establish data asset trees and data processing rules that are only applicable to industrial enterprises. The energy holographic archive management module supports functions such as data import, export, addition, modification, and query. Finally, the project can implement application layer interface calls to facilitate energy management and optimization of industrial enterprises. These interfaces can include real-time data query, alarm and warning, energy consumption analysis and optimization, etc., to help government management departments to conduct more effective energy management and optimization of industrial enterprises, and improve the competitiveness and sustainable development capabilities of enterprises.

[0070] For buildings, summarize the energy operation characteristics of various public buildings, extract indicator models from power distribution, lighting, HVAC, power and other systems, establish appropriate data asset trees and data processing rules, and complete the construction of indicator systems for holographic archives of various types of buildings. The energy holographic archive management module realizes the interface call of the application layer.

[0071] The above-described embodiment is only a preferred solution of the present invention and does not limit the present invention in any form. There are other variations and modifications without exceeding the technical solution described in the claims.

Claims

1. A method for evaluating equipment status based on energy data, characterized in that: The following steps are involved: S1: Collect energy data and pre-process the collected energy data; S2: Match the collected energy data according to the preset energy data matching model to obtain the initial energy holographic file; S3: Establish energy data asset trees and data processing rules for different types of industries; S4: For each energy data asset tree, extract equipment indicators according to energy consumption characteristics, establish an indicator system, calculate indicator data based on energy data, and generate an indicator data flow diagram; S5: Evaluate the equipment status based on the obtained indicator system and indicator data.

2. The method for evaluating equipment status based on energy data according to claim 1, characterized in that: The step S4 includes: generating an indicator data flow diagram according to the hierarchical relationship between the indicators, and determining the indicator data upstream and downstream of the current indicator data based on the indicator data flow direction and the indicator data traceability direction, wherein the indicator data flow direction is the direction of increasing hierarchy, and the indicator data traceability direction is the direction of decreasing hierarchy.

3. The method for evaluating equipment status based on energy data according to claim 1, characterized in that: The establishment of the energy data asset tree includes: constructing different types of energy data asset trees according to the energy holographic archive, in each type of energy data asset tree, the site is used as the first-level tree, the distribution room is used as the second-level tree, and the energy-consuming equipment is used as the third-level tree.

4. A method for evaluating equipment status based on energy data according to claim 1, 2 or 3, characterized in that: The step S1 includes: obtaining the original energy data sent by different users, and performing data cleaning and filtering on the original energy data, and then normalizing the cleaned original energy data according to preset standards, and performing association and completion processing on the related energy data in the normalized original energy data to form initial asset data and establish an initial energy database.

5. The method for evaluating equipment status based on energy data according to claim 1, 2 or 3, characterized in that: Determine the data threshold of each indicator and judge whether the indicator data obtained based on the energy data is within the threshold range. If not, an alarm is issued.

6. The method for evaluating equipment status based on energy data according to claim 1, 2 or 3, characterized in that: The energy data matching model has built-in data classification rules and matching rules.

7. A method for evaluating equipment status based on energy data according to claim 1, 2 or 3, characterized in that: For industrial enterprises, equipment indicators are extracted from distribution rooms, electrical equipment and process production lines based on energy consumption characteristics.

8. The method for evaluating equipment status based on energy data according to claim 3, characterized in that: In the energy data asset tree, each device can only be attached to one energy data asset tree.

9. The method for evaluating equipment status based on energy data according to claim 1, 2 or 3, characterized in that: The energy consumption characteristics include real-time data change trends, abnormal energy consumption data and energy performance parameters.

10. The method for evaluating equipment status based on energy data according to claim 4, characterized in that: The normalization processing of the original energy data includes: adding device ID and time to the energy data; and normalizing the energy data with inconsistent time description or field type.

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