An office energy management method and related equipment

Abstract

This application provides an office energy consumption management method and related equipment, belonging to the field of energy management technology. The method includes: collecting multi-source heterogeneous data from various levels of organizations; calculating unit energy consumption from the multi-source heterogeneous data to obtain unit energy consumption indicators; comparing the energy consumption targets issued by higher-level organizations with the unit energy consumption indicators using different evaluation scales to obtain comparison results; if abnormal energy consumption points are found in the comparison results, an energy efficiency work order is generated and pushed to the target terminal to handle the abnormal energy consumption points. This application embodiment can achieve unified monitoring of energy consumption at all levels of organizations.

Description

Technical Field

[0001] This application relates to the field of energy management technology, and in particular to an office energy consumption management method and related equipment. Background Technology

[0002] Large enterprises, especially those with numerous dispersed buildings and cross-regional operations, face significant challenges in energy management within their offices. In related technologies, energy consumption data (such as electricity, water, and oil) is often scattered across different business systems (such as vehicle management systems, logistics systems, and data centers), creating data silos and lacking unified analysis and processing. Furthermore, the lack of unified control over energy consumption across multiple organizational levels within large enterprise groups leads to inefficient management, difficulty in establishing energy-saving responsibilities, and a lack of precise data support for decision-making.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] The main objective of this application is to propose an office energy consumption management method and related equipment to achieve unified supervision of energy consumption at all levels of the organization.

[0005] To achieve the above objectives, one aspect of this application proposes an office energy consumption management method, the method comprising: Collect multi-source heterogeneous data from organizations at all levels; The unit energy consumption is calculated for the multi-source heterogeneous data to obtain the unit energy consumption index; The energy consumption targets issued by the higher-level organization are compared with the unit energy consumption index using different evaluation scales to obtain the comparison results; If the comparison results show abnormal energy consumption points, an energy efficiency work order is generated and pushed to the target terminal to process the abnormal energy consumption points.

[0006] In some embodiments, before performing unit energy consumption calculation on the multi-source heterogeneous data, the method further includes: The multi-source heterogeneous data is standardized to obtain standardized multi-source heterogeneous data.

[0007] In some embodiments, the step of calculating the unit energy consumption of the multi-source heterogeneous data to obtain the unit energy consumption index includes: Obtain the building area and number of personnel of organizations at all levels; Based on the building area, the energy consumption per unit area of ​​the multi-source heterogeneous data is calculated to obtain the energy consumption per unit area. Based on the number of people, the average energy consumption per person is calculated from the multi-source heterogeneous data to obtain the average energy consumption per person. The unit energy consumption index includes the unit area energy consumption and the per capita energy consumption.

[0008] In some embodiments, the energy consumption target is obtained through the following steps: Obtain overall energy consumption indicators and organizational data from all levels of organizations; The weighting factors for energy consumption task decomposition are determined based on the institutional data. The total energy consumption index is decomposed according to the weighting factors to obtain the energy consumption target.

[0009] In some embodiments, the institutional data includes a first building area, a first number of energy users, and first historical energy consumption data. The step of determining weighting factors for energy consumption task decomposition based on the institutional data includes: The first proportion is determined based on the ratio of the first building area of ​​the current organization to the total building area of ​​the same level organization; The second proportion is determined based on the ratio of the number of first energy consumers in the current organization to the total number of employees in the same level organization; The third proportion is determined based on the ratio of the first historical energy consumption data of the current organization to the total historical energy consumption of the same level organization; The weighting factor is obtained by weighting and summing the first proportion, the second proportion, and the third proportion.

[0010] In some embodiments, the energy consumption target includes constraint values, benchmark values, and guiding values. The energy consumption target issued by the superior organization is compared with the unit energy consumption indicator using different evaluation scales to obtain comparison results, including: The unit energy consumption index is evaluated on different scales based on the constraint value, the benchmark value, and the guiding value, and the comparison results under different evaluation scales are obtained.

[0011] In some embodiments, the method further includes: The unit energy consumption index of the current organization is compared with the average energy consumption of organizations at the same level to generate an energy consumption ranking of organizations at the same level and display it visually.

[0012] To achieve the above objectives, another aspect of this application provides an office energy management device, the device comprising: The data acquisition module is used to collect multi-source heterogeneous data from organizations at all levels. The calculation module is used to calculate the unit energy consumption of the multi-source heterogeneous data to obtain the unit energy consumption index. The comparison module is used to compare the energy consumption targets issued by the superior organization with the unit energy consumption index using different evaluation scales to obtain the comparison results. The alarm module is used to generate an energy efficiency work order if there are abnormal energy consumption points in the comparison results, and push the energy efficiency work order to the target terminal to process the abnormal energy consumption points.

[0013] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0014] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides an office energy consumption management method, device, electronic device, storage medium, and program product. This solution decomposes macro-level energy consumption targets into organizational levels and dynamically benchmarks them against standards in different regions to achieve a unified standard for energy consumption monitoring, improves the scientific nature of energy consumption anomaly monitoring, generates energy efficiency work orders based on abnormal energy consumption points, quickly implements energy-saving responsibilities, and enables rapid processing of abnormal energy consumption points, thus supporting the achievement of energy-saving targets. Attached Figure Description

[0017] Figure 1 This is a flowchart of the office energy consumption management method provided in the embodiments of this application; Figure 2 This is a schematic diagram of the application architecture of the office energy management method provided in the embodiments of this application; Figure 3 This is a flowchart of the energy consumption early warning and work order closed-loop processing provided in the embodiments of this application; Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] Large enterprises, especially conglomerates with numerous dispersed buildings and cross-regional operations (such as power grid companies), face significant challenges in energy management within their office environments. In related technologies, energy consumption data (such as electricity, water, and oil) is often scattered across different business systems (such as vehicle management systems, logistics systems, and data centers), creating data silos and lacking unified analysis and processing. Furthermore, the lack of unified control over energy consumption across multiple organizational levels within large conglomerates leads to inefficient management, difficulty in establishing energy-saving responsibilities, and a lack of precise data support for decision-making.

[0021] In summary, the technical problems existing in the relevant technologies need to be improved.

[0022] In view of this, this application provides an office energy consumption management method and related equipment. This solution decomposes the macro-level energy consumption target to each level of organization and dynamically benchmarks it against the standards of different regions to achieve a unified standard for energy consumption monitoring, improve the scientific nature of energy consumption anomaly monitoring, generate energy efficiency work orders based on abnormal energy consumption points, quickly implement energy-saving responsibilities, and achieve rapid processing of abnormal energy consumption points to support the achievement of energy-saving targets.

[0023] This application provides an office energy consumption management method, relating to the field of energy management technology. The office energy consumption management method provided in this application can be applied to a terminal, a server, or software running on a terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the office energy consumption management method, but is not limited to the above forms.

[0024] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0025] Figure 1 This is an optional flowchart of the office energy consumption management method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S104.

[0026] Step S101: Collect multi-source heterogeneous data from various levels of organizations; Step S102: Calculate the unit energy consumption of the multi-source heterogeneous data to obtain the unit energy consumption index; Step S103: Compare the energy consumption targets issued by the superior organization with the unit energy consumption indicators using different evaluation scales to obtain the comparison results; Step S104: If there are abnormal energy consumption points in the comparison results, an energy efficiency work order is generated and pushed to the target terminal to handle the abnormal energy consumption points.

[0027] Steps S101 to S104, as illustrated in this embodiment, comprehensively and in real-time grasp the overall energy consumption of enterprise administrative offices through multi-source data fusion. By decomposing macro-level energy consumption targets to each level of organization and dynamically benchmarking them against standards in different regions, a unified standard for energy consumption monitoring is achieved, improving the scientific rigor of energy consumption anomaly monitoring. Energy efficiency work orders are generated based on abnormal energy consumption points, enabling rapid implementation of energy-saving responsibilities and rapid handling of abnormal energy consumption points, thus supporting the achievement of energy-saving targets.

[0028] In step S101 of some embodiments, the multi-source heterogeneous data includes, but is not limited to, electricity consumption data, water consumption data, and oil consumption data. By executing the system access interface of the enterprise's Internet of Things platform, vehicle management system, data center, and unstructured platform, the system obtains building water meter and electricity meter data from the Internet of Things platform, oil consumption data from the vehicle management system, and partial electricity consumption data from the data center.

[0029] In some embodiments, before performing step S102, the office energy management method further includes step S110: Step S110: Standardize the multi-source heterogeneous data to obtain standardized multi-source heterogeneous data.

[0030] In step S110 of some embodiments, a unified standardization process is carried out on office electricity, water, and oil consumption data from different sources. This is achieved by standardizing data measurement units, unifying statistical time dimensions, calibrating data collection accuracy, cleaning up abnormal and missing values, and unifying field naming rules and data formats. This eliminates differences in statistical caliber, collection methods, and recording standards among different data sources, forming standardized energy consumption data that can be used for energy consumption management. This provides a reliable data foundation for subsequent office energy consumption statistics and energy consumption control.

[0031] In some embodiments, step S102 may include, but is not limited to, steps S121 to S123: Step S121: Obtain the building area and number of personnel for each level of organization; Step S122: Calculate the energy consumption per unit area of ​​the multi-source heterogeneous data based on the building area to obtain the energy consumption per unit area; Step S123: Calculate the per capita energy consumption based on the number of people in the multi-source heterogeneous data to obtain the per capita energy consumption; Among them, the unit energy consumption index includes energy consumption per unit area and per capita energy consumption.

[0032] In steps S121 to S123 of some embodiments, the organizations at each level can be provincial-municipal-county level organizations or branches. Based on standardized multi-source heterogeneous data, and combined with conversion factors such as office building area, number of employees, and equipment operating time, energy consumption per unit area and per capita energy consumption are calculated, such as electricity consumption per unit area, water consumption per unit area, per capita fuel consumption, and energy consumption per unit output value. After normalization and comparison with benchmark values, the energy utilization efficiency and resource consumption level of the office area are reflected, providing a quantitative basis for energy consumption benchmarking analysis.

[0033] In some embodiments, the energy consumption target can be obtained, but is not limited to, through steps S201 to S203; Step S201: Obtain total energy consumption indicators and organizational data at all levels; Step S202: Determine the weighting factors for energy consumption task decomposition based on the organization's data; Step S203: Decompose the total energy consumption index according to the weighting factors to obtain the energy consumption target.

[0034] In step S201 of some embodiments, the total energy consumption index can be determined by the corporate headquarters based on public energy consumption standards. The total energy consumption index includes the unit area electricity consumption constraint value, benchmark value, and per capita energy consumption. Organizational data includes the building area and number of employees of the corporate headquarters' provincial subsidiaries and its municipal and county-level institutions.

[0035] In some embodiments, step S202 may include, but is not limited to, steps S221 to S224: Step S221: Determine the first proportion based on the ratio of the first building area of ​​the current organization to the total building area of ​​the same level organizations; Step S222: Determine the second proportion based on the ratio of the number of primary energy consumers in the current organization to the total number of employees in the same level organization; Step S223: Determine the third proportion based on the ratio of the first historical energy consumption data of the current organization to the total historical energy consumption of the same level organizations; Step S224: The first proportion, the second proportion, and the third proportion are weighted and summed to obtain the weight factor.

[0036] In steps S221 to S224 of some embodiments, the total energy consumption index of the superior organization is decomposed to the subordinate organizations level by level according to weighting factors, and an energy consumption decomposition task is generated and pushed out. The weighting factors are calculated comprehensively based on the building area, number of energy users, and historical energy consumption data of the subordinate organizations, as follows: w_i=α·(A_i / ∑A)+β·(P_i / ∑P)+γ·(E_i^hist / ∑E^hist); Where w_i represents the weighting factor, α, β and γ are configurable weighting coefficients that satisfy α+β+γ=1, A_i represents the first building area of ​​the current organization, ∑A is the total building area of ​​the same level organization, P_i is the first energy user of the current organization, ∑P is the total number of people in the same level organization, E_i^hist is the first historical energy consumption data of the current organization, and ∑E^hist is the historical total energy consumption of the same level organization.

[0037] In step S303 of some embodiments, the energy consumption target of the lower-level organization is: E_i^target = E_total^target × w_i, where E_total^target is the total energy consumption index of the upper-level organization.

[0038] By using weighting factors, energy consumption targets for each subordinate organization can be dynamically allocated, automatically and scientifically decomposing macro-level energy consumption targets to each level of organization, making management based on evidence and ensuring that responsibilities are effectively implemented at each level.

[0039] In some embodiments, the energy consumption target includes a constraint value, a baseline value, and a guiding value, and step S103 may include, but is not limited to, step S131: Step S131: Evaluate the unit energy consumption index at different scales based on the constraint value, benchmark value and guiding value, and obtain the comparison results under different evaluation scales.

[0040] In step S131 of some embodiments, based on the energy consumption quota standards corresponding to each provincial, municipal, and county (district) level region, the standards include at least the constraint values, benchmark values, and guiding values ​​of energy consumption per unit building area and per capita comprehensive energy consumption, forming a three-level evaluation scale of "red line - average line - optimal line", providing differentiated assessment basis for different management stages.

[0041] In step S104 of some embodiments, when an abnormal energy consumption point is detected, a work order is automatically generated and pushed to the designated person in charge through the target terminal to track the processing process and archive the processing results for effectiveness analysis.

[0042] The method provided in this embodiment may further include step S105; Step S105: Compare the unit energy consumption index of the current organization with the average energy consumption of organizations at the same level, generate the energy consumption ranking of organizations at the same level, and display it visually.

[0043] In step S105 of some embodiments, energy consumption status, ranking benchmarking results and abnormal alarms are displayed in the form of energy consumption maps, heat maps, Sankey diagrams, etc., through large screens, web terminals and mobile terminals.

[0044] In some embodiments, an administrative office energy consumption quota decomposition and dynamic benchmarking management system based on multi-source data fusion is used to execute the office energy consumption management method of this embodiment. The system includes: The multi-source data fusion acquisition module is configured to interface with IoT platforms, vehicle management systems, data centers, and unstructured platforms to collect and standardize office electricity, water, and fuel data from different sources.

[0045] The energy consumption quota standard library module is configured to store and dynamically maintain the energy consumption quota standards corresponding to each provincial, municipal, and county (district) level region. The standards include at least the constraint value, benchmark value, and guiding value of energy consumption per unit building area and per capita comprehensive energy consumption, forming a three-level evaluation scale of "red line - average line - optimal line" to provide differentiated assessment basis for different management stages.

[0046] The indicator decomposition and task push module is configured to obtain organizational structure information and automatically decompose the total energy consumption or intensity target of the superior organization to the subordinate organization according to the standard value in the energy consumption quota standard library, and generate energy consumption decomposition tasks for push. The weighting factor is calculated based on the building area, number of energy users and historical energy consumption data of the subordinate institutions.

[0047] The dynamic benchmarking and anomaly analysis module is configured to perform multi-dimensional comparative analysis of real-time or periodically collected energy consumption data with data from the same level of organization, historical data from the same period, and constraint values ​​and benchmark values ​​in the energy consumption quota standard library, and to identify and mark energy consumption points that exceed the standard or are abnormal.

[0048] The visualization and work order closed-loop module is configured to display energy consumption status, ranking benchmarking results and abnormal alarms in the form of energy consumption maps, heat maps and Sankey diagrams through large screens, web terminals and mobile terminals. Based on the alarms, energy efficiency work orders are automatically generated and dispatched to the responsible persons for processing, forming a management closed loop of "monitoring-alarming-dispatch-processing-archiving".

[0049] In some embodiments, please refer to Figure 2 An application architecture for implementing the office energy management method of this embodiment includes an IOC dashboard (a three-level energy consumption monitoring platform), a web interface, an Elink interface, and an integration interface.

[0050] The IOC large screen (Level 3 Energy Consumption Monitoring Platform) serves as a visualization hub, enabling global energy consumption situation perception and centralized management. Through six core dashboards—energy consumption map, energy consumption status, energy use analysis, energy consumption branch analysis, energy consumption reporting statistics, and energy-saving effect analysis—it achieves real-time presentation of energy consumption data across all regions and dimensions, trend analysis, and quantitative evaluation of energy-saving effects, providing management with intuitive and efficient decision support.

[0051] The web interface serves as the core management backend for all business operations and is the central hub of the system. In terms of analytical capabilities, it possesses multi-dimensional and refined analytical capabilities, including quantitative energy consumption analysis, precise branch energy consumption analysis, energy consumption ranking benchmarking, and energy consumption big data mining. It can realize functions such as energy consumption trend judgment, branch energy consumption statistics, key equipment monitoring, anomaly identification, sub-item energy consumption management, branch energy consumption configuration, total energy consumption and unit area energy consumption ranking benchmarking, and daily, monthly, quarterly, and annual water load and electricity load energy consumption data analysis.

[0052] At the business control level, it integrates full-process business modules such as energy consumption device management, energy consumption reporting management, early warning mechanism, energy efficiency work order management, process management, system management, and message center to achieve full-link control including water meter and electricity meter ledger management, data collection, collection strategy configuration, reporting template management, reporting application, reporting summary, reporting notification, reporting assessment, historical reporting query, early warning rule configuration, indicator anomaly alarm, handling follow-up, event closure, work order ledger, work order approval, work order dispatch, work order configuration, work order statistics, process design, process release, process editing, process progress query, account management, dictionary management, scene space management, indicator management, log management, permission management, organizational structure management, account information synchronization, and energy and carbon configuration.

[0053] As a mobile collaborative terminal, Elink provides functions such as work order management, energy consumption ranking and indicators, and message center. It supports work order creation, approval, dispatch and processing, energy consumption ranking benchmarking, energy consumption indicator management, energy saving suggestions, energy saving plans, message management, task management, and announcement management. It breaks the limitations of time and space, supports efficient collaboration in energy consumption anomaly handling, work order circulation and task reception, and improves the efficiency of energy consumption control business execution.

[0054] As the foundation for system interconnection, the integration and docking layer uses standardized interfaces and protocols to achieve integration with external systems such as IoT platforms, Elink systems, cloud platform display windows, data centers, digital identity authentication platforms, vehicle systems, structured platforms, user centers, and metering automation systems. This enables cross-system sharing and collaboration of energy consumption data, business processes, identity authentication, and metering data, building a compatible and scalable energy management ecosystem.

[0055] The overall architecture is data-driven at its core, realizing full-process digital control of energy consumption data from collection, standardized processing, indicator calculation, analysis and judgment, early warning and handling to work order closed loop and effectiveness evaluation. At the same time, through multi-terminal collaboration and cross-system integration, it realizes full-cycle monitoring and refined management of energy consumption data such as electricity, water and oil in office scenarios.

[0056] In some embodiments, an administrative office energy consumption quota decomposition and dynamic benchmarking management method based on multi-source data fusion (office energy consumption management method) includes the following steps: S1. Data fusion steps: Unify access and clean real-time or near-real-time energy consumption data of electricity, water and oil from multiple heterogeneous systems.

[0057] S2. Standard configuration steps: Import or configure energy consumption quota standards that include constraint values, benchmark values, and guiding values ​​according to administrative divisions.

[0058] S3. Indicator Decomposition Steps: In response to the issuance of energy consumption targets by higher authorities, the system automatically calculates weighting factors based on the building area, number of energy users, or historical energy consumption data of subordinate institutions, and decomposes the energy consumption quota indicators of subordinate institutions according to the weighting factors.

[0059] S4. Dynamic benchmarking steps: Calculate the actual energy consumption indicators of each institution in real time, and dynamically benchmark them against the average of institutions at the same level, their own historical data, and the benchmark and constraint values ​​in the quota standard library to form rankings and early warnings.

[0060] S5. Closed-loop management steps: When energy consumption exceeds the standard or an anomaly is detected, a work order is automatically generated, pushed to the designated person in charge via mobile terminal, the processing process is tracked, and the processing results are archived for effectiveness analysis.

[0061] In some embodiments, please refer to Figure 3 During the work order processing, after the platform triggers the energy station-energy efficiency anomaly warning (level 2), the platform analyzes the energy efficiency data, issues an alarm reminder, notifies relevant personnel via SMS, coordinates on-site operation and maintenance personnel to handle on-site verification and investigation, and then reports back to the station to close the warning after completion.

[0062] The following is a detailed description and explanation of the solution of this invention, using a large power enterprise group with a multi-level structure of headquarters, provinces, cities, and counties as an example: First, deploy the system of this invention. Through a multi-source data fusion acquisition module, it connects to the enterprise's existing IoT platform (to acquire building water and electricity meter data), vehicle management system (to acquire fuel consumption data), and data center (to acquire partial electricity consumption data).

[0063] Then, in the energy consumption quota standard library module, the "Energy Consumption Quota" standards of different provinces are pre-imported, including the unit area electricity consumption constraint value and benchmark value of various types of buildings.

[0064] After the headquarters issues the annual office energy consumption target, the indicator decomposition and task push module automatically reads static data such as building area and number of employees of each subordinate provincial company and its municipal and county-level institutions, decomposes the total target into the annual energy consumption quota of each institution according to the weight, and generates "energy consumption indicator decomposition task", which is pushed to the person in charge of each institution through the system's to-do center.

[0065] During daily operation, the dynamic benchmarking and anomaly analysis module continuously calculates the actual "energy consumption per unit area" of each institution and compares it with the "benchmark value" in the provincial quota standard. If the energy consumption of a municipal institution exceeds the "constraint value" for three consecutive months, the system will automatically trigger an early warning.

[0066] The visualization and work order closed-loop module marks the area in red on the energy consumption heat map of the energy consumption dashboard and generates an energy consumption exceedance alarm work order, which is pushed to the organization's logistics manager via the Elink mobile app. The manager conducts on-site investigation (if an aging air conditioning system is found), handles the issue, fills out a processing record, and closes the work order. The system then compares the energy consumption data before and after the rectification in the energy-saving effect analysis to quantify the energy-saving effect.

[0067] Through the above process, full-chain digital and intelligent management was achieved, from target decomposition, process monitoring, anomaly alarms to rectification closure.

[0068] This application embodiment also provides an office energy management device that can implement the above-described method. The device includes: The data acquisition module is used to collect multi-source heterogeneous data from organizations at all levels. The calculation module is used to calculate the unit energy consumption of multi-source heterogeneous data and obtain the unit energy consumption index. The comparison module is used to compare the energy consumption targets issued by the superior organization with the unit energy consumption index using different evaluation scales to obtain the comparison results; The alarm module is used to generate an energy efficiency work order if there are abnormal energy consumption points in the comparison results, and push the energy efficiency work order to the target terminal to handle the abnormal energy consumption points.

[0069] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0070] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0071] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0072] Please see Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 901 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 902 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 902 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called and executed by the processor 901 using the methods described in the embodiments of this application. The input / output interface 903 is used to implement information input and output; The communication interface 904 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 905 transmits information between various components of the device (e.g., processor 901, memory 902, input / output interface 903, and communication interface 904); The processor 901, memory 902, input / output interface 903, and communication interface 904 are connected to each other within the device via bus 905.

[0073] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0074] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0075] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0076] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0077] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0078] The office energy management method, apparatus, electronic device, storage medium, and program product provided in this application have at least the following beneficial effects: (1) Break down data silos and achieve full-domain perception: Through the fusion of multi-source data, we can fully and in real time grasp the overall picture of the energy consumption of the enterprise's administrative office.

[0079] (2) Refined and standardized management: The macro energy consumption targets are automatically and scientifically decomposed to the grassroots units and dynamically benchmarked against national / local standards, so that management is based on evidence and responsibility is implemented at each level.

[0080] (3) Improve decision-making efficiency and accuracy: Through visualization methods such as energy consumption maps, heat maps, and multi-dimensional rankings, provide managers with intuitive and accurate decision support and quickly locate high-energy-consuming units or abnormal links.

[0081] (4) Forming a closed-loop management system to ensure energy-saving effectiveness: The online closed-loop management of the entire process from anomaly detection, alarm, work order dispatch to processing and archiving greatly improves the speed of problem response and problem-solving efficiency, and effectively supports the achievement of energy-saving and consumption-reducing goals.

[0082] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0083] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0084] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0085] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0086] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0087] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0088] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0089] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0090] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0091] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0092] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. An office energy consumption management method, characterized in that, The method includes the following steps: Collect multi-source heterogeneous data from organizations at all levels; The unit energy consumption is calculated for the multi-source heterogeneous data to obtain the unit energy consumption index; The energy consumption targets issued by the higher-level organization are compared with the unit energy consumption index using different evaluation scales to obtain the comparison results; If the comparison results show abnormal energy consumption points, an energy efficiency work order is generated and pushed to the target terminal to process the abnormal energy consumption points.

2. The method according to claim 1, characterized in that, Before performing the unit energy consumption calculation on the multi-source heterogeneous data, the method further includes: The multi-source heterogeneous data is standardized to obtain standardized multi-source heterogeneous data.

3. The method according to claim 1, characterized in that, The step of calculating the unit energy consumption of the multi-source heterogeneous data to obtain the unit energy consumption index includes: Obtain the building area and number of personnel of organizations at all levels; Based on the building area, the energy consumption per unit area of ​​the multi-source heterogeneous data is calculated to obtain the energy consumption per unit area. Based on the number of people, the average energy consumption per person is calculated from the multi-source heterogeneous data to obtain the average energy consumption per person. The unit energy consumption index includes the unit area energy consumption and the per capita energy consumption.

4. The method according to claim 1, characterized in that, The energy consumption target is obtained through the following steps: Obtain overall energy consumption indicators and organizational data from all levels of organizations; The weighting factors for energy consumption task decomposition are determined based on the institutional data. The total energy consumption index is decomposed according to the weighting factors to obtain the energy consumption target.

5. The method according to claim 4, characterized in that, The institutional data includes a first building area, a first number of energy users, and a first historical energy consumption data. The step of determining the weighting factors for energy consumption task decomposition based on the institutional data includes: The first proportion is determined based on the ratio of the first building area of ​​the current organization to the total building area of ​​the same level organization; The second proportion is determined based on the ratio of the first energy user in the current organization to the total number of employees in the same level organization; The third proportion is determined based on the ratio of the first historical energy consumption data of the current organization to the total historical energy consumption of the same level organization; The weighting factor is obtained by weighting and summing the first proportion, the second proportion, and the third proportion.

6. The method according to claim 1, characterized in that, The energy consumption targets include constraint values, benchmark values, and guiding values. The energy consumption targets issued by higher-level organizations are compared with the unit energy consumption indicators using different evaluation scales to obtain comparison results, including: The unit energy consumption index is evaluated on different scales based on the constraint value, the benchmark value, and the guiding value, and the comparison results under different evaluation scales are obtained.

7. The method according to claim 1, characterized in that, The method further includes: The unit energy consumption index of the current organization is compared with the average energy consumption of organizations at the same level to generate an energy consumption ranking of organizations at the same level and display it visually.

8. An office energy management device, characterized in that, The device includes: The data acquisition module is used to collect multi-source heterogeneous data from organizations at all levels. The calculation module is used to calculate the unit energy consumption of the multi-source heterogeneous data to obtain the unit energy consumption index. The comparison module is used to compare the energy consumption targets issued by the superior organization with the unit energy consumption index using different evaluation scales to obtain the comparison results. The alarm module is used to generate an energy efficiency work order if there are abnormal energy consumption points in the comparison results, and push the energy efficiency work order to the target terminal to process the abnormal energy consumption points.

9. An electronic device, characterized in that, include: At least one processor; At least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

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