Existing multifunctional building group distributed energy management system and transformation method

Abstract

The invention discloses an existing multifunctional building group distributed energy management system and a transformation method, relates to the technical field of energy management system transformation, and aims to solve the problems that multi-source data of an existing system cannot be fused and unified business support is lacked. The system comprises a distributed energy data acquisition unit which is deployed according to functional areas and energy types and comprises a water supply sub-unit, a heat supply sub-unit, a power supply sub-unit and an auxiliary acquisition sub-unit; the multi-mode communication transmission network is used for data local collection and remote transmission; the energy comprehensive management platform is connected with the communication network and comprises a data middle station, a service middle station and a technology middle station; and the AI quality conformity verification module is used for realizing intelligent verification and long-term trend monitoring of equipment installation quality and data transmission reliability based on an AI model of multi-modal data fusion analysis. The system is suitable for new construction or reconstruction of energy systems of complex building groups such as airports and large-scale parks, and distributed energy monitoring, centralized management and intelligent quality verification can be realized.

Description

Technical Field

[0001] This invention belongs to the field of energy management system transformation technology, specifically involving an existing multifunctional building complex distributed energy management system and its transformation method. It is applicable to the energy system upgrade and transformation of complex building complexes such as airports and large parks that contain multiple types of functional areas and multiple energy media, realizing distributed energy monitoring, centralized management and intelligent quality verification. Background Technology

[0002] Existing multifunctional building complexes (such as airports, large industrial parks, etc.) typically encompass multiple functional zones (such as terminal areas, living areas, production areas, etc.), involving various energy media such as water supply, heating, and power supply. They are characterized by large energy consumption, complex energy use scenarios, and relatively independent areas.

[0003] Currently, energy management systems for such building complexes typically employ a decentralized deployment structure. This means that various energy metering devices are distributed across different functional areas, including mechanical or semi-smart water meters for water supply systems, ordinary heat meters for heating systems, and traditional electricity meters for power supply systems. These metering devices mostly operate with local display and manual data reading, lacking remote data transmission capabilities or only possessing unidirectional data transmission capabilities. Separate monitoring systems are built for different energy types, such as independent energy consumption management systems (collecting only total electricity consumption data), power monitoring systems (monitoring the operating status of the power distribution system), and water supply monitoring systems (monitoring the operating status of water pumps). Each subsystem uses different communication protocols and data formats, and each is deployed with its own independent servers and monitoring terminals.

[0004] The aforementioned energy management system has the following problems:

[0005] 1. Outdated energy monitoring methods: Most energy metering instruments are mechanical or semi-intelligent, relying on manual data recording, which leads to problems such as data lag, inaccurate statistics, and difficulty in detecting leaks. In addition, data on various energy media (water supply, heating, and power supply) are scattered and lack unified integration.

[0006] 2. Poor system compatibility: Existing energy-related systems (such as independent energy consumption management systems and power monitoring systems) operate independently, with data not being shared and interfaces being incompatible. This prevents the integration and analysis of data from different energy types, such as water supply, heating, and power supply, on a single platform. Managers are unable to obtain comprehensive energy consumption per unit of output and cannot achieve global collaborative energy management.

[0007] 3. Poor system scalability: Each subsystem is built independently and adopts a tightly coupled architecture. When it is necessary to add new monitoring points or connect new energy types (such as charging piles or photovoltaic power generation), each subsystem needs to be modified separately, which is difficult and costly to implement.

[0008] To address the aforementioned issues, existing technologies offer some improvement solutions for single-energy systems (such as separately upgrading water supply or power supply systems, deploying smart water meters in water supply systems, and smart electricity meters in power supply systems). However, these solutions only improve data acquisition for a single energy source and cannot solve the problems of multi-energy data fusion and unified business management, making them unsuitable for the complex scenarios of multi-functional building complexes. Furthermore, traditional quality verification methods are inefficient and cannot meet the requirements for stable system operation after the upgrade. Therefore, there is an urgent need for an integrated solution that combines distributed upgrade implementation, multi-energy collaborative management, and intelligent quality verification to address the pain points of upgrading existing multi-functional building complex energy management systems. Summary of the Invention

[0009] The purpose of this invention is to provide a distributed energy management system and renovation method for existing multifunctional building complexes, which overcomes the problems of existing decentralized energy management systems, such as the inability to integrate multi-source data and the lack of unified business support, and realizes collaborative management and intelligent quality verification of multi-energy data.

[0010] The technical solution adopted in this invention is: an existing multi-functional building complex distributed energy management system, including a distributed energy data acquisition unit, a multi-mode communication transmission network, an energy integrated management platform, and an AI quality compliance verification module;

[0011] The distributed energy data acquisition unit is deployed in a distributed manner according to the functional zoning and energy type of the multi-functional building complex. It is used to collect energy data of each area and energy type, including water supply data acquisition subunit, heating data acquisition subunit, power supply data acquisition subunit and auxiliary acquisition subunit.

[0012] The multi-mode communication transmission network is a distributed communication network that combines wired and wireless technologies, enabling the local collection and remote transmission of energy data collected by the distributed energy data acquisition unit.

[0013] The energy integrated management platform is connected to a multi-mode communication transmission network to receive and integrate the energy data, thereby realizing centralized control and intelligent application of multi-energy data. The energy integrated management platform includes a data platform, a business platform, and a technology platform. The data platform is used to standardize multi-source heterogeneous energy data, the business platform is used to provide shareable energy management business components, and the technology platform is used to provide a system development and deployment environment.

[0014] The AI ​​quality compliance verification module is coupled with the energy integrated management platform to acquire multimodal data during the transformation process and operation phase. Based on the AI ​​model of multimodal data fusion analysis, it performs intelligent verification and long-term trend monitoring of equipment installation quality and data transmission reliability.

[0015] Furthermore, the water supply data acquisition subunit includes remote-reading smart water meters with valve control function deployed in the centralized water supply main pipelines of individual buildings in each functional area and at the user end; the remote-reading smart water meters are communicatively connected to the data fusion terminal in their respective functional areas to send the collected water supply data to the data fusion terminal; the data fusion terminal uploads the collected water supply data to the energy integrated management platform through a multi-mode communication transmission network.

[0016] Furthermore, the heating data acquisition subunit includes remote-reading smart heat meters and supply and return water pipe pressure sensors deployed at each heat energy center and building heating main. The remote-reading smart heat meters are equipped with temperature sensors for collecting heating data. The remote-reading smart heat meters and supply and return water pipe pressure sensors are communicatively connected to the data fusion terminal in their respective functional areas to send the collected heating data to the data fusion terminal. The data fusion terminal uploads the heating data to the energy integrated management platform through a multi-mode communication transmission network.

[0017] Furthermore, the power supply data acquisition subunit includes prepaid meters and multi-function energy meters deployed in substations and distribution cabinets / boxes in various regions. High-voltage circuits are equipped with multi-function energy meters using 0.2-level accuracy current transformers, while low-voltage circuits are equipped with either prepaid meters or ordinary multi-function meters according to the energy consumption scenario, to collect power supply data. The prepaid meters and multi-function energy meters are communicatively connected to the data fusion terminal in their respective functional areas to send the collected power supply data to the data fusion terminal. The data fusion terminal uploads the power supply data to the energy integrated management platform through a multi-mode communication transmission network.

[0018] Furthermore, the auxiliary acquisition subunit includes LED lights with integrated sensing functions deployed in public areas for intelligent control and data acquisition of lighting energy consumption; the auxiliary acquisition subunit also reserves standardized acquisition interfaces for connecting other energy-consuming or detection devices; the LED lights and other devices connected through the standardized acquisition interfaces are communicatively connected to the data fusion terminal in the functional area to send the acquired auxiliary data to the data fusion terminal; the data fusion terminal uploads the auxiliary data to the energy integrated management platform through a multi-mode communication transmission network.

[0019] Furthermore, the multi-mode communication transmission network includes a data fusion terminal, with one data fusion terminal configured in each functional area. The data fusion terminal is connected to a power source nearby and is used to collect data from various acquisition terminals within the area. The acquisition terminal and the data fusion terminal in the functional area communicate with each other via wired or wireless means.

[0020] The multi-mode communication transmission network uses the following methods for indoor transmission: signal and power lines of the acquisition terminal are laid openly in protective conduits or connected to the data fusion terminal in the building's power distribution room via low-voltage cable trays; outdoor transmission uses direct burial with a depth of 1 meter and backfilling with plain soil, and trenching and conduit installation is carried out where the network crosses hardened pavement and then restored; backbone transmission connects to the aggregation switches in each area via newly laid optical cables and then connects to the core switch; IoT data is accessed through digital leased lines via routers and IPS to the device network; and remote access is achieved through VPN and Internet lines.

[0021] Furthermore, in the aforementioned integrated energy management platform:

[0022] The data platform is connected to a multi-mode communication transmission network to receive energy data uploaded from various functional areas, acquire, store, calculate and process the data, support multiple IoT protocols such as ModBus, TCP and MQTT, and provide the standardized data to the business platform.

[0023] The business platform calls upon the standardized data provided by the data platform to provide shared components for energy planning, energy consumption benchmarking, cost management, prepaid management, and operation and maintenance management in a service-oriented manner, supporting the implementation of upper-layer functional modules;

[0024] The technology platform provides a system development and deployment environment for the data platform and business platform. It is based on a front-end and back-end separation model, supports multi-language development such as Java, C++, and Python, and uses Docker image containerization for deployment.

[0025] The energy management platform integrates core functional modules such as data acquisition and analysis, alarm management, energy planning, energy consumption benchmarking, energy auditing, cost accounting, prepaid management, operation and maintenance management, comprehensive monitoring, report generation, and carbon emission management. These functional modules call the shared components provided by the business platform to realize corresponding business functions and support access from both PC and mobile terminals.

[0026] Furthermore, the AI ​​quality compliance verification module includes a data input unit, a preprocessing unit, an AI analysis unit, and an output unit;

[0027] The data input unit acquires electrical parameter data from the distributed acquisition unit and image data reflecting the equipment installation status, and generates a time-synchronized multimodal dataset.

[0028] The preprocessing unit cleans and normalizes the multimodal dataset, and maps the processed data to the corresponding devices or regions through a preset device topology mapping table to generate partitioned data.

[0029] The AI ​​analysis unit is pre-set with an electrical anomaly detection model and a visual anomaly detection model trained with historical fault data. The partition data is input into the electrical anomaly detection model and the visual anomaly detection model respectively to generate electrical anomaly scores and visual anomaly scores respectively. The scores are then fused according to preset weight coefficients to generate a comprehensive quality score.

[0030] The output unit generates and outputs quality verification information based on the comprehensive quality score.

[0031] The method for retrofitting existing multi-functional building complex distributed energy management systems, based on the existing distributed energy management system for multi-functional building complexes, includes the following steps:

[0032] S1. Current Status Survey and Scheme Design: Conduct a survey on the current status of the energy system in each functional area of ​​the target building complex, and based on the survey results, divide the area into renovation units according to the functional areas. Design a distributed renovation scheme for each renovation unit, including functional modules such as energy data acquisition terminals, communication networks, and energy integrated management platforms.

[0033] S2. Implement the transformation in stages: According to the distributed transformation plan, the energy data acquisition terminal is installed, the communication network is deployed, and the data fusion terminal is debugged in sequence, taking the transformation unit as the unit, to complete the transformation of each transformation unit.

[0034] S3. Data integration and system commissioning: The data collected by each renovation unit is connected to the energy management platform, and the AI ​​quality compliance verification module is used to intelligently verify the installation quality and data transmission reliability of the renovated system. Based on the verification results, abnormal points are rectified.

[0035] S4. Intelligent Operation and Maintenance and Continuous Optimization: The energy system of the building complex is centrally monitored and managed through the energy integrated management platform, and the system operation status is continuously monitored using the AI ​​quality compliance verification module. Maintenance suggestions or optimized operating parameters are generated based on the monitoring data.

[0036] Furthermore, in step S3, the abnormal locations include locations with data transmission interruptions, excessive measurement errors, and installation process defects.

[0037] The beneficial effects of this invention are:

[0038] This invention employs distributed energy data acquisition units, deployed across functional areas and energy types such as water supply, heating, power supply, and auxiliary energy sources. This changes the existing system's limitation of only acquiring data from certain areas and energy types, achieving complete data acquisition across the entire building complex and across multiple energy types. Simultaneously, each acquisition terminal uploads data in real time via a multi-mode communication network, resolving the data lag issue caused by traditional manual data recording. Furthermore, the data platform of the integrated energy management system standardizes multi-source heterogeneous energy data, supporting various IoT protocols such as ModBus, TCP, and MQTT. This unifies data from different formats, including water supply, heating, and power supply, into a standardized data model, fundamentally breaking down the data silos created by the independent operation and incompatible interfaces of existing subsystems, laying a data foundation for multi-energy collaborative management.

[0039] This invention utilizes a business middleware platform within an integrated energy management system to provide shareable business components in a service-oriented manner, including energy planning, energy consumption benchmarking, cost management, prepaid management, and operation and maintenance management. This achieves a leap from data monitoring to business applications. Managers can complete the entire business process—including energy planning, real-time energy consumption benchmarking, automatic cost calculation, prepaid billing, and work order dispatch—through a unified platform, significantly improving management efficiency.

[0040] This invention integrates an AI quality compliance verification module. Through a multimodal AI model that fuses electrical parameter data and equipment installation image data, it achieves intelligent verification of equipment installation quality and data transmission reliability. Not only can it automatically generate quality verification reports after the modification is completed, locating installation process defects and data transmission anomalies, but it can also continuously monitor quality degradation trends during system operation, predict potential failure points, and generate maintenance suggestions, elevating quality management from post-installation manual spot checks to pre-installation intelligent early warning.

[0041] This invention constructs a complete closed loop of "collection-transmission-management-application-verification" through the collaborative work of distributed data acquisition units, a multi-mode communication transmission network, a three-in-one platform, and an AI verification module. Distributed acquisition ensures the integrity of the data source, multi-mode transmission ensures smooth data channels, the three-in-one platform realizes data standardization and business componentization, and AI verification ensures the reliability of system quality. This system enables building complex managers to monitor the consumption of various areas and energy types in real time, perform multi-energy collaborative optimization scheduling, and achieve the goals of energy conservation, cost reduction, and efficiency improvement. Attached Figure Description

[0042] Figure 1 This is a system architecture diagram of the present invention;

[0043] Figure 2 This is a flowchart of the modification method of the present invention;

[0044] Figure 3 This is the logic diagram for the AI ​​quality compliance verification module.

[0045] In the diagram, 1-Distributed energy data acquisition unit, 11-Water supply data acquisition sub-unit, 12-Heating data acquisition sub-unit, 13-Power supply data acquisition sub-unit, 14-Auxiliary acquisition sub-unit, 2-Multi-mode communication transmission network, 3-Energy integrated management platform, 31-Data middle platform, 32-Business middle platform, 33-Technology middle platform, 4-AI quality compliance verification module, 41-Data input unit, 42-Preprocessing unit, 43-AI analysis unit, 44-Output unit. Detailed Implementation

[0046] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0047] The existing multifunctional building complex distributed energy management system disclosed in this invention, such as Figure 1 As shown, the architecture adopts a "distributed acquisition - networked transmission - centralized management and control - intelligent verification" approach, including a distributed energy data acquisition unit 1, a multi-mode communication transmission network 2, an integrated energy management platform 3, and an AI quality compliance verification module 4. These components work together to achieve the energy system transformation and management optimization of the existing multi-functional building complex.

[0048] 1. Distributed Energy Data Acquisition Unit 1

[0049] The distributed energy data acquisition unit 1 deploys acquisition terminals in a distributed manner according to the functional zones and energy types of the multi-functional building complex. It is used to collect energy data from various areas and energy types, achieving localized acquisition of energy data for each functional area. Functional zones refer to areas divided according to their functional characteristics, such as the terminal area, living area, production area, and flight area of ​​an airport. Energy types include water supply, heating, and power supply. The distributed energy data acquisition unit 1 includes a water supply data acquisition subunit 11, a heating data acquisition subunit 12, a power supply data acquisition subunit 13, and an auxiliary acquisition subunit 14, as detailed below:

[0050] Water Supply Data Acquisition Subunit 11: Remote-controlled smart water meters with valve control functions are installed on the centralized water supply main pipelines and user terminals of individual buildings in each functional area. These remote-controlled smart water meters support flow signal acquisition, data storage, and remote transmission. They are waterproof, low-power, and their metering errors meet relevant national standards. This solves the problems of manual meter reading, data lag, inability to remotely manage, and difficulty in detecting leaks in water supply systems. It enables real-time and accurate acquisition and remote transmission of water supply data. The valve control function supports remote switching, timely detection of leaks, and refined water management.

[0051] Heating data acquisition subunit 12: Remote intelligent heat meters and supply and return water pipe pressure sensors are deployed at each heat energy center and building heating main. The remote intelligent heat meters are equipped with temperature sensors to collect heating data such as flow rate, supply water temperature, return water temperature, and pressure parameters. They also support data storage by date and remote transmission. This solves the problem of the lack of monitoring of key operating parameters in the heating system, which hinders thermal balance and energy-saving optimization. It comprehensively collects key parameters such as flow rate, temperature, and pressure, providing data support for thermal balance regulation, load forecasting, and energy-saving operation.

[0052] Power Supply Data Acquisition Subunit 13: Prepaid meters and multi-functional energy meters are installed in substations and distribution cabinets / boxes in various areas. High-voltage circuits are equipped with multi-functional energy meters using 0.2-level accuracy current transformers, while low-voltage circuits are equipped with either prepaid meters or ordinary multi-functional meters according to energy consumption scenarios. These meters are used to collect power supply data such as voltage, current, power, and energy consumption. Power Supply Data Acquisition Subunit 13 adopts a tiered meter configuration to address the problem of coarse-grained monitoring of the power supply system, which cannot meet the needs of different scenarios. It achieves precise metering of high and low voltage power supply circuits through tiered classification. Prepaid meters solve the problem of fee collection, and multi-functional meters provide detailed data for power quality analysis and load management.

[0053] Auxiliary data acquisition subunit 14: Deploys LED lights with integrated sensing functions in public areas, including human body sensing and illuminance sensing. This enables intelligent control and data acquisition of lighting energy consumption. Standardized data acquisition interfaces are reserved for connecting other energy-consuming or monitoring devices (such as rainwater well water levels, charging piles, air conditioning equipment, etc.), supporting future functional expansion. This solves the problems of wasted energy consumption in public area lighting and poor future system scalability. The sensing LEDs achieve "lights off when people leave," resulting in significant energy savings; the standardized reserved interfaces ensure smooth integration of future new energy-consuming devices, demonstrating foresight and scalability.

[0054] 2. Multi-mode communication transmission network

[0055] The multi-mode communication transmission network 2 is a distributed communication network combining wired and wireless technologies. It enables local aggregation and remote transmission of energy data collected by the distributed energy data acquisition unit 1, solving the problems of poor data transmission stability and difficult wiring in complex building complex environments. A hybrid "wired + wireless" network is established, with data fusion terminals achieving local aggregation, ensuring stable transmission of data collected from various functional areas. Details are as follows:

[0056] Data fusion terminal: Each building or functional area is equipped with a data fusion terminal, which is connected to a nearby 220V power supply to collect data from various acquisition terminals in the area. Each power supply circuit can connect to up to 12 meters and upload the data to the energy management platform through a multi-mode communication transmission network (such as a 4G wireless transmission module).

[0057] In-building transmission: The data acquisition terminal communicates with the data fusion terminal in its functional area via wired or wireless means to achieve local data aggregation. For example, the signal and power cables of the acquisition terminal are laid openly in JDG protective conduits or using low-voltage cable trays to connect to the data fusion terminal in the building's power distribution room.

[0058] Outdoor transmission: In outdoor areas, direct burial is used (1 meter burial depth, backfill with plain soil). Where it crosses a hardened road surface, a groove is cut to lay SC pipe and then restored.

[0059] Backbone transmission: Newly laid optical cables connect the aggregation switches in each area to the core switch; IoT data is accessed through digital leased lines via routers and IPS to the device network, and remote access is achieved using VPN + Internet lines.

[0060] 3. Integrated Energy Management Platform

[0061] The energy integrated management platform 3 is connected to a multi-mode communication transmission network to receive and integrate energy data from various functional areas, enabling centralized management and intelligent application of multi-energy data. Centralized management includes operational functions such as real-time monitoring of multi-energy data, equipment control, anomaly alarms, and scheduling optimization. Intelligent applications include data-driven energy consumption diagnosis, energy efficiency assessment, load forecasting, carbon emission calculation, and advanced functions such as AI-based quality verification, fault prediction, and operation and maintenance decision-making. The energy integrated management platform 3 adopts a three-in-one architecture, including a data platform 31, a business platform 32, and a technology platform 33. The data platform 31 is used for standardizing multi-source heterogeneous energy data; the business platform 32 provides shareable energy management business components; and the technology platform 33 provides a system development and deployment environment. This addresses the problems of difficulty in integrating multi-source heterogeneous data, redundant development of business functions, and complex system deployment and maintenance, as detailed below:

[0062] Data Platform 31: Connects to a multi-mode communication transmission network to receive energy data uploaded from various functional areas, standardizes and integrates multi-source heterogeneous energy data, and provides the ability to acquire, store, compute, and process structured (energy consumption data), unstructured (image data), and semi-structured data. It supports multiple IoT protocols such as ModBus, TCP, and MQTT. After completing the standardization process, the data platform provides the standardized data to the business platform for use.

[0063] Business Platform 32: Utilizes standardized data provided by Data Platform 31 to consolidate common business capabilities such as energy planning, energy consumption benchmarking, cost management, prepaid management, and operation and maintenance management. These capabilities are encapsulated into shareable service-oriented components, providing shareable energy management business components in a service-oriented manner to support rapid response to management needs across different functional areas. The shareable service-oriented components provided by the business platform are available for upper-layer functional modules to call, enabling specific business functions.

[0064] Technology Platform 33: Provides a system development and deployment environment for Data Platform 31 and Business Platform 32. Based on a front-end / back-end separation model, it supports development in multiple languages ​​such as Java, C++, and Python, and adopts containerized deployment (such as Docker images) to achieve flexible system expansion and centralized maintenance. The Technology Platform ensures the stable operation and independent upgrades of the Data Platform and Business Platform by providing a unified development framework, API management, and container orchestration capabilities.

[0065] Core functional modules: Based on the shared components provided by the business middle platform, these include core functional modules such as data collection and analysis, alarm management, energy planning, energy consumption benchmarking, energy auditing, cost accounting, prepaid management, operation and maintenance management, comprehensive monitoring, report generation, and carbon emission management. Each functional module implements its corresponding business logic by calling the shared components of the business middle platform, and supports access from both PC and mobile devices.

[0066] 4. AI Quality Compliance Verification Module

[0067] The AI ​​quality compliance verification module 4 is coupled to the energy integrated management platform 3, integrating an AI model for multimodal data fusion analysis. It acquires multimodal data during the renovation process and operation phase, and performs intelligent verification and long-term trend monitoring of equipment installation quality and data transmission reliability. This solves the problems of traditional manual quality verification being subjective, inefficient, and unable to achieve long-term trend monitoring. By fusing electrical parameters and visual images through multimodal AI analysis, it achieves objective, accurate, and automated quality assessment, predicts quality degradation trends, and enables predictive maintenance. It includes a data input unit 41, a preprocessing unit 42, an AI analysis unit 43, and an output unit 44, specifically:

[0068] Data input unit 41: used to acquire electrical parameter data (voltage, current, power, etc.) and image data reflecting the equipment installation status (installation process, line connection, component fixation, etc.) from distributed energy data acquisition unit 1, and generate a time-synchronized multimodal dataset;

[0069] Preprocessing unit 42: used to clean and normalize the multimodal dataset, and map the processed data to the corresponding device or region according to the preset device topology mapping table to generate partitioned data;

[0070] AI Analysis Unit 43: such as Figure 3 As shown, there are pre-set electrical anomaly detection models and visual anomaly detection models trained with historical fault data. These models are used to input the partitioned data into the models respectively to generate electrical anomaly scores and visual anomaly scores. The weight coefficients are determined based on the causes of historical faults, and the weighted fusion is used to generate a comprehensive quality score.

[0071] Output unit 44: Used to generate and output quality verification information based on the comprehensive quality score, including fault location maps in the form of heatmaps and multi-level visual verification reports; store data to form a long-term monitoring dataset, generate quality degradation trends through time series analysis, predict potential fault points and generate maintenance suggestions; support receiving user feedback and optimizing the dataset to update the AI ​​model.

[0072] Based on the above system transformation methods, the process will be implemented according to the workflow of "regional survey - phased transformation - data integration - intelligent verification - continuous optimization", such as... Figure 2 As shown, the specific steps include:

[0073] S1. Current Status Survey and Solution Design: Conduct a survey on the current status of the energy system in each functional area of ​​the target building complex, including the distribution of water supply, heating, and power supply networks, the types of existing metering devices, data transmission methods, and the functions and interfaces of the existing energy management system; compile data on energy consumption, energy costs, and frequency of failures in each area, identify energy waste points, safety hazards, and management pain points, and form a current status survey report.

[0074] Based on the survey results, the renovation units were divided according to functional areas. For each unit, a distributed renovation plan was independently developed, including energy data acquisition terminals, a multi-mode communication transmission network, and functional modules for an integrated energy management platform. Specifically, the models, installation locations, and quantities of smart meters (water meters, heat meters, and electricity meters) were clearly defined to ensure that the renovation would not affect normal operation within the unit; a multi-mode communication transmission network scheme was designed; and the functional modules, data interface standards, and AI quality verification parameters of the integrated energy management platform were designed in conjunction with the overall energy management needs of the building complex. For functional areas requiring uninterrupted operation (such as airport flight zones), a distributed renovation plan blueprint was designed for non-stop construction.

[0075] S2. Phased Implementation of the Transformation: In accordance with the aforementioned distributed transformation plan, the transformation will be carried out in units of transformation, prioritizing areas with high energy consumption and prominent problems. This will be done sequentially by installing energy data acquisition terminals, deploying communication networks, and debugging data fusion terminals. Old metering devices will be removed and smart meters and sensor lights will be installed at the designed locations. Indoor and outdoor transmission pipelines will be laid and network equipment configured. Local data acquisition and transmission tests will be conducted after each area's transformation is completed. Servers, switches, UPS, and other hardware will be deployed in the core computer room, and a three-in-one energy management platform will be built. An AI quality compliance verification module will be deployed, and historical fault data will be imported to train the AI ​​model.

[0076] S3. Data Integration and Intelligent Verification: Connect the data collected by each renovation unit to the energy integrated management platform, complete the data interface docking of the existing energy system, and realize the standardized integration of multi-source data; conduct system joint debugging and testing to verify the accuracy of data collection, transmission stability, and platform functional integrity; use the AI ​​quality compliance verification module to intelligently verify the installation quality and data transmission reliability of the renovated system, locate and rectify abnormal points (including data transmission interruption, excessive metering error, and installation process defects).

[0077] S4. Intelligent Operation and Maintenance and Continuous Optimization: The energy system of the building complex is centrally monitored and managed through the energy integrated management platform 3, including energy consumption trend analysis, fault alarms, prepaid billing, and work order dispatch; the AI ​​quality compliance verification module 4 is used to continuously monitor the system operation status, regularly generate quality verification reports and maintenance suggestions, and optimize equipment operating parameters; the energy consumption benchmark value is updated based on long-term operating data, the energy plan is adjusted, and the data acquisition terminal and platform function modules are expanded according to the needs of newly added energy-consuming equipment; the entire transformation process follows relevant national and industry technical standards, and the construction requirements for building complexes that need continuous operation are implemented without interrupting operation.

[0078] For building complexes requiring continuous operation (such as airports), strict adherence to non-stop construction requirements is essential: a coordination meeting system must be established, construction organization and management plans and emergency response plans must be developed, dedicated safety officers and fire-fighting equipment must be provided, and construction must be enclosed with fencing to avoid damage to existing pipelines and facilities. The entire renovation process must comply with national and industry standards such as the "Requirements for Content and Depth of Construction Drawing Design Documents for Civil Airport Engineering" (MH 5022-2005), the "General Specification for Building Energy Conservation and Renewable Energy Utilization" (GB 55015-2021), and the "Information Security Technology—Basic Requirements for Network Security Level Protection" (GB / T 22239-2019).

[0079] Example: Taking an airport (a typical case of a multi-functional building complex) as an example, the following explanation is provided:

[0080] (I) System Deployment

[0081] 1. Deployment of Distributed Energy Data Acquisition Unit 1

[0082] Water supply data acquisition subunit 11: A total of 1966 remote-reading smart water meters are installed in the South Zone (Buildings A1-A24), North Zone (Buildings B7-B13), East Zone (Buildings B3-B6), and Terminal Zone (Terminals T1-T3). The room-level meters use DN20 gauge, while the main building pipes use DN50-DN300 gauge, supporting valve control and remote communication. Each water meter communicates with the data fusion terminal in its respective functional area, sending the collected data to the data fusion terminal.

[0083] Heating Data Acquisition Subunit 12: 130 sets of remote-reading smart heat meters are installed at the No. 1 Heating Center, No. 2 Heating Center, South District Heating Center, and the main heating pipes of each building. These meters are equipped with pressure and temperature sensors, with specifications ranging from DN25 to DN350, to meet the requirements of the on-site installation environment. Each heat meter and sensor communicates with the data fusion terminal in its respective functional area, transmitting the collected flow, temperature, and pressure data to the data fusion terminal.

[0084] Power Supply Data Acquisition Subunit 13: 200 new power meters (including 56 prepaid meters and 132 multi-functional energy meters) will be added. 48 multi-functional energy meters will be installed in the 10kV / 35kV outgoing line cabinets of the South Area 35kV substation, 50 prepaid meters will be installed in the shops of Terminal 3, and the remaining meters will be installed in the main distribution cabinets / boxes of each area. Each meter will communicate with the data fusion terminal of its respective functional area, sending voltage, current, power, and energy consumption data to the fusion terminal.

[0085] Auxiliary data collection subunit 14: Replace 1,573 LED lights with integrated human body and illuminance sensing functions in areas such as the regulatory office building, terminal corridor, and office area corridors to achieve intelligent control and data collection of lighting energy consumption. Each light fixture communicates with the data fusion terminal of its functional area to send lighting energy consumption data to the fusion terminal.

[0086] 2. Deployment of Multi-mode Communication Transmission Network

[0087] Data fusion terminal: Data fusion terminals are configured in each functional area (south area, north area, east area, terminal area, etc.), connected to a 220V power supply nearby, with each power supply circuit connecting no more than 12 instruments, and integrating a 4G wireless transmission module.

[0088] In-building transmission: The acquisition terminal and the data fusion terminal are connected by a wired signal cable, which is laid openly in JDG conduit or used in the ceiling or low-voltage cable tray, and connected to the data fusion terminal in each functional area. As a preferred solution, this embodiment uses a wired connection to ensure transmission reliability.

[0089] Outdoor transmission: Direct burial is used in areas such as the South Zone, North Zone, and East Zone, with a burial depth of 1 meter. When crossing the runway or hardened pavement, SC pipes are cut through grooves and laid, and then restored with quick-drying cement.

[0090] Backbone network: The 35kV central station aggregation switch is connected to the core switch of Terminal 3 via optical fiber. IoT data is accessed to the airport equipment network via digital leased line, and remote access is achieved through the airport VPN.

[0091] 3. Deployment of the Integrated Energy Management Platform

[0092] Hardware deployment: Deploy 2 energy management application servers, 2 data management servers, 2 interface servers, 2 aggregation switches and 1 UPS in the 35kV central station weak current equipment room; install dual-link operating consoles, 2 management workstations and 1 printer in the monitoring center, and connect to the existing large screen; set up 2 management workstations and 1 printer in the power department office building.

[0093] Software Platform: This platform comprises a data middle platform (supporting multi-source data integration and compatible with ModBus, TCP, and MQTT protocols), a business middle platform (including modules for energy consumption analysis, prepaid management, and operations and maintenance management), and a technology middle platform (containerized deployment, supporting Java and Python development languages). The platform integrates core functional modules such as data acquisition and analysis, alarm management, energy planning, energy consumption benchmarking, cost accounting, prepaid management, operations and maintenance management, comprehensive monitoring, report generation, and carbon emission management, supporting access from both PC and mobile devices.

[0094] 4. Deployment of AI Quality Compliance Verification Module 4

[0095] Data input: Voltage and current data of smart meters are collected through sensor networks, and images of meter installation process and wiring connections are captured by image acquisition equipment to generate time-synchronized multimodal datasets.

[0096] Preprocessing: The dataset is cleaned and normalized, and then divided into logical partitions such as 35kV substation, terminal area, and living area according to the airport power distribution system topology mapping table.

[0097] AI analysis: The system includes a pre-set electrical anomaly detection model (using a neural network algorithm) and a visual anomaly detection model (using a CNN algorithm) trained on historical airport fault data. Weight coefficients are set based on the causes of historical faults, and the models are fused to generate a comprehensive quality score.

[0098] Output: Generates a fault location map in heatmap format; outputs a multi-level visual verification report including installation quality and data reliability; stores data to form a long-term monitoring dataset; and generates quality degradation trend analysis quarterly. The model is updated every six months to incorporate the latest operational data and continuously optimize detection accuracy.

[0099] (II) Implementation Steps of the Modification Method

[0100] S1. Current Situation Survey and Solution Design

[0101] A survey of the airport's water, heating, and power supply systems revealed issues such as manual meter reading, outdated data, and independent systems. The total energy cost for 2023 was estimated at approximately 45 million yuan. A regional renovation plan was developed, dividing the airport into renovation units such as the terminal area, south area, north area, east area, and flight area. Renovations in the flight area and terminal area avoided peak flight times, employing a non-stop construction approach. The plan also included the design of smart meter selection, communication paths, platform functional modules, and AI verification parameters.

[0102] S2. Phased renovation implementation

[0103] Priority will be given to upgrading the energy-intensive T3 terminal and the South Zone building complex, installing smart meters and data fusion terminals, and laying communication pipelines; then the North Zone, East Zone, and Flight Area will be upgraded, and an integrated energy management platform will be built simultaneously, deploying an AI quality compliance verification module and importing historical fault data to train the AI ​​model. The installation process complies with technical standards such as the "Low-voltage Power Distribution Design Code" (GB 50054-2011).

[0104] S3, Data Integration and Intelligent Verification

[0105] Data from various regions was integrated into the platform, connecting with existing energy management and power monitoring systems. An AI module detected three wiring defects and two water meter data transmission anomalies, which were subsequently rectified. The anomalies included data transmission interruptions, excessive metering errors, and installation defects.

[0106] S4, Intelligent Operation and Maintenance and Continuous Optimization

[0107] After the system is operational, it enables real-time monitoring, fault alarms, and prepaid billing through the platform. The AI ​​module updates its model every six months, optimizing heating and lighting operating parameters based on energy consumption data, and is expected to reduce energy consumption and costs by more than 10% annually. The entire renovation process complies with the "Requirements for Content and Depth of Construction Drawing Design Documents for Civil Airport Engineering" (MH 5022-2005), the "General Specification for Building Energy Conservation and Renewable Energy Utilization" (GB 55015-2021), and the "Information Security Technology—Basic Requirements for Network Security Level Protection" (GB / T 22239-2019).

[0108] (III) Compliance Assurance

[0109] During construction, strict adherence to the requirement of uninterrupted operation was enforced. A dedicated safety officer was assigned, a hot work permit system was established, and construction was conducted in a closed enclosure to avoid impacting flight operations. All equipment selection and installation processes complied with the fourth revision of the "Technical Standards for Civil Airport Flight Areas" (MH 5001-2021), the "General Specifications for Building Electrical and Intelligent Systems" (GB 55024-2022), and the "Heat Meter" (GB / T 32224-2020), among other national and industry standards. System safety protection met the requirements of Level II Information Security Protection.

[0110] The existing multi-functional building complex distributed energy management system and its retrofit method disclosed in this invention are applicable not only to airports, but also to the construction or retrofitting of energy systems in large industrial parks, hospitals, universities, commercial complexes, and other multi-functional building complexes, demonstrating good versatility and promotional value. Through distributed deployment, centralized management and control, and intelligent verification, energy management efficiency can be significantly improved, energy consumption costs reduced, and normal operation ensured during the retrofitting process.

[0111] The described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

Claims

1. An existing multi-functional building complex distributed energy management system, characterized in that: This includes distributed energy data acquisition units, multi-mode communication transmission networks, an integrated energy management platform, and an AI quality compliance verification module; The distributed energy data acquisition unit is deployed in a distributed manner according to the functional zoning and energy type of the multi-functional building complex. It is used to collect energy data of each area and energy type, including water supply data acquisition subunit, heating data acquisition subunit, power supply data acquisition subunit and auxiliary acquisition subunit. The multi-mode communication transmission network is a distributed communication network that combines wired and wireless technologies, enabling the local collection and remote transmission of energy data collected by the distributed energy data acquisition unit. The energy integrated management platform is connected to a multi-mode communication transmission network to receive and integrate the energy data, thereby realizing centralized control and intelligent application of multi-energy data. The energy integrated management platform includes a data platform, a business platform, and a technology platform. The data platform is used to standardize multi-source heterogeneous energy data, the business platform is used to provide shareable energy management business components, and the technology platform is used to provide a system development and deployment environment. The AI ​​quality compliance verification module is coupled with the energy integrated management platform to acquire multimodal data during the transformation process and operation phase. Based on the AI ​​model of multimodal data fusion analysis, it performs intelligent verification and long-term trend monitoring of equipment installation quality and data transmission reliability.

2. The existing multi-functional building complex distributed energy management system according to claim 1, characterized in that, The water supply data acquisition subunit includes remote-reading smart water meters with valve control function deployed in the centralized water supply main pipelines of individual buildings in each functional area and at the user end; the remote-reading smart water meters are communicatively connected to the data fusion terminal in their respective functional areas to send the collected water supply data to the data fusion terminal; the data fusion terminal uploads the collected water supply data to the energy integrated management platform through a multi-mode communication transmission network.

3. The existing multi-functional building complex distributed energy management system according to claim 1, characterized in that, The heating data acquisition subunit includes remote-reading smart heat meters and supply and return water pipe pressure sensors deployed at each heat energy center and building heating main. The remote-reading smart heat meters are equipped with temperature sensors for collecting heating data. The remote-reading smart heat meters and supply and return water pipe pressure sensors are communicatively connected to the data fusion terminal in their respective functional areas to send the collected heating data to the data fusion terminal. The data fusion terminal uploads the heating data to the energy integrated management platform through a multi-mode communication transmission network.

4. The existing multi-functional building complex distributed energy management system according to claim 1, characterized in that, The power supply data acquisition subunit includes prepaid electricity meters and multi-functional electricity meters deployed in substations and distribution cabinets / boxes in various regions. The high-voltage circuit is equipped with a 0.2-level accuracy current transformer and a multi-functional electricity meter. The low-voltage circuit is equipped with a prepaid electricity meter or an ordinary multi-functional electricity meter according to the energy consumption scenario to collect power supply data. The prepaid electricity meter and the multi-functional electricity meter are communicatively connected to the data fusion terminal of their respective functional areas to send the collected power supply data to the data fusion terminal; the data fusion terminal uploads the power supply data to the energy integrated management platform through a multi-mode communication transmission network.

5. The existing multi-functional building complex distributed energy management system according to claim 1, characterized in that, The auxiliary data acquisition subunit includes LED lights with integrated sensing functions deployed in public areas for intelligent control and data acquisition of lighting energy consumption. The subunit also has a reserved standardized acquisition interface for connecting other energy-consuming or detection devices. The LED lights and other devices connected via the standardized acquisition interface are communicatively connected to the data fusion terminal in their respective functional areas to send the acquired auxiliary data to the data fusion terminal. The data fusion terminal then uploads the auxiliary data to the integrated energy management platform via a multi-mode communication transmission network.

6. The existing multi-functional building complex distributed energy management system according to claim 1, characterized in that... ； The multi-mode communication transmission network includes a data fusion terminal, with one data fusion terminal configured in each functional area. The data fusion terminal is connected to a power source nearby and is used to collect data from various acquisition terminals within the area. The acquisition terminal and the data fusion terminal in the functional area communicate with each other via wired or wireless means. The multi-mode communication transmission network uses the following methods for indoor transmission: signal and power lines of the acquisition terminal are laid openly in protective conduits or connected to the data fusion terminal in the building's power distribution room via low-voltage cable trays; outdoor transmission uses direct burial with a depth of 1 meter and backfilling with plain soil, and trenching and conduit installation is carried out where the network crosses hardened pavement and then restored; backbone transmission connects to the aggregation switches in each area via newly laid optical cables and then connects to the core switch; IoT data is accessed through digital leased lines via routers and IPS to the device network; and remote access is achieved through VPN and Internet lines.

7. The existing multi-functional building complex distributed energy management system according to claim 1, characterized in that, In the aforementioned integrated energy management platform: The data platform is connected to a multi-mode communication transmission network to receive energy data uploaded from various functional areas, acquire, store, calculate and process the data, support multiple IoT protocols such as ModBus, TCP and MQTT, and provide the standardized data to the business platform. The business platform calls upon the standardized data provided by the data platform to provide shared components for energy planning, energy consumption benchmarking, cost management, prepaid management, and operation and maintenance management in a service-oriented manner, supporting the implementation of upper-layer functional modules; The technology platform provides a system development and deployment environment for the data platform and business platform. It is based on a front-end and back-end separation model, supports multi-language development such as Java, C++, and Python, and uses Docker image containerization for deployment. The energy management platform integrates core functional modules such as data acquisition and analysis, alarm management, energy planning, energy consumption benchmarking, energy auditing, cost accounting, prepaid management, operation and maintenance management, comprehensive monitoring, report generation, and carbon emission management. These functional modules call the shared components provided by the business platform to realize corresponding business functions and support access from both PC and mobile terminals.

8. The existing multi-functional building complex distributed energy management system according to claim 1, characterized in that, The AI ​​quality compliance verification module includes a data input unit, a preprocessing unit, an AI analysis unit, and an output unit; The data input unit acquires electrical parameter data from the distributed acquisition unit and image data reflecting the equipment installation status, and generates a time-synchronized multimodal dataset. The preprocessing unit cleans and normalizes the multimodal dataset, and maps the processed data to the corresponding devices or regions through a preset device topology mapping table to generate partitioned data. The AI ​​analysis unit is pre-set with an electrical anomaly detection model and a visual anomaly detection model trained with historical fault data. The partition data is input into the electrical anomaly detection model and the visual anomaly detection model respectively to generate electrical anomaly scores and visual anomaly scores respectively. The scores are then fused according to preset weight coefficients to generate a comprehensive quality score. The output unit generates and outputs quality verification information based on the comprehensive quality score.

9. A method for retrofitting an existing multi-functional building complex distributed energy management system, implemented based on the existing multi-functional building complex distributed energy management system as described in any one of claims 1-8, characterized in that, Includes the following steps: S1. Current Status Survey and Scheme Design: Conduct a survey on the current status of the energy system in each functional area of ​​the target building complex, and based on the survey results, divide the area into renovation units according to the functional areas. Design a distributed renovation scheme for each renovation unit, including functional modules such as energy data acquisition terminals, communication networks, and energy integrated management platforms. S2. Implement the transformation in stages: According to the distributed transformation plan, the energy data acquisition terminal will be installed, the communication network will be deployed, and the data fusion terminal will be debugged in sequence, taking the transformation unit as the unit, to complete the transformation of each transformation unit. S3. Data integration and system commissioning: The data collected by each renovation unit is connected to the energy management platform, and the AI ​​quality compliance verification module is used to intelligently verify the installation quality and data transmission reliability of the renovated system. Based on the verification results, abnormal points are rectified. S4. Intelligent Operation and Maintenance and Continuous Optimization: The energy system of the building complex is centrally monitored and managed through the energy integrated management platform, and the system operation status is continuously monitored using the AI ​​quality compliance verification module. Maintenance suggestions or optimized operating parameters are generated based on the monitoring data.

10. The method for retrofitting an existing multi-functional building complex distributed energy management system according to claim 9, characterized in that, In step S3, the abnormal points include points where data transmission is interrupted, measurement errors exceed the standard, or installation process defects occur.

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