A building energy intelligent central control system

Abstract

The application discloses a kind of building energy intelligent central control system, including server and central control unit, the signal port of the central control unit is connected with environment perception module, AI self-adapting control module, prediction analysis module, intelligent operation and maintenance module and unified transmission module, each module cooperates and realizes building energy global monitoring, intelligent control and operation and maintenance management;The application has the advantages that: through multidimensional perception and AI self-adapting control, global collaborative energy saving is realized, relying on prediction analysis and intelligent operation and maintenance, passive treatment is changed into active prevention and control to reduce cost and prolong life, edge cloud cooperation and wired, wireless hybrid networking compatible new and old building reconstruction are used, and the demand of low-carbon, efficient and intelligent management of building is met.

Description

Technical Field

[0001] This invention relates to the field of building intelligent energy management technology, specifically to a building intelligent central control system. Background Technology

[0002] Building energy management is a core aspect of energy conservation and consumption reduction in public buildings, commercial complexes, and office buildings. With the upgrading of building intelligence, energy control systems are gradually developing towards automation and integration.

[0003] Patent CN106066625A discloses an intelligent central control system for building energy, including an air conditioning control unit, a heating control unit, a lighting control unit, an appliance control unit, and an energy management system. The air conditioning control unit, heating control unit, lighting control unit, and appliance control unit respectively send energy consumption data for air conditioning, heating, lighting, and appliances to the energy management system. The energy management system archives consumed energy and allocates and schedules unused energy. This invention classifies and monitors energy consumption within the building and monitors and handles abnormal energy consumption situations.

[0004] Existing technologies still have some shortcomings. They can only classify, archive, and perform simple scheduling of energy data from various subsystems, without incorporating multi-dimensional environmental parameters such as temperature, humidity, CO2, light intensity, and occupancy density for adaptive control. They still operate in traditional ways with fixed parameters and timed start-stop, resulting in significant energy waste. Furthermore, subsystems such as air conditioning, lighting, power supply and distribution, and fresh air systems are independent, with data that cannot be shared, creating serious data silos and hindering global equipment coordination and scheduling, thus failing to fully unleash the building's overall energy-saving potential. They can only perform post-event energy consumption statistics and passive alarms, lacking the ability to accurately predict energy consumption and proactively identify potential equipment failures. Fault handling and equipment maintenance rely on manual inspections and post-event repairs, leading to low operational efficiency, high labor costs, and potential unplanned equipment downtime, shortening the lifespan of electromechanical equipment. The single communication architecture and centralized control mode cannot adapt to the differentiated deployment needs of new and renovated buildings, and they lack functions such as carbon emission control and refined energy management, failing to meet the development requirements of low-carbon, efficient, and intelligent building operation. Therefore, we propose an intelligent central control system for building energy. Summary of the Invention

[0005] The technical problem that this invention aims to solve is that existing building energy control systems suffer from extensive control, data silos, lagging management and control, and inefficient operation and maintenance, resulting in high energy consumption, frequent equipment failures, and high management costs.

[0006] The present invention solves the above-mentioned technical problems by adopting the following technical solution: It provides a building energy intelligent central control system, including a server and a central control unit. The signal port of the central control unit is connected to an environmental perception module, an AI adaptive control module, a predictive analysis module, an intelligent operation and maintenance module, and a unified transmission module. The modules work together to realize the full-domain monitoring, intelligent control, and operation and maintenance management of building energy. The server is bidirectionally connected to the central control unit through an electrical signal and is used to store basic building data, historical energy consumption data, equipment operating parameters, and operation and maintenance records. The central control unit, as the core hub, receives data transmitted from each module and performs fusion analysis to generate control commands, early warning signals, and operation and maintenance strategies. The environmental sensing module is used to collect building indoor environmental parameters, energy consumption data, and equipment operating status data. The AI ​​adaptive control module executes adaptive adjustments to equipment such as air conditioning, fresh air systems, and lighting based on instructions from the central control unit; The predictive analysis module is used for building energy consumption prediction and equipment failure hazard diagnosis. The intelligent operation and maintenance module is used for equipment health management, operation and maintenance work order generation, and closed-loop control of the maintenance process. The unified transmission module provides a multi-protocol compatible, stable and reliable data transmission channel between each module and the central control unit and server.

[0007] Preferably, the environmental sensing module includes a temperature and humidity sensor, a CO2 sensor, a light sensor, a personnel presence detection unit, a smart meter, and an equipment status acquisition unit. Each acquisition terminal is electrically connected to the central control unit to transmit environmental and energy consumption monitoring data in real time.

[0008] Preferably, the AI ​​adaptive control module includes a frequency converter, an intelligent relay, an electric valve, and a terminal actuator, which can dynamically adjust the operating status of air conditioning, fresh air, and lighting equipment according to environmental parameters, personnel density, and energy-saving strategies to achieve on-demand energy supply.

[0009] Preferably, the predictive analysis module incorporates an LSTM time-series prediction model and an anomaly feature recognition algorithm, integrating historical energy consumption, meteorological data, and building operation and maintenance patterns to achieve accurate short-term energy consumption prediction and early prediction of equipment operation failures.

[0010] Preferably, the unified transmission module includes a BACnet, Modbus, OPC UA multi-protocol conversion unit, an Ethernet interface, a LoRa, NB-IoT wireless communication unit, and a local cache unit, supporting wired and wireless hybrid networking and compatible with equipment access in newly built and existing buildings.

[0011] Preferably, the unified transmission module supports local autonomy during network outages, and the locally cached data is automatically synchronized to the server after the network is restored, ensuring data continuity and control reliability.

[0012] Preferably, the intelligent operation and maintenance module includes a health diagnosis unit, an automatic work order generation unit, an operation and maintenance terminal push unit, and an equipment file management unit, which can automatically determine equipment maintenance needs and track the entire operation and maintenance process.

[0013] Preferably, the AI ​​adaptive control module supports scenario-based mode switching, including office mode, meeting mode, off-get off work mode, and holiday mode, and can trigger corresponding device linkage control with one click.

[0014] Preferably, the central control unit adopts an industrial-grade edge computing gateway, which integrates real-time data from the environmental perception module and analysis results from the predictive analysis module to achieve coordinated operation of local real-time control and cloud-based global optimization.

[0015] Preferably, the predictive analysis module and the intelligent operation and maintenance module are linked through a central control unit, and the fault prediction result directly triggers the operation and maintenance work order, forming a closed-loop management of "prediction, early warning and operation and maintenance".

[0016] Compared with the prior art, the present invention provides an intelligent central control system for building energy, which has the following beneficial effects: 1. This intelligent central control system for building energy uses an environmental sensing module to collect real-time data on temperature, humidity, CO2, light intensity, occupancy density, and energy-consuming equipment status from multiple dimensions. Combined with an AI adaptive control module, it dynamically adjusts the operating parameters of air conditioning, ventilation, lighting, and other equipment based on actual indoor needs. Simultaneously, relying on a central control unit and a unified transmission module, it breaks down data barriers between various energy subsystems, enabling global equipment collaborative scheduling. This upgrades from single-point, extensive control to precise, on-demand energy supply across the entire system. While ensuring indoor environmental comfort, it significantly reduces overall building energy consumption, fundamentally solving the core problems of outdated traditional system control methods, severe energy waste, and data silos hindering collaboration. 2. This building energy intelligent central control system is equipped with a predictive analysis module to achieve accurate prediction of building energy consumption and intelligent identification of potential equipment operation hazards. It transforms the traditional passive "fault alarm and post-event maintenance" into an active "pre-judgment and pre-event prevention" system. The intelligent operation and maintenance module completes equipment health diagnosis, automatic generation of operation and maintenance work orders and closed-loop management of the whole process, which greatly reduces the workload of manual inspection and operation and maintenance costs, effectively reduces the probability of sudden equipment failure and reduces unplanned downtime, while optimizing equipment operating conditions and significantly extending the overall service life of electromechanical equipment. 3. This intelligent central control system for building energy adopts a collaborative architecture of edge computing and cloud optimization, as well as a hybrid wired and wireless networking method. It has strong compatibility and scalability, and can be adapted to the integrated deployment of new buildings. It can also quickly connect to the existing equipment in existing buildings to complete energy-saving renovations. The system can flexibly expand functional interfaces, perfectly meeting the development needs of building carbon emission control, refined energy consumption management, and intelligent operation and maintenance upgrades, and providing comprehensive support for the low-carbon, efficient, and intelligent operation of building energy. Attached Figure Description

[0017] Figure 1 This is a diagram showing the module relationships of the present invention; Figure 2 This is a complete flowchart of the system workflow of the present invention.

[0018] In the diagram: 1. Server; 2. Central control unit; 3. Environmental perception module; 4. AI adaptive control module; 5. Predictive analysis module; 6. Intelligent operation and maintenance module; 7. Unified transmission module. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Please see Figure 1-2 A building energy intelligent central control system includes a server 1 and a central control unit 2. The signal port of the central control unit 2 is connected to an environmental perception module 3, an AI adaptive control module 4, a predictive analysis module 5, an intelligent operation and maintenance module 6, and a unified transmission module 7. The modules work together to realize the full-domain monitoring, intelligent control, and operation and maintenance management of building energy. The server 1 is bidirectionally connected to the central control unit 2 via electrical signals and is used to store basic building data, historical energy consumption data, equipment operating parameters, and operation and maintenance records. The central control unit 2 serves as the core hub, receiving data transmitted from each module and performing fusion analysis to generate control commands, early warning signals, and operation and maintenance strategies. Environmental sensing module 3 is used to collect building indoor environmental parameters, energy consumption data, and equipment operating status data; The AI ​​adaptive control module 4 executes adaptive adjustments to air conditioning, fresh air, lighting, and other equipment based on instructions from the central control unit 2. Predictive analysis module 5 is used for building energy consumption prediction and equipment failure hazard diagnosis; The intelligent operation and maintenance module 6 is used for equipment health management, operation and maintenance work order generation, and closed-loop control of the maintenance process; The unified transmission module 7 provides a multi-protocol compatible, stable and reliable data transmission channel between each module and the central control unit 2 and the server 1.

[0021] In this embodiment, the environmental sensing module 3 includes a temperature and humidity sensor, a CO2 sensor, a light sensor, a personnel presence detection unit, a smart meter, and an equipment status acquisition unit. Each acquisition terminal is electrically connected to the central control unit 2 to transmit environmental and energy consumption monitoring data in real time.

[0022] Specifically, the temperature and humidity sensor is used to collect indoor temperature and humidity data, the CO2 sensor is used to monitor indoor CO2 concentration, the light sensor is used to detect indoor light intensity, the personnel presence detection unit is used to identify the density of people in the area, the smart meter is used to collect data on electricity, water and gas consumption, and the equipment status acquisition unit is used to collect operating parameters of equipment such as air conditioning, fresh air and lighting. All kinds of data are uploaded to the central control unit 2 in real time.

[0023] In this embodiment, the AI ​​adaptive control module 4 includes a frequency converter, an intelligent relay, an electric valve, and a terminal actuator. It can dynamically adjust the operating status of air conditioning, fresh air, and lighting equipment according to environmental parameters, personnel density, and energy-saving strategies to achieve on-demand energy supply.

[0024] Specifically, the frequency converter is used to adjust the operating frequency of the equipment, the intelligent relay is used to control the on / off of the power supply and lighting circuits, the electric valve is used to adjust the flow of air and water, and the terminal execution unit receives instructions to execute adjustment actions and dynamically adjusts the equipment status based on real-time data to achieve on-demand energy supply.

[0025] In this embodiment, the prediction and analysis module 5 incorporates an LSTM time series prediction model and an anomaly feature recognition algorithm, and integrates historical energy consumption, meteorological data, and building operation and maintenance patterns to achieve accurate short-term energy consumption prediction and early prediction of equipment operation failures.

[0026] Specifically, the LSTM time series prediction model outputs short-term energy consumption prediction results based on multi-source data computation, and the abnormal feature recognition algorithm performs feature matching on equipment operating parameters to identify potential equipment faults and complete energy consumption prediction and fault prediction.

[0027] In this embodiment, the unified transmission module 7 includes a BACnet, Modbus, OPC UA multi-protocol conversion unit, an Ethernet interface, a LoRa, an NB-IoT wireless communication unit, and a local cache unit, supporting wired and wireless hybrid networking and compatible with equipment access in newly built and existing buildings.

[0028] Specifically, the multi-protocol conversion unit realizes the parsing and conversion of BACnet, Modbus, and OPC UA protocols, the Ethernet interface provides a wired transmission channel, the LoRa and NB-IoT wireless communication units realize wireless networking, the local cache unit is used to temporarily store data, supports wired and wireless hybrid networking, and is compatible with the access of new and old building equipment.

[0029] In this embodiment, the unified transmission module 7 supports local autonomy when the network is down. After the network is restored, the local cached data is automatically synchronized to the server 1, ensuring data continuity and control reliability.

[0030] Specifically, when the network is interrupted, the unified transmission module 7 enters the local autonomous operation mode. After the network is restored, the data temporarily stored in the local cache unit is automatically synchronized to the server 1 to ensure data continuity and control reliability.

[0031] In this embodiment, the intelligent operation and maintenance module 6 includes a health diagnosis unit, an automatic work order generation unit, an operation and maintenance terminal push unit, and an equipment file management unit, which can automatically determine equipment maintenance needs and track the entire operation and maintenance process.

[0032] Specifically, the health diagnosis unit is used to determine equipment maintenance needs, the work order automatic generation unit is used to automatically create maintenance work orders, the maintenance terminal push unit pushes the work orders to the maintenance personnel's terminals, and the equipment file management unit is used to record maintenance information and track the entire maintenance process.

[0033] In this embodiment, the AI ​​adaptive control module 4 supports scene-based mode switching, including office mode, meeting mode, off-get off work mode, and holiday mode, and can trigger corresponding device linkage control with one click.

[0034] Specifically, the AI ​​adaptive control module 4 has preset office, meeting, after-get off work, and holiday modes. Based on the scenario, it can trigger the linkage adjustment of equipment such as air conditioning, fresh air, and lighting with one click to adapt to different time periods and energy-saving needs.

[0035] In this embodiment, the central control unit 2 adopts an industrial-grade edge computing gateway, which integrates real-time data from the environmental perception module 3 with the analysis results from the predictive analysis module 5 to achieve coordinated operation of local real-time control and cloud-based global optimization.

[0036] Specifically, the central control unit 2 adopts an industrial-grade edge computing gateway, which integrates real-time data from the environmental perception module 3 with the analysis results from the predictive analysis module 5. The local end realizes real-time control of the equipment, while the cloud completes global strategy optimization, achieving collaborative operation between the local and cloud.

[0037] In this embodiment, the predictive analysis module 5 and the intelligent operation and maintenance module 6 are linked through the central control unit 2. The fault prediction result directly triggers the operation and maintenance work order, forming a closed-loop management of "prediction, early warning and operation and maintenance".

[0038] Specifically, the predictive analysis module 5 uploads the fault prediction results to the central control unit 2. The central control unit 2 issues instructions to control the intelligent operation and maintenance module 6 to generate operation and maintenance work orders, forming a closed-loop management of the entire process of prediction, early warning and operation and maintenance.

[0039] It should be noted that the environmental sensing module 3 collects real-time data on indoor temperature and humidity, CO2 concentration, light intensity, personnel density, energy consumption of various items, and equipment operating status. This data is then transmitted to the central control unit 2 via Ethernet, LoRa, and NB-IoT links through the unified transmission module 7. The central control unit 2 compares the preset comfort threshold with the energy-saving threshold to determine the indoor environment and equipment operating status. Intelligent control: The central control unit 2 sends adjustment instructions to the AI ​​adaptive control module 4 based on environmental parameters, personnel density and scene requirements. The AI ​​adaptive control module 4 dynamically adjusts the operating parameters of equipment such as air conditioning, fresh air and lighting according to office, meeting, after-get off work and holiday modes to achieve on-demand energy supply. Data processing: The central control unit 2 integrates real-time data from the environmental perception module 3 with energy consumption prediction and fault diagnosis results from the predictive analysis module 5, and comprehensively analyzes the overall energy consumption trend and equipment health status. If abnormal energy consumption, excessive parameters, or equipment hazards are found, early warning signals, control instructions, and operation and maintenance strategies are generated. Operation and maintenance linkage: The intelligent operation and maintenance module 6 receives the fault prediction and operation and maintenance requirements of the central control unit 2, automatically generates operation and maintenance work orders and pushes them to the operation and maintenance personnel's terminals, and updates the equipment health records after the maintenance and repair are completed; Communication assurance: Under normal operating conditions, data is transmitted via Ethernet and wireless links; when the network is interrupted, the unified transmission module 7 starts local autonomy and the local cache unit temporarily stores the data. After the network is restored, the cached data is automatically synchronized to the server 1 to ensure that the data is not lost and the control is not interrupted.

[0040] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0041] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A building energy intelligent central control system, comprising a server (1) and a central control unit (2), characterized in that: The signal port of the central control unit (2) is connected to the environmental perception module (3), the AI ​​adaptive control module (4), the predictive analysis module (5), the intelligent operation and maintenance module (6), and the unified transmission module (7). The modules work together to realize the full-domain monitoring, intelligent control and operation and maintenance management of building energy. The server (1) is bidirectionally connected to the central control unit (2) through electrical signals and is used to store building basic data, energy consumption history data, equipment operating parameters and operation and maintenance records. The central control unit (2) serves as the core hub, receiving data transmitted from each module and performing fusion analysis to generate control commands, early warning signals, and operation and maintenance strategies. The environmental sensing module (3) is used to collect building indoor environmental parameters, energy consumption data and equipment operating status data; The AI ​​adaptive control module (4) performs adaptive adjustment of air conditioning, fresh air, lighting and other equipment according to the instructions of the central control unit (2); The predictive analysis module (5) is used for building energy consumption prediction and equipment failure hazard diagnosis; The intelligent operation and maintenance module (6) is used for equipment health management, operation and maintenance work order generation and closed-loop control of maintenance process; The unified transmission module (7) provides a multi-protocol compatible, stable and reliable data transmission channel between each module and the central control unit (2) and the server (1).

2. The intelligent central control system for building energy management according to claim 1, characterized in that: The environmental sensing module (3) includes a temperature and humidity sensor, a CO2 sensor, a light sensor, a personnel presence detection unit, a smart meter and an equipment status acquisition unit. Each acquisition terminal is electrically connected to the central control unit (2) to transmit environmental and energy consumption monitoring data in real time.

3. The intelligent central control system for building energy management according to claim 1, characterized in that: The AI ​​adaptive control module (4) includes a frequency converter, intelligent relay, electric valve and end effector unit, which can dynamically adjust the operating status of air conditioning, fresh air and lighting equipment according to environmental parameters, personnel density and energy-saving strategies to achieve on-demand energy supply.

4. The intelligent central control system for building energy management according to claim 1, characterized in that: The prediction and analysis module (5) incorporates an LSTM time series prediction model and anomaly feature recognition algorithm, and integrates historical energy consumption, meteorological data, and building operation and rest patterns to achieve accurate short-term energy consumption prediction and early prediction of equipment operation failures.

5. The intelligent central control system for building energy management according to claim 1, characterized in that: The unified transmission module (7) includes BACnet, Modbus, OPC UA multi-protocol conversion unit, Ethernet interface, LoRa, NB-IoT wireless communication unit and local cache unit, supports wired and wireless hybrid networking, and is compatible with equipment access in newly built and existing buildings.

6. The intelligent central control system for building energy management according to claim 5, characterized in that: The unified transmission module (7) supports local autonomy when the network is down. After the network is restored, the local cached data is automatically synchronized to the server (1), ensuring data continuity and control reliability.

7. The intelligent central control system for building energy management according to claim 1, characterized in that: The intelligent operation and maintenance module (6) includes a health diagnosis unit, an automatic work order generation unit, an operation and maintenance terminal push unit, and an equipment file management unit. It can automatically determine equipment maintenance needs and track the entire operation and maintenance process.

8. The intelligent central control system for building energy management according to claim 1, characterized in that: The AI ​​adaptive control module (4) supports scenario-based mode switching, including office mode, meeting mode, off-duty mode, and holiday mode, and can trigger the corresponding device linkage control with one click.

9. The intelligent central control system for building energy management according to claim 1, characterized in that: The central control unit (2) adopts an industrial-grade edge computing gateway, which integrates real-time data from the environmental perception module (3) with the analysis results from the predictive analysis module (5) to achieve coordinated operation of local real-time control and cloud-based global optimization.

10. A building energy intelligent central control system according to claim 1, characterized in that: The predictive analysis module (5) and the intelligent operation and maintenance module (6) are linked through the central control unit (2). The fault prediction result directly triggers the operation and maintenance work order, forming a closed-loop management of "prediction, early warning and operation and maintenance".

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