Differential building efficient interaction of sense module of analog modular intelligent connection regulation and control device and application

Abstract

The application discloses a differential building efficient interaction sensing and communication modular intelligent connection regulation and control device and application, and belongs to the technical field of building power regulation. The device contains a sensing unit, a communication unit, a computing unit and a cloud platform, which are connected through a unified bus. The sensing unit collects multi-dimensional information and guarantees data quality, the communication unit integrates multiple protocols to realize cross-protocol semantic intercommunication, the computing unit is structured to adapt to different needs of different buildings, and the cloud platform provides management and scheduling services. A hierarchical and domain building power grid interaction semantic modeling method is also proposed, three-layer sub-models and end-to-end semantic links are constructed, and efficient interaction between buildings and power grids is realized. The application solves the pain points such as heterogeneous intercommunication, adapts to multiple types of buildings, and provides support for the transformation of buildings into active energy units and the construction of new-type power systems.

Description

Technical Field

[0001] This invention relates to the field of building power control technology, and in particular to a modular intelligent control device and its application for efficient interaction in differentiated buildings. Background Technology

[0002] Buildings are not only the main carriers of energy consumption and carbon emissions, but also important terminals for achieving coordinated optimization of energy sources, grids, loads, and storage, as well as coordinated management of electricity and carbon emissions. To address issues such as the increasing proportion of distributed renewable energy integration, enhanced energy load volatility, and the continuously rising demand for flexible grid regulation, buildings are gradually transforming from passive energy users into active, interactive energy units with multi-functional attributes of generation, storage, and consumption. However, significant structural contradictions and technological bottlenecks still exist in the interaction between existing building terminal devices and the grid.

[0003] First, the diversity of building types presents challenges in adaptation. Different types of buildings, such as commercial, office, hotel, and industrial buildings, exhibit significant differences in energy system structure, load characteristics, comfort requirements, and control logic. Traditional building automation systems (BAS) and energy management systems (EMS) often employ a single control architecture and fixed logic, making it difficult to meet the differentiated control needs of various building types. This results in poor system versatility, high deployment costs, and limited control effectiveness.

[0004] Secondly, the heterogeneity of the perception and communication layers leads to inefficient data interaction. Multiple communication protocols exist within buildings, such as BACnet, Modbus, KNX, LoRa, and Zigbee, with closed data interfaces from manufacturers. This prevents efficient data exchange between different subsystems, creating "information silos." Simultaneously, existing semantic frameworks primarily focus on local building devices and location tags, lacking a unified extension and cross-domain mapping for power grid interaction semantics. This results in inconsistent expression, verification, and automatic compilation of data, constraints, and control strategies at the semantic layer.

[0005] Finally, the existing device structure and functions are overly coupled, making flexible expansion and rapid adaptation difficult. Existing control devices mostly employ closed hardware architectures and fixed functional units, lacking unified interface standards and decoupling designs between different modules. As building types and application scenarios change, system function expansion or upgrades often require complete device replacement, resulting in redundant construction and resource waste. Simultaneously, the communication, sensing, and computing modules within the device are interdependent, making independent maintenance and functional reconfiguration difficult, limiting flexible deployment and engineering versatility in building-grid interactions. At the semantic level, the lack of a unified ontology and cross-protocol alignment mechanisms, as well as a compilation and auditing link from semantics to optimization / control, further restricts the cross-scenario migration and rapid implementation of strategies. Summary of the Invention

[0006] The purpose of this invention is to provide a modular intelligent control device and application for efficient interaction in differentiated buildings, which solves the problems of existing building terminal control devices, such as difficulty in interoperability of heterogeneous systems, inflexible allocation of computing resources, insufficient adaptability and scalability, and low interaction efficiency. Furthermore, it lacks a unified ontology and cross-protocol alignment, as well as a compilation and auditing mechanism from semantics to optimization / control at the semantic layer.

[0007] To achieve the above objectives, this invention provides a modular intelligent control device for efficient interaction between differentiated buildings and communication systems, including a sensing unit, a communication unit, a computing unit, and a cloud platform supporting the device system. The four components are interconnected through a unified device bus to form the core execution device for interaction between the building and the power grid. The sensing unit is used to collect building interior environmental parameters, energy consumption status and equipment operation information; the sensing unit is equipped with multiple types of sensing modules, and each module is connected to the signal acquisition bus of the intelligent control device through a standardized interface; the sensing unit has built-in data synchronization and quality diagnosis functions, and has the functions of sensing acquisition, anomaly identification, data enhancement and data completion. The communication unit is located on the mainboard of the device and is used to realize secure data communication between building equipment and upper-level systems. The communication unit supports communication protocols including BACnet, Modbus, KNX, MQTT, and LoRa, and has a unified communication adaptation layer PAL. A communication semantic recognition mechanism PSRM is embedded on top of PAL. The communication unit automatically identifies the meaning of message fields according to the type of building equipment, realizes cross-protocol semantic interoperability, and has transmission optimization, data compression, dynamic encryption, and command issuance functions. The computing unit is the core of decision-making and execution for the intelligent control device, responsible for local data processing, operation strategy calculation and control command issuance; the computing unit loads different types of algorithm modules, including equipment control logic, energy consumption optimization strategy and status assessment algorithm; the computing unit has building identification, HVAC identification, target decomposition and feature extraction functions; The device system supports a cloud platform that provides configuration, monitoring, and management services for intelligent control devices, including device registration, operational status monitoring, parameter configuration, firmware upgrades, and log recording. The device system supports a cloud platform that enables centralized management of multiple intelligent control devices through cloud interfaces, supporting collaborative control and remote scheduling at the building cluster level. The device bus consists of three parts: a power channel, a data channel, and a control channel, which are used to realize power supply, data transmission, and control signal communication between modules. The power channel and the data channel adopt a dual-channel isolation design, thereby supporting hot-swapping and plug-and-play functions of algorithm modules.

[0008] Preferably, the environmental parameters, energy consumption status, and equipment operation information collected by the sensing unit are multi-dimensional information, including temperature and humidity, power, valve position, occupancy rate, and air quality.

[0009] Preferably, the PSRM of the communication unit consists of a semantic feature extraction module, a semantic matching module, and a semantic library self-learning module, which is used to perform semantic-level recognition and unified mapping of heterogeneous protocol data.

[0010] Preferably, the computing unit is based on a modular slot design, and algorithm modules can be added or removed according to the building's functional requirements, supporting hot-swappable expansion and remote firmware upgrades.

[0011] Preferably, the communication adaptation layer PAL embeds a building-grid interaction semantic modeling method. The building-grid interaction semantic modeling method adopts a hierarchical and domain-based modeling approach, including a building entity semantic sub-model, a building flexibility semantic sub-model, and a grid interaction semantic sub-model. The three sub-models are associated through predefined semantic relationships to form an end-to-end semantic link from the building physical entity to the grid interaction benefits, so that the grid interaction information can be uniformly understood and invoked by the intelligent control device. The building entity semantic sub-model is used to characterize the basic objects within a building and their relationships with the objects they serve. It includes four semantic classes: building equipment, areas, users, and control mechanisms. In terms of semantic relationships, it defines at least the following object attributes: located in the area `locatedIn`, serving users `servesUser`, and possessing control mechanisms `hasControl` or active in the area `actsOn`. Specifically: Located in area: Used to describe the relationship between building equipment and area; ServesUser: Used to describe the group of users of building equipment or area services; "hasControl / actsOn" describes the object on which the control measures are applied. The building flexibility semantic sub-model is used to characterize the flexibility provided by a building to the power grid under a given control method and the benefits generated within the building. It includes two semantic classes: flexibility features and flexibility benefits. Semantically, it defines at least the following object attributes: `inducesFlexFeature` (flexibility feature), `hasFlexFeature` (possessing flexibility feature), and `causesFlexBenefit` (generating flexibility benefits). Specifically: Including the flexibility feature introducedFlexFeature: used to characterize the flexibility features induced by regulatory means; HasFlexFeature: Characterizes the inherent flexibility of building equipment or areas under current operating conditions; FlexBenefit: Used to characterize the benefits and impacts of flexibility features within a building; The power grid interaction semantic sub-model is used to characterize the target requirements and system-level benefits of building-side flexibility under different power grid service scenarios. It includes three semantic classes: interaction scenarios, interaction goals, and interaction benefits. Semantically, it defines at least the following object properties: `supportsScenario` for adapting the interaction scenario, `aimsAtObjective` for the purpose of the interaction goal, and `yieldsInteractionBenefit` for contributing the interaction benefit. Specifically: The `supportsScenario` property is used to characterize the interactive scenarios that specific flexibility features can be used to support. The purpose of the interactive target (aimsAtObjective) is used to represent the power grid operation target corresponding to the interactive scenario. InteractionBenefit: This term represents the system benefits obtained after achieving the interaction goal in a specific interaction scenario.

[0012] Preferably, in the semantic sub-model of building entities: The semantic class for building equipment represents the specific energy-consuming equipment and system units involved in regulation, including air conditioning units, fresh air units, cold and heat storage devices, electric vehicle charging piles, and lighting systems; The regional semantic class represents spatial areas within a building that have relatively consistent functions and environmental conditions, including office areas, shop areas, guest room floors, and computer room areas; The user semantic class represents the personnel and user groups who are active in the area and are affected by regulation, including office staff, customers, guests, and production operators; The semantic class of control measures represents the specific control methods applied to building equipment and areas, including switch control, setpoint adjustment, operating mode switching, load shifting, and start-stop strategies.

[0013] In the preferred semantic sub-model of building flexibility: The flexibility feature semantic class is used to describe the adjustability provided by buildings and equipment after a certain control measure is implemented, including adjustable power, duration of operation, response time, ramp rate, available time window, comfort impact level, and recovery / rebound characteristics; The flexibility benefit semantic class is used to describe the benefits and costs of flexible actions within a building, including energy savings, cost changes, comfort changes, and process risk changes; quantitative characterization is achieved using energy savings, changes in operating costs, and comfort deviation indicators.

[0014] Preferably, in the power grid interaction semantic sub-model: The semantic class of interactive scenarios represents the specific business scenarios in which buildings participate in grid interaction, including seven types of interactive scenarios: peak shaving, frequency regulation, heavy overload management, voltage regulation, loss reduction, tiered consumption of new energy, and emergency backup. Each scenario further includes triggering conditions, time scale, and geographical range attributes. Interactive target semantic class represents the operational goals that the grid side hopes to achieve in a given interactive scenario, including reducing feeder peak power, reducing frequency deviation, constraining node voltage, reducing network losses, increasing renewable energy absorption rate, and improving power supply reliability; The semantic class of interactive benefits represents the comprehensive benefits generated at the system level by building-grid interaction, including grid-side economic benefits, power quality improvement, carbon emission reduction, and reserve capacity replacement; it is further mapped to indicators such as reduced dispatch costs and investment postponement.

[0015] Preferably, the specific relationships in the end-to-end semantic link include, but are not limited to: Building equipment is located in a specific area and serves a specific user: Building Device → located in the area → Building Zone → serves User → Building User; For a specific device or area, select the appropriate control method: Building Device / Building Zone → Has Control → Control Action; Control measures induce specific flexibility features under given operating conditions and user demand constraints: ControlAction → induces FlexFeature → FlexFeature; Flexibility features generate corresponding flexibility benefits or costs within a building: Flex Feature → Flex Benefits → Flex Benefits; Based on the time scale, capacity size, and reliability attributes of flexibility features, suitable power grid interaction scenarios are matched: FlexFeature → supportsScenario → InteractionScenario. For each interactive scenario, clearly define the corresponding interactive goal and interactive benefit: InteractionScenario → Purpose; InteractionGoal → InteractionObjective; InteractionScenario → Contribution; InteractionBenefit → InteractionBenefit.

[0016] This invention also provides a method for using a modular intelligent control device based on differentiated building efficient interaction, comprising the following steps: S1. Device Access and Basic Configuration: Complete device installation and wiring in the target building, connect the sensing unit to the field sensors, metering devices and energy-consuming equipment, connect the communication unit to the building's existing network and upper-level platform; complete device registration, permission configuration and basic parameter distribution on the cloud platform, and load the building power grid interaction semantic model and strategy template. S2. Building Entity Information Collection and Semantic Modeling: Collect information on building area division, equipment list, user type and service relationship through sensing units and manual input. Based on the building entity semantic sub-model, map equipment, area, user and control means into semantic instances, and establish relationships such as being located in an area, serving users, and having control means to form a semantic view of building entities on the device side. S3. Real-time acquisition and preprocessing of operating data: The sensing unit collects multi-dimensional operating data, including temperature and humidity, power, electricity, valve position, occupancy rate, and air quality, according to a preset cycle. The data is then synchronized in time, anomaly detected, missing data is filled in, and noise is filtered to generate a standardized time-series sensing dataset, which is then written to the local cache. S4. Communication Protocol Adaptation and Cross-Protocol Semantic Alignment: The communication unit performs unified parsing of heterogeneous protocols such as BACnet, Modbus, CJ / T188, DL / T645, MQTT, and LoRa through the protocol abstraction layer, calls the communication semantic recognition mechanism, and automatically maps the fields of different protocol messages to unified semantic tags to achieve semantic-level alignment and unified naming of multi-vendor and multi-protocol device points. S5. Building Flexibility Identification and Capability Assessment: Based on standardized perception data and entity semantic view, the calculation unit performs building thermal / cooling / electric dynamic characteristic identification, estimates the flexibility characteristics of each area and key equipment, including power, duration, response time, and comfort impact level, and constructs a building flexibility semantic sub-model to obtain a quantitative capability description of "how much can be adjusted, how long can it be adjusted, and how much impact it has on people and working conditions". S6. Grid Interaction Demand Analysis and Control Task Generation: The device receives price signals, demand response instructions, peak shaving and frequency regulation tasks, and emergency event interaction requests from the grid side and the cloud platform. Based on the grid interaction semantic sub-model, the requests are parsed into specific interaction scenarios, operating objectives, and constraints. Interaction scenarios include peak shaving, frequency regulation, and heavy overload management. Combining building flexibility semantic features, the device selects participating equipment and regions and generates corresponding local control task sets. S7. Collaborative Optimization Calculation and Control Command Issuance: The calculation unit calls the preset optimization and control algorithm module, comprehensively considers the power grid operation target, building flexibility and user comfort constraints, and solves the equipment control sequence and setpoint adjustment scheme at each time scale; the communication unit translates the optimization results into control messages of the corresponding protocol and sends them to the field equipment for execution, completing the collaborative control of multiple devices on the building side; S8. Closed-loop monitoring and strategy self-learning update: The sensing unit continuously monitors the equipment response and environmental changes after the control is executed, and the computing unit compares the expected and actual effects to perform online correction of the flexibility characteristic parameters and control model. The operating data and effect evaluation results are transmitted back through the cloud platform to update the semantic library, model parameters and strategy library, so that the device can achieve continuous self-learning update in multiple buildings and multiple scenarios.

[0017] Therefore, this invention adopts the aforementioned modular intelligent control device and application for efficient interaction in differentiated buildings, which uses a "sensory communication and computing integration with modular interfaces" design concept. It can be quickly deployed in different types of buildings, realizing standardized access and intelligent interaction of multi-source devices. The three-layer semantic sub-model constructs an end-to-end link, matching building flexibility and power grid needs, balancing multiple benefits, and can also perform local optimization and collaborative scheduling, supporting carbon management, providing support for building transformation and new power systems, and significantly improving the data interconnection and processing capabilities of edge devices and the building's power grid interaction efficiency.

[0018] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0019] Figure 1 This is a system architecture diagram of the modular intelligent control device according to an embodiment of the present invention; Figure 2 This is a semantic modeling diagram of the interaction between buildings and power grids according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating the process of an embodiment of the present invention. Detailed Implementation

[0020] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0021] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0022] Example 1 This invention provides a modular intelligent control device for efficient interaction in differentiated buildings, with the system architecture as follows: Figure 1 As shown, it includes a sensing unit, a communication unit, a computing unit, and a device system supporting a cloud platform. The four are interconnected through a unified device bus to form the core execution device for interaction between the building and the power grid. The sensing unit is used to collect environmental parameters, energy consumption status, and equipment operation information within the building. The sensing unit is equipped with multiple types of sensing modules, and each module is connected to the signal acquisition bus of the intelligent control device through a standardized interface. The sensing unit has built-in data synchronization and quality diagnosis functions, and has the functions of sensing acquisition, anomaly identification, data enhancement, and data completion. The environmental parameters, energy consumption status, and equipment operation information collected by the sensing unit are multi-dimensional information, including temperature and humidity, power, valve position, occupancy rate, and air quality.

[0023] The communication unit is located on the mainboard of the device and is used to realize secure data communication between building equipment and upper-level systems. The communication unit supports communication protocols including BACnet, Modbus, KNX, MQTT, and LoRa, and has a unified communication adaptation layer PAL. A communication semantic recognition mechanism PSRM is embedded on top of PAL. The PSRM of the communication unit consists of a semantic feature extraction module, a semantic matching module, and a semantic library self-learning module, which is used to perform semantic-level recognition and unified mapping of heterogeneous protocol data. The communication unit automatically identifies the meaning of message fields according to the type of building equipment, realizes cross-protocol semantic interoperability, and has transmission optimization, data compression, dynamic encryption, and command issuance functions. The computing unit is the core of decision-making and execution for the intelligent control device, responsible for local data processing, operation strategy calculation, and control command issuance. The computing unit loads different types of algorithm modules, including equipment control logic, energy consumption optimization strategies, and status assessment algorithms. The computing unit has functions such as building identification, HVAC identification, target decomposition, and feature extraction. The computing unit is based on a modular slot design, and algorithm modules can be added or removed according to the building's functional requirements. It supports hot-swappable expansion and remote firmware upgrades.

[0024] The device system supports a cloud platform that provides configuration, monitoring, and management services for intelligent control devices, including device registration, operational status monitoring, parameter configuration, firmware upgrades, and log recording. The device system supports a cloud platform that enables centralized management of multiple intelligent control devices through cloud interfaces, supporting collaborative control and remote scheduling at the building cluster level. The device bus consists of three parts: a power channel, a data channel, and a control channel, which are used to realize power supply, data transmission, and control signal communication between modules. The power channel and the data channel adopt a dual-channel isolation design, thereby supporting hot-swapping and plug-and-play functions of algorithm modules.

[0025] The Communication Adaptation Layer (PAL) embeds a building power grid interaction semantic modeling method, which includes methods such as... Figure 2 As shown, a hierarchical and domain-based modeling approach is adopted, including a building entity semantic sub-model, a building flexibility semantic sub-model, and a power grid interaction semantic sub-model. The three sub-models are associated through predefined semantic relationships to form an end-to-end semantic link from the building physical entity to the power grid interaction benefits, so that the power grid interaction information can be uniformly understood and invoked by the intelligent control device. The building entity semantic sub-model is used to characterize the basic objects inside a building and the relationships between them and the objects they serve. It includes four semantic classes: building equipment, areas, users, and control methods. The building equipment semantic class represents the specific energy-consuming equipment and system units involved in control, including air conditioning units, fresh air units, cold and heat storage devices, electric vehicle charging piles, and lighting systems. The regional semantic class represents spatial areas within a building that have relatively consistent functions and environmental conditions, including office areas, shop areas, guest room floors, and computer room areas; The user semantic class represents the personnel and user groups who are active in the area and are affected by regulation, including office staff, customers, guests, and production operators; The semantic class of control measures represents the specific control methods applied to building equipment and areas, including switch control, setpoint adjustment, operating mode switching, load shifting, and start-stop strategies.

[0026] In terms of semantic relationships, at least the following object attributes should be defined: located in the `locatedIn` region, serving the user (`servesUser`), and having control mechanisms (`hasControl`) or active in the `actsOn` region; specifically: Located in area: Used to describe the relationship between building equipment and area; ServesUser: Used to describe the group of users of building equipment or area services; "hasControl / actsOn" describes the object on which the control measures are applied.

[0027] The building flexibility semantic sub-model is used to characterize the flexibility provided by a building to the power grid under a given control method and the benefits generated inside the building. It includes two semantic classes: flexibility features and flexibility benefits.

[0028] The flexibility feature semantic class is used to describe the adjustability provided by buildings and equipment after a certain control measure is implemented, including adjustable power, duration of operation, response time, ramp rate, available time window, comfort impact level, and recovery / rebound characteristics; The flexibility benefit semantic class is used to describe the benefits and costs of flexible actions within a building, including energy savings, cost changes, comfort changes, and process risk changes; quantitative characterization is achieved using energy savings, changes in operating costs, and comfort deviation indicators.

[0029] In terms of semantic relationships, at least the following object properties are defined: `inducesFlexFeature` (induces flexibility feature), `hasFlexFeature` (possessing flexibility feature), and `causesFlexBenefit` (generating flexibility benefits); specifically: Including the flexibility feature introducedFlexFeature: used to characterize the flexibility features induced by regulatory means; HasFlexFeature: Characterizes the inherent flexibility of building equipment or areas under current operating conditions; Causes of flexibility benefits: Used to characterize the benefits and impacts of flexibility features within a building.

[0030] The power grid interaction semantic sub-model is used to characterize the target requirements of building-side flexibility under different power grid service scenarios and the benefits at the system level. It includes three semantic classes: interaction scenario, interaction goal, and interaction benefit.

[0031] The semantic class of interactive scenarios represents the specific business scenarios in which buildings participate in grid interaction, including seven types of interactive scenarios: peak shaving, frequency regulation, heavy overload management, voltage regulation, loss reduction, tiered consumption of new energy, and emergency backup. Each scenario further includes triggering conditions, time scale, and geographical range attributes. Interactive target semantic class represents the operational goals that the grid side hopes to achieve in a given interactive scenario, including reducing feeder peak power, reducing frequency deviation, constraining node voltage, reducing network losses, increasing renewable energy absorption rate, and improving power supply reliability; The semantic class of interactive benefits represents the comprehensive benefits generated at the system level by building-grid interaction, including grid-side economic benefits, power quality improvement, carbon emission reduction, and reserve capacity replacement; it is further mapped to indicators such as reduced dispatch costs and investment postponement.

[0032] In terms of semantic relationships, at least the following object properties should be defined: `supportsScenario` (adapting to the interaction scenario), `aimsAtObjective` (the purpose of the interaction), and `yieldsInteractionBenefit` (contributing to the interaction benefits); specifically: The `supportsScenario` property is used to characterize the interactive scenarios that specific flexibility features can be used to support. The purpose of the interactive target (aimsAtObjective) is used to represent the power grid operation target corresponding to the interactive scenario. InteractionBenefit: This term represents the system benefits obtained after achieving the interaction goal in a specific interaction scenario.

[0033] Through the above modeling, the power grid interaction semantic sub-model elevates the power grid-side business types, operational objectives, and benefit evaluations from "scheduling constraints" to reusable semantic entities, facilitating integration with building-side flexibility semantics. These object attributes create a complete semantic link between the building entity semantic sub-model, the building flexibility semantic sub-model, and the power grid interaction semantic sub-model. Building equipment is located in a specific area and serves a specific user: Building Device → located in the area → Building Zone → serves User → Building User; For a specific device or area, select the appropriate control method: Building Device / Building Zone → Has Control → Control Action; Control measures induce specific flexibility features under given operating conditions and user demand constraints: ControlAction → induces FlexFeature → FlexFeature; Flexibility features generate corresponding flexibility benefits or costs within a building: Flex Feature → Flex Benefits → Flex Benefits; Based on the time scale, capacity size, and reliability attributes of flexibility features, suitable power grid interaction scenarios are matched: FlexFeature → supportsScenario → InteractionScenario. For each interactive scenario, clearly define the corresponding interactive goal and interactive benefit: InteractionScenario → Purpose; InteractionGoal → InteractionObjective; InteractionScenario → Contribution; InteractionBenefit → InteractionBenefit.

[0034] Through the aforementioned end-to-end semantic modeling, this invention achieves a full-chain semantic expression from "building equipment - region - user - control means - flexibility characteristics - flexibility benefits - interaction scenarios - interaction goals - interaction benefits", making the correlation between building-side perceived data, control strategies and grid-side service needs clear and traceable. It can be directly invoked by intelligent control devices and their upper-level optimization and inference modules, thereby supporting unified modeling, flexible combination and transferable deployment of various types of differentiated buildings in various grid interaction scenarios.

[0035] The method of using the intelligent control device described in this embodiment is as follows: Figure 3 As shown, it includes the following steps: S1. Device Access and Basic Configuration: Complete device installation and wiring in the target building, connect the sensing unit to the field sensors, metering devices and energy-consuming equipment, connect the communication unit to the building's existing network and upper-level platform; complete device registration, permission configuration and basic parameter distribution on the cloud platform, and load the building power grid interaction semantic model and strategy template. S2. Building Entity Information Collection and Semantic Modeling: Collect information on building area division, equipment list, user type and service relationship through sensing units and manual input. Based on the building entity semantic sub-model, map equipment, area, user and control means into semantic instances, and establish relationships such as being located in an area, serving users, and having control means to form a semantic view of building entities on the device side. S3. Real-time acquisition and preprocessing of operating data: The sensing unit collects multi-dimensional operating data, including temperature and humidity, power, electricity, valve position, occupancy rate, and air quality, according to a preset cycle. The data is then synchronized in time, anomaly detected, missing data is filled in, and noise is filtered to generate a standardized time-series sensing dataset, which is then written to the local cache. S4. Communication Protocol Adaptation and Cross-Protocol Semantic Alignment: The communication unit performs unified parsing of heterogeneous protocols such as BACnet, Modbus, CJ / T188, DL / T645, MQTT, and LoRa through the protocol abstraction layer, calls the communication semantic recognition mechanism, and automatically maps the fields of different protocol messages to unified semantic tags to achieve semantic-level alignment and unified naming of multi-vendor and multi-protocol device points. S5. Building Flexibility Identification and Capability Assessment: Based on standardized perception data and entity semantic view, the calculation unit performs building thermal / cooling / electric dynamic characteristic identification, estimates the flexibility characteristics of each area and key equipment, including power, duration, response time, and comfort impact level, and constructs a building flexibility semantic sub-model to obtain a quantitative capability description of "how much can be adjusted, how long can it be adjusted, and how much impact it has on people and working conditions". S6. Grid Interaction Demand Analysis and Control Task Generation: The device receives price signals, demand response instructions, peak shaving and frequency regulation tasks, and emergency event interaction requests from the grid side and the cloud platform. Based on the grid interaction semantic sub-model, the requests are parsed into specific interaction scenarios, operating objectives, and constraints. Interaction scenarios include peak shaving, frequency regulation, and heavy overload management. Combining building flexibility semantic features, the device selects participating equipment and regions and generates corresponding local control task sets. S7. Collaborative Optimization Calculation and Control Command Issuance: The calculation unit calls the preset optimization and control algorithm module, comprehensively considers the power grid operation target, building flexibility and user comfort constraints, and solves the equipment control sequence and setpoint adjustment scheme at each time scale; the communication unit translates the optimization results into control messages of the corresponding protocol and sends them to the field equipment for execution, completing the collaborative control of multiple devices on the building side; S8. Closed-loop monitoring and strategy self-learning update: The sensing unit continuously monitors the equipment response and environmental changes after the control is executed, and the computing unit compares the expected and actual effects to perform online correction of the flexibility characteristic parameters and control model. The operating data and effect evaluation results are transmitted back through the cloud platform to update the semantic library, model parameters and strategy library, so that the device can achieve continuous self-learning update in multiple buildings and multiple scenarios.

[0036] Therefore, this invention adopts the aforementioned modular intelligent control device and application for efficient interaction in differentiated buildings, which uses a "sensory communication and computing integration with modular interfaces" design concept. It can be quickly deployed in different types of buildings, realizing standardized access and intelligent interaction of multi-source devices. The three-layer semantic sub-model constructs an end-to-end link, matching building flexibility and power grid needs, balancing multiple benefits, and can also perform local optimization and collaborative scheduling, supporting carbon management, providing support for building transformation and new power systems, and significantly improving the data interconnection and processing capabilities of edge devices and the building's power grid interaction efficiency.

[0037] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A modular intelligent control device for efficient interaction in differentiated buildings, characterized in that: It includes a sensing unit, a communication unit, a computing unit, and a device system supporting a cloud platform. The four components are interconnected through a unified device bus to form the core execution device for interaction between the building and the power grid. The sensing unit is used to collect building interior environmental parameters, energy consumption status and equipment operation information; the sensing unit is equipped with multiple types of sensing modules, and each module is connected to the signal acquisition bus of the intelligent control device through a standardized interface; the sensing unit has built-in data synchronization and quality diagnosis functions, and has the functions of sensing acquisition, anomaly identification, data enhancement and data completion. The communication unit is located on the main board of the device and is used to enable secure data communication between building equipment and the upper-level system; The communication unit supports communication protocols including BACnet, Modbus, KNX, MQTT, and LoRa, and has a unified communication adaptation layer PAL, on which a communication semantic recognition mechanism PSRM is embedded. The communication unit automatically identifies the meaning of message fields based on the type of building equipment, enabling cross-protocol semantic interoperability and possessing functions such as transmission optimization, data compression, dynamic encryption, and command issuance. The computing unit is the core of decision-making and execution for the intelligent control device, responsible for local data processing, operation strategy calculation and control command issuance; the computing unit loads different types of algorithm modules, including equipment control logic, energy consumption optimization strategy and status assessment algorithm; the computing unit has building identification, HVAC identification, target decomposition and feature extraction functions; The device system supports a cloud platform that provides configuration, monitoring, and management services for intelligent control devices, including device registration, operational status monitoring, parameter configuration, firmware upgrades, and log recording. The device system supports a cloud platform that enables centralized management of multiple intelligent control devices through cloud interfaces, supporting collaborative control and remote scheduling at the building cluster level. The device bus consists of three parts: a power channel, a data channel, and a control channel, which are used to realize power supply, data transmission, and control signal communication between modules. The power channel and data channel adopt a dual-channel isolation design, thereby supporting hot-swapping and plug-and-play functionality of the algorithm module; The communication adaptation layer PAL embeds a building-grid interaction semantic modeling method. The building-grid interaction semantic modeling method adopts a hierarchical and domain-based modeling approach, including a building entity semantic sub-model, a building flexibility semantic sub-model, and a grid interaction semantic sub-model. The three sub-models are associated through predefined semantic relationships to form an end-to-end semantic link from the building physical entity to the grid interaction benefits, so that the grid interaction information can be uniformly understood and invoked by the intelligent control device. The building entity semantic sub-model is used to characterize the basic objects within a building and their relationships with the objects they serve. It includes four semantic classes: building equipment, areas, users, and control mechanisms. In terms of semantic relationships, it defines at least the following object attributes: located in the area `locatedIn`, serving users `servesUser`, and possessing control mechanisms `hasControl` or active in the area `actsOn`. Specifically: Located in area: Used to describe the relationship between building equipment and area; ServesUser: Used to describe the group of users of building equipment or area services; "hasControl / actsOn" describes the object on which the control measures are applied. The building flexibility semantic sub-model is used to characterize the flexibility provided by a building to the power grid under a given control method and the benefits generated within the building. It includes two semantic classes: flexibility features and flexibility benefits. Semantically, it defines at least the following object attributes: `inducesFlexFeature` (flexibility feature), `hasFlexFeature` (possessing flexibility feature), and `causesFlexBenefit` (generating flexibility benefits). Specifically: Including the flexibility feature introducedFlexFeature: used to characterize the flexibility features induced by regulatory means; HasFlexFeature: Characterizes the inherent flexibility of building equipment or areas under current operating conditions; FlexBenefit: Used to characterize the benefits and impacts of flexibility features within a building; The power grid interaction semantic sub-model is used to characterize the target requirements and system-level benefits of building-side flexibility under different power grid service scenarios. It includes three semantic classes: interaction scenarios, interaction goals, and interaction benefits. Semantically, it defines at least the following object properties: `supportsScenario` for adapting the interaction scenario, `aimsAtObjective` for the purpose of the interaction goal, and `yieldsInteractionBenefit` for contributing the interaction benefit. Specifically: The `supportsScenario` property is used to characterize the interactive scenarios that specific flexibility features can be used to support. The purpose of the interactive target (aimsAtObjective) is used to represent the power grid operation target corresponding to the interactive scenario. InteractionBenefit: This term represents the system benefits obtained after achieving the interaction goal in a specific interaction scenario.

2. The modular intelligent control device for efficient interactive sensing in differentiated buildings according to claim 1, characterized in that, The environmental parameters, energy consumption status, and equipment operation information collected by the sensing unit are multi-dimensional information, including temperature and humidity, power, valve position, occupancy rate, and air quality.

3. The modular intelligent control device for efficient interactive sensing in differentiated buildings according to claim 1, characterized in that, The PSRM of the communication unit consists of a semantic feature extraction module, a semantic matching module, and a semantic library self-learning module, which is used to perform semantic-level recognition and unified mapping of heterogeneous protocol data.

4. The modular intelligent control device for efficient interaction in differentiated buildings according to claim 1, characterized in that, The computing unit is based on a modular slot design, allowing for the addition or removal of algorithm modules according to building functional requirements, and supports hot-swappable expansion and remote firmware upgrades.

5. The modular intelligent control device for efficient interaction in differentiated buildings according to claim 1, characterized in that, In the semantic sub-model of building entities: The semantic class for building equipment represents the specific energy-consuming equipment and system units involved in regulation, including air conditioning units, fresh air units, cold and heat storage devices, electric vehicle charging piles, and lighting systems; The regional semantic class represents spatial areas within a building that have relatively consistent functions and environmental conditions, including office areas, shop areas, guest room floors, and computer room areas; The user semantic class represents the personnel and user groups who are active in the area and are affected by regulation, including office staff, customers, guests, and production operators; The semantic class of control measures represents the specific control methods applied to building equipment and areas, including switch control, setpoint adjustment, operating mode switching, load shifting, and start-stop strategies.

6. The modular intelligent control device for efficient interaction in differentiated buildings according to claim 1, characterized in that, In the semantic sub-model of building flexibility: The flexibility feature semantic class is used to describe the adjustability provided by buildings and equipment after a certain control measure is implemented, including adjustable power, duration of operation, response time, ramp rate, available time window, comfort impact level, and recovery / rebound characteristics; The flexibility benefit semantic class is used to describe the benefits and costs of flexible actions within a building, including energy savings, cost changes, comfort changes, and process risk changes. Quantitative characterization is achieved using indicators such as energy savings, changes in operating costs, and deviations in comfort levels.

7. The modular intelligent control device for efficient interaction in differentiated buildings according to claim 1, characterized in that, In the power grid interaction semantic sub-model: The semantic class of interactive scenarios represents the specific business scenarios in which buildings participate in grid interaction, including seven types of interactive scenarios: peak shaving, frequency regulation, heavy overload management, voltage regulation, loss reduction, tiered consumption of new energy, and emergency backup. Each scenario further includes triggering conditions, time scale, and geographical range attributes. Interactive target semantic class represents the operational goals that the grid side hopes to achieve in a given interactive scenario, including reducing feeder peak power, reducing frequency deviation, constraining node voltage, reducing network losses, increasing renewable energy absorption rate, and improving power supply reliability; The semantic class of interactive benefits represents the comprehensive benefits generated at the system level by building-grid interaction, including grid-side economic benefits, power quality improvement, carbon emission reduction, and reserve capacity replacement; it is further mapped to indicators such as reduced dispatch costs and investment postponement.

8. The modular intelligent control device for efficient interaction in differentiated buildings according to claim 1, characterized in that, The specific relationships in the end-to-end semantic link include, but are not limited to: Building equipment is located in a specific area and serves a specific user: Building Device → located in the area → Building Zone → serves User → Building User; For a specific device or area, select the appropriate control method: Building Device / Building Zone → Has Control → Control Action; Control measures induce specific flexibility features under given operating conditions and user demand constraints: ControlAction → induces FlexFeature → FlexFeature; Flexibility features generate corresponding flexibility benefits or costs within a building: Flex Feature → Flex Benefits → Flex Benefits; Based on the time scale, capacity size, and reliability attributes of flexibility features, suitable power grid interaction scenarios are matched: FlexFeature → supportsScenario → InteractionScenario. For each interactive scenario, clearly define the corresponding interactive goal and interactive benefit: InteractionScenario → Purpose; InteractionGoal → InteractionObjective; InteractionScenario → Contribution; InteractionBenefit → InteractionBenefit.

9. The method of using the modular intelligent control device for efficient interaction in differentiated buildings as described in any one of claims 1-8, characterized in that, Includes the following steps: S1. Device Access and Basic Configuration: Complete device installation and wiring in the target building, connect the sensing unit to the field sensors, metering devices and energy-consuming equipment, connect the communication unit to the building's existing network and upper-level platform; complete device registration, permission configuration and basic parameter distribution on the cloud platform, and load the building power grid interaction semantic model and strategy template. S2. Building Entity Information Collection and Semantic Modeling: Collect information on building area division, equipment list, user type and service relationship through sensing units and manual input. Based on the building entity semantic sub-model, map equipment, area, user and control means into semantic instances, and establish relationships such as being located in an area, serving users, and having control means to form a semantic view of building entities on the device side. S3. Real-time acquisition and preprocessing of operating data: The sensing unit collects multi-dimensional operating data, including temperature and humidity, power, electricity, valve position, occupancy rate, and air quality, according to a preset cycle. The data is then synchronized in time, anomaly detected, missing data is filled in, and noise is filtered to generate a standardized time-series sensing dataset, which is then written to the local cache. S4. Communication Protocol Adaptation and Cross-Protocol Semantic Alignment: The communication unit performs unified parsing of heterogeneous protocols such as BACnet, Modbus, CJ / T188, DL / T645, MQTT, and LoRa through the protocol abstraction layer, calls the communication semantic recognition mechanism, and automatically maps the fields of different protocol messages to unified semantic tags to achieve semantic-level alignment and unified naming of multi-vendor and multi-protocol device points. S5. Building Flexibility Identification and Capability Assessment: Based on standardized perception data and entity semantic view, the calculation unit performs building thermal / cooling / electric dynamic characteristic identification, estimates the flexibility characteristics of each area and key equipment, including power, duration, response time, and comfort impact level, and constructs a building flexibility semantic sub-model to obtain a quantitative capability description of "how much can be adjusted, how long can it be adjusted, and how much impact it has on people and working conditions". S6. Power Grid Interaction Demand Analysis and Control Task Generation: The device receives price signals, demand response instructions, peak shaving and frequency regulation tasks and emergency event interaction requests from the power grid side and the cloud platform. Based on the power grid interaction semantic sub-model, the requests are analyzed into specific interaction scenarios, operating objectives and constraints. Interactive scenarios include peak shaving, frequency modulation, and heavy overload management; By combining semantic features of building flexibility, we can select participating equipment and areas and generate corresponding local control task sets. S7. Collaborative Optimization Calculation and Control Command Issuance: The calculation unit calls the preset optimization and control algorithm module, comprehensively considers the power grid operation target, building flexibility and user comfort constraints, and solves the equipment control sequence and setpoint adjustment scheme at each time scale; the communication unit translates the optimization results into control messages of the corresponding protocol and sends them to the field equipment for execution, completing the collaborative control of multiple devices on the building side; S8. Closed-loop monitoring and strategy self-learning update: The sensing unit continuously monitors the equipment response and environmental changes after the control is executed, and the computing unit compares the expected and actual effects to perform online correction of the flexibility characteristic parameters and control model. The operating data and effect evaluation results are transmitted back through the cloud platform to update the semantic library, model parameters and strategy library, so that the device can achieve continuous self-learning update in multiple buildings and multiple scenarios.

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