Urban building energy consumption prediction method and device, electronic equipment and medium

Abstract

The present application relates to the field of energy simulation, and discloses a method and device for predicting urban building energy consumption, electronic equipment and medium. The method comprises: reconstructing each component in the urban climate state of the previous time step by mapping to determine the building boundary state; determining the energy consumption state quantity of the building according to the building boundary state; updating the urban climate state of the current time step according to the energy consumption state quantity, thereby predicting the urban building energy consumption of each time step. The present application can accurately depict the evolution law of urban building energy consumption under future climate change scenarios.

Description

Technical Field

[0001] This invention relates to the field of energy simulation, and more particularly to methods, apparatus, electronic devices and media for predicting energy consumption of urban buildings. Background Technology

[0002] Against the backdrop of global climate change and the transformation towards energy-efficient buildings, accurately predicting building energy consumption under multi-scale meteorological evolution has become a key issue in urban planning, energy management, and climate-adaptive design. In the context of climate change, urban building energy consumption exhibits significant time-varying and nonlinear characteristics. Its evolution is not only influenced by long-term climate change trends but also closely related to the interaction between local wind fields, thermal environment, and building operational behavior at the urban scale. Current technologies for building energy consumption simulation typically use pre-generated static meteorological data or typical meteorological years as input boundaries. Climate processes and building operational processes are independent of each other, lacking cross-scale consistency constraints and dynamic feedback mechanisms, making it difficult to accurately characterize the evolution of urban building energy consumption under future climate change scenarios.

[0003] It is recommended to emphasize the shortcomings of existing technologies. Summary of the Invention

[0004] This invention aims to address at least one of the technical problems existing in the prior art. To this end, this invention proposes a method for predicting urban building energy consumption, capable of accurately depicting the evolution of urban building energy consumption under future climate change scenarios.

[0005] The present invention also proposes an apparatus, device and medium having the above-mentioned method for predicting urban building energy consumption.

[0006] A method for predicting urban building energy consumption according to a first aspect of the present invention includes: The components of the urban climate state at the above time step are mapped and reconstructed to determine the building boundary state. Based on the building boundary state, determine the building's energy consumption state quantity; Based on the energy consumption status, the urban climate status at the current time step is updated to predict the urban building energy consumption at each time step.

[0007] According to an embodiment of the present invention, a method for predicting urban building energy consumption has at least the following beneficial effects: The present invention forms a closed-loop coupling between urban climate state and building operation state through mapping reconstruction and bidirectional feedback, links climate process and building operation process, and performs unified time advancement to coordinate the time evolution process of state variables at different scales, thereby accurately depicting the evolution law of urban building energy consumption under future climate change scenarios.

[0008] According to some embodiments of the present invention, mapping and reconstructing the components of the urban climate state at the previous time step to determine the building boundary state includes: For each building, the boundary states of each external surface of the building are mapped according to the components of the urban climate state corresponding to the building; among them, the components of the urban climate state include: the spatial location of the building, temperature, wind speed, air humidity, and radiation-related state quantities. The building boundary state is obtained by collecting the boundary states of each external surface of the building.

[0009] According to some embodiments of the present invention, determining the building's energy consumption state quantity based on the building boundary state includes: Under the constraints of the building boundary state, determine the sensible heat exchange, latent heat, or water vapor exchange of the building at that time step; The energy state parameters of a building are determined based on its sensible heat exchange, latent heat, or water vapor exchange at that time step.

[0010] According to some embodiments of the present invention, updating the urban climate state at the current time step based on the energy consumption state quantity includes: Based on the building's energy consumption status and spatial location, the incremental update of the urban climate status is obtained. Based on the incremental update of the city's climate status, the city's climate status at the previous time step is obtained to determine the city's climate status at the current time step.

[0011] According to some embodiments of the present invention, it further includes: Within any given time period, determine whether the urban climate state and the energy consumption state are both stable. If so, proceed to the next time period; otherwise, adjust the mapping and reconstruction, and perform mapping and reconstruction based on each component of the urban climate state within the time step of that time period. The time period includes several time steps.

[0012] An urban building energy consumption prediction device according to a second aspect embodiment of the present invention includes: The building energy consumption dynamic solution support module is connected to the building energy consumption dynamic solution support module. It is used to map and reconstruct each component of the urban climate state at the previous time step to determine the building boundary state; and to determine the building energy consumption state quantity based on the building boundary state. The urban-scale microclimate dynamic solution support module is used to update the urban climate state at the current time step based on the energy consumption state quantity; and input the urban climate state at the current time step into the building energy consumption dynamic solution support module.

[0013] According to some embodiments of the present invention, determining the building's energy consumption state quantity based on the building boundary state includes: Under the constraints of the building boundary state, determine the sensible heat exchange, latent heat, or water vapor exchange of the building at that time step; The energy state parameters of a building are determined based on its sensible heat exchange, latent heat, or water vapor exchange at that time step.

[0014] According to some embodiments of the present invention, updating the urban climate state at the current time step based on the energy consumption state quantity includes: Based on the building's energy consumption status and spatial location, the incremental update of the urban climate status is obtained. Based on the incremental update of the city's climate status, the city's climate status at the previous time step is obtained to determine the city's climate status at the current time step.

[0015] An electronic device according to a third aspect of the present invention includes: Memory, used to store programs; A processor for executing a program stored in the memory, wherein when the processor executes the program stored in the memory, the processor is configured to perform the method as described in any one of the first aspects.

[0016] According to a fourth aspect of the present invention, a storage medium stores computer-executable instructions for performing the method as described in any one of the first aspects.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0018] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0019] Figure 1 This is a flowchart of a method for predicting urban building energy consumption according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] It should be understood that in the description of the embodiments of the present invention, "multiple" (or "amounts") means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. If "first," "second," etc., are used in the description, they are only for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0022] like Figure 1 As shown, this embodiment of the invention provides a method for predicting urban building energy consumption, including: Step S100: Map and reconstruct each component of the urban climate state at the previous time step to determine the building boundary state; Step S200: Determine the energy consumption state quantity of the building based on the building boundary state; Step S300: Update the urban climate status at the current time step based on the energy consumption status data, thereby predicting the urban building energy consumption at each time step.

[0023] This invention couples urban climate status and building operation status through mapping reconstruction and bidirectional feedback to form a closed loop, linking climate processes and building operation processes, and unifying time progression to coordinate the temporal evolution of state variables at different scales, thereby accurately depicting the evolution of urban building energy consumption under future climate change scenarios.

[0024] It should be noted that the focus of this embodiment is not on limiting specific urban microclimate models or building energy consumption models, but on illustrating how to achieve cross-scale dynamic solutions for urban microclimate and building energy consumption under the drive of future climate scenarios through unified time progression, cross-scale variable mapping, construction of building feedback source terms, and cross-scale collaborative convergence control. The urban climate state with an initial time step is set at a certain future time point as the starting point, and climate prediction is performed for that future time point. Each component in the future urban climate state includes at least one of air temperature, humidity, wind speed, and radiation, and is adapted to a unified time progression index through time interpolation, resampling, or state representation.

[0025] It is easy to understand that the predicted energy consumption of urban buildings is the energy state quantity of the buildings.

[0026] In one embodiment, in step S100, the components of the urban climate state at the previous time step are mapped and reconstructed to determine the building boundary state, including: For each building, the boundary states of each external surface of the building are mapped according to the components of the urban climate state corresponding to the building; among them, the components of the urban climate state include: the spatial location of the building, temperature, wind speed, air humidity, and radiation-related state quantities. The boundary states of a building are obtained by collecting the boundary states of each of its external surfaces.

[0027] Specifically, the expression for the urban climate state is as follows: in, This represents the air temperature field at the city scale. This represents the wind speed vector field at the city scale. This indicates the state of air humidity. Represents radiation-related state quantities. Indicates the spatial location of a building; The boundary state of building b is explicitly defined as follows: Where i represents the number of the i-th outer surface of the building. This indicates the number of exterior surfaces of building b; Therefore, the boundary state of any outer surface i at time t can be expressed as: The components represent, in turn, the temperature, effective wind speed, humidity, and radiation state of the air near the building's exterior surface. Under a unified time-progression index, the cross-scale variable mapping operator (i.e., the mapping relationship used to obtain the boundary states of various external surfaces of a building) can be abstractly represented as: in, This represents the microclimate state vector at the city scale. Let represent the set of geometric and spatial attributes of building b. This indicates the orientation and normal information of each exterior surface of the building; The above mapping relationship is used to characterize how to dynamically generate boundary state quantities related to building spatial attributes based on continuous climate conditions at the city scale within a given time step; the boundary state quantity mapping adopts different mapping methods according to the variable type, including: scalar variables adopt interpolation; vector variables adopt projection combined with the normal direction of the building's outer surface.

[0028] To further illustrate the structural characteristics of the cross-scale variable mapping operator, it can be described by component-level expansion. For the building's outer surface i, the boundary state variables are: in, This indicates the spatial location of the outer surface i at the urban scale; Family of mapping functions corresponding to different physical quantities, cross-scale variable mapping operator Equivalent to A set of.

[0029] It should be noted that the above-mentioned family of functions is only used to express the structural constraints of the mapping relationship, and its specific mathematical form is not limited to a specific function or algorithm. The cross-scale variable mapping operator in this invention is used to establish the mapping relationship between the urban-scale climate state and the building-scale boundary state during the dynamic solution process. It is not limited to a specific interpolation or projection algorithm. The improvement is that, within a unified time-progression framework, this type of mapping operator realizes the dynamic reconstruction of the building boundary state and enables it to participate in the cross-scale collaborative solution and bidirectional feedback process. The specific implementation form of the mapping operator can be selected according to the application scenario.

[0030] In one optional implementation, the cross-scale variable mapping operator can be implemented using spatial interpolation. Specifically, for any point on the building's exterior surface, several sampling points adjacent to that point are selected in the urban-scale microclimate state field, and the climate state variables are reconstructed by weighting according to their spatial relative positions, thereby obtaining the instantaneous boundary state of the corresponding building's exterior surface. In this implementation, the interpolation weights can be set according to spatial distance, relative orientation, or other spatial relationships; the interpolation process is dynamically executed within each time progression cycle, so that the building boundary state is continuously updated with the evolution of the urban microclimate.

[0031] In one embodiment, in step S200, determining the building's energy consumption state quantity based on the building boundary state includes: Under the constraints of the building boundary state, determine the sensible heat exchange, latent heat, or water vapor exchange of the building at that time step; Based on the building's sensible heat exchange, latent heat, or water vapor exchange at this time step, the building's energy consumption state quantity is determined; the above output not only serves as the building's energy consumption result, but also constitutes the building's feedback state quantity, which is used to participate in the updating of the urban microclimate state within the current time progression cycle.

[0032] Specifically, the expression for the building's energy consumption state quantities is as follows: in, This is a dynamic solution operator for building energy consumption, used to solve the energy and water vapor exchange state during building operation under given building scale boundary state constraints. Its specific implementation form is not limited. This refers to the energy state quantity of a building. For building boundary state, For the building in time step The amount of sensible heat exchanged, released or absorbed into the surrounding air. Indicates the building in time The amount of latent heat or water vapor exchange generated.

[0033] In one embodiment, in step S300, updating the city's climate state at the current time step based on energy consumption status includes: Based on the building's energy consumption status and spatial location, the incremental update of the urban climate status is obtained. Based on the incremental update of the city's climate status, the city's climate status at the previous time step is obtained to determine the city's climate status at the current time step.

[0034] Specifically, the expression for the incremental update of the urban climate state is as follows: in, Indicates the spatial location acting on the city scale The distribution of feedback source terms, Indicates the number of buildings. This indicates the spatial location of the building; the feedback operator is used to describe how building energy consumption is distributed spatially and participates in the dynamic updating of the urban microclimate. The update of urban climate status can be represented as: in, For time The city-scale microclimate state; ⊕ represents the state increment update operation, used to incorporate building energy consumption feedback into the city-scale state evolution process.

[0035] It should be noted that the above expressions are only used to describe the structural relationship of feedback updates and do not limit the specific numerical form or solution method of urban microclimate state updates.

[0036] The building-climate bidirectional feedback mechanism in this invention does not simply backfill building energy consumption results into the climate model. Instead, within a unified time-progression framework, it transforms building energy consumption status into feedback quantities that participate in updating the urban microclimate status through feedback operators. The innovation of this mechanism lies in the fact that building operating status and urban microclimate status co-evolve within the same dynamic system, and its specific feedback form can be implemented according to application needs, and is not limited to a particular feedback algorithm.

[0037] In one alternative implementation, the building energy consumption state quantity can be constructed into a spatially distributed feedback source item within the urban-scale computational domain according to the building's spatial location and its influence range. Specifically, the sensible heat and latent heat feedback quantities can be allocated to the corresponding urban-scale spatial control volume according to the location of the building's outer surface or the building's volume range, thereby enabling the building energy consumption to have a spatially related impact on the local climate state.

[0038] In one embodiment, the method further includes: Within any given time period, determine whether the urban climate state and energy consumption state are stable. If so, proceed to the next time period; otherwise, adjust the mapping and reconstruct the mapping, using the components of the urban climate state at the time step of that time period. The time period includes several time steps.

[0039] Specifically, this invention constructs a cross-scale cooperative convergence criterion to determine whether the cross-scale dynamic solution process within the current time advancement cycle has reached a cooperative stable state. The criterion can be abstractly represented as follows: in: Indicates changes in urban climate status The allowable threshold; Represents the change in energy consumption state quantity The allowable threshold; When the co-convergence criterion is met, the system enters the next time advance cycle; when the criterion is not met, the system can coordinate and adjust the mapping or feedback process within the current time advance cycle to maintain the stability of the dynamic solution process.

[0040] This invention also provides a device for predicting urban building energy consumption, comprising: The building energy consumption dynamic solution support module is connected to the building energy consumption dynamic solution support module. It is used to map and reconstruct the components of the urban climate state at the previous time step to determine the building boundary state; and to determine the building energy consumption state quantity based on the building boundary state. The urban-scale microclimate dynamic solution support module is used to update the urban climate status at the current time step based on energy consumption status quantities; and input the urban climate status at the current time step into the building energy consumption dynamic solution support module.

[0041] It should be noted that the urban building energy consumption prediction device in this embodiment is used to execute the above-described urban building energy consumption prediction method.

[0042] In one embodiment, the urban-scale microclimate dynamic solution module is used to describe the evolution of air conditions within urban space over time and generate the urban-scale microclimate state vector required by the cross-scale dynamic solution system. Under the unified time-progression framework, this module updates the urban-scale microclimate state in each time-progression cycle. The update result serves as the input to the cross-scale variable mapping operator and simultaneously receives feedback from the building energy consumption feedback operator. The specific physical model, numerical format, and parameter settings of this module can be selected according to application requirements. Its function is to provide continuously evolving urban-scale state quantities for the cross-scale dynamic solution system. The building energy consumption dynamic solution module is used to describe the energy and water vapor exchange behavior between a building and its external environment during operation; in this invention, the building energy consumption dynamic solution module advances the index at a unified time. The program runs on the following scale, and its input is the building-scale boundary state dynamically reconstructed by the cross-scale variable mapping operator. Its output is the energy consumption feedback state quantity generated during building operation. ; The specific implementation of this module can adopt any calculation model that can characterize the building's energy consumption behavior, and its implementation method does not affect the establishment of the cross-scale dynamic solution mechanism and bidirectional feedback mechanism described in this invention.

[0043] The urban-scale microclimate dynamic solution module and the building energy consumption dynamic solution module do not operate independently, but work together under the constraints of a unified time progression and collaborative convergence control mechanism.

[0044] Specifically, within any given time period: ① Update of the urban-scale microclimate dynamic solution module ; ② Cross-scale variable mapping operator based on Dynamically generate architectural-scale boundary states; ③ The building energy consumption dynamic solution module outputs building energy consumption feedback state quantities. ; ④ The building energy consumption feedback state quantity participates in the city-scale state update of the next time advance cycle through the feedback operator.

[0045] Through the aforementioned collaborative relationship, the support module and the core innovation mechanism together form a complete cross-scale dynamic solution closed loop.

[0046] This invention also provides an electronic device, which includes, but is not limited to: Memory, used to store programs; The processor is used to execute programs stored in memory. When the processor executes the programs stored in memory, it is used to execute the aforementioned method for predicting urban building energy consumption.

[0047] The processor and memory can be connected via a bus or other means.

[0048] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs, such as the method described in the embodiments of the present invention. The processor implements the above method by running the non-transitory software program and instructions stored in the memory.

[0049] The memory may include a program storage area and a data storage area, wherein the program storage area may store the operating system and application programs required for at least one function; the data storage area may store data for executing the methods described above. Furthermore, the memory may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include memory remotely located relative to the processor, which can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0050] The non-transitory software program and instructions required to implement the above terminal selection method are stored in memory and are executed by one or more processors.

[0051] This invention also provides a storage medium storing computer-executable instructions for performing the above-described methods.

[0052] In one embodiment, the storage medium stores computer-executable instructions that are executed by one or more control processors.

[0053] The embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0054] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically include computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0055] This document describes embodiments of the invention, including preferred embodiments known to the inventors for carrying out the invention. Variations of these embodiments will become apparent to those skilled in the art upon reading the foregoing description. The inventors encourage those skilled in the art to adopt such variations as appropriate, and the inventors intend to practice embodiments of the invention in ways other than those specifically described herein. Therefore, the scope of the invention includes all modifications and equivalents of the subject matter set forth in the appended claims, as permitted by applicable law. Furthermore, the scope of the invention covers any combination of the foregoing elements in all possible variations thereof, unless otherwise indicated herein or otherwise clearly contradicted by the context.

Claims

1. A method for predicting urban building energy consumption, characterized in that, include: The components of the urban climate state at the above time step are mapped and reconstructed to determine the building boundary state. Based on the building boundary state, determine the building's energy consumption state quantity; Based on the energy consumption status, the urban climate status at the current time step is updated to predict the urban building energy consumption at each time step.

2. The method for predicting urban building energy consumption according to claim 1, characterized in that, The components of the urban climate state at the above-mentioned time step are mapped and reconstructed to determine the building boundary state, including: For each building, the boundary states of each external surface of the building are mapped according to the components of the urban climate state corresponding to the building; among them, the components of the urban climate state include: the spatial location of the building, temperature, wind speed, air humidity, and radiation-related state quantities. The building boundary state is obtained by collecting the boundary states of each external surface of the building.

3. The method for predicting urban building energy consumption according to claim 1, characterized in that, The process of determining the building's energy consumption state parameters based on the building's boundary state includes: Under the constraints of the building boundary state, determine the sensible heat exchange, latent heat, or water vapor exchange of the building at that time step; The energy state parameters of a building are determined based on its sensible heat exchange, latent heat, or water vapor exchange at that time step.

4. The method for predicting urban building energy consumption according to claim 1, characterized in that, The step of updating the urban climate status at the current time step based on the energy consumption status includes: Based on the building's energy consumption status and spatial location, the incremental update of the urban climate status is obtained. Based on the incremental update of the city's climate status, the city's climate status at the previous time step is obtained to determine the city's climate status at the current time step.

5. The method for predicting urban building energy consumption according to claim 1, characterized in that, Also includes: Within any given time period, determine whether the urban climate state and the energy consumption state are both stable. If so, proceed to the next time period; otherwise, adjust the mapping and reconstruction, and perform mapping and reconstruction based on each component of the urban climate state within the time step of that time period. The time period includes several time steps.

6. A device for predicting urban building energy consumption, characterized in that, include: The building energy consumption dynamic solution support module is connected to the building energy consumption dynamic solution support module. It is used to map and reconstruct each component of the urban climate state at the previous time step to determine the building boundary state; and to determine the building energy consumption state quantity based on the building boundary state. The urban-scale microclimate dynamic solution support module is used to update the urban climate state at the current time step based on the energy consumption state quantity. Input the current urban climate status at the current time step into the building energy consumption dynamic solution support module.

7. The urban building energy consumption prediction device according to claim 6, characterized in that, The process of determining the building's energy consumption state parameters based on the building's boundary state includes: Under the constraints of the building boundary state, determine the sensible heat exchange, latent heat, or water vapor exchange of the building at that time step; The energy state parameters of a building are determined based on its sensible heat exchange, latent heat, or water vapor exchange at that time step.

8. The urban building energy consumption prediction device according to claim 6, characterized in that, The step of updating the urban climate status at the current time step based on the energy consumption status includes: Based on the building's energy consumption status and spatial location, the incremental update of the urban climate status is obtained. Based on the incremental update of the city's climate status, the city's climate status at the previous time step is obtained to determine the city's climate status at the current time step.

9. An electronic device, characterized in that, include: Memory, used to store programs; A processor for executing a program stored in the memory, wherein when the processor executes the program stored in the memory, the processor is configured to perform the method as described in any one of claims 1 to 5.

10. A storage medium, characterized in that, The device stores computer-executable instructions for performing the method as described in any one of claims 1 to 5.

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