A building energy management method, device, equipment and storage medium

Abstract

The present application provides a building energy management method, device, equipment and storage medium, which relates to the field of technical energy regulation. The method includes: dividing the building into multiple areas according to the 3D GIS model of the building, and determining the important index of each area according to the functional type and usage frequency of each area; combining the current energy usage data and historical energy usage data of each area, predicting the energy change trend of each area, and generating energy adjustment plans for each area according to the change trend; adjusting the energy adjustment plan of each area according to the important index of each area, and generating an initial energy adjustment plan for each area; adjusting the initial energy adjustment plan of each area according to the correlation between the areas, and generating a target energy adjustment plan for each area. The technical effect of the present application is: dynamically adjusting the energy supply according to the actual usage and demand of each area in the building.

Description

Technical Field

[0001] The present application relates to the field of energy regulation technology, and specifically to a building energy management method, device, equipment and storage medium. Background Art

[0002] With the development of society, the scale of buildings is constantly expanding, and the floor area of ​​large buildings such as office buildings and shopping malls is getting larger and larger. Such large buildings usually have high energy consumption, and how to achieve intelligent energy management of buildings has become an important technical issue.

[0003] At present, the building energy management system adopts a unified control strategy, that is, the energy supply of the entire building is uniformly dispatched through a central system. However, the building contains areas with different functions, such as office areas, commercial areas, etc. The above method ignores the differences in usage time, traffic flow and equipment conditions of different functional areas in the building; at the same time, the nature of the building is different, and the reference value and energy curve of energy consumption are also different. It is impossible to dynamically adjust the energy supply according to the actual conditions of various buildings and areas, which may lead to energy supply mismatch in some areas, resulting in energy waste. Summary of the invention

[0004] The present application provides a building energy management method, device, equipment and storage medium for dynamically adjusting energy supply according to actual usage and demand of various areas in a building.

[0005] In a first aspect, the present application provides a building energy management method, the method comprising: obtaining a 3D GIS model of a target building, dividing the target building into regions according to the 3D GIS model to obtain a plurality of target regions, and determining an important index of each target region according to the building purpose, functional type, personnel density and usage frequency of each target region; obtaining current energy usage data and historical energy usage data for at least three years for each target region, and providing an evaluation curve; predicting the energy change trend of each target region in combination with the current energy usage data and the historical energy usage data, and generating an energy adjustment plan for each target region and an energy reference value for the next five years based on the energy change trend; adjusting the energy adjustment plan for each target region according to the important index of each target region, and generating an initial energy adjustment plan for each target region; adjusting the initial energy adjustment plan for each target region according to the correlation between each target region, and generating a target energy adjustment plan for each target region.

[0006] By adopting the above technical solutions, by obtaining the 3D GIS model of the building, different target areas in the building are identified, and the functional type and frequency of use of the area are evaluated, and the important index of the area is calculated. Then, the historical and current energy usage data of the area are collected, the future regional demand trend is predicted, and the initial energy adjustment plan for different areas is formulated. Adjustments are made according to the importance of the area, so as to achieve energy priority for key areas. Then, based on the correlation adjustment plan between regions, the differentiated identification of the internal areas of the building is realized, and the energy supply is dynamically adjusted according to the actual use and demand of each area in the building.

[0007] Optionally, dividing the target building into areas according to the 3D GIS model to obtain multiple target areas, including: reading floor information, room information and room usage information of each floor in the 3D GIS model; dividing each floor into initial target areas according to the floor information to obtain multiple first target areas; merging rooms in each first target area that have the same purpose, are adjacent in location and meet a preset area according to the room information and the room usage information in each first target area to obtain the second target area of ​​each floor; and combining the first target area and the second target area of ​​each floor to obtain multiple target areas.

[0008] By adopting the above technical solution, the process of gradually dividing the target area by reading the floor information, room information and room usage in the model is carried out. First, each floor is used as the initial target area according to the floor information. Then, based on the room usage and location, the rooms of the same category and adjacent rooms are merged to obtain a larger second target area to weaken the difference in room granularity. Finally, the initial area and the merged area are combined to form multiple target areas. The effective division of the internal area of ​​the building is achieved, which provides a good foundation for subsequent differentiated energy management.

[0009] Optionally, the building uses include public buildings, parks, residences, offices, and businesses, and the importance index of each target area is determined according to the building use, function type, population density, and usage frequency of each target area, including: obtaining the function type of each target area, where the function type includes an office area, an activity area, and a public area; determining a preset importance index corresponding to each function type, where the preset importance index of the office area is greater than the preset importance index of the activity area, and the preset importance index of the activity area is greater than the preset importance index of the public area; arithmetically multiplying the preset importance index corresponding to the function type of each target area by the usage frequency of each target area to obtain the importance index of each target area.

[0010] By adopting the above technical solution, the functional type of the area is obtained, the corresponding preset index is set according to the functional type, and then the index is calculated in combination with the frequency of use. On this basis, the preset index is further multiplied by the actual frequency of use of the area, so that the final index not only takes into account the difference in functional types, but also reflects the influence of the specific frequency of use. In this way, important office core areas can obtain a higher index to ensure their energy supply. At the same time, the influence of the actual frequency of use is also taken into account to avoid the one-sidedness caused by the functional type alone. Compared with the direct subjective designation of the importance of the area, this calculation method combining preset priority and dynamic frequency can better objectively reflect the importance of the area. It provides effective support for the subsequent differentiated energy management based on importance, and also makes the distinction of the importance of the internal areas of complex buildings more scientific and intelligent.

[0011] Optionally, the combining of the current energy usage data and the historical energy usage data to predict the energy change trend of each of the target areas includes: calculating the average change rate of the historical energy usage of each of the target areas based on the historical energy usage data of each of the target areas; and predicting the energy change trend of each of the target areas within a preset time period by combining the current energy usage data and the average change rate of each of the target areas.

[0012] By adopting the above technical solution, the average change rate is calculated based on historical data, and then combined with current data to predict the trend for a period of time in the future. This solution makes full use of the change law information implicit in the historical energy data of the region. By calculating the average change rate, it can objectively reflect the general trend of regional energy usage over time. On this basis, combining the current actual data with the historical trend can make the forecast reflect the overall change trend and integrate the current actual situation, avoiding the problem of being out of touch with reality due to general trends alone. This historical data-driven forecasting method can make the forecast of regional energy change trends more objective and accurate.

[0013] Optionally, the energy adjustment plan of each target area is adjusted according to the energy consumption index of each target area, and an initial energy adjustment plan and a dynamic curve of each target area are generated, including: obtaining a first target area to be adjusted whose importance index is greater than a first threshold and a second target area to be adjusted whose importance index is less than a second threshold, and the first threshold is greater than the second threshold; adjusting the energy adjustment plan corresponding to the first target area to be adjusted to generate a first initial energy adjustment plan, and the first initial energy adjustment plan includes: increasing the energy supply of the first target area to be adjusted; adjusting the energy adjustment plan corresponding to the second target area to be adjusted to generate a second initial energy adjustment plan, and the second initial energy adjustment plan includes: reducing the energy supply of the second target area to be adjusted.

[0014] By adopting the above technical solution, the importance index of the region is distinguished by setting a double threshold method, and an initial plan is formed according to different adjustment strategies. The region with an importance index higher than the upper threshold is determined as the first region to be adjusted, and an adjustment plan is formulated according to increasing energy supply; the second region to be adjusted below the lower threshold is formulated according to reducing energy supply. The upper threshold is greater than the lower threshold, so the region that meets certain importance requirements can obtain supply guarantees, and the supply of less important regions will be reduced to achieve differentiated treatment. This dual threshold adjustment strategy based on importance distinction enables important regions to obtain better energy supply and realizes the guarantee of core areas. At the same time, it also avoids excessive supply to less important areas and saves energy resources.

[0015] Optionally, the correlation includes spatial correlation and functional correlation, and the initial energy adjustment plan of each target area is adjusted according to the correlation between each target area to generate a target energy adjustment plan for each target area, including: determining the overall correlation between each target area according to the spatial correlation and the functional correlation between each target area; obtaining associated target areas whose overall correlation is greater than a preset threshold, and judging whether there is an adjustment conflict in the initial energy adjustment plan corresponding to the associated target area; if there is an adjustment conflict, adjusting the initial energy adjustment plan corresponding to the target area whose importance index in the associated target area is less than a preset value to generate the target energy adjustment plan of the associated target area; if there is no adjustment conflict, determining the initial energy adjustment plan corresponding to the associated target area as the target energy adjustment plan of the associated target area.

[0016] By adopting the above technical solution, when considering regional correlation, the two aspects of spatial correlation and functional correlation are distinguished, and the overall correlation is calculated and determined by combining the two aspects. For related areas with correlation higher than the threshold, it is further determined whether there is a conflict in their adjustment plan. If there is a conflict, the area with a lower importance index in the related area is selected for adjustment to resolve the conflict. If there is no conflict, the initial adjustment plan of each area is directly adopted. The correlation between regions in the two dimensions of location and function is fully considered, and the degree of correlation between regions can be more comprehensively judged. Conflict judgment and processing of highly correlated areas can effectively coordinate the previously inconsistent adjustment strategies between related areas and realize collaborative management between regions. Through the strategy of correlation evaluation and conflict processing, the coordination between regions can be further improved on the basis of meeting the needs of a single area, and negative interference between related areas can be avoided.

[0017] Optionally, after generating the target energy adjustment plan for each of the target areas, it also includes: sending the target energy adjustment plan for each of the target areas to a building energy management system, so that the building energy management system controls the equipment in each of the target areas to adjust the energy supply according to the received target energy adjustment plan for each of the target areas.

[0018] By adopting the above technical solutions and through the system's automatic control execution capabilities, the scientifically formulated energy management optimization plan can be effectively converted into actual control of equipment in each area. This automated execution technology can efficiently and accurately realize the mapping and execution of energy management plans between virtual and real systems, and convert the value of the plan into real energy control and saving effects.

[0019] In a second aspect, the present application provides a building energy management device, which includes: a first acquisition module, a second acquisition module, a combination module, a first adjustment module and a second adjustment module; wherein the first acquisition module is used to acquire a 3D GIS model of a target building, divide the target building into regions according to the 3D GIS model to obtain a plurality of target regions, and determine the importance index of each target region according to the functional type and usage frequency of each target region; the second acquisition module is used to acquire current energy usage data and historical energy usage data of each target region; the combination module is used to combine the current energy usage data and the historical energy usage data to predict the energy change trend of each target region, and generate an energy adjustment plan for each target region according to the energy change trend; the first adjustment module is used to adjust the energy adjustment plan of each target region according to the importance index of each target region, and generate an initial energy adjustment plan for each target region; the second adjustment module is used to adjust the initial energy adjustment plan of each target region according to the correlation between each target region, and generate a target energy adjustment plan for each target region.

[0020] In a third aspect, the present application provides an electronic device that adopts the following technical solution: it includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program such as any one of the above-mentioned building energy management methods.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: storing a computer program that can be loaded by a processor and execute any of the above-mentioned building energy management methods.

[0022] In summary, the present application includes at least one of the following beneficial technical effects:

[0023] 1. Dynamically adjust energy supply based on actual usage and demand in each area of ​​the building;

[0024] 2. The correlation between regions in terms of location and function is fully considered, and the degree of correlation between regions can be more comprehensively judged. Conflict judgment and processing of highly correlated regions can effectively coordinate the previously inconsistent adjustment strategies between related regions and achieve collaborative management between regions. Through the strategies of correlation assessment and conflict processing, the coordination between regions can be further improved on the basis of meeting the needs of a single region, avoiding negative interference between related regions. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a flow chart of a building energy management method provided in an embodiment of the present application;

[0026] Figure 2 It is a structural schematic diagram of a building energy management device provided in an embodiment of the present application;

[0027] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0028] Description of reference numerals: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0030] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0031] Figure 1 It is a flow chart of a building energy management method provided in an embodiment of the present application. It should be understood that although Figure 1The steps in the flowchart are shown in sequence as indicated by the arrows, but the steps are not necessarily executed in the order indicated by the arrows; unless otherwise specified in this document, there is no strict order restriction for the execution of the steps, and the steps may be executed in other orders; and Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0032] The present application discloses a building energy management method, such as Figure 1 As shown, the method includes S101-S104.

[0033] S101, obtaining a 3D GIS model of a target building, dividing the target building into regions according to the 3D GIS model to obtain a plurality of target regions, and determining an important index of each target region according to a functional type and a usage frequency of each target region.

[0034] 3D GIS models can be built using professional 3D GIS software, such as Revit, ArchiCAD, etc. The model building process includes: Collecting 2D design drawings of the target building, such as floor plans, elevations, and sections. Build the overall structure of the 3D model in the 3D GIS software, including architectural elements such as walls, floors, stairs, doors, and windows. Map the room and space information in the design drawings to the 3D model, and add specific attributes of the room, such as height, purpose, and area. Continue to add non-spatial elements, such as pipelines, equipment, furniture, and other details. Add materials and rendering effects, and output 3D GIS models in different formats.

[0035] Determination of the important index: The important index can take into account the following factors: functional type: office area>activity area>public area; frequency of use: the higher the index of an area with a high frequency of use; area area: the larger the area, the larger the index; special areas: special areas such as computer rooms and stairwells can be set with a higher index; management setting: the index of certain areas is set manually according to management needs.

[0036] The calculation of the importance index can be realized by a professional algorithm, or it can be calculated according to certain weights with reference to data such as frequency of use and area ratio. The importance index can select one or more of the above dimensions according to actual conditions, or add other dimensions. For the specific calculation method, please refer to the following embodiment, which will not be described in detail here.

[0037] In one example, the purpose of this embodiment is to obtain a 3D GIS model of a target building and perform building area division to determine the important index of each area. First, a 3D GIS three-dimensional digital model of the target building is obtained, which contains detailed information such as geometric information, material information, location information, functional zoning information, etc. of the target building. Then, based on the floor information, room information, and room usage information of each floor in the 3D GIS model, each floor can be divided into multiple initial target areas, that is, the rooms on each floor are grouped and merged according to their location and purpose. Then, based on the purpose and area requirements of the rooms in the area, the rooms with the same purpose and adjacent positions can be further merged to obtain another target area on the floor. By summarizing the target areas obtained on each floor, the division results of multiple target areas of the entire building can be obtained.

[0038] The purpose of regional division is to accurately locate each area and determine the functional type of the area. Therefore, after obtaining each target area, it is necessary to determine its importance index based on the functional type of the area (such as office, public activities, etc.) and the frequency of use. The more important the area, the greater its importance index. The purpose of determining the importance index of each area is to provide a basis for subsequent regional energy management.

[0039] The precise division of regions using 3D GIS models and the determination of important indexes for the characteristics of each region have laid the foundation for the subsequent refined energy management of target buildings in different regions. Energy regulation can be carried out in each region in a targeted manner, thereby achieving the goal of improving energy utilization efficiency and saving energy.

[0040] Based on the above embodiment, as an optional implementation, in S101, dividing the target building into regions according to the 3D GIS model to obtain multiple target regions specifically includes the following steps:

[0041] S201, reading the floor information, room information and room usage information of each floor in the 3D GIS model.

[0042] Specifically, floor information mainly refers to the specific attributes of each floor in the 3D GIS model, including: floor number: such as the first floor, the second floor, etc.; floor height: the specific height of each floor; floor area: the floor area of ​​the entire floor.

[0043] Room information refers to the information of different rooms on each floor, including: room number: unique identification such as Room 101, Room 201, etc.; room location: the plane location coordinates of the room; room area: the usable area of ​​the room; room height: the vertical height of the room.

[0044] Room usage information: refers to the functional type of the room, including: office, conference room, tea room, etc.; equipment room, machine room, elevator room, etc.; public areas such as toilets and corridors. Through the 3D GIS model, detailed information on each floor and room in the building can be obtained, providing basic data for subsequent regional division.

[0045] S202, dividing each floor into initial target areas according to the floor information to obtain a plurality of first target areas;

[0046] S203: Based on the room information and room usage information in each first target area, the rooms in each first target area that have the same usage, are adjacent in location and meet the preset area are merged to obtain the second target area on each floor.

[0047] In one example, in the first target area, based on the existing room information and room usage information in the 3D GIS model, rooms with the same usage (e.g., all offices) and adjacent locations (i.e., shared walls on the plane) can be selected for merging. At the same time, the total area of ​​the merged rooms needs to meet the preset minimum area requirement (e.g., reaching 50 square meters or more) to avoid the area being too small. According to this method, the offices in the first target area can be merged one by one. If the merged area meets the requirements, a second target area is formed.

[0048] After the detailed merging of rooms as basic units, the second target area with a single function and a reasonable area can be obtained, which improves the first target area division scheme that is only divided by floors. This division method makes the room functions and usage properties in the area more consistent, and is also convenient for the later statistics of regional energy consumption. It is also convenient for classification management according to the room and regional function types.

[0049] S204: The first target area and the second target area of ​​each floor are combined to obtain a plurality of target areas.

[0050] Based on the above embodiment, as an optional implementation, in S101, determining the importance index of each target area according to the function type and usage frequency of each target area specifically includes:

[0051] The function type of each target area is obtained, and the function type includes an office area, an activity area, and a public area. The preset importance index corresponding to each function type is determined, wherein the preset importance index of the office area is greater than the preset importance index of the activity area, and the preset importance index of the activity area is greater than the preset importance index of the public area. The preset importance index corresponding to the function type of each target area is multiplied by the usage frequency of each target area to obtain the importance index of each target area.

[0052] In one example, after obtaining the various areas of the target building, it is necessary to determine the importance index of each area, which is used to evaluate the importance of the area. The reason for determining the importance index is to distinguish between core areas and non-core areas so as to carry out differentiated energy management later.

[0053] Specifically, first, the area can be divided into office area, activity area and public area according to the functional type of the room. Then, different important index range values ​​are preset for different types, with the office area having the largest index, the public area having the smallest index, and the activity area being in the middle. Because the office area is the core area to ensure daily work, the activity area is second, and the public area can be appropriately reduced. Next, the actual frequency of use data of the area can be obtained, multiplied by the preset index, and the digitized important index that comprehensively considers the area type and frequency of use can be calculated.

[0054] For example, a frequently used office area has a high importance index, while a public area that is used occasionally has a low importance index. This method can make the importance index meet actual needs and more accurately reflect the core degree of the area. This provides a basis for the subsequent formulation of differentiated energy-saving strategies, which not only guarantees the energy demand of the core area, but also can save energy according to the actual situation of the non-core area.

[0055] S102, obtaining the current energy usage data of each target area and the historical energy usage data of at least three years, and providing an evaluation curve.

[0056] In one example, after completing the regional division of the target building and determining the important indexes of each target area, it is necessary to obtain the current and past energy usage data of each target area. Generally speaking, it is necessary to obtain at least three years of historical energy utility data for regional energy usage analysis. The evaluation curve is a key tool for analyzing and evaluating the energy usage of the target area. Specifically, the evaluation curve compares and analyzes the current energy usage data with the historical energy usage data to help identify trends, anomalies, and opportunities for improvement. The evaluation curve is a graphical representation tool used to show the energy usage of the target area over different time periods. It combines current energy usage data with at least three years of historical energy usage data to provide intuitive trend and pattern analysis.

[0057] Specifically, by installing smart meters and other sensor equipment in each target area, real-time data on the area's light, temperature and humidity, equipment energy consumption, and other parameters can be collected, and energy consumption can be calculated based on the area and usage time, to obtain the current energy usage data for the target area. At the same time, it is also necessary to obtain energy usage data for each area over a period of time in the past, in order to establish a database for energy usage patterns in different seasons and time periods.

[0058] The effect of obtaining the current and past energy usage data of the target area is that the energy usage patterns of each area can be analyzed according to the database. For example, the office area has a large amount of electricity consumption during rush hour. By combining it with important indexes, it can be determined which areas have serious energy waste; at the same time, it can also determine the areas with more reasonable energy use, which can be used as a benchmark for evaluating the effectiveness of energy management. This provides a basis for subsequent regional energy use forecasts and the formulation of adjustment measures.

[0059] By obtaining detailed energy usage data of the target area, support is provided for the refinement of regional energy management, so that the energy management strategy can be optimized according to the characteristics of each target area, thereby achieving the effect of improving energy utilization efficiency and saving energy usage.

[0060] S103, combining the current energy usage data and the historical energy usage data, predicting the energy change trend of each target area, and generating an energy adjustment plan for each target area and an energy reference value for the next five years based on the energy change trend.

[0061] In one example, after obtaining the current and historical energy usage data of each target area, it is necessary to predict the energy change trend of each area in the future based on these data, and formulate an energy adjustment plan based on the energy demand changes in the area in the future to improve energy utilization efficiency.

[0062] Specifically, it includes: analyzing the average change rate of energy consumption in each target area over the past period of time based on historical energy usage data, which can reflect the general law of energy demand changes in different regions. Combining with current energy usage data, it can be determined whether there are special changes in regional energy demand, and then based on the average change rate, it can be predicted how the energy demand of each region will change in the future, such as how much it will increase or decrease.

[0063] Based on the prediction of future energy change trends, energy adjustment plans can be formulated for each target area. For example, if it is predicted that the energy demand in a certain area will decrease significantly in the next week, the lighting, air conditioning and other equipment in that area can be reduced to avoid energy waste. On the contrary, if it is predicted that the energy demand in a certain area will increase, the power system in that area can be increased in advance to ensure demand.

[0064] By combining the current and historical energy usage data of the target area to predict future demand trends, the energy management adjustment strategy can be made more in line with the actual situation, avoiding resource waste or supply and demand contradictions caused by blind adjustments, thereby achieving scientific and refined energy management and saving more energy.

[0065] The energy reference values ​​for the next five years are the expected energy consumption of each target area in the next five years predicted based on current energy usage data and historical energy usage data. These reference values ​​can help the building management system formulate long-term energy management strategies to ensure efficient and sustainable energy use.

[0066] Specifically, energy reference values ​​for the next five years are derived by analyzing the changing trends of historical data and current usage. These values ​​provide a quantitative estimate of future energy demand, enabling managers to plan energy supply in advance, develop energy-saving measures, and optimize energy distribution.

[0067] Based on the above embodiment, as an optional implementation scheme, in S103, combining the current energy usage data and the historical energy usage data, predicting the energy change trend of each target area specifically includes:

[0068] Based on the historical energy usage data of each target area, the average change rate of historical energy usage of each target area is calculated; combined with the current energy usage data and the average change rate of each target area, the energy change trend of each target area within a preset time period is predicted.

[0069] In one example, in order to formulate a reasonable energy adjustment plan for each target area, it is necessary to predict the energy change trend of these areas in the future. Specifically, first, the monthly energy consumption data of each area in the past year can be collected to calculate the average change rate of energy usage in each area in the past year. The change rate can reflect the seasonal change law of regional energy demand. Then, combined with the actual energy usage data of the latest month, it is judged whether there are new changes in demand. Finally, based on the change rate, combined with the actual situation, the energy demand change trend of each region in the next three months is predicted, such as demand will increase by 20% or decrease by 10%.

[0070] By analyzing historical data to summarize the changing trends and adjusting the forecast based on the current new data, the future energy demand forecast can be more accurate and in line with the latest actual conditions in each region. The energy adjustment plan formulated on this basis will also be more scientific and reasonable, which will not cause waste due to inaccurate forecasts and can also meet the actual changes in regional demand.

[0071] S104, adjusting the energy adjustment plan of each target area according to the important index of each target area, and generating an initial energy adjustment plan of each target area.

[0072] In one example, after predicting the future energy change trend of each target area and formulating a corresponding energy adjustment plan, it is necessary to further adjust the energy adjustment plan according to the important index of each area to generate an initial energy adjustment plan.

[0073] In actual operation, the energy supply of regions with different importance should be different. The more important the region is, the more stable and sufficient its energy supply should be, which is related to the normal operation of the region. Specifically, two importance index thresholds are set in advance. Regions with importance indexes higher than the upper threshold can increase their energy supply, while regions with importance indexes lower than the lower threshold can appropriately reduce their energy supply.

[0074] For example, for office areas with a high importance index, if its energy demand is predicted to increase, its power distribution system can be upgraded in advance to ensure subsequent power supply; for storage areas with a low importance index, redundant power supply and lighting can be appropriately reduced. In addition, for areas with a medium importance index, the original supply can be kept unchanged.

[0075] By adjusting the energy adjustment plan in combination with important indexes, important areas can be given priority in obtaining energy security, while non-important areas can appropriately reduce energy acquisition, thereby improving energy utilization efficiency and maximizing the effectiveness of limited energy resources. This energy management that takes regional differences into consideration is also more in line with actual needs.

[0076] Based on the above embodiment, as an optional implementation, in S104, adjusting the energy adjustment plan of each target area according to the important index of each target area, and generating the initial energy adjustment plan of each target area specifically includes:

[0077] Acquire a first target area to be adjusted whose importance index is greater than a first threshold and a second target area to be adjusted whose importance index is less than a second threshold, wherein the first threshold is greater than the second threshold; adjust the energy adjustment plan corresponding to the first target area to be adjusted to generate a first initial energy adjustment plan, wherein the first initial energy adjustment plan includes: increasing the energy supply to the first target area to be adjusted; adjust the energy adjustment plan corresponding to the second target area to be adjusted to generate a second initial energy adjustment plan, wherein the second initial energy adjustment plan includes: reducing the energy supply to the second target area to be adjusted.

[0078] In one example, after predicting the energy change trend of each target area, it is necessary to further adjust the energy adjustment plan according to the importance index. Specifically, a higher and a lower importance index threshold can be set in advance. First, the important areas with importance indexes higher than the higher threshold are screened out as the first areas to be adjusted, and the non-important areas with importance indexes lower than the lower threshold are screened out as the second areas to be adjusted. Then, on the basis of the original adjustment plan, the energy supply to the first area to be adjusted is increased, such as adding a backup power supply, etc., to form a first initial adjustment plan. The energy supply to the second area to be adjusted can be reduced, such as by appropriately shutting down some equipment, to form a second initial adjustment plan.

[0079] Through such differentiated adjustments, important areas can be given priority in energy supply, and non-important areas can appropriately reduce energy consumption. This not only meets the differences in regional importance, but also improves the overall energy efficiency of the building. Moreover, regional adjustments based on different thresholds can prevent insufficient supply in important areas.

[0080] Assume that there are three target areas: Office Area A: This area is the core office area of ​​the office building, and the importance index is calculated as 90 points. Auxiliary Area B: This area is the auxiliary area of ​​the office building, such as the printing room and archive room, and the importance index is calculated as 60 points. Public Area C: This area is the public area of ​​the office building, such as the lobby, stairwell, corridor, etc., and the importance index is calculated as 40 points. First, set the high threshold line of the importance index to 80 points and the low threshold line to 50 points. Then the index of Office Area A is higher than 80 points, and it is designated as the first area to be adjusted; the index of Public Area C is lower than 50 points, and it is designated as the second area to be adjusted. For Office Area A, air conditioning and lighting equipment are added on the basis of the original adjustment plan to ensure the energy demand of the office, forming the first initial adjustment plan. For Public Area C, the lighting equipment opening time in non-critical areas is appropriately reduced to form the second initial adjustment plan. Through such differentiated adjustments, better energy security and supply effects are achieved in important areas.

[0081] S105, adjusting the initial energy adjustment plan of each target area according to the correlation between each target area, and generating a target energy adjustment plan for each target area.

[0082] In one example, after generating an initial energy adjustment plan for each target area according to the important index, it is also necessary to consider the correlation between the target areas and further adjust the initial plan to generate a final target energy adjustment plan.

[0083] Because multiple target areas are functionally and spatially related, energy adjustments between areas will affect each other. The correlation between areas is determined based on the spatial proximity of the areas and the similarity of their functions. For areas with high correlation, their energy adjustment plans need to be reasonably coordinated to avoid supply and demand conflicts.

[0084] For example, according to the important index, the original plan for conference room A is to increase the power supply, while the plan for its adjacent conference room B is to reduce the power supply. Since the two spaces are adjacent and have similar functions, there is a strong correlation. In order to avoid unbalanced power load, the plan for conference room B can be readjusted to keep its power supply unchanged.

[0085] By considering the correlation between target areas, energy adjustments in each area can be made more coordinated and reasonable, avoiding the negative impact caused by adjusting a certain area alone. The final target energy adjustment plan can further improve the overall benefits of energy management on the basis of meeting regional supply and demand.

[0086] Based on the above embodiment, as an optional implementation, in S105, the correlation includes spatial correlation and functional correlation. According to the correlation between the target areas, the initial energy adjustment plan of each target area is adjusted, and the target energy adjustment plan of each target area is generated, which specifically includes the following steps:

[0087] S501, determining the overall correlation between the target areas according to the spatial correlation and functional correlation between the target areas.

[0088] Specifically, spatial correlation mainly refers to the degree of correlation between target areas in terms of spatial location. Specifically, the following aspects can be considered: whether there are shared walls, floors and other architectural elements between areas; the distance between areas in a straight line; whether the areas are located on the same floor or consecutive floors; whether there are passages between areas that facilitate the flow of people.

[0089] Functional relevance: mainly refers to the degree of functional relevance of the target areas. The following factors can be considered: whether the functional types of the areas are the same or similar; whether the user groups of the areas overlap; whether there is a correlation in the use time of the areas; and whether the energy supply systems of the areas are shared.

[0090] Overall relevance: Taking into account spatial relevance and functional relevance, the degree of relevance between regions is evaluated as a whole. Usually, each indicator can be quantified and scored, and the overall relevance can be determined by calculating the scores comprehensively.

[0091] For example, firstly, the positional relationship between regions is evaluated based on the spatial correlation of the regions, such as adjacent regions and regions on the same floor have stronger spatial correlation. Then, the functional correlation is evaluated based on factors such as the similarity of regional functional types and the overlap of usage time. Then, the evaluation of spatial correlation and functional correlation can be quantified into indicators for calculation to obtain the overall correlation score of the two regions.

[0092] After obtaining the correlation indicators between the regions, we focus on the regions with strong correlation and analyze whether there are contradictions in their initial adjustment plans. For example, if one adjacent region increases the power supply while the other decreases, load imbalance will occur. Then we can coordinate the plans of the two regions to achieve synergy and consistency.

[0093] S502, obtaining associated target areas whose overall association is greater than a preset threshold, and determining whether there is an adjustment conflict in the initial energy adjustment plan corresponding to the associated target area.

[0094] In one example, after calculating the correlation index between the target areas, it is necessary to screen out the strongly correlated areas whose correlation is greater than a preset threshold, and further determine whether there is a conflict between the initial adjustment plans of these areas.

[0095] A threshold for correlation evaluation is set in advance, and all combinations of regions with correlation scores higher than the threshold are selected as correlation target regions. Then the initial adjustment plans of these regions are compared to determine whether there are any contradictions between the plans. For example, the power supply adjustment of adjacent regions is increased while that of adjacent regions is decreased, or there is an incoordination in the adjustment during the peak period of energy consumption in functionally related regions.

[0096] By identifying areas with strong correlation and potential conflicts, it can provide a basis for the coordination and optimization of subsequent adjustment plans. The specific plans that determine the conflicts can be revised so that the final target plans of the related areas can be coordinated and consistent, eliminating potential conflicts.

[0097] S503: If there is an adjustment conflict, the initial energy adjustment plan corresponding to the target area whose importance index in the associated target area is less than a preset value is adjusted to generate a target energy adjustment plan for the associated target area.

[0098] In one example, the areas with lower importance indexes in the conflicting area combination will be selected as the adjustment objects first. This is because the energy supply of the areas with higher importance indexes needs to be ensured more, and the adjustment plans of these areas are prioritized. Then, the energy supply of the area to be adjusted can be appropriately increased or decreased to coordinate its plan with the associated areas.

[0099] For example, if the storage room, which was originally planned to reduce power supply, conflicts with the adjacent office, which will increase power supply, the original power supply plan for the storage room can be appropriately increased to achieve a coordinated match with the increased power supply for the office.

[0100] S504: If there is no adjustment conflict, determining the initial energy adjustment plan corresponding to the associated target area as the target energy adjustment plan of the associated target area.

[0101] After generating the target energy adjustment plan for each target area, it also includes: sending the target energy adjustment plan for each target area to the building energy management system, so that the building energy management system controls the equipment in each target area to adjust the energy supply according to the received target energy adjustment plan for each target area.

[0102] In one example, after the target area is determined, energy forecasting is carried out, preliminary plan formulation is made, and plan optimization is carried out, an energy adjustment plan optimized for each target area is formed. Next, these adjustment plans need to be transmitted to the building's energy management system to complete the actual control of the regional equipment.

[0103] Specifically, the detailed parameters of the equipment control in the solution, such as the value of the air conditioning temperature adjustment and the proportion of the lighting brightness adjustment, can be transmitted to the building management system in a standardized format. The system can parse the received parameters and use the internal control program to send control instructions to the equipment in each area to achieve automatic adjustment of the equipment status, such as turning off the lighting on a specific floor or lowering the office temperature by 2 degrees Celsius.

[0104] In this way, the regional energy adjustment plan can be smoothly transformed into the control execution of actual equipment, ultimately achieving scientific and reasonable building energy management and saving energy consumption. At the same time, the optimized control plan can also be stored as historical data for reference when adjusting the subsequent plan.

[0105] Based on the above method, the present application also discloses a building energy management device, such as Figure 2 As shown, Figure 2 It is a structural schematic diagram of a building energy management device provided in an embodiment of the present application.

[0106] A building energy management device comprises: a first acquisition module, a second acquisition module, a combination module, a first adjustment module and a second adjustment module; wherein the first acquisition module is used to acquire a 3D GIS model of a target building, divide the target building into regions according to the 3D GIS model, obtain a plurality of target regions, and determine the important index of each target region according to the function type and the use frequency of each target region; the second acquisition module is used to acquire the current energy use data of each target region and the historical energy use data of at least three years, and provide an evaluation curve; the combination module is used to combine the current energy use data with the historical energy use data, predict the energy change trend of each target region, and generate the energy adjustment plan of each target region and the energy reference value for the next five years according to the energy change trend; the first adjustment module is used to adjust the energy adjustment plan of each target region according to the important index of each target region, and generate the initial energy adjustment plan of each target region; the second adjustment module is used to adjust the initial energy adjustment plan of each target region according to the correlation between each target region, and generate the target energy adjustment plan of each target region.

[0107] In one example, the first acquisition module is also used to read the floor information, room information and room usage information of each floor in the 3D GIS model; according to the floor information, each floor is divided into an initial target area to obtain multiple first target areas; according to the room information and room usage information in each first target area, the rooms with the same purpose, adjacent locations and meeting the preset area in each first target area are merged to obtain the second target area of ​​each floor; the first target area and the second target area of ​​each floor are combined to obtain multiple target areas.

[0108] In one example, the first acquisition module is also used to obtain the functional type of each target area, the functional types including office area, activity area and public area; determine the preset importance index corresponding to each functional type, wherein the preset importance index of the office area is greater than the preset importance index of the activity area, and the preset importance index of the activity area is greater than the preset importance index of the public area; multiply the preset importance index corresponding to the functional type of each target area by the usage frequency of each target area to obtain the importance index of each target area.

[0109] In one example, the combination module is also used to calculate the average change rate of historical energy usage of each target area based on the historical energy usage data of each target area; and combine the current energy usage data and the average change rate of each target area to predict the energy change trend of each target area within a preset time period.

[0110] In one example, the first adjustment module is also used to obtain a first target area to be adjusted whose importance index is greater than a first threshold and a second target area to be adjusted whose importance index is less than a second threshold, wherein the first threshold is greater than the second threshold; adjust the energy adjustment plan corresponding to the first target area to be adjusted to generate a first initial energy adjustment plan, and the first initial energy adjustment plan includes: increasing the energy supply of the first target area to be adjusted; adjust the energy adjustment plan corresponding to the second target area to be adjusted to generate a second initial energy adjustment plan, and the second initial energy adjustment plan includes: reducing the energy supply of the second target area to be adjusted.

[0111] Optionally, the first adjustment module is also used to determine the overall correlation between the target areas based on the spatial correlation and functional correlation between the target areas; obtain the associated target areas whose overall correlation is greater than a preset threshold, and determine whether there is an adjustment conflict in the initial energy adjustment plan corresponding to the associated target area; if there is an adjustment conflict, adjust the initial energy adjustment plan corresponding to the target area whose importance index in the associated target area is less than a preset value, and generate a target energy adjustment plan for the associated target area; if there is no adjustment conflict, determine the initial energy adjustment plan corresponding to the associated target area as the target energy adjustment plan for the associated target area.

[0112] Optionally, the above-mentioned device is also used to send the target energy adjustment plan of each target area to the building energy management system, so that the building energy management system controls the equipment in each target area to adjust the energy supply according to the received target energy adjustment plan of each target area.

[0113] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0114] See also Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0115] The communication bus 1002 is used to realize the connection and communication between these components.

[0116] The user interface 1003 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0117] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0118] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented separately through a chip.

[0119] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may optionally also be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of a building energy management method.

[0120] exist Figure 3In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call an application program storing a building energy management method in the memory 1005. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0121] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0122] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0123] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0124] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0125] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0126] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0127] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0128] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A building energy management method, characterized in that: The method comprises: A 3D GIS model of a target building is obtained, and the target building is divided into regions according to the 3D GIS model to obtain a plurality of target regions, and an important index of each target region is determined according to a functional type and a usage frequency of each target region; the determining the important index of each target region according to the functional type and the usage frequency of each target region includes: obtaining a functional type of each target region, and the functional type includes an office area, an activity area, and a public area; Determine a preset importance index corresponding to each of the function types, wherein the preset importance index of the office area is greater than the preset importance index of the activity area, and the preset importance index of the activity area is greater than the preset importance index of the public area; Multiplying the preset importance index corresponding to the function type of each target area by the usage frequency of each target area to obtain the importance index of each target area; Obtaining current energy usage data and historical energy usage data of each target area, and providing an evaluation curve; Combine the current energy usage data and the historical energy usage data to predict the energy change trend of each target area, and generate an energy adjustment plan for each target area and an energy reference value for the next five years based on the energy change trend; According to the important index of each target area, the energy adjustment plan of each target area is adjusted to generate the initial energy adjustment plan of each target area; according to the important index of each target area, the energy adjustment plan of each target area is adjusted to generate the initial energy adjustment plan of each target area, including: Acquire a first target area to be adjusted whose importance index is greater than a first threshold and a second target area to be adjusted whose importance index is less than a second threshold, wherein the first threshold is greater than the second threshold; Adjusting the energy adjustment plan corresponding to the first target area to be adjusted to generate a first initial energy adjustment plan, wherein the first initial energy adjustment plan includes: increasing the energy supply to the first target area to be adjusted; Adjusting the energy adjustment plan corresponding to the second target area to be adjusted to generate a second initial energy adjustment plan, wherein the second initial energy adjustment plan includes: reducing the energy supply of the second target area to be adjusted; According to the correlation between each of the target areas, the initial energy adjustment plan of each of the target areas is adjusted to generate a target energy adjustment plan for each of the target areas; the correlation includes spatial correlation and functional correlation, and according to the correlation between each of the target areas, the initial energy adjustment plan of each of the target areas is adjusted to generate a target energy adjustment plan for each of the target areas, including: determining the overall correlation between each of the target areas according to the spatial correlation and the functional correlation between each of the target areas; obtaining the associated target areas whose overall correlation is greater than a preset threshold, and judging whether there is an adjustment conflict in the initial energy adjustment plan corresponding to the associated target area; if there is an adjustment conflict, adjusting the initial energy adjustment plan corresponding to the target area whose importance index in the associated target area is less than a preset value to generate the target energy adjustment plan for the associated target area; if there is no adjustment conflict, determining the initial energy adjustment plan corresponding to the associated target area as the target energy adjustment plan for the associated target area.

2. The building energy management method according to claim 1, characterized in that: The target building is divided into regions according to the 3D GIS model to obtain a plurality of target regions, including: Reading floor information, room information and room usage information of each floor in the 3D GIS model; According to the floor information, each of the floors is divided into an initial target area to obtain a plurality of first target areas; According to the room information and the room usage information in each of the first target areas, the rooms in each of the first target areas that have the same usage, are adjacent in location and meet the preset area are merged to obtain the second target area on each of the floors; The first target areas and the second target areas of each of the floors are combined to obtain a plurality of target areas.

3. The building energy management method according to claim 1, characterized in that: The combining the current energy usage data and the historical energy usage data to predict the energy change trend of each target area includes: Calculating the average change rate of the historical energy usage of each target area according to the historical energy usage data of each target area; The energy change trend of each target area within a preset time period is predicted by combining the current energy usage data and the average change rate of each target area.

4. The building energy management method according to claim 1, characterized in that: After the target energy adjustment plan for each target area is generated, the method further includes: The target energy adjustment plan of each target area is sent to a building energy management system, so that the building energy management system controls the equipment in each target area to adjust the energy supply according to the received target energy adjustment plan of each target area.

5. A building energy management device, characterized in that: The device comprises: a first acquisition module, a second acquisition module, a combination module, a first adjustment module and a second adjustment module; wherein, The first acquisition module is used to acquire a 3D GIS model of a target building, divide the target building into regions according to the 3D GIS model to obtain a plurality of target regions, and determine the importance index of each target region according to the function type and usage frequency of each target region; the determining the importance index of each target region according to the function type and usage frequency of each target region includes: acquiring the function type of each target region, the function type including office area, activity area and public area; Determine a preset importance index corresponding to each of the function types, wherein the preset importance index of the office area is greater than the preset importance index of the activity area, and the preset importance index of the activity area is greater than the preset importance index of the public area; Multiplying the preset importance index corresponding to the function type of each target area by the usage frequency of each target area to obtain the importance index of each target area; The second acquisition module is used to acquire the current energy usage data and the historical energy usage data of each target area, and provide an evaluation curve; The combining module is used to combine the current energy usage data and the historical energy usage data to predict the energy change trend of each target area, and generate an energy adjustment plan for each target area and an energy reference value for the next five years based on the energy change trend; The first adjustment module is used to adjust the energy adjustment scheme of each target area according to the important index of each target area, and generate the initial energy adjustment scheme of each target area; the energy adjustment scheme of each target area according to the important index of each target area is adjusted to generate the initial energy adjustment scheme of each target area, including: Acquire a first target area to be adjusted whose importance index is greater than a first threshold and a second target area to be adjusted whose importance index is less than a second threshold, wherein the first threshold is greater than the second threshold; Adjusting the energy adjustment plan corresponding to the first target area to be adjusted to generate a first initial energy adjustment plan, wherein the first initial energy adjustment plan includes: increasing the energy supply to the first target area to be adjusted; Adjusting the energy adjustment plan corresponding to the second target area to be adjusted to generate a second initial energy adjustment plan, wherein the second initial energy adjustment plan includes: reducing the energy supply of the second target area to be adjusted; The second adjustment module is used to adjust the initial energy adjustment plan of each target area according to the correlation between each target area, and generate a target energy adjustment plan for each target area; the correlation includes spatial correlation and functional correlation, and the initial energy adjustment plan of each target area is adjusted according to the correlation between each target area to generate a target energy adjustment plan for each target area, including: determining the overall correlation between each target area according to the spatial correlation and the functional correlation between each target area; obtaining the associated target area whose overall correlation is greater than a preset threshold, and judging whether there is an adjustment conflict in the initial energy adjustment plan corresponding to the associated target area; if there is an adjustment conflict, adjusting the initial energy adjustment plan corresponding to the target area whose importance index in the associated target area is less than a preset value, and generating the target energy adjustment plan for the associated target area; if there is no adjustment conflict, determining the initial energy adjustment plan corresponding to the associated target area as the target energy adjustment plan for the associated target area.

6. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 4.

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