A commercial office building energy management system, method and device

Abstract

The present application provides a commercial office building energy management system, method and equipment, the system includes intelligent meters, network communication equipment, server cloud and terminal equipment; data collection function is realized based on intelligent meters and network communication equipment, analysis and diagnosis function is realized based on server cloud, and interactive application function is realized based on terminal equipment; intelligent meters collect energy data of each metering point in commercial office buildings according to the distribution system structure of commercial office buildings; network communication equipment sends energy data to server cloud; server cloud performs data analysis based on energy data and outputs diagnostic suggestions; terminal equipment interacts with operation and management personnel based on diagnostic suggestions. The present application can comprehensively collect energy data of commercial office buildings, analyze energy data from different dimensions, ensure data quality, and promptly warn of abnormal data, thereby improving the efficiency and convenience of energy management and reducing energy waste and loss.

Description

Technical Field

[0001] The present application relates to the field of energy management technology, and in particular to a commercial office building energy management system, method and equipment. Background Art

[0002] In commercial office buildings, there are many existing energy management system products, but most of them have single functions, only simple functions such as automatic metering, report statistics, and year-on-year and month-on-month energy consumption of smart energy consumption meters, and their practical value is limited. The energy management system has the problem of information islands. The meters at the consumer end of the energy management object are scattered in various systems. There is no reasonable topological structure, and the upper and lower structure correlation analysis and application cannot be carried out, and the potential value of energy data cannot be mined.

[0003] Most existing energy management systems remain at the level of data collection and data display, and their data analysis and diagnosis application functions for actual operation and management needs are relatively weak. In addition, there are also problems with the standardization and unification of equipment and system configuration, which leads to poor interoperability of energy management systems and imperfect application functions. Summary of the invention

[0004] The present application provides a commercial office building energy management system and method thereof, which are used to comprehensively collect energy data of commercial office buildings, analyze energy data from different dimensions, ensure data quality, issue timely alarms for abnormal data, improve the efficiency and convenience of energy management, and reduce energy waste and loss.

[0005] In a first aspect, the present application provides a commercial office building energy management system, the commercial office building energy management system comprising a smart meter, a network communication device, a server cloud and a terminal device; a data collection function is implemented based on the smart meter and the network communication device, an analysis and diagnosis function is implemented based on the server cloud, and an interactive application function is implemented based on the terminal device;

[0006] The smart meter is used to collect energy data of various metering points in the commercial office building according to the power distribution system structure of the commercial office building;

[0007] The network communication device is used to send the energy data to the server cloud;

[0008] The server cloud is used to perform data analysis based on the energy data and output diagnostic suggestions; the data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis;

[0009] The terminal device is used to perform interactive applications with operation management personnel based on the diagnostic suggestions; the interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction and data alarm interaction.

[0010] In a second aspect, the present application further provides a commercial office building energy management method, which is applied to the commercial office building energy management system as described in any one of the first aspects, wherein the commercial office building energy management includes smart meters, network communication equipment, server cloud and terminal equipment, and the method includes:

[0011] The smart meter collects energy data of each metering point in the commercial office building according to the power distribution system structure of the commercial office building;

[0012] Sending the energy data to the server cloud via the network communication device;

[0013] The server cloud performs data analysis based on the energy data and outputs diagnostic suggestions; the data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis;

[0014] The terminal device is used to interact with the operation management personnel according to the diagnostic suggestions; the interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction, and data alarm interaction.

[0015] The present application also provides an electronic device, including: a memory for storing a computer program; a processor for reading and executing the computer program, thereby implementing the commercial office building energy management method as described above.

[0016] The present application also provides a non-transitory computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the commercial office building energy management method as described above is implemented.

[0017] The present application also provides a computer program product, including a computer program, which implements the commercial office building energy management method as described above when the computer program is executed by a processor.

[0018] The commercial office building energy management system provided in the embodiment of the present application includes smart meters, network communication equipment, server cloud and terminal equipment; data collection function is realized based on smart meters and network communication equipment, analysis and diagnosis function is realized based on server cloud, and interactive application function is realized based on terminal equipment; smart meters are used to collect energy data of various metering points in commercial office buildings according to the distribution system structure of commercial office buildings; network communication equipment is used to send energy data to server cloud; server cloud is used to perform data analysis based on energy data and output diagnostic suggestions; data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis; terminal equipment is used to interact with operation management personnel according to diagnostic suggestions; interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction and data alarm interaction, therefore, energy data of commercial office buildings can be comprehensively collected, energy data analysis can be performed from different dimensions, data quality can be guaranteed, abnormal data can be timely alarmed, the efficiency and convenience of energy management can be improved, and energy waste and loss can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the structure of the commercial office building energy management system provided by this application;

[0020] Figure 2 It is a schematic diagram of the power distribution system structure of a commercial office building provided by the present application;

[0021] Figure 3 It is a schematic diagram of the application workflow of the commercial office building energy management system provided by this application;

[0022] Figure 4 It is a flow chart of the commercial office building energy management method provided by this application;

[0023] Figure 5 A schematic diagram of an embodiment of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0025] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, "plurality" means two or more, unless otherwise clearly and specifically defined.

[0026] In the description of the present application, the term "for example" is used to mean "used as an example, illustration or description". Any embodiment described as "for example" in the present application is not necessarily to be interpreted as being more preferred or advantageous than other embodiments. In order to enable any technician in the field to implement and use the present application, the following description is given. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present application can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid unnecessary details to obscure the description of the present application. Therefore, the present application is not intended to be limited to the embodiments shown, but is consistent with the widest range of principles and features disclosed in the present application.

[0027] Reference Figure 1 , Figure 1 It is a structural diagram of the commercial office building energy management system provided by the present application. The commercial office building energy management system includes smart meters, network communication equipment, server cloud and terminal equipment. The data collection function of energy data can be realized through the smart meters and the network communication equipment, the analysis and diagnosis function of energy data can be realized through the server cloud, and the interactive application function of energy data can be realized through the terminal equipment. Specifically:

[0028] Optionally, the smart meter collects energy data from each metering point in the commercial office building according to the power distribution system structure of the commercial office building. Figure 2 , Figure 2 This is a schematic diagram of the power distribution system structure of a commercial office building provided by this application. Figure 2It can be seen that the distribution system structure includes multiple metering points, including the high-voltage side incoming line M1, the low-voltage distribution cabinet main incoming line M2, the low-voltage distribution cabinet outgoing line M3, the floor main distribution box M4, the floor sub-distribution box M5, each distribution circuit M6 and the key energy-consuming equipment M7; among them, M1, M2 and M3 are necessary metering points; M4, M5 and M6 are optional metering points for measuring the energy consumption of lighting sockets and air-conditioning terminal equipment; key energy-consuming equipment includes air-conditioning chillers, air-conditioning water pumps, air-conditioning cooling towers and elevators. In addition, independent metering can be performed for the project's own solar photovoltaic power generation system, two-way charging piles, energy storage systems, etc. Optionally, the parameters collected by a single intelligent meter include three-phase voltage, three-phase current, three-phase power, active power, reactive power, apparent power, power factor, active power and reactive power.

[0029] Optionally, the network communication device sends the energy data to a server cloud.

[0030] Optionally, the server cloud performs data analysis based on the energy data and outputs diagnostic suggestions, where the data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis.

[0031] First, for balance analysis, the energy data collected by the smart meter includes the total energy input and total energy output of each metering point, specifically:

[0032] The server cloud performs a balance analysis based on the total energy input and total energy output of each metering point to determine the balance relationship of energy consumption data between each metering point, specifically to determine whether the total energy input and total energy output are equal, that is, whether the total energy input-total energy output is equal to 0. When the total energy input is equal to the total energy output, that is, the total energy input-total energy output is equal to 0, the balance relationship of energy consumption data is balanced. When the total energy input is not equal to the total energy output, that is, the total energy input-total energy output is not equal to 0, the balance relationship of energy consumption data is unbalanced.

[0033] If the balance relationship of the energy consumption data of the smart meter is unbalanced, the server cloud determines the size of the imbalance rate between each metering point based on the total energy input and total energy output of each metering point. The specific formula is as follows:

[0034]

[0035] F represents the magnitude of the imbalance rate, Q in represents the total energy input, Q out Represents the total energy output.

[0036] Second, for deviation analysis, the energy data collected by the smart meter includes parameter curves of each metering point, specifically:

[0037] The server cloud determines the deviation amplitude value of each metering point according to the benchmark reference value and the actual monitoring parameter value in the parameter curve of each metering point, that is, the difference between the benchmark reference value and the actual monitoring parameter value is calculated to obtain the deviation amplitude value. Therefore, the deviation amplitude value = |actual monitoring parameter value-benchmark reference value|.

[0038] Furthermore, the server cloud determines the abnormal problems of each metering point according to the size relationship between the deviation amplitude value of each metering point and its corresponding benchmark reference value, wherein the abnormal problems include metering instrument data drift, data transmission disconnection and equipment system operation overload, specifically:

[0039] If the deviation amplitude value is less than or equal to one tenth of the benchmark reference value, the server cloud determines that the abnormal problem is the drift of the meter data. If the deviation amplitude value is greater than one tenth of the quasi-reference value and less than or equal to one quarter of the quasi-reference value, the server cloud determines that the abnormal problem is the data transmission disconnection. If the deviation amplitude value is greater than one quarter of the quasi-reference value, the server cloud determines that the abnormal problem is the overload of the equipment system.

[0040] Third, for classification analysis, the energy data collected by smart meters include the energy consumption of each metering point, specifically:

[0041] According to the business application needs of commercial office buildings, the server cloud classifies and summarizes the energy consumption of each metering point from the dimensions of energy responsibility and rights, energy attribute type, and energy physical space, and obtains the energy consumption proportion of each metering point in each dimension. Among them, the energy responsibility and rights dimension includes owners and tenants, the energy attribute type dimension includes air conditioning, lighting, and elevators, and the energy physical space dimension includes office floors and office areas.

[0042] Furthermore, the server cloud determines whether the energy consumption ratio of each metering point in each dimension is greater than its corresponding preset ratio threshold, wherein the preset ratio threshold is set according to the business application requirements. If it is determined that the energy consumption ratio of each metering point in each dimension is greater than its corresponding preset ratio threshold, the server cloud determines that the energy consumption of each metering point in this dimension is unreasonable, and the energy consumption of each metering point in this dimension needs to be adjusted. If it is determined that the energy consumption ratio of each metering point in each dimension is less than or equal to its corresponding preset ratio threshold, the server cloud determines that the energy consumption of each metering point in this dimension is reasonable.

[0043] Fourth, for trend analysis, the energy data collected by the smart meter includes energy data including energy consumption data curves of each metering point, specifically:

[0044] The server cloud obtains the energy consumption data of each metering point at the same time in different time dimensions, wherein the time dimension includes year, month and day, and the same time in different time dimensions represents the time of adjacent, separated, or continuous time periods in the year, month and day dimensions. In one embodiment, the time dimension is year, the current time is August 2024, and the same time in different time dimensions can be August 2023, August 2022, or August from 2020 to 2023. The time dimension is month, the current time is August, and the same time in different time dimensions can be May of the second quarter, February of the first quarter, February and May of the first and second quarters. The time dimension is day, the current time is August 15, 2024, and the same time in different time dimensions can be August 15, 2023, August 15, 2022, or August 15 from 2020 to 2023.

[0045] Furthermore, the server cloud sets the same time in different time dimensions as the period before the current time. Therefore, according to the energy consumption data of each metering point in the previous period and the energy consumption data of each metering point at the current time, the percentage increase or decrease of energy consumption of each metering point is determined. The specific formula is:

[0046]

[0047] Among them, A represents the percentage of energy consumption increase or decrease, W i-1 Indicates the energy consumption data for the previous period, W i Indicates the energy consumption data at the current time.

[0048] Furthermore, the server cloud determines the energy consumption trend of each metering point according to the percentage of energy consumption increase or decrease. Specifically, if it is determined that the percentage of energy consumption increase or decrease is within the first preset ratio of the preset warning threshold, the energy consumption trend of each metering point is determined to be stable. If it is determined that the percentage of energy consumption increase or decrease is greater than the first preset ratio of the preset warning threshold, and is less than or equal to the second preset ratio of the preset warning threshold, the server cloud determines that the energy consumption trend of each metering point is significantly increased. If it is determined that the percentage of energy consumption increase or decrease is greater than the second preset ratio of the preset warning threshold, the server cloud determines that the energy consumption trend of each metering point is severely increased. Among them, the preset warning threshold, the first preset ratio and the second preset ratio are set according to the actual situation. For example, the first preset ratio is 10% and the second preset ratio is 20%.

[0049] Optionally, the terminal device interacts with the operation management personnel based on the diagnosis suggestions. The terminal devices include PCs (Personal Computers), mobile terminals, large-screen terminals, etc. The interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction, and data alarm interaction.

[0050] For data dashboard interaction, operation managers can choose to view the overall energy consumption of the project by year, month and day, tenant energy consumption, public area energy consumption and energy consumption of each sub-item in the public area, as well as year-on-year and month-on-month change trends, imbalance rate, energy consumption indicators, comparative data and energy consumption alarm information on the energy data dashboard.

[0051] For data query interaction, according to the energy data collection structure, the corresponding data metering structure is configured in the energy management system, so that the operating personnel can accurately identify and query the location, metering function, real-time parameters, historical parameters, and related parameters of each smart meter, and configure the data statistics structure in the energy management system according to the classification and summary structure of energy data, so as to query the real-time energy consumption data and historical energy consumption data of each category, as well as the data relationship between the upper and lower levels.

[0052] For benchmark configuration interaction, according to the energy data analysis and diagnosis requirements, the imbalance rate control point, energy consumption deviation control point, energy consumption index benchmark, comparative benchmark parameters and energy consumption quota configuration are configured in the energy management system.

[0053] For data alarm interaction, based on real-time energy data and benchmark configuration parameters, through preset analysis and diagnosis rules, data alarms of different levels of imbalance rate abnormalities, deviation abnormalities and comparison indicator abnormalities are automatically given, and the troubleshooting direction and suggestions for energy data abnormalities are given.

[0054] Therefore, it can be understood that the application of the commercial office building energy management system in the embodiment of the present application needs to collect energy data, configure the energy system structure and benchmark parameters, and further automatically perform diagnostic analysis based on given analysis and diagnosis rules, issue diagnostic alarm information and present or push it to the operation and management personnel on the software platform to inform the troubleshooting direction and suggestions. The specific workflow is referenced in Figure 3 As shown, Figure 3 It is a schematic diagram of the application workflow of the commercial office building energy management system provided by this application.

[0055] The commercial office building energy management system provided in the embodiment of the present application includes smart meters, network communication equipment, server cloud and terminal equipment; data collection function is realized based on smart meters and network communication equipment, analysis and diagnosis function is realized based on server cloud, and interactive application function is realized based on terminal equipment; smart meters are used to collect energy data of various metering points in commercial office buildings according to the distribution system structure of commercial office buildings; network communication equipment is used to send energy data to server cloud; server cloud is used to perform data analysis based on energy data and output diagnostic suggestions; data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis; terminal equipment is used to interact with operation management personnel according to diagnostic suggestions; interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction and data alarm interaction, therefore, energy data of commercial office buildings can be comprehensively collected, energy data analysis can be performed from different dimensions, data quality can be guaranteed, abnormal data can be timely alarmed, the efficiency and convenience of energy management can be improved, and energy waste and loss can be reduced.

[0056] See also Figure 4 , Figure 4 This is a flow chart of the commercial office building energy management method provided by this application. The commercial office building energy management method includes:

[0057] Step S10, collecting energy data of each metering point in the commercial office building through the smart meter according to the power distribution system structure of the commercial office building;

[0058] Step S20, sending the energy data to the server cloud via a network communication device;

[0059] Step S30, performing data analysis based on energy data through the server cloud and outputting diagnostic suggestions; data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis;

[0060] Step S40, interactive applications are performed with operation management personnel through terminal devices according to diagnostic suggestions; interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction, and data alarm interaction.

[0061] Optionally, the smart meter collects energy data from each metering point in the commercial office building according to the power distribution system structure of the commercial office building. Figure 2The distribution system structure includes multiple metering points, including the high-voltage side incoming line M1, the low-voltage distribution cabinet main incoming line M2, the low-voltage distribution cabinet outgoing line M3, the floor main distribution box M4, the floor sub-distribution box M5, each distribution circuit M6 and the key energy-consuming equipment M7; among them, M1, M2 and M3 are necessary metering points; M4, M5 and M6 are optional metering points for measuring the energy consumption of lighting sockets and air-conditioning terminal equipment; key energy-consuming equipment includes air-conditioning chillers, air-conditioning water pumps, air-conditioning cooling towers and elevators. In addition, independent metering can be performed for the project's own solar photovoltaic power generation system, two-way charging piles, energy storage systems, etc. Optionally, the parameters collected by a single intelligent meter include three-phase voltage, three-phase current, three-phase power, active power, reactive power, apparent power, power factor, active power and reactive power.

[0062] Optionally, the network communication device sends the energy data to a server cloud.

[0063] Optionally, the server cloud performs data analysis based on the energy data and outputs diagnostic suggestions, where the data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis.

[0064] First, for balance analysis, the energy data collected by the smart meter includes the total energy input and total energy output of each metering point, specifically:

[0065] The server cloud performs a balance analysis based on the total energy input and total energy output of each metering point to determine the balance relationship of energy consumption data between each metering point, specifically to determine whether the total energy input and total energy output are equal, that is, whether the total energy input-total energy output is equal to 0. When the total energy input is equal to the total energy output, that is, the total energy input-total energy output is equal to 0, the balance relationship of energy consumption data is balanced. When the total energy input is not equal to the total energy output, that is, the total energy input-total energy output is not equal to 0, the balance relationship of energy consumption data is unbalanced.

[0066] If the balance relationship of the energy consumption data of the smart meter is unbalanced, the server cloud determines the size of the imbalance rate between each metering point based on the total energy input and total energy output of each metering point. The specific formula is as follows:

[0067]

[0068] F represents the magnitude of the imbalance rate, Q in represents the total energy input, Q out Represents the total energy output.

[0069] Second, for deviation analysis, the energy data collected by the smart meter includes parameter curves of each metering point, specifically:

[0070] The server cloud determines the deviation amplitude value of each metering point according to the benchmark reference value and the actual monitoring parameter value in the parameter curve of each metering point, that is, the difference between the benchmark reference value and the actual monitoring parameter value is calculated to obtain the deviation amplitude value. Therefore, the deviation amplitude value = |actual monitoring parameter value-benchmark reference value|.

[0071] Furthermore, the server cloud determines the abnormal problems of each metering point according to the size relationship between the deviation amplitude value of each metering point and its corresponding benchmark reference value, wherein the abnormal problems include metering instrument data drift, data transmission disconnection and equipment system operation overload, specifically:

[0072] If the deviation amplitude value is less than or equal to one tenth of the benchmark reference value, the server cloud determines that the abnormal problem is the drift of the meter data. If the deviation amplitude value is greater than one tenth of the quasi-reference value and less than or equal to one quarter of the quasi-reference value, the server cloud determines that the abnormal problem is the data transmission disconnection. If the deviation amplitude value is greater than one quarter of the quasi-reference value, the server cloud determines that the abnormal problem is the overload of the equipment system.

[0073] Third, for classification analysis, the energy data collected by smart meters include the energy consumption of each metering point, specifically:

[0074] According to the business application needs of commercial office buildings, the server cloud classifies and summarizes the energy consumption of each metering point from the dimensions of energy responsibility and rights, energy attribute type, and energy physical space, and obtains the energy consumption proportion of each metering point in each dimension. Among them, the energy responsibility and rights dimension includes owners and tenants, the energy attribute type dimension includes air conditioning, lighting, and elevators, and the energy physical space dimension includes office floors and office areas.

[0075] Furthermore, the server cloud determines whether the energy consumption ratio of each metering point in each dimension is greater than its corresponding preset ratio threshold, wherein the preset ratio threshold is set according to the business application requirements. If it is determined that the energy consumption ratio of each metering point in each dimension is greater than its corresponding preset ratio threshold, the server cloud determines that the energy consumption of each metering point in this dimension is unreasonable, and the energy consumption of each metering point in this dimension needs to be adjusted. If it is determined that the energy consumption ratio of each metering point in each dimension is less than or equal to its corresponding preset ratio threshold, the server cloud determines that the energy consumption of each metering point in this dimension is reasonable.

[0076] Fourth, for trend analysis, the energy data collected by the smart meter includes energy data including energy consumption data curves of each metering point, specifically:

[0077] The server cloud obtains the energy consumption data of each metering point at the same time in different time dimensions, wherein the time dimension includes year, month and day, and the same time in different time dimensions represents the time of adjacent, separated, or continuous time periods in the year, month and day dimensions. In one embodiment, the time dimension is year, the current time is August 2024, and the same time in different time dimensions can be August 2023, August 2022, or August from 2020 to 2023. The time dimension is month, the current time is August, and the same time in different time dimensions can be May of the second quarter, February of the first quarter, February and May of the first and second quarters. The time dimension is day, the current time is August 15, 2024, and the same time in different time dimensions can be August 15, 2023, August 15, 2022, or August 15 from 2020 to 2023.

[0078] Furthermore, the server cloud sets the same time in different time dimensions as the period before the current time. Therefore, according to the energy consumption data of each metering point in the previous period and the energy consumption data of each metering point at the current time, the percentage increase or decrease of energy consumption of each metering point is determined. The specific formula is:

[0079]

[0080] Among them, A represents the percentage of energy consumption increase or decrease, W i-1 Indicates the energy consumption data for the previous period, W i Indicates the energy consumption data at the current time.

[0081] Furthermore, the server cloud determines the energy consumption trend of each metering point according to the percentage of energy consumption increase or decrease. Specifically, if it is determined that the percentage of energy consumption increase or decrease is within the first preset ratio of the preset warning threshold, the energy consumption trend of each metering point is determined to be stable. If it is determined that the percentage of energy consumption increase or decrease is greater than the first preset ratio of the preset warning threshold, and is less than or equal to the second preset ratio of the preset warning threshold, the server cloud determines that the energy consumption trend of each metering point is significantly increased. If it is determined that the percentage of energy consumption increase or decrease is greater than the second preset ratio of the preset warning threshold, the server cloud determines that the energy consumption trend of each metering point is severely increased. Among them, the preset warning threshold, the first preset ratio and the second preset ratio are set according to the actual situation. For example, the first preset ratio is 10% and the second preset ratio is 20%.

[0082] Optionally, the terminal device interacts with the operation management personnel based on the diagnosis suggestions, wherein the interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction and data alarm interaction.

[0083] For data dashboard interaction, operation managers can choose to view the overall energy consumption of the project by year, month and day, tenant energy consumption, public area energy consumption and energy consumption of each sub-item in the public area, as well as year-on-year and month-on-month change trends, imbalance rate, energy consumption indicators, comparative data and energy consumption alarm information on the energy data dashboard.

[0084] For data query interaction, according to the energy data collection structure, the corresponding data metering structure is configured in the energy management system, so that the operating personnel can accurately identify and query the location, metering function, real-time parameters, historical parameters, and related parameters of each smart meter, and configure the data statistics structure in the energy management system according to the classification and summary structure of energy data, so as to query the real-time energy consumption data and historical energy consumption data of each category, as well as the data relationship between the upper and lower levels.

[0085] For benchmark configuration interaction, according to the energy data analysis and diagnosis requirements, the imbalance rate control point, energy consumption deviation control point, energy consumption index benchmark, comparative benchmark parameters and energy consumption quota configuration are configured in the energy management system.

[0086] For data alarm interaction, based on real-time energy data and benchmark configuration parameters, through preset analysis and diagnosis rules, data alarms of different levels of imbalance rate abnormalities, deviation abnormalities and comparison indicator abnormalities are automatically given, and the troubleshooting direction and suggestions for energy data abnormalities are given.

[0087] The embodiments of the present application can comprehensively collect energy data of commercial office buildings, analyze energy data from different dimensions, ensure data quality, and issue timely alarms for abnormal data, thereby improving the efficiency and convenience of energy management and reducing energy waste and losses.

[0088] See also Figure 5 , Figure 5 This is a schematic diagram of an electronic device provided in an embodiment of the present application. Figure 5 As shown, an embodiment of the present application provides an electronic device, which includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114;

[0089] The memory 113 is used to store the computer program. When the processor 111 executes the computer program, the following steps are implemented:

[0090] The smart meter collects energy data of each metering point in the commercial office building according to the power distribution system structure of the commercial office building;

[0091] Sending the energy data to the server cloud via the network communication device;

[0092] The server cloud performs data analysis based on the energy data and outputs diagnostic suggestions; the data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis;

[0093] The terminal device is used to interact with the operation management personnel according to the diagnostic suggestions; the interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction, and data alarm interaction.

[0094] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0095] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0096] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0097] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0098] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0099] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0100] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A commercial office building energy management system, characterized in that: The commercial office building energy management system includes smart meters, network communication equipment, server cloud and terminal equipment; data collection function is realized based on the smart meters and the network communication equipment, analysis and diagnosis function is realized based on the server cloud, and interactive application function is realized based on the terminal equipment; The smart meter is used to collect energy data of various metering points in the commercial office building according to the power distribution system structure of the commercial office building; The network communication device is used to send the energy data to the server cloud; The server cloud is used to perform data analysis based on the energy data and output diagnostic suggestions; the data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis; The terminal device is used to perform interactive applications with the operation management personnel according to the diagnostic suggestions; the interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction and data alarm interaction; The power distribution system structure includes multiple metering points, including high-voltage side incoming line M1, low-voltage distribution cabinet main incoming line M2, low-voltage distribution cabinet outgoing line M3, floor main distribution box M4, floor sub-distribution box M5, each distribution circuit M6 and key energy-consuming equipment M7; among them, M1, M2 and M3 are necessary metering points; M4, M5 and M6 are optional metering points, which are used to measure the energy consumption of lighting sockets and air-conditioning terminal equipment; the key energy-consuming equipment includes air-conditioning chillers, air-conditioning water pumps, air-conditioning cooling towers and elevators; The energy data includes energy consumption at each metering point; The server cloud is used for: According to the business application requirements of commercial office buildings, the energy consumption of each metering point is classified and analyzed from the dimensions of energy responsibility and rights, energy attribute type, and physical space, and the energy consumption ratio of each metering point in each dimension is obtained; Analyze the rationality of energy consumption at each metering point based on the energy consumption ratio of each metering point in each dimension; Among them, the energy responsibility and rights dimension includes owners and tenants, the energy attribute type dimension includes air conditioning, lighting and elevators, and the energy physical space dimension includes office floors and office areas; The energy data includes parameter curves of each metering point; The server cloud is used for: Determine the deviation amplitude value of each metering point according to the benchmark reference value and the actual monitoring parameter value in the parameter curve of each metering point; Determine the abnormal problems of each metering point based on the deviation amplitude value of each metering point; the abnormal problems include metering instrument data drift, data transmission disconnection and equipment system operation overload; Among them, if the deviation amplitude value is less than or equal to one tenth of the benchmark reference value, the abnormal problem is determined to be meter data drift; if the deviation amplitude value is greater than one tenth of the quasi-reference value and less than or equal to one quarter of the quasi-reference value, the abnormal problem is determined to be data transmission disconnection; if the deviation amplitude value is greater than one quarter of the quasi-reference value, the abnormal problem is determined to be equipment system overload.

2. The commercial office building energy management system according to claim 1, characterized in that: The energy data includes the total energy input and total energy output of each metering point; The server cloud is used for: Perform a balance analysis based on the total energy input and total energy output of each metering point to determine the balance relationship of energy consumption data between each metering point; wherein, when the total energy input is equal to the total energy output, the energy consumption data balance relationship is balanced, and when the total energy input is not equal to the total energy output, the energy consumption data balance relationship is unbalanced; If the energy consumption data balance relationship is unbalanced, the magnitude of the unbalance rate between the metering points is determined based on the total energy input and total energy output of each metering point, wherein the specific formula is as follows: F represents the magnitude of the imbalance rate, Q in represents the total energy input, Q out Represents the total energy output.

3. The commercial office building energy management system according to claim 1, characterized in that: The energy data includes energy consumption data curves of each metering point; The server cloud is used for: Obtain energy consumption data of each metering point at the same time in different time dimensions; the time dimensions include year, month and day, and the same time in different time dimensions represents the time of adjacent, separated, or continuous time periods in the year, month and day dimensions; Determining the percentage increase or decrease of energy consumption at each metering point according to the energy consumption data; The energy consumption trend of each metering point is determined based on the energy consumption increase or decrease percentage.

4. The commercial office building energy management system according to claim 1, characterized in that: The interactive representation of the data dashboard: the operation management personnel can select to view the overall energy consumption of the project by year, month and day, the energy consumption of tenants, the energy consumption of public areas and the energy consumption of each sub-item of public areas, as well as the year-on-year and month-on-month change trends, imbalance rate, energy consumption index, comparative data and energy consumption alarm information on the energy data dashboard; The data query interaction representation is as follows: according to the energy data collection structure, a corresponding data metering structure is configured in the energy management system so that the operating personnel can accurately identify and query the location, metering function, real-time parameters, historical parameters, and associated parameters of each smart meter, and according to the classification and summary structure of the energy data, a data statistical structure is configured in the energy management system so that the real-time energy consumption data and historical energy consumption data of each classification can be queried, as well as the data relationship between the upper and lower levels.

5. The commercial office building energy management system according to claim 1, characterized in that: The benchmark configuration interaction characterization: according to the energy data analysis and diagnosis requirements, the imbalance rate control point, the energy consumption deviation control point, the energy consumption index benchmark, the comparative benchmark parameters and the energy consumption quota configuration are configured in the energy management system; The data alarm interaction characterization: based on real-time energy data and benchmark configuration parameters, through preset analysis and diagnosis rules, automatically gives data alarms of imbalance rate anomalies, deviation anomalies and comparison index anomalies of different levels, and gives troubleshooting directions and suggestions for energy data anomalies.

6. A commercial office building energy management method, characterized in that: Applied to the commercial office building energy management system according to any one of claims 1 to 5, the commercial office building energy management includes smart meters, network communication equipment, server cloud and terminal equipment, and the method includes: Collecting energy data of each metering point in the commercial office building through the smart meter according to the power distribution system structure of the commercial office building; Sending the energy data to the server cloud via the network communication device; The server cloud performs data analysis based on the energy data and outputs diagnostic suggestions; the data analysis includes balance analysis, deviation analysis, classification analysis and trend analysis; The terminal device is used to interact with the operation management personnel according to the diagnostic suggestions; the interactive applications include data dashboard interaction, data query interaction, benchmark configuration interaction, and data alarm interaction.

7. An electronic device, characterized in that: The electronic device includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the program, the commercial office building energy management method as claimed in claim 6 is implemented.

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