Banking outlet power utilization energy efficiency optimization method, device, equipment and medium

Abstract

The invention provides a bank outlet power utilization energy efficiency optimization method. The method can be applied to the technical field of artificial intelligence and the technical field of Internet of Things. The method comprises the steps of obtaining a banking outlet identifiers, obtaining monitoring data of each banking outlet in the a banking outlets in an nth preset period based on the a banking outlet identifiers, and further obtaining b banking outlet identifiers. And performing energy efficiency evaluation on the b banking outlets, and screening c banking outlet identifiers. And obtaining d bank outlet identifiers from the a bank outlet identifiers, and obtaining feature data of each electric device in the d bank outlets. And inputting the electric equipment characteristic data of each of the d bank outlets into a pre-generated power utilization energy efficiency model, and outputting an electric equipment configuration scheme of each of the d bank outlets, so as to optimize the power utilization energy efficiency of each of the d bank outlets. The invention further provides a bank outlet power utilization energy efficiency optimization device and equipment, a storage medium and a program product.

Description

Technical Field

[0001] The present disclosure relates to the field of artificial intelligence, specifically to the field of Internet of Things technology, and in particular to a method, device, equipment, medium and program product for optimizing the electricity energy efficiency of bank branches. Background Art

[0002] In enterprises including banks, as the concept of green and low-carbon is deeply rooted in people's minds, enterprises are paying more and more attention to energy conservation and emission reduction and improving energy efficiency. As the front line of banks facing customers, the energy consumption and operating environment of bank branches will directly affect the corporate image and social responsibility. Therefore, establishing a set of scientific and effective methods for optimizing electricity efficiency is not only an important step for enterprises to achieve green development, but also an important manifestation of fulfilling social responsibilities. In order to provide data support for enterprises to avoid waste of energy efficiency resources and achieve green and low-carbon development, the stable operation of business and effective control of energy consumption levels can be achieved. Summary of the invention

[0003] In view of the above problems, the present disclosure provides a method, device, equipment, medium and program product for optimizing the electricity energy efficiency of bank branches.

[0004] According to a first aspect of the present disclosure, a method for optimizing the electricity energy efficiency of bank branches is provided, the method comprising: obtaining a bank branch identifiers, wherein each of the a bank branch identifiers is unique, a is greater than or equal to 2 and is an integer; based on the a bank branch identifiers, obtaining monitoring data of each of the a bank branch identifiers in an nth preset period, and obtaining b bank branch identifiers from the a bank branch identifiers according to the monitoring data, wherein b is greater than or equal to 1 and b is an integer, b is less than or equal to a, and n is greater than or equal to 2 and is an integer; based on the b bank branch identifiers, performing energy efficiency evaluation on the b bank branch identifiers, and screening out c bank branch identifiers according to the energy efficiency evaluation results, wherein c is greater than or equal to 1 and c is integer, c is less than or equal to b; obtaining d bank branch identifiers from a bank branch identifiers, wherein the d bank branch identifiers and the c bank branch identifiers do not overlap with each other, d is greater than or equal to 1 and d is an integer, and the sum of d and c is equal to a; based on the d bank branch identifiers, obtaining characteristic data of each power-consuming device in the d bank branches; and inputting the characteristic data of the power-consuming device of each of the d bank branches into a pre-generated power energy efficiency model, and using the power energy efficiency model to output a power equipment configuration plan for each of the d bank branches, so as to optimize the power energy efficiency of each of the d bank branches, wherein the power energy efficiency model is generated based on the training of the characteristic data of the power-consuming devices of the c bank branches.

[0005] According to an embodiment of the present disclosure, the monitoring data includes: dynamic environment monitoring data, the monitoring data of each bank branch among a bank branches within the nth preset period is obtained, and b bank branch identifications are obtained from a bank branch identifications according to the monitoring data, including: obtaining the dynamic environment monitoring data of each bank branch among a bank branches within the nth preset period, performing data processing on the dynamic environment monitoring data, and generating dynamic environment values ​​of a bank branches; and obtaining b bank branch identifications whose dynamic environment values ​​are less than or equal to a preset dynamic environment threshold from the a bank branch identifications, and generating b bank branch identifications.

[0006] According to an embodiment of the present disclosure, the dynamic environment monitoring data includes: the number of real-time warnings within the nth preset period, the number of risk event warnings within the nth preset period, and the failure rate within the nth preset period. The dynamic environment monitoring data of each bank branch in a bank branch in the nth preset period is obtained, and the dynamic environment monitoring data is processed to generate the dynamic environment values ​​of a bank branch, including: obtaining the number of real-time warnings of each bank branch in the nth preset period among a bank branches, the weight of the preset number of real-time warnings is a first weight, and the product of the number of real-time warnings of each bank branch in the nth preset period and the first weight is calculated to generate a first association value for each bank branch; obtaining the number of real-time warnings of each bank branch in a bank branch, The number of risk event warnings of each bank branch in the nth preset period, the weight of the preset number of risk event warnings is the second weight, the product of the number of risk event warnings of each bank branch in the nth preset period and the second weight is calculated, and the second association value of each bank branch is generated; the failure rate of each bank branch in the nth preset period is obtained among a bank branches, the weight of the preset failure rate is the third weight, the product of the failure rate of each bank branch in the nth preset period and the third weight is calculated, and the third association value of each bank branch is generated; and the sum of the first association value, the second association value and the third association value of each bank branch in the a bank branches is calculated to generate the dynamic ring value of the a bank branches.

[0007] According to an embodiment of the present disclosure, the energy efficiency evaluation value includes: an electricity consumption energy efficiency value and an electricity consumption floating value. The energy efficiency evaluation is performed on the b bank branch identifiers based on the b bank branch identifiers, and c bank branch identifiers are screened out according to the energy efficiency evaluation results, including: calculating the electricity consumption energy efficiency value of each of the b bank branch identifiers within the nth preset period; calculating the electricity consumption floating value of each of the b bank branch identifiers within the nth preset period; and obtaining, from the b bank branch identifiers, c bank branch identifiers whose electricity consumption energy efficiency values ​​within the nth preset period are less than or equal to the energy efficiency threshold and whose electricity consumption floating values ​​are greater than or equal to the floating threshold, to generate c bank branch identifiers.

[0008] According to the embodiment of the present disclosure, the calculation of the electricity consumption energy efficiency value of each bank branch among the b bank branches in the nth preset period includes: obtaining the total electricity consumption of the uninterruptible power consumption equipment of each bank branch among the b bank branches in the nth preset period as the first electricity consumption of each bank branch in the nth preset period; obtaining the total electricity consumption of the intermittent power consumption equipment of each bank branch among the b bank branches in the nth preset period as the second electricity consumption of each bank branch in the nth preset period; calculating the sum of the first electricity consumption of each bank branch among the b bank branches in the nth preset period and the second electricity consumption of each bank branch in the nth preset period to generate a fourth associated value for each bank branch; and calculating the quotient of the fourth associated value of each bank branch among the b bank branches and the first electricity consumption of each bank branch in the nth preset period to generate the electricity consumption energy efficiency value of each bank branch in the nth preset period.

[0009] According to an embodiment of the present disclosure, the electricity consumption floating value of each of b bank branches in the nth preset period is calculated, including: calculating the electricity consumption energy efficiency value of each of the b bank branches in the n-1th preset period; and calculating the absolute value of the difference between the electricity consumption energy efficiency value of each of the b bank branches in the nth preset period and the electricity consumption energy efficiency value in the n-1th preset period, to generate the electricity consumption floating value of each bank branch in the nth preset period.

[0010] According to the embodiment of the present disclosure, the step of obtaining d bank branch identifications from a bank branch identifications includes: obtaining e bank branch identifications whose dynamic ring values ​​are greater than a preset dynamic ring threshold from the a bank branch identifications, wherein e is greater than or equal to 1 and e is an integer, and the sum of e and b is equal to a; obtaining f bank branch identifications whose electricity energy efficiency values ​​are greater than the energy efficiency threshold or whose electricity floating values ​​are less than the floating threshold in the nth preset period from the b bank branch identifications, wherein f is greater than or equal to 1 and d is an integer, and the sum of f and c is equal to b; and obtaining e bank branch identifications and f bank branch identifications to generate d bank branch identifications, wherein the sum of e and f is equal to d.

[0011] According to an embodiment of the present disclosure, before inputting the characteristic data of electrical equipment of each of the d bank branches into a pre-generated electricity energy efficiency model, it also includes: performing data cleaning, removing outliers, removing missing values ​​and removing noise data on the characteristic data of electrical equipment of each of the d bank branches.

[0012] According to a second aspect of the present disclosure, a device for optimizing the electricity energy efficiency of bank branches is provided, and the device includes: a first acquisition module, used to acquire a bank branch identifiers, wherein each of the a bank branch identifiers is unique, wherein a is greater than or equal to 2 and is an integer; a second acquisition module, used to acquire monitoring data of each of the a bank branch identifiers in the nth preset period based on the a bank branch identifiers, and acquire b bank branch identifiers from the a bank branch identifiers according to the monitoring data, wherein b is greater than or equal to 1 and b is an integer, b is less than or equal to a, and n is greater than or equal to 2 and n is an integer; a first screening module, used to perform energy efficiency evaluation on b bank branch identifiers based on the b bank branch identifiers, and screen out c bank branch identifiers according to the energy efficiency evaluation results, wherein c is greater than or equal to 1 and c is an integer, c is less than or equal to b; a third acquisition module is used to obtain d bank branch identifiers from a bank branch identifiers, wherein the d bank branch identifiers and the c bank branch identifiers do not overlap with each other, d is greater than or equal to 1 and d is an integer, and the sum of d and c is equal to a; a fourth acquisition module is used to obtain the characteristic data of each power-consuming device in the d bank branches based on the d bank branch identifiers; and a first generation module is used to input the characteristic data of the power-consuming device of each of the d bank branches into a pre-generated power energy efficiency model, and use the power energy efficiency model to output the power equipment configuration plan of each of the d bank branches, so as to optimize the power energy efficiency of each of the d bank branches, wherein the power energy efficiency model is generated based on the training of the characteristic data of the power-consuming devices of the c bank branches.

[0013] According to an embodiment of the present disclosure, the second acquisition module includes: a second generation module, used to obtain the dynamic environment monitoring data of each bank branch among a bank branches within the nth preset period, perform data processing on the dynamic environment monitoring data, and generate dynamic environment values ​​of a bank branches; and a third generation module, used to obtain b bank branch identifications whose dynamic environment values ​​are less than or equal to the preset dynamic environment threshold from the a bank branch identifications, and generate b bank branch identifications.

[0014] According to an embodiment of the present disclosure, the second generating module includes: a fourth generating module, which is used to obtain the number of real-time warnings of each bank branch in the nth preset period among a bank branches, the weight of the preset number of real-time warnings is a first weight, and calculate the product of the number of real-time warnings of each bank branch in the nth preset period and the first weight to generate a first association value for each bank branch; a fifth generating module, which is used to obtain the number of risk event warnings of each bank branch in the nth preset period among a bank branches, the weight of the preset number of risk event warnings is a second weight, and calculate the product of the number of real-time warnings of each bank branch in the nth preset period and the first weight to generate a first association value for each bank branch. The product of the number of risk event warnings within the nth preset period and the second weight is used to generate the second association value of each bank branch; the sixth generation module is used to obtain the failure rate of each bank branch in the nth preset period among a bank branches, the weight of the preset failure rate is the third weight, and the product of the failure rate of each bank branch in the nth preset period and the third weight is calculated to generate the third association value of each bank branch; and the seventh generation module is used to calculate the sum of the first association value, the second association value and the third association value of each bank branch among a bank branches to generate the dynamic ring value of a bank branch.

[0015] According to an embodiment of the present disclosure, the third generation module includes: a first calculation module, used to calculate the electricity consumption energy efficiency value of each bank branch among b bank branches within the nth preset period; a second calculation module, used to calculate the electricity consumption floating value of each bank branch among the b bank branches within the nth preset period; and an eighth generation module, used to obtain c bank branch identifications whose electricity consumption energy efficiency values ​​within the nth preset period are less than or equal to the energy efficiency threshold and whose electricity consumption floating values ​​are greater than or equal to the floating threshold from the b bank branch identifications, and generate c bank branch identifications.

[0016] According to an embodiment of the present disclosure, the first calculation module includes: a fifth acquisition module, which is used to obtain the total power consumption of the uninterruptible power equipment of each bank branch among b bank branches within the nth preset period as the first power consumption of each bank branch within the nth preset period; a sixth acquisition module, which is used to obtain the total power consumption of the intermittent power equipment of each bank branch among b bank branches within the nth preset period as the second power consumption of each bank branch within the nth preset period; a ninth generation module, which is used to calculate the sum of the first power consumption of each bank branch among the b bank branches within the nth preset period and the second power consumption of each bank branch within the nth preset period, and generate a fourth associated value for each bank branch; and a tenth generation module, which is used to calculate the quotient of the fourth associated value of each bank branch among the b bank branches and the first power consumption of each bank branch within the nth preset period, and generate the power consumption energy efficiency value of each bank branch within the nth preset period.

[0017] According to an embodiment of the present disclosure, the second calculation module includes: a third calculation module, used to calculate the electricity consumption energy efficiency value of each bank branch among b bank branches in the n-1th preset period; and an eleventh generation module, used to calculate the absolute value of the difference between the electricity consumption energy efficiency value of each bank branch among the b bank branches in the nth preset period and the electricity consumption energy efficiency value in the n-1th preset period, and generate the electricity consumption floating value of each bank branch in the nth preset period.

[0018] According to an embodiment of the present disclosure, the third acquisition module includes: a seventh acquisition module, used to obtain e bank branch identifications whose dynamic ring values ​​are greater than a preset dynamic ring threshold from the a bank branch identifications, wherein e is greater than or equal to 1 and e is an integer, and the sum of e and b is equal to a; an eighth acquisition module, used to obtain f bank branch identifications whose electricity energy efficiency values ​​are greater than the energy efficiency threshold or whose electricity floating values ​​are less than the floating threshold in the nth preset period from the b bank branch identifications, wherein f is greater than or equal to 1 and d is an integer, and the sum of f and c is equal to b; and a twelfth generation module, used to obtain e bank branch identifications and f bank branch identifications, and generate d bank branch identifications, wherein the sum of e and f is equal to d.

[0019] According to a third aspect of the present disclosure, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned method for optimizing electricity energy efficiency in bank branches.

[0020] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which executable instructions or computer programs are stored. When the instructions or computer programs are executed by a processor, the processor executes the above-mentioned method for optimizing the electricity energy efficiency of bank branches.

[0021] According to a fifth aspect of the present disclosure, a computer program product is also provided, including a computer program, which implements the above-mentioned bank branch electricity energy efficiency optimization method when executed by a processor.

[0022] By screening multiple bank outlets according to monitoring data and energy efficiency evaluation, the outlets that meet the requirements are selected, and the outlets that meet the requirements are used as samples for model training to generate an electricity energy efficiency model. The trained electricity energy efficiency model is input into the outlets that do not meet the requirements to generate the corresponding electrical equipment configuration plan, so as to optimize the electricity energy efficiency of each outlet in the d target bank outlets. The technical problem that the electricity energy efficiency of some bank outlets is too high and causes waste of resources can be solved. By screening and generating sample outlets according to monitoring data and energy efficiency evaluation, the electricity energy efficiency model is generated, and the accuracy of the electricity energy efficiency model is improved. Then, the outlets that need to change the configuration plan of the electricity equipment are applied to the generated electricity efficiency model, and the accuracy and rationality of the generated configuration plan of the electricity equipment are improved, so as to achieve the technical effect of accurately selecting bank outlets for energy management, formulating scientific and reasonable energy-saving and emission reduction measures for the outlets in a targeted manner, and thus improving energy-saving efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0024] Figure 1 A diagram schematically shows an application scenario of a method and device for optimizing electricity efficiency of bank outlets according to an embodiment of the present disclosure;

[0025] Figure 2 A flowchart of a method for optimizing electricity energy efficiency of bank outlets according to an embodiment of the present disclosure is schematically shown;

[0026] Figure 3 A flowchart for generating b bank branch identifiers in a method for optimizing the power consumption efficiency of bank branches according to an embodiment of the present disclosure is schematically shown;

[0027] Figure 4 A flowchart of generating dynamic ring values ​​of a bank outlets in a method for optimizing the power consumption efficiency of bank outlets according to an embodiment of the present disclosure is schematically shown;

[0028] Figure 5 A flowchart for generating c bank branch identifiers in a bank branch electricity energy efficiency optimization method according to an embodiment of the present disclosure is schematically shown;

[0029] Figure 6 A flowchart of generating the power consumption energy efficiency value of each bank branch in the nth preset period in the bank branch power consumption energy efficiency optimization method according to an embodiment of the present disclosure is schematically shown;

[0030] Figure 7 A flowchart for generating a floating value of electricity consumption of each bank branch in an nth preset period in a method for optimizing electricity consumption efficiency of bank branches according to an embodiment of the present disclosure is schematically shown;

[0031] Figure 8 A flowchart for generating d bank branch identifiers in a method for optimizing the power consumption efficiency of bank branches according to an embodiment of the present disclosure is schematically shown;

[0032] Fig. 9 A schematic diagram of a structure of a device for optimizing the power consumption efficiency of a bank branch according to an embodiment of the present disclosure is shown; and

[0033] Fig.10 A block diagram of an electronic device suitable for implementing a method for optimizing electricity energy efficiency at a bank branch according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0034] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0035] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0036] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0037] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0038] Some block diagrams and / or flow charts are shown in the accompanying drawings. It should be understood that some blocks or combinations thereof in the block diagrams and / or flow charts may be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable control device, so that these instructions, when executed by the processor, may create a device for implementing the functions / operations described in these block diagrams and / or flow charts.

[0039] First, the technical terms that appear in this article are explained as follows:

[0040] Power environment monitoring data: that is, power environment monitoring data, is a kind of comprehensive data for centralized monitoring and maintenance of power equipment and environment in computer rooms distributed in different locations.

[0041] The embodiment of the present disclosure provides a method for optimizing the energy efficiency of electricity consumption of bank outlets, the method comprising: obtaining a bank outlet identifiers, wherein each of the a bank outlet identifiers is unique, a is greater than or equal to 2 and a is an integer. Based on the a bank outlet identifiers, obtaining monitoring data of each of the a bank outlets in the nth preset period, and obtaining b bank outlet identifiers from the a bank outlet identifiers according to the monitoring data, wherein b is greater than or equal to 1 and b is an integer, b is less than or equal to a, and n is greater than or equal to 2 and n is an integer. Based on the b bank outlet identifiers, energy efficiency evaluation is performed on the b bank outlets, and c bank outlet identifiers are screened out according to the energy efficiency evaluation results, wherein c is greater than or equal to 1 and c is an integer, and c is less than or equal to. Obtaining d bank outlet identifiers from the a bank outlet identifiers, wherein the d bank outlet identifiers and the c bank outlet identifiers do not overlap with each other, d is greater than or equal to 1 and d is an integer, and the sum of d and c is equal to a. Based on the d bank branch identifiers, characteristic data of each power-consuming device in the d bank branches are obtained. The characteristic data of the power-consuming device in each of the d bank branches is input into a pre-generated power consumption energy efficiency model, and the power consumption energy efficiency model is used to output a configuration plan of the power-consuming device in each of the d bank branches, so as to optimize the power consumption energy efficiency of each of the d bank branches, wherein the power consumption energy efficiency model is generated by training based on the characteristic data of the power-consuming devices in the c bank branches.

[0042] According to the disclosed embodiment, multiple bank outlets are screened according to monitoring data and energy efficiency evaluation, and outlets that meet the requirements are selected. The outlets that meet the requirements are used as samples for model training to generate an electricity energy efficiency model. The trained electricity energy efficiency model is input into the outlets that do not meet the requirements, and the corresponding electrical equipment configuration plan is generated to optimize the electricity energy efficiency of each outlet in the d target bank outlets. The technical problem that the electricity energy efficiency of some bank outlets is too high and causes waste of resources can be solved. By screening and generating sample outlets according to monitoring data and energy efficiency evaluation, generating an electricity energy efficiency model, the accuracy of the electricity energy efficiency model is improved, and then by applying the generated electricity efficiency model to the outlets that need to change the electricity equipment configuration plan, the accuracy and rationality of the generated electricity equipment configuration plan are improved, and the technical effect of accurately selecting bank outlets for energy management and formulating scientific and reasonable energy-saving and emission reduction measures for the outlets in a targeted manner to improve energy-saving efficiency is achieved.

[0043] Figure 1 The following schematically shows an application scenario diagram of the bank branch electricity energy efficiency optimization method and device according to an embodiment of the present disclosure. It should be noted that: Figure 1 The examples shown are merely scenarios in which the embodiments of the present disclosure can be applied, to help those skilled in the art understand the technical content of the present disclosure, but do not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0044] like Figure 1 As shown, the application scenario 100 according to this embodiment may include an application scenario of optimizing the power efficiency of bank outlets. The network 104 is used to provide a medium for a communication link between the first terminal device 101, the second terminal device 102, the third terminal device 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0045] The user can use the first terminal device 101, the second terminal device 102, and the third terminal device 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, the second terminal device 102, and the third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0046] The first terminal device 101, the second terminal device 102, and the third terminal device 103 may be various electronic devices having display screens and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0047] The server 105 may be a server that provides various services, such as a background management server (only as an example) that provides support for websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0048] It should be noted that the bank branch electricity energy efficiency optimization method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the bank branch electricity energy efficiency optimization device provided in the embodiment of the present disclosure can generally be set in the server 105. The bank branch electricity energy efficiency optimization method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105. Correspondingly, the bank branch electricity energy efficiency optimization device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the first terminal device 101, the second terminal device 102, the third terminal device 103 and / or the server 105.

[0049] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0050] The following will be based on Figure 1 The scene described by Figure 2~Figure 8 The bank branch electricity energy efficiency optimization method of the disclosed embodiment is described in detail. It should be noted that the above application scenarios are only shown to facilitate understanding of the spirit and principle of the present disclosure, and the embodiments of the present disclosure are not limited in this regard. On the contrary, the embodiments of the present disclosure can be applied to any applicable scenario.

[0051] Figure 2 The flowchart of the method for optimizing electricity energy efficiency of bank branches according to an embodiment of the present disclosure is schematically shown.

[0052] like Figure 2 As shown, the method 200 includes steps S201 to S206.

[0053] Step S201, obtaining a bank branch identifiers, wherein each of the a bank branch identifiers is unique, a is greater than or equal to 2 and a is an integer.

[0054] For example, the bank branch logo is a unique logo for each bank branch and is an important symbol used to distinguish between different bank branches.

[0055] Step S202, based on a bank branch identifiers, obtain monitoring data of each of the a bank branch identifiers in the nth preset period, and obtain b bank branch identifiers from the a bank branch identifiers according to the monitoring data, where b is greater than or equal to 1 and b is an integer, b is less than or equal to a, and n is greater than or equal to 2 and n is an integer.

[0056] For example, the monitoring data may include: dynamic environment monitoring data. The dynamic environment monitoring data includes: the number of real-time warnings within the nth preset period, the number of risk event warnings within the nth preset period, and the failure rate within the nth preset period.

[0057] Dynamic environment monitoring data can be composed of various collectors, which can realize the collection of power input, power output, temperature, humidity, and environmental status in the computer room. The collector can be deployed alone, or it can be combined with the existing uninterruptible power supply equipment or integrated cabinets of the branch to achieve the same function. The data collected by the branch collector can be transmitted to the bank's core computer room through the branch's existing business network.

[0058] The monitoring personnel in the computer room can use the dynamic environment monitoring data collected by the collector to intuitively display the operating status of all outlets within the jurisdiction on the large screen, and conduct manual intervention in emergencies in a timely manner. If the collected data finds an abnormality, such as power input interruption, uninterruptible power supply equipment starting discharge, temperature and humidity exceeding the threshold, smoke alarm, monitoring communication abnormality, etc., a real-time alarm will be issued through an outbound call to notify the corresponding outlet technicians and core computer room monitoring personnel set in the system. Relevant personnel can rush to the scene to deal with it as soon as possible after receiving the alarm.

[0059] The server in the computer room can analyze historical monitoring data and issue early warnings for risk events, such as regular maintenance warnings for power facilities, low UPS battery warnings, and large fluctuations in power consumption during specific periods of time, so as to prevent problems before they occur.

[0060] The server in the computer room can also analyze historical data, conduct statistical analysis on the failure rate on a weekly, monthly, and annual basis, and issue a failure rate report. Branches can optimize infrastructure based on the report to further improve the stability of the power environment. Monitoring personnel can assess some branches with higher failure rates based on the ranking of failure rates of branches within their jurisdiction, and help branches improve the stability of the power environment in a targeted manner.

[0061] Figure 3 The flowchart of generating b bank branch identifiers in the bank branch electricity energy efficiency optimization method according to the embodiment of the present disclosure is schematically shown.

[0062] like Figure 3As shown, the method 300 includes steps S301-S302.

[0063] Step S301, obtaining dynamic environment monitoring data of each bank branch in a bank branches within an nth preset period, performing data processing on the dynamic environment monitoring data, and generating dynamic environment values ​​of the a bank branches.

[0064] Figure 4 The flowchart of generating dynamic ring values ​​of a bank outlets in the method for optimizing the electricity energy efficiency of bank outlets according to an embodiment of the present disclosure is schematically shown.

[0065] like Figure 4 As shown, the method 400 includes steps S401 to S404.

[0066] Step S401, obtaining the number of real-time warnings of each bank branch in the nth preset period among a bank branches, where the weight of the preset number of real-time warnings is a first weight, and calculating the product of the number of real-time warnings of each bank branch in the nth preset period and the first weight to generate a first association value for each bank branch.

[0067] Step S402, obtain the number of risk event warnings of each bank branch in the nth preset period among a bank branches, the weight of the preset number of risk event warnings is the second weight, calculate the product of the number of risk event warnings of each bank branch in the nth preset period and the second weight, and generate a second association value for each bank branch.

[0068] Step S403, obtaining the failure rate of each bank branch in the nth preset period among a bank branches, where the weight of the preset failure rate is a third weight, calculating the product of the failure rate of each bank branch in the nth preset period and the third weight, and generating a third association value for each bank branch.

[0069] Step S404, calculating the sum of the first association value, the second association value and the third association value of each bank branch among the a bank branches, and generating the dynamic ring values ​​of the a bank branches.

[0070] The dynamic ring value of the branch is calculated based on the number of real-time warnings, risk events and failure rate warnings within the nth preset period. B bank branch identifications can be generated based on the accurate calculation of dynamic ring monitoring data to improve the reliability of the b bank branch identifications.

[0071] Return to reference Figure 3 In step S302, b bank branch identifications whose dynamic ring values ​​are less than or equal to the preset dynamic ring threshold are obtained from a bank branch identifications to generate b bank branch identifications.

[0072] The first step of screening the outlets through dynamic environment monitoring data can improve the accuracy of generating b bank outlet identifications.

[0073] Return to reference Figure 2 In step S203, based on the b bank branch identifiers, energy efficiency evaluation is performed on the b bank branch identifiers, and c bank branch identifiers are screened out according to the energy efficiency evaluation results, where c is greater than or equal to 1 and c is an integer, and c is less than or equal to b.

[0074] For example, energy efficiency evaluation values ​​may include: power efficiency value and power floating value. Smart meters can be deployed at the power input end of the outlets to collect power consumption data in different functional areas. The collected data is also transmitted to the bank's core computer room through the outlet's existing business network for data analysis.

[0075] Figure 5 The flowchart of generating c bank branch identifiers in the bank branch electricity energy efficiency optimization method according to the embodiment of the present disclosure is schematically shown.

[0076] like Figure 5 As shown, the method 500 includes steps S501 to S503.

[0077] Step S501, calculating the power consumption energy efficiency value of each of the b bank outlets in the nth preset period.

[0078] Figure 6 The flowchart of generating the power consumption energy efficiency value of each bank branch in the nth preset cycle in the bank branch power consumption energy efficiency optimization method according to the embodiment of the present disclosure is schematically shown.

[0079] like Figure 6 As shown, the method 600 includes steps S601 to S604.

[0080] Step S601, obtaining the total power consumption of the uninterruptible power consumption equipment of each bank branch in the nth preset period as the first power consumption of each bank branch in the nth preset period.

[0081] For example, multiple smart meters can be used to collect electricity consumption in different functional areas. Obtaining the total electricity consumption of uninterruptible power equipment in each of b bank outlets within the nth preset period can include obtaining the total electricity consumption of computer room power equipment with 24-hour power supply and the total electricity consumption of non-computer room power equipment with 24-hour power supply in each of b bank outlets within the nth preset period. Core network equipment includes network equipment, servers, monitoring equipment, etc., which need to be provided with 24-hour uninterruptible power supply, and belong to uninterruptible computer room power equipment. This scenario is the most important power consumption scenario of the outlet, if and only if core equipment is deployed, and the number of equipment access is strictly controlled. Generally refers to 24-hour self-service equipment and supporting facilities for customer use, which need to be provided with 24-hour uninterruptible power supply, and belong to uninterruptible non-computer room power equipment.

[0082] Step S602, obtaining the total power consumption of the intermittent power-consuming equipment of each of the b bank outlets in the nth preset period as the second power consumption of each bank outlet in the nth preset period.

[0083] For example, obtaining the total power consumption of intermittent power equipment in each of b bank branches in the nth preset period may include obtaining the total power consumption of computer room power equipment with non-24-hour power supply and the total power consumption of non-computer room power equipment with non-24-hour power supply in each of b bank branches in the nth preset period. The total power consumption of computer room power equipment with non-24-hour power supply refers to equipment that is deployed in the computer room but is not a core device, such as computer room lighting and fresh air facilities, which do not need to be provided with 24-hour uninterrupted power supply. They are intermittent computer room power equipment, and even if the power is cut off, it will not affect the business of the branch. For facilities, lighting, air conditioning, etc. related to the employee rest area or business processing area, although power outages will affect the customer experience, business processing can still proceed normally. They do not need to be provided with 24-hour uninterrupted power supply, and are intermittent non-computer room power equipment.

[0084] Step S603, calculating the sum of the first power consumption of each bank branch in the b bank branches in the nth preset period and the second power consumption of each bank branch in the nth preset period, and generating a fourth correlation value for each bank branch.

[0085] For example, the power consumption efficiency value of each bank branch in the nth preset period can be represented by P, the first power consumption of each bank branch in the nth preset period can be represented by Pi, and the second power consumption of each bank branch in the nth preset period can be represented by Pu. The fourth associated value of each bank branch is Pi+Pu.

[0086] Step S604, calculating the quotient of the fourth correlation value of each bank branch among the b bank branches and the first power consumption of each bank branch in the nth preset period, and generating the power consumption energy efficiency value of each bank branch in the nth preset period.

[0087] The power consumption energy efficiency value of each bank branch in the nth preset cycle can be expressed as: P = (Pi + Pu) / Pi. The ratio of total power consumption divided by power consumption in important power consumption scenarios is used as the energy efficiency index for analysis. The smaller the value of P, the higher the proportion of power consumption in important scenarios, that is, the more rational the power consumption is. Conversely, the larger the value of P, the more the rationality of power consumption needs to be improved.

[0088] The power consumption energy efficiency value of each bank branch in the nth preset period is calculated according to the total power consumption of the uninterruptible power equipment and the total power consumption of the intermittent power equipment, so as to improve the authenticity of the generated c bank branch identifications.

[0089] Return to reference Figure 5 In step S502, the floating value of electricity consumption of each of the b bank outlets in the nth preset period is calculated.

[0090] Figure 7 The flowchart of generating the floating value of electricity consumption of each bank branch in the nth preset cycle in the method for optimizing the electricity consumption energy efficiency of bank branches according to the embodiment of the present disclosure is schematically shown.

[0091] like Figure 7 As shown, the method 700 includes steps S701-S702.

[0092] Step S701, calculating the power consumption energy efficiency value of each of the b bank outlets in the n-1th preset period.

[0093] Step S702, calculating the absolute value of the difference between the power consumption energy efficiency value of each bank branch in the nth preset cycle and the power consumption energy efficiency value in the (n-1)th preset cycle, and generating the power consumption floating value of each bank branch in the nth preset cycle.

[0094] By calculating the floating value of electricity consumption of each bank branch in the nth preset cycle through the electricity consumption energy efficiency value of each bank branch in the current cycle and the previous cycle, the fidelity of generating the c bank branch identifications can be improved.

[0095] Return to reference Figure 5 In step S503, c bank branch identifiers whose power consumption energy efficiency values ​​are less than or equal to the energy efficiency threshold and whose power consumption floating values ​​are greater than or equal to the floating threshold in the nth preset period are obtained from the b bank branch identifiers to generate c bank branch identifiers.

[0096] By conducting a second step of screening of outlets based on electricity energy efficiency values ​​and electricity floating values, the accuracy of generating c bank outlet identifications can be improved.

[0097] In addition, an electricity consumption evaluation model can be generated based on the electricity consumption energy efficiency value and the electricity consumption floating value. Using the above energy efficiency indicators as reference, all outlets are included in the evaluation model for vertical and horizontal comparison. The vertical indicator uses the numerical value of the electricity efficiency value of all outlets within the jurisdiction within a specific time period (weekly, monthly or annually) as the rating standard. The smaller the electricity efficiency value, the higher the rationality of electricity consumption. Sort the electricity efficiency values ​​of all outlets within the jurisdiction from small to large, and divide them equally into 3 levels, P1, P2, and P3, where P1 represents the lowest energy efficiency index. The horizontal indicator uses the electricity floating value of the change of the electricity efficiency value of the outlet itself within a specific time period (weekly, monthly or annually) as the rating standard. The more obvious the decline, the more in place the optimization measures are implemented. For example, the electricity consumption floating value can be represented by Ps. The electricity consumption floating value values ​​of all outlets are sorted from large to small and divided equally into 3 levels, Ps1, Ps2, and Ps3, where Ps1 represents the largest decline. The evaluation model can be divided into 9 levels, with level 1 indicating the lowest energy efficiency and the largest reduction, and level 9 indicating the highest energy efficiency and the smallest reduction (or the largest increase).

[0098] For example, there are 450 outlets participating in the assessment in the jurisdiction. According to the above rules, there will be 50 outlets at each level. Managers can refer to the above assessment model, regularly praise outlets with higher ratings (level 1), and invite them to share their energy efficiency management experience. At the same time, they can provide targeted guidance to outlets with lower ratings (level 9) to help them improve their electricity efficiency. Of course, the assessment model can also be combined with actual conditions to reward outlets with a significant decline in energy efficiency but ranked low, to encourage them to further reduce energy efficiency. The specific usage method can be adjusted dynamically based on actual working conditions.

[0099] Return to reference Figure 2 In step S204, d bank branch identifiers are obtained from a bank branch identifiers, wherein the d bank branch identifiers and the c bank branch identifiers do not overlap with each other, d is greater than or equal to 1 and d is an integer, and the sum of d and c is equal to a.

[0100] Figure 8 The flowchart of generating d bank branch identifiers in the bank branch electricity energy efficiency optimization method according to the embodiment of the present disclosure is schematically shown.

[0101] like Figure 8 As shown, the method 800 includes steps S801 to S803.

[0102] Step S801, obtaining e bank branch identifiers whose dynamic ring values ​​are greater than a preset dynamic ring threshold from the a bank branch identifiers, wherein e is greater than or equal to 1 and e is an integer, and the sum of e and b is equal to a.

[0103] Step S802, obtaining f bank branch identifiers from the b bank branch identifiers whose electricity energy efficiency values ​​are greater than the energy efficiency threshold or whose electricity floating values ​​are less than the floating threshold in the nth preset period, where f is greater than or equal to 1 and d is an integer, and the sum of f and c is equal to b.

[0104] Step S803, obtaining e bank branch identifiers and f bank branch identifiers, and generating d bank branch identifiers, wherein the sum of e and f is equal to d.

[0105] Through the dynamic ring value, electricity efficiency value and electricity floating value, d bank outlets that need energy efficiency transformation are screened out, which can improve the reliability of the generated d bank outlets.

[0106] Step S205: based on the d bank branch identifiers, acquiring characteristic data of each electrical device in the d bank branches.

[0107] Step S206, inputting the characteristic data of the power equipment of each of the d bank outlets into a pre-generated power energy efficiency model, and using the power energy efficiency model to output the power equipment configuration plan of each of the d bank outlets, so as to optimize the power energy efficiency of each of the d bank outlets, wherein the power energy efficiency model is generated by training based on the characteristic data of the power equipment of the c bank outlets.

[0108] Before inputting the characteristic data of electrical equipment of each of the d bank branches into the pre-generated electricity energy efficiency model, the characteristic data of electrical equipment of each of the d bank branches may also be cleaned to remove outliers, missing values ​​and noise data.

[0109] By cleaning the data of d bank branches, removing outliers, removing missing values ​​and denoising, the computing efficiency can be improved and computing resources can be saved.

[0110] This solution can ensure that the outlets are always in the best operating state by obtaining dynamic environment monitoring data in real time, providing technical support for the stable operation of the business. At the same time, a quantitative analysis is conducted based on the size of the outlets and power consumption, and a set of outlet energy efficiency evaluation system is constructed to identify problems in energy utilization and provide data support for energy conservation and emission reduction for enterprises.

[0111] Fig. 9 The structural block diagram of the bank branch electricity energy efficiency optimization device according to the embodiment of the present disclosure is schematically shown.

[0112] like Fig. 9 As shown, the device 900 includes: a first acquisition module 901 , a second acquisition module 902 , a first screening module 903 , a third acquisition module 904 , a fourth acquisition module 905 and a first generation module 906 .

[0113] The first acquisition module 901 is used to acquire a bank branch identifiers, wherein each of the a bank branch identifiers is unique, a is greater than or equal to 2 and a is an integer. In one embodiment, the first acquisition module 901 can be used to execute the step S201 described above, which will not be repeated here.

[0114] The second acquisition module 902 is used to acquire monitoring data of each of the a bank branch identifiers in the nth preset period based on the a bank branch identifiers, and acquire b bank branch identifiers from the a bank branch identifiers according to the monitoring data, wherein b is greater than or equal to 1 and b is an integer, b is less than or equal to a, and n is greater than or equal to 2 and n is an integer. In one embodiment, the second acquisition module 902 can be used to execute step S202 described above.

[0115] The second acquisition module 902 includes: a second generation module and a third generation module.

[0116] The second generation module is used to obtain the dynamic environment monitoring data of each of the a bank outlets in the nth preset period, perform data processing on the dynamic environment monitoring data, and generate dynamic environment values ​​of the a bank outlets. In one embodiment, the second generation module can be used to execute step S301 described above.

[0117] The second generation module includes: a fourth generation module, a fifth generation module, a sixth generation module and a seventh generation module.

[0118] The fourth generating module is used to obtain the number of real-time warnings of each bank branch in the nth preset period among the a bank branches, the weight of the preset number of real-time warnings is a first weight, and calculate the product of the number of real-time warnings of each bank branch in the nth preset period and the first weight to generate a first association value for each bank branch. In one embodiment, the fourth generating module can be used to execute step S401 described above, which will not be repeated here.

[0119] The fifth generation module is used to obtain the number of risk event warnings of each bank branch in the nth preset period among a bank branches, the weight of the preset number of risk event warnings is the second weight, calculate the product of the number of risk event warnings of each bank branch in the nth preset period and the second weight, and generate a second association value for each bank branch. In one embodiment, the fifth generation module can be used to execute step S402 described above, which will not be repeated here.

[0120] The sixth generation module is used to obtain the failure rate of each bank branch in the nth preset period among the a bank branches, the weight of the preset failure rate is the third weight, calculate the product of the failure rate of each bank branch in the nth preset period and the third weight, and generate a third association value for each bank branch. In one embodiment, the sixth generation module can be used to execute step S403 described above, which will not be repeated here.

[0121] The seventh generation module is used to calculate the sum of the first association value, the second association value and the third association value of each bank branch among the a bank branches, and generate the dynamic ring value of the a bank branches. In one embodiment, the seventh generation module can be used to execute the step S404 described above, which will not be repeated here.

[0122] The third generation module is used to obtain b bank branch identifications whose dynamic ring values ​​are less than or equal to the preset dynamic ring threshold from a bank branch identifications to generate b bank branch identifications. In one embodiment, the third generation module can be used to execute step S302 described above, which will not be repeated here.

[0123] The first screening module 903 is used to perform energy efficiency evaluation on the b bank outlets based on the b bank outlet identifiers, and screen out c bank outlet identifiers according to the energy efficiency evaluation results, where c is greater than or equal to 1 and c is an integer, and c is less than or equal to b. In one embodiment, the first screening module 903 can be used to execute step S203 described above.

[0124] The first screening module 903 includes a first calculation module, a second calculation module and an eighth generation module.

[0125] The first calculation module is used to calculate the power consumption efficiency value of each of the b bank outlets in the nth preset period. In one embodiment, the first calculation module can be used to execute step 501 described above.

[0126] The first calculation module includes: a fifth acquisition module, a sixth acquisition module, a ninth generation module and a tenth generation module.

[0127] The fifth acquisition module is used to obtain the total power consumption of the uninterruptible power consumption equipment of each of the b bank branches in the nth preset period as the first power consumption of each bank branch in the nth preset period. In one embodiment, the fifth acquisition module can be used to execute step S601 described above, which will not be repeated here.

[0128] The sixth acquisition module is used to obtain the total power consumption of the intermittent power-consuming equipment of each of the b bank outlets in the nth preset period as the second power consumption of each bank outlet in the nth preset period. In one embodiment, the sixth acquisition module can be used to execute step S602 described above, which will not be repeated here.

[0129] The ninth generating module is used to calculate the sum of the first power consumption of each bank branch in the nth preset period and the second power consumption of each bank branch in the nth preset period, and generate a fourth correlation value for each bank branch. In one embodiment, the ninth generating module can be used to execute step S603 described above, which will not be repeated here.

[0130] The tenth generating module is used to calculate the quotient of the fourth correlation value of each bank branch among the b bank branches and the first power consumption of each bank branch in the nth preset period, and generate the power consumption energy efficiency value of each bank branch in the nth preset period. In one embodiment, the tenth generating module can be used to execute step S604 described above, which will not be repeated here.

[0131] The second calculation module is used to calculate the floating value of electricity consumption of each of the b bank outlets in the nth preset period. In one embodiment, the second calculation module can be used to execute the step S502 described above.

[0132] The second calculation module includes: a third calculation module and an eleventh generation module.

[0133] The third calculation module is used to calculate the power consumption efficiency value of each of the b bank outlets in the n-1th preset period. In one embodiment, the third calculation module can be used to execute the step S701 described above, which will not be described in detail here.

[0134] The eleventh generating module is used to calculate the absolute value of the difference between the power consumption energy efficiency value of each bank branch in the nth preset period and the power consumption energy efficiency value in the n-1th preset period of each bank branch among the b bank branches, and generate the power consumption floating value of each bank branch in the nth preset period. In one embodiment, the eleventh generating module can be used to execute step S702 described above, which will not be repeated here.

[0135] The eighth generation module is used to obtain, from the b bank branch identifiers, c bank branch identifiers whose power consumption energy efficiency value is less than or equal to the energy efficiency threshold and whose power consumption floating value is greater than or equal to the floating threshold in the nth preset period, and generate c bank branch identifiers. In one embodiment, the eighth generation module can be used to execute step S503 described above, which will not be repeated here.

[0136] The third acquisition module 904 is used to acquire d bank branch identifiers from a bank branch identifiers, wherein the d bank branch identifiers and the c bank branch identifiers do not overlap with each other, d is greater than or equal to 1 and d is an integer, and the sum of d and c is equal to a. In one embodiment, the third acquisition module 904 can be used to execute step S204 described above.

[0137] The third acquisition module 904 includes: a seventh acquisition module, an eighth acquisition module and a twelfth generation module.

[0138] The seventh acquisition module is used to obtain e bank branch identifiers whose dynamic ring values ​​are greater than a preset dynamic ring threshold from the a bank branch identifiers, where e is greater than or equal to 1 and e is an integer, and the sum of e and b is equal to a. In one embodiment, the seventh acquisition module can be used to execute step S801 described above, which will not be repeated here.

[0139] The eighth acquisition module is used to obtain, from the b bank branch identifiers, f bank branch identifiers whose power consumption energy efficiency value is greater than the energy efficiency threshold or whose power consumption floating value is less than the floating threshold in the nth preset period, where f is greater than or equal to 1 and d is an integer, and the sum of f and c is equal to b. In one embodiment, the eighth acquisition module can be used to execute step S802 described above, which will not be repeated here.

[0140] The twelfth generation module is used to obtain e bank branch identifiers and f bank branch identifiers to generate d bank branch identifiers, where the sum of e and f is equal to d. In one embodiment, the twelfth generation module can be used to execute step S803 described above, which will not be repeated here.

[0141] The fourth acquisition module 905 is used to acquire characteristic data of each power-consuming device in the d bank outlets based on the d bank outlets identifiers. In one embodiment, the fourth acquisition module 905 can be used to execute the step S205 described above, which will not be described in detail here.

[0142] The first generation module 906 is used to input the characteristic data of the power consumption equipment of each of the d bank outlets into a pre-generated power consumption energy efficiency model, and use the power consumption energy efficiency model to output the configuration plan of the power consumption equipment of each of the d bank outlets, so as to optimize the power consumption energy efficiency of each of the d bank outlets, wherein the power consumption energy efficiency model is generated based on the training of the characteristic data of the power consumption equipment of the c bank outlets. In one embodiment, the first generation module 906 can be used to execute step S206 described above, which will not be repeated here.

[0143] According to an embodiment of the present disclosure, any multiple modules of the first acquisition module 901, the second acquisition module 902, the first screening module 903, the third acquisition module 904, the fourth acquisition module 905 and the first generation module 906 can be combined in one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first acquisition module 901, the second acquisition module 902, the first screening module 903, the third acquisition module 904, the fourth acquisition module 905 and the first generation module 906 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware and firmware or in an appropriate combination of any of them. Alternatively, at least one of the first acquisition module 901, the second acquisition module 902, the first screening module 903, the third acquisition module 904, the fourth acquisition module 905 and the first generation module 906 can be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function can be executed.

[0144] Fig.10 A block diagram of an electronic device suitable for implementing a method for optimizing electricity energy efficiency at a bank branch according to an embodiment of the present disclosure is schematically shown.

[0145] like Fig.10 As shown, the electronic device 1000 according to an embodiment of the present disclosure includes a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage part 1008 to a random access memory (RAM) 1003. The processor 1001 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include an onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0146] In RAM1003, various programs and data required for the operation of electronic device 1000 are stored. Processor 1001, ROM 1002 and RAM1003 are connected to each other via bus 1004. Processor 1001 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM1002 and / or RAM1003. It should be noted that the program can also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0147] According to an embodiment of the present disclosure, the electronic device 1000 may further include an input / output (I / O) interface 1005, which is also connected to the bus 1004. The electronic device 1000 may further include one or more of the following components connected to the I / O interface 1005: an input portion 1006 including a keyboard, a mouse, etc.; an output portion 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 1008 including a hard disk, etc.; and a communication portion 1009 including a network interface card such as a LAN card, a modem, etc. The communication portion 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed, so that a computer program read therefrom is installed into the storage portion 1008 as needed.

[0148] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0149] According to an embodiment of the present disclosure, a computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, a computer-readable storage medium may include the ROM 1002 and / or the RAM 1003 described above and / or one or more memories other than the ROM 1002 and the RAM 1003.

[0150] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the bank branch electricity energy efficiency optimization method provided by the embodiment of the present disclosure.

[0151] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 1001. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0152] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 1009, and / or installed from the removable medium 1011. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0153] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1009, and / or installed from the removable medium 1011. When the computer program is executed by the processor 1001, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0154] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0155] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0156] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0157] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for optimizing the electricity efficiency of bank outlets, characterized in that: The method includes: Obtain a bank branch identifiers, wherein each of the a bank branch identifiers is unique, a is greater than or equal to 2 and a is an integer; Based on a bank branch identifiers, obtain monitoring data of each bank branch in the a bank branch identifiers in the nth preset period, and obtain b bank branch identifiers from the a bank branch identifiers according to the monitoring data, wherein b is greater than or equal to 1 and b is an integer, b is less than or equal to a, and n is greater than or equal to 2 and n is an integer; Based on the b bank branch identifiers, perform energy efficiency evaluation on the b bank branch identifiers, and select c bank branch identifiers according to the energy efficiency evaluation results, where c is greater than or equal to 1 and c is an integer, and c is less than or equal to b; Obtaining d bank branch identifiers from a bank branch identifiers, wherein the d bank branch identifiers and the c bank branch identifiers do not overlap with each other, d is greater than or equal to 1 and d is an integer, and the sum of d and c is equal to a; Based on the d bank branch identifiers, acquiring characteristic data of each electrical device in the d bank branches; and The characteristic data of power consumption equipment of each of the d bank outlets is input into a pre-generated power consumption energy efficiency model, and the power consumption energy efficiency model is used to output a configuration plan of power consumption equipment of each of the d bank outlets, so as to optimize the power consumption energy efficiency of each of the d bank outlets, wherein the power consumption energy efficiency model is generated by training based on the characteristic data of power consumption equipment of the c bank outlets.

2. The method according to claim 1, characterized in that The monitoring data includes: dynamic environment monitoring data, the monitoring data of each bank branch in the a bank branches in the nth preset period is obtained, and b bank branch identifiers are obtained from the a bank branch identifiers according to the monitoring data, including: Acquire dynamic environment monitoring data of each bank branch in a bank branches within an nth preset period, perform data processing on the dynamic environment monitoring data, and generate dynamic environment values ​​of the a bank branches; and Obtain b bank branch identifications whose dynamic ring values ​​are less than or equal to a preset dynamic ring threshold from a bank branch identifications, and generate b bank branch identifications.

3. The method according to claim 2, characterized in that The dynamic environment monitoring data includes: the number of real-time warnings within the nth preset period, the number of risk event warnings within the nth preset period, and the failure rate within the nth preset period. The dynamic environment monitoring data of each bank branch in the a bank branches in the nth preset period is obtained, and the dynamic environment monitoring data is processed to generate the dynamic environment values ​​of the a bank branches, including: Obtaining the number of real-time warnings of each bank branch in the nth preset period among a bank branches, where the weight of the preset number of real-time warnings is a first weight, calculating the product of the number of real-time warnings of each bank branch in the nth preset period and the first weight, and generating a first association value of each bank branch; Obtaining the number of risk event warnings of each bank branch in the nth preset period among a bank branches, where the weight of the preset number of risk event warnings is a second weight, and calculating the product of the number of risk event warnings of each bank branch in the nth preset period and the second weight to generate a second association value for each bank branch; Obtaining the failure rate of each bank branch in the nth preset period among a bank branches, where the weight of the preset failure rate is a third weight, calculating the product of the failure rate of each bank branch in the nth preset period and the third weight, and generating a third association value for each bank branch; and The sum of the first association value, the second association value and the third association value of each bank branch among a bank branches is calculated to generate the dynamic ring values ​​of the a bank branches.

4. The method according to claim 1, characterized in that: The energy efficiency evaluation value includes: an electricity energy efficiency value and an electricity floating value. Based on the b bank branch identifiers, the energy efficiency evaluation is performed on the b bank branch identifiers, and c bank branch identifiers are screened out according to the energy efficiency evaluation results, including: Calculate the power consumption energy efficiency value of each of the b bank branches in the nth preset period; Calculating the floating value of electricity consumption of each of the b bank outlets in the nth preset period; and Obtain c bank branch identifications whose electricity energy efficiency values ​​are less than or equal to the energy efficiency threshold and whose electricity floating values ​​are greater than or equal to the floating threshold in the nth preset period from b bank branch identifications, and generate c bank branch identifications.

5. The method according to claim 4, characterized in that The calculating of the power consumption energy efficiency value of each of the b bank outlets in the nth preset period includes: Obtaining the total power consumption of the uninterruptible power consumption equipment of each of the b bank branches in the nth preset period as the first power consumption of each bank branch in the nth preset period; Obtaining the total power consumption of the intermittent power-consuming equipment of each of the b bank outlets in the nth preset period as the second power consumption of each bank outlet in the nth preset period; Calculating the sum of the first power consumption of each bank branch in the nth preset period and the second power consumption of each bank branch in the nth preset period, and generating a fourth correlation value for each bank branch; and The quotient of the fourth correlation value of each bank branch among the b bank branches and the first power consumption of each bank branch in the nth preset period is calculated to generate the power consumption energy efficiency value of each bank branch in the nth preset period.

6. The method according to claim 4, characterized in that Calculating the floating value of electricity consumption of each of the b bank outlets in the nth preset period, including: Calculate the power consumption energy efficiency value of each of the b bank branches in the n-1th preset period; and The absolute value of the difference between the power consumption energy efficiency value of each bank branch in the nth preset cycle and the power consumption energy efficiency value in the n-1th preset cycle is calculated to generate the power consumption floating value of each bank branch in the nth preset cycle.

7. The method according to claim 4, characterized in that The step of obtaining d bank branch identifiers from a bank branch identifiers includes: Obtaining e bank branch identifiers whose dynamic ring values ​​are greater than a preset dynamic ring threshold from the a bank branch identifiers, wherein e is greater than or equal to 1 and e is an integer, and the sum of e and b is equal to a; Obtaining from the b bank branch identifiers f bank branch identifiers whose power consumption energy efficiency value is greater than the energy efficiency threshold or whose power consumption floating value is less than the floating threshold in the nth preset period, where f is greater than or equal to 1 and d is an integer, and the sum of f and c is equal to b; and Obtain e bank branch IDs and f bank branch IDs, and generate d bank branch IDs, where the sum of e and f is equal to d.

8. The method according to any one of claims 1 to 7, characterized in that: Before inputting the characteristic data of the electric equipment of each of the d bank outlets into the pre-generated electric energy efficiency model, the method further includes: The characteristic data of electrical equipment in each of the d bank outlets are cleaned, outliers are removed, missing values ​​are removed, and noise data is removed.

9. A bank branch electricity energy efficiency optimization device, characterized in that: The device includes: A first acquisition module is used to acquire a bank branch identifiers, wherein each of the a bank branch identifiers is unique, wherein a is greater than or equal to 2 and a is an integer; A second acquisition module is used to acquire monitoring data of each of the a bank branch identifiers in the nth preset period based on the a bank branch identifiers, and acquire b bank branch identifiers from the a bank branch identifiers according to the monitoring data, wherein b is greater than or equal to 1 and b is an integer, b is less than or equal to a, and n is greater than or equal to 2 and n is an integer; A first screening module is used to perform energy efficiency evaluation on b bank outlets based on the b bank outlet identifiers, and screen out c bank outlet identifiers according to the energy efficiency evaluation results, where c is greater than or equal to 1 and c is an integer, and c is less than or equal to b; A third acquisition module is used to acquire d bank branch identifiers from a bank branch identifiers, wherein the d bank branch identifiers and the c bank branch identifiers do not overlap with each other, d is greater than or equal to 1 and d is an integer, and the sum of d and c is equal to a; A fourth acquisition module, configured to acquire characteristic data of each electrical device in the d bank outlets based on the d bank outlet identifiers; and The first generation module is used to input the characteristic data of power consumption equipment of each of the d bank outlets into a pre-generated power consumption energy efficiency model, and use the power consumption energy efficiency model to output the power consumption equipment configuration plan of each of the d bank outlets, so as to optimize the power consumption energy efficiency of each of the d bank outlets, wherein the power consumption energy efficiency model is generated based on the training of the characteristic data of power consumption equipment of the c bank outlets.

10. An electronic device comprising: one or more processors; a memory for storing one or more computer programs, It is characterized in that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program or instruction is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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