Electric power data query method and device, equipment, storage medium and program product

Abstract

The invention discloses an electric power data query method and device, equipment, a storage medium and a program product, and relates to the technical field of electric power data management. The method comprises the steps of obtaining data query task content; understanding the content of the data query task to obtain structured query task description data related to the power grid knowledge data; and querying associated target power data from a power database according to the target power grid knowledge data matched with the structured query task description data. The spoken data query task content is converted into the structured query task description data related to the power grid knowledge data, and the professional power data is queried based on the target power grid knowledge data matched with the structured query task description data, so that the efficiency, accuracy and friendliness of querying the power data by non-power professionals are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power data management, and in particular to a power data query method, device, equipment, storage medium and program product. Background Art

[0002] In the field of data management and analysis in the power industry, the professionalism and complexity of power data have always been a challenge in the industry. Traditional power data management systems are mainly aimed at professional users in the power industry. These systems are usually highly specialized and complex, and can meet the needs of power professionals for accurate management and in-depth analysis of data. However, this specialized data management method also brings some problems.

[0003] Electricity data usually contains a large number of professional terms, complex parameters and multi-dimensional information, all of which require certain electricity expertise to correctly interpret and apply. In some cross-industry application scenarios, such as energy management, environmental protection, urban planning and other fields, non-electricity professionals may need to combine electricity data for comprehensive analysis and decision-making. However, for users in non-electricity industries or non-electricity professionals, it is very difficult to understand and use these professional electricity data. When they need to query electricity data, they often need to rely on the help of electricity professionals, which not only increases the workload of electricity professionals, but also makes the efficiency and accuracy of electricity data query poor. Summary of the invention

[0004] The present invention provides a power data query method, device, equipment, storage medium and program product to solve the problem of poor efficiency and accuracy of power data query by non-power professionals.

[0005] In a first aspect, an embodiment of the present invention provides a method for querying power data, comprising:

[0006] Get the data query task content;

[0007] Understanding the content of the data query task to obtain structured query task description data related to power grid knowledge data;

[0008] According to the target power grid knowledge data matched by the structured query task description data, the associated target power data is queried from the power database.

[0009] In a second aspect, an embodiment of the present invention provides a power data query device, comprising:

[0010] Task content acquisition module, used to obtain data query task content;

[0011] A task content understanding module, used to understand the content of the data query task and obtain structured query task description data related to the power grid knowledge data;

[0012] The data query module is used to query the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data.

[0013] In a third aspect, an embodiment of the present invention provides an electronic device, the electronic device comprising:

[0014] at least one processor; and

[0015] a memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the power data query method described in any embodiment of the present invention.

[0017] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power data query method described in any embodiment of the present invention when executed.

[0018] In a fifth aspect, an embodiment of the present invention provides a computer program product including a computer program, and when the computer program is executed by a processor, the power data query method described in any embodiment of the present invention is implemented.

[0019] The technical solution of the embodiment of the present invention obtains the data query task content; understands the data query task content, obtains the structured query task description data related to the power grid knowledge data; and queries the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data. By converting the colloquial data query task content into the structured query task description data related to the power grid knowledge data, and querying the professional power data based on the target power grid knowledge data matched by the structured query task description data, the problem of poor efficiency and accuracy of non-power professionals in querying power data is solved, and the efficiency, accuracy and friendliness of non-power professionals in querying power data are improved.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A flowchart of a power data query method provided in Embodiment 1 of the present invention;

[0023] Figure 2 A schematic diagram of the structure of a power data query device provided in Embodiment 2 of the present invention;

[0024] Figure 3 A schematic diagram of the structure of an electronic device for implementing the power data query method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment 1

[0028] Figure 1 This is a flow chart of a power data query method provided in the first embodiment of the present invention. This embodiment is applicable to situations where non-power professionals query power data. The method can be executed by a power data query device. The power data query device can be implemented in the form of hardware and / or software. The power data query device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0029] S110, obtaining data query task content.

[0030] Among them, the data query task content can be understood as the content used to describe the data query task, which can be a data query question or a data query instruction input by the user. In this embodiment, the data query task content is the content used to query power data described in natural language. It can be understood that the purpose of the data query task content is to query professional power data, but for non-power professionals, the proposed data query task content may have colloquial problems, and may be inconsistent with the professional description of actual power data, which also increases the difficulty and accuracy of power data query.

[0031] Exemplarily, a method for acquiring the data query task content is to acquire the data query task content described in a natural language input by a user through a human-computer interaction interface of the electronic device.

[0032] S120: Understand the data query task content and obtain structured query task description data related to power grid knowledge data.

[0033] Among them, the structured query task description data can be understood as the result of using power grid knowledge data to standardize the data query task content. Compared with the colloquial data query task content, the semantics of the structured query task description data remains basically unchanged, but it is closer to the professional terminology expression of power grid knowledge data.

[0034] Specifically, the data query task content is semantically understood, and based on the semantics of the data query task content, the data query task content is expressed using relevant professional terms of the power grid knowledge data to obtain structured query task description data related to the power grid knowledge data, so as to accurately query power data in the power database.

[0035] Exemplarily, the method of understanding the content of the data query task and obtaining structured query task description data related to the power grid knowledge data can be a rule-based method, a natural language processing algorithm-based method, or a large language model-based method, and the embodiments of the present invention do not impose any restrictions on this.

[0036] S130 , querying the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data.

[0037] The target power grid knowledge data can be understood as the power grid knowledge data that matches the structured query task description data, and the power grid knowledge data can be understood as data related to professional knowledge in the power grid. The power database can be understood as a database for storing power data. The target power data can be understood as the power data to be queried by the data query task content.

[0038] Specifically, the target power grid knowledge data matching the structured query task description data is queried from the power grid knowledge database, and the target power data associated with the target power grid knowledge data is queried from the power database.

[0039] The technical solution of the embodiment of the present invention obtains the data query task content; understands the data query task content, obtains the structured query task description data related to the power grid knowledge data; and queries the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data. By converting the colloquial data query task content into the structured query task description data related to the power grid knowledge data, and querying the professional power data based on the target power grid knowledge data matched by the structured query task description data, the efficiency, accuracy and friendliness of non-power professionals querying power data are improved.

[0040] As an optional embodiment of the embodiment of the present application, S120, the understanding of the data query task content to obtain structured query task description data matching the power grid knowledge data, includes:

[0041] S121. A semantic understanding module based on a task content understanding model performs semantic understanding on the data query task content to obtain query task content semantic data.

[0042] The task content understanding model can be understood as a model for understanding the content of data query tasks. The task content understanding model includes: a semantic understanding module and a semantic association module; the semantic understanding module is used to understand the semantics of the data query task content. The query task content semantic data can be understood as data used to describe the semantics of the data query task content, for example, it can be key data or feature data in the query task content semantic data.

[0043] It is understandable that the task content understanding model may be a deep learning model or a large language model. In order to better understand the data query task content described in natural language, the task content understanding model may be a large language model.

[0044] Specifically, the data query task content is input into the task content understanding model, and the data query task content is semantically understood through the semantic understanding module to obtain the query task content semantic data of the data query task content, and the query task content semantic data is input into the semantic association module.

[0045] S122. A semantic association module based on a task description content understanding model generates structured query task description data related to the power grid knowledge data according to the query task content semantic data.

[0046] Among them, the semantic association module is used to semantically associate the query task content semantic data with the power grid knowledge.

[0047] Specifically, the semantic association module of the task description content understanding model determines the power grid knowledge data that has semantic association with the input query task content semantic data, and generates structured query task description data based on the power grid knowledge data. Thus, the colloquial query task description content is converted into structured query task description data related to the power grid knowledge data.

[0048] This embodiment can provide a basis for querying professional power data by converting unstructured query task description content into structured query task description data related to power grid knowledge data.

[0049] As an optional embodiment of this embodiment, S130, querying the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data, includes:

[0050] S131. A matching module based on a power data query model searches for target power grid knowledge data matching the structured query task description data from a power grid knowledge database, and matches power key data associated with the target power grid knowledge data from the power database.

[0051] Among them, the power data query model can be understood as a model for querying power data, and the power data query model can be a large language model. The power data query model includes a matching module and a query module. The matching module is used to determine the power grid knowledge data and power key data that match the structured query task description data. The power key data can be key information for classifying power data, such as the type of power data, collection time, and collection object.

[0052] Specifically, through the matching module of the power data query model, the power grid knowledge database is searched based on the structured query task description data related to the power grid knowledge data to obtain the target power grid knowledge data that matches the structured query task description data. The power database is queried based on the target power grid knowledge data to obtain the power key data that matches the target power grid knowledge data, and the power key data is sent to the query module.

[0053] In an optional embodiment, searching for target power grid knowledge data that matches the structured query task description data from a power grid knowledge database includes: calculating the difference between the structured query task description data and each power grid knowledge data in the power grid knowledge database; if the difference is less than a threshold, determining the power grid knowledge data as the target power grid knowledge data that matches the structured query task description data.

[0054] Exemplarily, based on the difference between the structured query task description data and each power grid knowledge data in the power grid knowledge database, a calculation method for determining the target power grid knowledge data matching the structured query task description data can be expressed as:

[0055]

[0056] When the above formula is satisfied, it indicates the matching degree between the nth structured query task description data and the mth power grid knowledge data. n represents the nth structured query task description data, n is a positive integer, ε is the preset threshold, D m Represents the mth power grid knowledge data, where m is a positive integer.

[0057] S132. A query module based on a power data query model queries the target power data associated with the power key data from the power database.

[0058] Specifically, through the query module of the power data query model, the power database is queried based on the received power key data to obtain the target power data associated with the power key data.

[0059] In an optional embodiment, it also includes: using the key power data as a label of the target power data, which can further improve the power data retrieval efficiency and data comprehensive application speed.

[0060] This embodiment queries the key power data associated with the power grid knowledge according to the structured query task description data related to the power grid knowledge data, and searches for the power data associated with the key power data. It can find the related power data based on the power grid knowledge corresponding to the query task description data, so that non-power professionals do not need to master the professional knowledge of the power grid, but can query highly specialized and complex power data by inputting natural language, thereby improving the friendliness of power data query to non-power professionals and making it simple, accurate and efficient for non-power professionals to query specialized and complex power data.

[0061] As an optional embodiment of the embodiment of the present application, before obtaining the data query task content, it also includes:

[0062] Extract key data of power data in power database;

[0063] Associating the key data with power grid knowledge data in a power grid knowledge database;

[0064] A power data query model is constructed based on a data set consisting of the key data, power data related to the key data, and power grid knowledge data associated with the key data.

[0065] Specifically, the key data of the power data in the power database is extracted to obtain the key data and the relationship between the key data and the power data; and the key data is associated with the power grid knowledge data in the power grid knowledge base. A data set is formed based on the key data, the power data related to the key data, and the power grid knowledge data associated with the key data, and a basic model is trained based on the data set to obtain a power data query model.

[0066] Exemplarily, a method of establishing association between key data and power grid knowledge data in a power grid knowledge database may be to establish a relationship mapping table or a knowledge graph.

[0067] Embodiment 2

[0068] Figure 2 This is a schematic diagram of the structure of a power data query device provided by Embodiment 2 of the present invention. Figure 2 As shown, the device includes: a task content acquisition module 210, a task content understanding module 220 and a data query module 230; wherein,

[0069] The task content acquisition module 210 is used to acquire the data query task content;

[0070] The task content understanding module 220 is used to understand the data query task content and obtain structured query task description data related to the power grid knowledge data;

[0071] The data query module 230 is used to query the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data.

[0072] The technical solution of the embodiment of the present invention obtains the data query task content; understands the data query task content, obtains the structured query task description data related to the power grid knowledge data; and queries the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data. By converting the colloquial data query task content into the structured query task description data related to the power grid knowledge data, and querying the professional power data based on the target power grid knowledge data matched by the structured query task description data, the efficiency, accuracy and friendliness of non-power professionals querying power data are improved.

[0073] Optionally, the task content understanding module 220 is specifically used to:

[0074] A semantic understanding module based on a task content understanding model performs semantic understanding on the data query task content to obtain query task content semantic data;

[0075] A semantic association module based on a task content understanding model generates structured query task description data related to the power grid knowledge data according to the query task content semantic data.

[0076] Optionally, the data query module 230 includes:

[0077] A data matching unit, configured to search a power grid knowledge database for target power grid knowledge data matching the structured query task description data based on a matching module of a power data query model, and to match power key data associated with the target power grid knowledge data from the power database;

[0078] A data query unit is used to query the target power data associated with the power key data from the power database based on the query module of the power data query model.

[0079] Optionally, a data matching unit is used to:

[0080] Calculate the difference between the structured query task description data and each power grid knowledge data in the power grid knowledge database;

[0081] If the difference is less than a threshold, the power grid knowledge data is determined as target power grid knowledge data that matches the structured query task description data.

[0082] Optionally, also include:

[0083] A key data extraction module is used to extract key data of the power data in the power database before obtaining the data query task content; the key data is associated with the power grid knowledge data in the power grid knowledge database;

[0084] The power data query model construction module is used to construct a power data query model according to a data set consisting of the key data, power data related to the key data, and power grid knowledge data associated with the key data.

[0085] Optionally, also include:

[0086] The label determination module is used to use the key power data as a label of the target power data.

[0087] The power data query device provided in the embodiment of the present invention can execute the power data query method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0088] Embodiment 3

[0089] Figure 3 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0090] like Figure 3 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0091] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0092] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the power data query method.

[0093] In some embodiments, the power data query method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the power data query method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the power data query method in any other appropriate manner (e.g., by means of firmware).

[0094] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0095] In some embodiments, the power data query method may be implemented as a computer program, which is invisibly included in a computer program product. The computer program implements the power data query method of the present invention when executed by a processor. The computer program product can be understood as a software product that implements its solution mainly through a computer program. The computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the computer program, when executed by the processor, implements the functions / operations specified in the flowchart and / or block diagram. The computer program can be executed entirely on the machine, partially on the machine, partially on the machine as an independent software package and partially on a remote machine, or entirely on a remote machine or server.

[0096] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0097] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0098] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0099] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0100] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0101] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for querying power data, characterized in that: include: Get the data query task content; Understanding the content of the data query task to obtain structured query task description data related to power grid knowledge data; According to the target power grid knowledge data matched by the structured query task description data, the associated target power data is queried from the power database.

2. The method according to claim 1, characterized in that The step of understanding the content of the data query task and obtaining structured query task description data matching the power grid knowledge data includes: A semantic understanding module based on a task content understanding model performs semantic understanding on the data query task content to obtain query task content semantic data; A semantic association module based on a task content understanding model generates structured query task description data related to the power grid knowledge data according to the query task content semantic data.

3. The method according to claim 1, characterized in that The step of querying the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data includes: A matching module based on the power data query model searches for target power grid knowledge data matching the structured query task description data from a power grid knowledge database, and matches power key data associated with the target power grid knowledge data from the power database; A query module based on the power data query model queries the target power data associated with the power key data from the power database.

4. The method according to claim 3, characterized in that Searching the target power grid knowledge data matching the structured query task description data from the power grid knowledge database includes: Calculate the difference between the structured query task description data and each power grid knowledge data in the power grid knowledge database; If the difference is less than a threshold, the power grid knowledge data is determined as target power grid knowledge data that matches the structured query task description data.

5. The method according to claim 3, characterized in that: Before obtaining the data query task content, it also includes: Extracting key data of power data in the power database; the key data is associated with power grid knowledge data in the power grid knowledge database; A power data query model is constructed based on a data set consisting of the key data, power data related to the key data, and power grid knowledge data associated with the key data.

6. The method according to claim 3, characterized in that: Also includes: The key power data is used as a label of the target power data.

7. A power data query device, characterized in that: include: Task content acquisition module, used to obtain data query task content; A task content understanding module, used to understand the content of the data query task and obtain structured query task description data related to the power grid knowledge data; The data query module is used to query the associated target power data from the power database according to the target power grid knowledge data matched by the structured query task description data.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the power data query method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power data query method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements the power data query method according to any one of claims 1 to 6.

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