Energy data analysis method and device, equipment, storage medium and program product

Abstract

The invention discloses an energy data analysis method and device, equipment, a storage medium and a program product, and belongs to the technical field of data analysis, the method is executed by an energy data analysis service platform, and the method comprises the steps of responding to a click operation of a demand side in a data analysis interface, and skipping to an analysis parameter configuration interface; determining to-be-processed energy data according to demand information acquired from the data analysis interface; in response to a parameter setting operation of the demand side in the analysis parameter configuration interface, determining a target analysis parameter corresponding to the to-be-processed energy data; generating a target data analysis model according to the target analysis parameters; and performing data analysis on the to-be-processed energy data by adopting the target data analysis model to obtain a data analysis result. The use experience of the demand side is improved, the flexibility of energy data analysis is improved, manual errors are reduced, the maintenance cost of the energy data analysis method is reduced, and the analysis efficiency of the energy data is improved.

Description

Technical Field

[0001] The present invention relates to the field of data analysis technology, and in particular to an energy data analysis method, device, equipment, storage medium and program product. Background Art

[0002] Nowadays, energy has become an indispensable basic element of human society. With the increasing tension of energy and environmental deterioration, effective analysis of energy data has become an urgent need of today's society.

[0003] The data analysis algorithms of existing energy analysis methods are fixed and written by R&D personnel through code solidification. Every time the data analysis requirements of the demand side change, the R&D personnel need to modify the code, which results in large workload, high maintenance costs, poor flexibility, high error rate, and reduces the efficiency of energy data analysis. Summary of the invention

[0004] The present invention provides an energy data analysis method, device, equipment, storage medium and program product to improve the flexibility of energy data analysis, reduce maintenance costs, reduce manual errors, and improve the efficiency of energy data analysis.

[0005] According to one aspect of the present invention, there is provided an energy data analysis method, which is performed by an energy data analysis service platform. The method comprises:

[0006] In response to a click operation by the demander in the data analysis interface, jump to the analysis parameter configuration interface; and determine the energy data to be processed based on the demand information obtained from the data analysis interface;

[0007] In response to the parameter setting operation of the demand side in the analysis parameter configuration interface, determining the target analysis parameters corresponding to the energy data to be processed;

[0008] Generate a target data analysis model based on target analysis parameters;

[0009] The target data analysis model is used to analyze the energy data to be processed and obtain the data analysis results.

[0010] According to another aspect of the present invention, there is provided an energy data analysis device, which is configured in an energy data analysis service platform, and includes:

[0011] The module for determining the energy data to be processed is used to jump to the analysis parameter configuration interface in response to a click operation of the demander in the data analysis interface; and determine the energy data to be processed according to the demand information obtained from the data analysis interface;

[0012] A target analysis parameter determination module is used to determine the target analysis parameters corresponding to the energy data to be processed in response to the parameter setting operation of the demand side in the analysis parameter configuration interface;

[0013] A data analysis model generation module is used to generate a target data analysis model according to target analysis parameters;

[0014] The data analysis result determination module is used to perform data analysis on the energy data to be processed using a target data analysis model to obtain data analysis results.

[0015] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0016] at least one processor; and

[0017] a memory communicatively connected to at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by at least one processor. The computer program is executed by at least one processor so that the at least one processor can execute the energy data analysis method of any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the energy data analysis method of any embodiment of the present invention when executed.

[0020] According to another aspect of the present invention, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the energy data analysis method according to any embodiment of the present invention is implemented.

[0021] The technical solution of the embodiment of the present invention jumps to the analysis parameter configuration interface in response to the click operation of the demander in the data analysis interface; and determines the energy data to be processed according to the demand information obtained from the data analysis interface; determines the target analysis parameters corresponding to the energy data to be processed in response to the parameter setting operation of the demander in the analysis parameter configuration interface; generates a target data analysis model according to the target analysis parameters; uses the target data analysis model to perform data analysis on the energy data to be processed to obtain data analysis results. The above technical solution determines the energy data to be processed according to the demand information of the demander, rather than analyzing all the energy data in the energy data analysis service platform, thereby avoiding the waste of computing resources and saving computing resources; secondly, the setting of the target analysis parameters is completed with the help of the analysis parameter configuration interface, so as to obtain the target data analysis model that meets the personalized energy analysis needs of the demander according to the target analysis parameters, thereby realizing the personalized analysis of the energy data to be processed, meeting the personalized energy analysis needs of the demander, improving the user experience of the demander, and improving the flexibility of energy data analysis. Furthermore, during the entire energy data analysis process, R&D personnel do not need to modify the corresponding code of the back-end energy data analysis, thereby reducing human errors, reducing the maintenance cost of the energy data analysis method, and improving the efficiency of energy data analysis.

[0022] 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

[0023] 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.

[0024] Figure 1 is a flow chart of an energy data analysis method provided according to Embodiment 1 of the present invention;

[0025] Figure 2 is a flow chart of an energy data analysis method provided according to Embodiment 2 of the present invention;

[0026] Figure 3 is a schematic diagram of the structure of an energy data analysis device provided according to Embodiment 3 of the present invention;

[0027] Figure 4 It is a schematic diagram of the structure of an electronic device for implementing the energy data analysis method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] 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.

[0029] It should be noted that the terms "target", "candidate", "first" and "second" 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 interchangeable 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.

[0030] In addition, it should be noted that the collection, storage, use, processing, transmission, provision and disclosure of candidate calculation methods, candidate data visualization methods, data analysis model generation templates and abnormal warning conditions involved in the technical solution of the present invention all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0031] Embodiment 1

[0032] Figure 1 This is a flow chart of an energy data analysis method provided in the first embodiment of the present invention. This embodiment is applicable to the case of performing data analysis on park energy data. The method can be executed by an energy data analysis device, which can be implemented in the form of hardware and / or software and can be configured in an electronic device with an energy data analysis service platform. Figure 1 As shown, the method is executed by an energy data analysis service platform, and includes:

[0033] S101. In response to a click operation of a demander in a data analysis interface, jump to an analysis parameter configuration interface; and determine energy data to be processed according to demand information obtained from the data analysis interface.

[0034] The data analysis interface refers to an interface for energy data analysis. The demander refers to a party that has a demand for energy data analysis. The analysis parameter configuration interface refers to an interface for setting the analysis parameters required for energy data analysis. Demand information refers to the data analysis demand information entered by the demander in the data analysis interface; optionally, the demand information includes but is not limited to the park to which the energy data belongs, the type of energy data, and the range of energy data. The energy data types include but are not limited to electricity data, hydraulic data, and gas data.

[0035] Specifically, after the demander inputs the demand information in the data analysis interface, the energy data analysis service platform jumps to the analysis parameter configuration interface in response to the demander's click operation on a specific button (e.g., an analysis button) in the data analysis interface; at the same time, the energy data analysis service platform parses the demand information obtained from the data analysis interface to obtain demand keywords; uses the demand keywords as input parameters of the search statement construction algorithm, and obtains the search statement after the search statement construction algorithm is operated; and obtains the energy data to be processed from the preset energy data storage library through the search statement.

[0036] It should be noted that the specific button refers to a button in the data analysis interface that can trigger a jump operation and jump to the analysis parameter configuration interface. The search statement construction algorithm can be preset according to actual business needs, and the embodiment of the present invention does not specifically limit it.

[0037] S102: In response to the parameter setting operation of the demander in the analysis parameter configuration interface, determine the target analysis parameters corresponding to the energy data to be processed.

[0038] Among them, the parameter setting operation includes but is not limited to the parameter input operation and the parameter selection operation. The target analysis parameters refer to the parameters required for analyzing the energy data to be processed; optionally, the target analysis parameters include the target calculation cycle, the target calculation method and the target visualization method. The target calculation cycle refers to the calculation cycle used when analyzing the energy data to be processed; wherein the calculation cycle refers to the cycle for statistics and calculations of energy data based on a certain time interval. The target calculation method refers to the calculation method used when analyzing the energy data to be processed. The target visualization method refers to the data visualization method used to display the data analysis results obtained by analyzing the energy data to be processed; wherein the data visualization method refers to the method of displaying energy data in the form of charts; optionally, the data visualization method includes but is not limited to single value charts, column charts, bar charts, line charts, pie charts, funnel charts and area charts.

[0039] Specifically, in response to the demand party's input operation on the algorithm calculation cycle in the analysis parameter configuration interface, the target calculation cycle can be obtained; in response to the demand party's selection operation on the candidate calculation method in the analysis parameter configuration interface, the target calculation method can be determined; in response to the demand party's selection operation on the candidate data visualization method in the analysis parameter configuration interface, the target visualization method can be determined.

[0040] Among them, the algorithm calculation cycle refers to the cycle for calculating energy data, for example, the algorithm calculation cycle can be one day, one week, one month or one year. The candidate calculation method refers to the calculation method provided by the analysis parameter configuration interface. It should be noted that the number of candidate calculation methods is at least one. The candidate data visualization method refers to the data visualization method provided by the analysis parameter configuration interface. It should be noted that the number of candidate data visualization methods is at least one. It should also be noted that the analysis parameter configuration interface will display the first description information of the algorithm calculation cycle, the second description information of each candidate calculation method, and the third description information of each candidate data visualization method to the demander, so as to help the demander complete the setting of the target analysis parameters more quickly.

[0041] S103. Generate a target data analysis model according to the target analysis parameters.

[0042] The target data analysis model refers to the model actually used to perform data analysis on the energy data to be processed.

[0043] Specifically, the target data analysis model can be generated based on the data analysis model generation template and the target analysis parameters. More specifically, the target calculation cycle is filled in the location of the algorithm calculation cycle in the data analysis model generation template, the target calculation method is filled in the location of the calculation method in the data analysis model generation template, and the target visualization method is filled in the location of the data visualization method in the data analysis model generation template, so as to obtain the target data analysis model.

[0044] It can be understood that each time a target data analysis model is generated, it is only necessary to fill in the target analysis parameters into the corresponding position in the data analysis model generation template. There is no need to suspend the operation of the energy data analysis service platform. The R&D personnel can modify the corresponding code of the back-end energy data analysis of the energy data analysis service platform, thereby reducing human errors and reducing the maintenance cost of the energy data analysis method.

[0045] S104. Use the target data analysis model to perform data analysis on the energy data to be processed to obtain data analysis results.

[0046] The technical solution of the embodiment of the present invention jumps to the analysis parameter configuration interface in response to the click operation of the demander in the data analysis interface; and determines the energy data to be processed according to the demand information obtained from the data analysis interface; determines the target analysis parameters corresponding to the energy data to be processed in response to the parameter setting operation of the demander in the analysis parameter configuration interface; generates a target data analysis model according to the target analysis parameters; uses the target data analysis model to perform data analysis on the energy data to be processed to obtain data analysis results. The above technical solution determines the energy data to be processed according to the demand information of the demander, rather than analyzing all the energy data in the energy data analysis service platform, thereby avoiding the waste of computing resources and saving computing resources; secondly, the setting of the target analysis parameters is completed with the help of the analysis parameter configuration interface, so as to obtain the target data analysis model that meets the personalized energy analysis needs of the demander according to the target analysis parameters, thereby realizing the personalized analysis of the energy data to be processed, meeting the personalized energy analysis needs of the demander, improving the user experience of the demander, and improving the flexibility of energy data analysis. Furthermore, during the entire energy data analysis process, R&D personnel do not need to modify the corresponding code of the back-end energy data analysis, thereby reducing human errors, reducing the maintenance cost of the energy data analysis method, and improving the efficiency of energy data analysis.

[0047] Embodiment 2

[0048] Figure 2 This is a flow chart of an energy data analysis method provided in Example 2 of the present invention. Based on the above examples, this example provides an optional implementation scheme for generating early warning information. It should be noted that for the parts not described in detail in the examples of the present invention, reference may be made to the relevant descriptions of other examples.

[0049] like Figure 2 As shown, the method is executed by an energy data analysis service platform, and includes:

[0050] S201. In response to a click operation of the demander in the data analysis interface, jump to the analysis parameter configuration interface; and determine the energy data to be processed according to the demand information obtained from the data analysis interface.

[0051] Optionally, the demander can also add new data analysis functions to the energy data analysis service platform through the new function sub-interface in the data analysis interface, thereby enhancing the service capabilities of the energy data analysis service platform and broadening the service scope of the energy data analysis service platform.

[0052] For example, the demander can add an energy consumption assessment function to the energy data analysis service platform through the new function sub-interface in the data analysis interface to adjust the energy structure of the park according to the energy consumption assessment results, thereby realizing the control of the energy consumption of the park and achieving the goal of energy conservation and emission reduction.

[0053] S202: In response to the parameter setting operation of the demander in the analysis parameter configuration interface, determine the target analysis parameters corresponding to the energy data to be processed.

[0054] S203: Generate a target data analysis model according to the target analysis parameters.

[0055] S204: Use the target data analysis model to perform data analysis on the energy data to be processed to obtain data analysis results.

[0056] S205: Check whether the data analysis results meet the abnormal warning conditions.

[0057] Among them, the abnormal warning conditions can be determined according to the standardized energy data corresponding to the energy data to be processed.

[0058] Specifically, if it is detected that the data analysis result does not meet the abnormal warning condition, a template is generated based on the analysis report, a data analysis report is generated according to the data analysis result, and the data analysis report is visualized and stored; otherwise, S206 is executed.

[0059] S206: If yes, generate warning information based on the data analysis results.

[0060] Among them, the warning information includes but is not limited to the cause of energy data anomalies, warning type, warning level and anomaly solutions.

[0061] Specifically, if it is detected that the data analysis results meet the abnormal warning conditions, the warning mechanism will be triggered and warning information will be generated so that relevant personnel can promptly discover abnormal energy data and manage the energy equipment in the park based on the abnormal energy data, thereby ensuring the stability of the energy equipment in the park.

[0062] Optionally, early warning information can be sent to relevant personnel in the form of email, text message, voice, etc.

[0063] The technical solution of the embodiment of the present invention jumps to the analysis parameter configuration interface in response to the click operation of the demander in the data analysis interface; and determines the energy data to be processed according to the demand information obtained from the data analysis interface; determines the target analysis parameters corresponding to the energy data to be processed in response to the parameter setting operation of the demander in the analysis parameter configuration interface; generates a target data analysis model according to the target analysis parameters; uses the target data analysis model to perform data analysis on the energy data to be processed to obtain data analysis results; detects whether the data analysis results meet the abnormal warning conditions; if so, generates warning information according to the data analysis results. The above technical solution determines the energy data to be processed according to the demand information of the demander, rather than analyzing all the energy data in the energy data analysis service platform, thereby avoiding the waste of computing resources and saving computing resources; secondly, the target analysis parameters are set with the help of the analysis parameter configuration interface, so as to obtain the target data analysis model that meets the personalized energy analysis needs of the demander according to the target analysis parameters, thereby realizing the personalized analysis of the energy data to be processed, meeting the personalized energy analysis needs of the demander, improving the user experience of the demander, and improving the flexibility of energy data analysis. Furthermore, during the entire energy data analysis process, R&D personnel do not need to modify the corresponding code of the back-end energy data analysis, thereby reducing manual errors, reducing the maintenance cost of the energy data analysis method, and improving the efficiency of energy data analysis. In addition, early warning information is generated based on the data analysis results, which facilitates relevant personnel to promptly discover abnormal energy data and manage the energy equipment in the park based on the abnormal energy data, ensuring the stability of the energy equipment in the park.

[0064] Embodiment 3

[0065] Figure 3 This is a schematic diagram of the structure of an energy data analysis device provided in the third embodiment of the present invention. This embodiment is applicable to the case of analyzing the energy data of a park. The device can be implemented in the form of hardware and / or software and can be configured in an electronic device with an energy data analysis service platform. Figure 3 As shown, the device is configured in the energy data analysis service platform, including:

[0066] The module 301 for determining the energy data to be processed is used to jump to the analysis parameter configuration interface in response to a click operation of the demander in the data analysis interface; and determine the energy data to be processed according to the demand information obtained from the data analysis interface;

[0067] The target analysis parameter determination module 302 is used to determine the target analysis parameters corresponding to the energy data to be processed in response to the parameter setting operation of the demand side in the analysis parameter configuration interface;

[0068] The data analysis model generation module 303 is used to generate a target data analysis model according to target analysis parameters;

[0069] The data analysis result determination module 304 is used to perform data analysis on the energy data to be processed using a target data analysis model to obtain data analysis results.

[0070] The technical solution of the embodiment of the present invention jumps to the analysis parameter configuration interface in response to the click operation of the demander in the data analysis interface; and determines the energy data to be processed according to the demand information obtained from the data analysis interface; determines the target analysis parameters corresponding to the energy data to be processed in response to the parameter setting operation of the demander in the analysis parameter configuration interface; generates a target data analysis model according to the target analysis parameters; uses the target data analysis model to perform data analysis on the energy data to be processed to obtain data analysis results. The above technical solution determines the energy data to be processed according to the demand information of the demander, rather than analyzing all the energy data in the energy data analysis service platform, thereby avoiding the waste of computing resources and saving computing resources; secondly, the setting of the target analysis parameters is completed with the help of the analysis parameter configuration interface, so as to obtain the target data analysis model that meets the personalized energy analysis needs of the demander according to the target analysis parameters, thereby realizing the personalized analysis of the energy data to be processed, meeting the personalized energy analysis needs of the demander, improving the user experience of the demander, and improving the flexibility of energy data analysis. Furthermore, during the entire energy data analysis process, R&D personnel do not need to modify the corresponding code of the back-end energy data analysis, thereby reducing human errors, reducing the maintenance cost of the energy data analysis method, and improving the efficiency of energy data analysis.

[0071] Optionally, the target analysis parameters include a target calculation period, a target calculation method, and a target visualization method;

[0072] The target analysis parameter determination module 302 is specifically used for:

[0073] In response to the input operation of the algorithm calculation cycle by the demander in the analysis parameter configuration interface, a target calculation cycle is obtained;

[0074] In response to the demander's selection operation of a candidate calculation method in the analysis parameter configuration interface, determining a target calculation method;

[0075] In response to the selection operation of the demander on the candidate data visualization mode in the analysis parameter configuration interface, the target visualization mode is determined.

[0076] Optionally, the data analysis model generation module 303 is specifically used to:

[0077] Generate a target data analysis model based on the data analysis model template and target analysis parameters.

[0078] Optionally, the device further includes an early warning module, wherein the early warning module is specifically used to:

[0079] Check whether the data analysis results meet the abnormal warning conditions;

[0080] If so, a warning message is generated based on the data analysis results.

[0081] The energy data analysis device provided in the embodiment of the present invention can execute the energy data analysis method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing each energy data analysis method.

[0082] According to an embodiment of the present invention, the present invention also provides an electronic device, a readable storage medium and a computer program product.

[0083] Embodiment 4

[0084] Figure 4 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, energy data analysis service platforms, blade energy data analysis service platforms, 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.

[0085] like Figure 4 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, ROM 12 and 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.

[0086] 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.

[0087] 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 energy data analysis method.

[0088] In some embodiments, the energy data analysis 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 energy data analysis method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the energy data analysis method in any other appropriate manner (e.g., by means of firmware).

[0089] 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.

[0090] The computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or energy data analysis service platform.

[0091] 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.

[0092] 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).

[0093] The systems and techniques described herein may be implemented in a computing system including backend components (e.g., as a data energy data analysis service platform), or a computing system including middleware components (e.g., an application energy data analysis service platform), or a computing system including frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by digital data communication of any form or medium (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.

[0094] The computing system may include a client and an energy data analysis service platform. The client and the energy data analysis service platform are generally remote from each other and usually interact through a communication network. The relationship between the client and the energy data analysis service platform is generated by computer programs running on corresponding computers and having a client-energy data analysis service platform relationship with each other. The energy data analysis service platform may be a cloud energy data analysis service platform, also known as a cloud computing energy data analysis service platform or a 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.

[0095] 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.

[0096] 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. An energy data analysis method, characterized in that: Executed by an energy data analysis service platform, the method includes: In response to a click operation by the demander in the data analysis interface, jump to the analysis parameter configuration interface; and determine the energy data to be processed according to the demand information obtained from the data analysis interface; In response to the parameter setting operation of the demander in the analysis parameter configuration interface, determining the target analysis parameter corresponding to the energy data to be processed; Generate a target data analysis model according to the target analysis parameters; The target data analysis model is used to perform data analysis on the energy data to be processed to obtain data analysis results.

2. The method according to claim 1, characterized in that The target analysis parameters include target calculation period, target calculation method and target visualization method; The step of determining the target analysis parameters corresponding to the energy data to be processed in response to the parameter setting operation of the demand party in the analysis parameter configuration interface includes: In response to the demander's input operation on the algorithm calculation cycle in the analysis parameter configuration interface, obtaining a target calculation cycle; In response to the demander's selection operation of a candidate calculation method in the analysis parameter configuration interface, determining a target calculation method; In response to the demander's selection operation on a candidate data visualization mode in the analysis parameter configuration interface, a target visualization mode is determined.

3. The method according to claim 1, characterized in that: Generating a target data analysis model according to the target analysis parameters includes: Based on the data analysis model generation template, a target data analysis model is generated according to the target analysis parameters.

4. The method according to claim 1, characterized in that: The method further comprises: Detecting whether the data analysis results meet abnormal warning conditions; If so, a warning message is generated based on the data analysis result.

5. An energy data analysis device, characterized in that: Configured in the energy data analysis service platform, the device includes: The module for determining the energy data to be processed is used to jump to the analysis parameter configuration interface in response to a click operation of the demander in the data analysis interface; and determine the energy data to be processed according to the demand information obtained from the data analysis interface; A target analysis parameter determination module, configured to determine the target analysis parameters corresponding to the energy data to be processed in response to the parameter setting operation of the demander in the analysis parameter configuration interface; A data analysis model generation module, used to generate a target data analysis model according to the target analysis parameters; The data analysis result determination module is used to perform data analysis on the energy data to be processed using the target data analysis model to obtain data analysis results.

6. The device according to claim 5, characterized in that The target analysis parameters include target calculation period, target calculation method and target visualization method; The target analysis parameter determination module is specifically used for: In response to the demander's input operation on the algorithm calculation cycle in the analysis parameter configuration interface, obtaining a target calculation cycle; In response to the demander's selection operation of a candidate calculation method in the analysis parameter configuration interface, determining a target calculation method; In response to the demander's selection operation on a candidate data visualization method in the analysis parameter configuration interface, a target visualization method is determined.

7. The device according to claim 5, characterized in that The data analysis model generation module is specifically used for: Based on the data analysis model generation template, a target data analysis model is generated according to the target analysis parameters.

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 perform the energy data analysis method according to any one of claims 1 to 4.

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 energy data analysis method according to any one of claims 1 to 4 when executed.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the energy data analysis method according to any one of claims 1 to 4 is implemented.

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