Business management method and system

Abstract

The invention discloses a business management method and system, relates to the technical field of power grid operation management, and is beneficial to improving the operation efficiency of a power grid. The business management method comprises the steps of obtaining multi-dimensional data generated in a power grid operation process in a preset time period, wherein the multi-dimensional data comprises power data, equipment operation data and energy consumption data; determining an electric energy quality index value of the power grid based on the multi-dimensional data; and determining whether to send early warning information based on the power quality index value, the early warning information being used for indicating whether power utilization of the power grid is abnormal.

Description

Technical Field

[0001] The present application relates to the technical field of power grid operation management, and in particular to a business management method and system. Background Art

[0002] Electricity is an important driving force for the development of the modern economy. The efficient operation of the power grid can support the smooth progress of industrial production, service industries and other economic activities, and promote sustained economic growth. At the same time, the power grid is an important infrastructure connecting power generation and power consumption, ensuring the smooth transmission of electricity from power plants to users. Stable power grid operation can guarantee the electricity needs of residents and enterprises, and avoid the inconvenience and economic losses caused by power outages. Analyzing relevant data on power grid operation is an important link in ensuring power grid operation.

[0003] The existing power grid analysis system does not analyze and calculate the relevant data in the power operation, and does not generate early warning signals to analyze and optimize the abnormal operation of the power grid, resulting in the inability to monitor the abnormal power quality in a timely manner, thereby reducing the efficiency of the power grid operation. Summary of the Invention

[0004] The purpose of this application is to provide a business management method that is conducive to improving the efficiency of power grid operation.

[0005] To achieve the above objectives, this application adopts the following technical solutions:

[0006] In the first aspect, the present application provides a business management method, including: obtaining multi-dimensional data generated during the operation of the power grid within a preset time period, the multi-dimensional data including power data, equipment operation data and energy consumption data; based on the multi-dimensional data, determining the power quality index value of the power grid; based on the power quality index value, determining whether to send an early warning information, the early warning information is used to indicate whether the power consumption of the power grid is abnormal.

[0007] The service management method provided in the embodiments of the present application determines the power quality index value of the power grid by acquiring multi-dimensional data including power data, equipment operation data, and energy consumption data generated during the operation of the power grid within a preset time period, thereby improving the accuracy and comprehensiveness of the power quality index value determination. Based on the power quality index value, it is then determined whether to send an early warning message, facilitating timely monitoring of abnormal power consumption in the power grid. In the event of abnormal power consumption, an early warning message can be sent in a timely manner to optimize the power grid and thereby improve the efficiency of the power grid operation.

[0008] In some embodiments, determining the power quality index value of the power grid based on multi-dimensional data includes: determining the multi-dimensional evaluation index of the power grid based on the multi-dimensional data; the multi-dimensional evaluation index includes at least one of the following: power efficiency within a preset time period, equipment utilization within a preset time period, average equipment repair time within a preset time period, and power load forecast within a preset time period; determining the power quality index value of the power grid based on the multi-dimensional evaluation index.

[0009] In some embodiments, the power data includes at least one of the following: power output power at each moment in a preset time period, and power input power at each moment in a preset time period.

[0010] In some embodiments, the power efficiency within a preset time period is determined based on the following formula:

[0011]

[0012] Among them, Ydxl represents the power efficiency within the preset time period, Px i Indicates the power output at the i-th moment in the preset time period, Po i represents the power input / output rate at the i-th moment in the preset time period, n is the number of moments in the preset time period, and t i Indicates the weighting factor corresponding to the i-th moment in the preset time period.

[0013] In some embodiments, the equipment operation data includes at least one of the following: the actual operation time of the equipment within a preset time period, the available time of the equipment within a preset time period, the number of equipment failures within a preset time period, the number of equipment failures repaired within a preset time period, and the time for each equipment failure repair within a preset time period.

[0014] In some embodiments, the device utilization rate within a preset time period is determined based on the following formula:

[0015]

[0016] Among them, Sbly represents the equipment utilization rate within the preset time period, Tsjy represents the actual equipment running time within the preset time period, and Tkys represents the equipment available time within the preset time period.

[0017] In some embodiments, the average repair time of a device within a preset time period is determined based on the following formula:

[0018]

[0019] Among them, Xfsj represents the power efficiency within the preset time period, Repa kIt represents the time when the kth fault of the device is repaired within the preset time period, N represents the number of times the device faults occur within the preset time period, and p represents the number of times the faults of the device are repaired within the preset time period.

[0020] In some embodiments, the energy consumption data includes electricity load within a preset time period.

[0021] In some embodiments, the power load forecast for a preset time period is determined based on the following formula:

[0022] Ycfh=β0+β1*Tm+β2*Hm+β3*Px+∈

[0023] Where Ycfh represents the predicted power load within the preset time period, β0, β1, β2, and β3 represent the preset regression coefficients, Tm represents temperature, Hm represents humidity, Px represents the power load within the preset time period, and ∈ represents the error term.

[0024] In a second aspect, the present application provides a business management system, which includes a data collection module, a data analysis module, and an early warning module;

[0025] A data acquisition module is used to obtain multi-dimensional data generated during the operation of the power grid within a preset time period, where the multi-dimensional data includes at least one of the following: power data, equipment operation data, and energy consumption data;

[0026] A data analysis module is used to determine the power quality index value of the power grid based on multi-dimensional data;

[0027] The early warning module is used to determine whether to send an early warning message based on the power quality index value.

[0028] In a third aspect, the present application provides an electronic device comprising: a processor and a memory; wherein the memory is used to store one or more programs, and the one or more programs include computer-executable instructions. When the device is running, the processor executes the computer-executable instructions stored in the memory to control the device to execute the method of the first aspect above.

[0029] In a fourth aspect, the present application provides a computer-readable storage medium. When the computer-executable instructions stored in the computer-readable storage medium are executed by a processor of an electronic device, the electronic device can execute the method of the first aspect described above.

[0030] In a fifth aspect, the present application provides a computer program product, which includes: a computer program or instructions, which, when the computer program or instructions are run on a computer, enables the computer to execute the method of the first aspect as described above.

[0031] It should be noted that the descriptions of the second to fifth aspects of this application can refer to the detailed description of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present application, 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 application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0033] Figure 1 A schematic diagram of the structure of a business management system provided in an embodiment of the present application;

[0034] Figure 2 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0035] Figure 3 A flowchart of a service management method provided in an embodiment of the present application;

[0036] Figure 4 A schematic diagram of the structure of the service management device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0038] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connected," and "connected" should be understood broadly. For example, they may refer to fixed connections, detachable connections, or integral connections. They may be directly connected, indirectly connected through an intermediary, or internally connected between two components. Those skilled in the art will understand the specific meanings of these terms in this application based on the specific circumstances.

[0039] In the embodiments of the present application, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, article, or device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of other identical elements in the process, article, or device comprising the element.

[0040] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0041] In the description of this specification, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.

[0042] Electricity is an important driving force for the development of the modern economy. The efficient operation of the power grid can support the smooth progress of industrial production, service industries and other economic activities, and promote sustained economic growth. At the same time, the power grid is an important infrastructure connecting power generation and power consumption, ensuring the smooth transmission of electricity from power plants to users. Stable power grid operation can guarantee the electricity needs of residents and enterprises, and avoid the inconvenience and economic losses caused by power outages. Analyzing relevant data on power grid operation is an important link in ensuring power grid operation.

[0043] The existing power grid analysis system does not analyze and calculate the relevant data in the power operation, and does not generate early warning signals to analyze and optimize the abnormal operation of the power grid, resulting in the inability to monitor the abnormal power quality in a timely manner, reducing the efficiency of the power grid operation.

[0044] In view of this, the present application provides a business management method that determines the power quality index value of the power grid by acquiring multi-dimensional data including power data, equipment operation data, and energy consumption data generated during the operation of the power grid within a preset time period, thereby improving the accuracy and comprehensiveness of the power quality index value determination. Then, based on the power quality index value, it is determined whether to send an early warning message, so as to facilitate timely monitoring of whether the power consumption of the power grid is abnormal. In the event of abnormal power consumption, an early warning message can be sent in a timely manner to optimize the power grid and thereby improve the efficiency of the power grid operation.

[0045] Figure 1 This is a schematic diagram of the structure of a business management system provided in an embodiment of the present application. Figure 1 As shown, the business management system includes a data collection module 101 , a data analysis module 102 , an early warning module 103 , an optimization module 104 and a result display module 105 .

[0046] The data acquisition module 101 is configured to acquire multi-dimensional data generated during grid operation within a preset time period. This multi-dimensional data includes at least one of the following: power data, equipment operation data, and energy consumption data. The data acquisition module 101 is communicatively connected to the data analysis module 102 and transmits the multi-dimensional data to the data analysis module 102.

[0047] The data analysis module 102 is configured to determine the power quality index value of the power grid based on the multi-dimensional data. The data analysis module 102 is in communication with the early warning module 103 and is configured to send the power quality index value to the early warning module 103.

[0048] The early warning module 103 is used to determine whether to send early warning information based on the power quality index value. The early warning module 103 is in communication with the optimization module 104 and is used to send the early warning information to the result optimization module 104.

[0049] The optimization module 104 is configured to optimize the power grid energy consumption according to the early warning information and generate a power grid optimization report. The optimization module 104 is in communication with the result display module 105 and is configured to send the power grid optimization report to the result display module 105.

[0050] The result display module 105 is used to display the power grid optimization report on a visual interface.

[0051] In some embodiments, the data analysis module 102 is specifically configured to determine multi-dimensional evaluation indicators for the power grid based on the multi-dimensional data. The multi-dimensional evaluation indicators include at least one of the following: power efficiency within a preset time period, equipment utilization within a preset time period, average equipment repair time within a preset time period, and power load forecast within a preset time period. Based on the multi-dimensional evaluation indicators, a power quality indicator value for the power grid is determined.

[0052] In some embodiments, the data collection module 101 is further used to compile the collected power data into a power data set. For example, the power data set is {Dlsj n-9 ,Dlsj n-8 ,Dlsj n-7 ,...,Dlsj n}.

[0053] In some embodiments, the data collection module 101 is further configured to compile the collected device operation data into a device operation data set. For example, the device operation data set is {Sbyx n-9 ,Sbyx n-8 ,Sbyx n-7 ,...,Sbyx n}.

[0054] In some embodiments, the data collection module 101 is further configured to compile the collected energy consumption data into an energy consumption data set. For example, the energy consumption data set is {Nhsj n-9 ,Nhsj n-8 ,Nhsj n-7 ,...,hsj n}.

[0055] It is understandable that the business management system provided by this application may include other modules in addition to the above modules, and this application does not limit this.

[0056] Figure 2 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 2 As shown, the electronic device may include: a processor 10 , a memory 20 , a communication line 30 , a communication interface 40 , and an input / output interface 50 .

[0057] The processor 10 , the memory 20 , the communication interface 40 , and the input / output interface 50 may be connected via a communication line 30 .

[0058] The processor 10 is used to execute the instructions stored in the memory 20 to implement the business management method provided in the following embodiments of the present application. The processor 10 can be a CPU, a general-purpose processor network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller (MCU) / single chip microcomputer / single chip microcomputer, a programmable logic device (PLD) or any combination thereof. The processor 10 can also be any other device with processing functions, such as a circuit, a device or a software module, which is not limited in the embodiments of the present application. In one example, the processor 10 may include one or more CPUs, such as Figure 2 As an optional implementation, the electronic device may include multiple processors, for example, in addition to the processor 10, it may also include a processor 60 ( Figure 2 The dashed line is used as an example.

[0059] The memory 20 is used to store instructions. For example, the instruction may be a computer program. Optionally, the memory 20 may be a read-only memory (ROM) or other types of static storage devices that can store static information and / or instructions, or a random access memory (RAM) or other types of dynamic storage devices that can store information and / or instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, etc., and the embodiments of the present application are not limited thereto.

[0060] It should be noted that the memory 20 may exist independently of the processor 10 or may be integrated with the processor 10. The memory 20 may be located inside the electronic device or outside the electronic device, which is not limited in the embodiment of the present application.

[0061] The communication line 30 is used to transmit information between various components included in the electronic device.

[0062] Communication interface 40 is used to communicate with other devices or other communication networks. Such other communication networks may be Ethernet, radio access networks (RAN), wireless local area networks (WLAN), etc. Communication interface 40 may be a module, circuit, transceiver, or any other device capable of communication.

[0063] It should be noted that Figure 2 The structure shown in the figure does not constitute a limitation on the electronic device, except Figure 2 In addition to the components shown, the electronic device may include more or fewer components than shown (eg, only the processor 10 and the memory 20 ), or a combination of certain components, or a different arrangement of components.

[0064] The following introduces the business management method provided in the embodiment of the present application.

[0065] Figure 3 This is a flow chart of a business management method provided in an embodiment of the present application. Figure 3 As shown, the business management method includes the following steps:

[0066] S101. Acquire multi-dimensional data generated during the operation of a power grid within a preset time period.

[0067] Among them, multi-dimensional data includes power data, equipment operation data and energy consumption data.

[0068] In some embodiments, the power data includes at least one of the following: power output power at each moment in a preset time period, and power input power at each moment in a preset time period.

[0069] In some embodiments, the power data further includes voltage within a preset time period and current frequency within a preset time period.

[0070] In some embodiments, the equipment operation data includes at least one of the following: actual equipment operation time within a preset time period, equipment availability time within a preset time period, number of equipment failures within a preset time period, number of equipment failure repairs within a preset time period, and time required for each equipment failure repair within a preset time period. The equipment may include power generation equipment (e.g., steam turbines, boilers, generators, etc.), power transmission equipment (e.g., overhead lines, cables, etc.), power distribution equipment (e.g., distribution transformers, etc.), and power consumption equipment (e.g., smart meters, air conditioners, etc.).

[0071] In some embodiments, the energy consumption data includes electricity load within a preset time period.

[0072] In some embodiments, the energy consumption data also includes power consumption within a preset time period and power factor within a preset time period.

[0073] S102: Determine the power quality index value of the power grid based on the multi-dimensional data.

[0074] In some embodiments, determining a power quality indicator value of a power grid based on multi-dimensional data includes: determining a multi-dimensional evaluation indicator of the power grid based on the multi-dimensional data. Determining the power quality indicator value of the power grid based on the multi-dimensional evaluation indicator. The multi-dimensional evaluation indicator includes at least one of the following: power efficiency within a preset time period, equipment utilization within a preset time period, average equipment repair time within a preset time period, and power load forecast within a preset time period.

[0075] In some embodiments, the power efficiency within a preset time period is determined based on the following formula:

[0076]

[0077] Among them, Ydxl represents the power efficiency within the preset time period, Px i Indicates the power output at the i-th moment in the preset time period, Po irepresents the power input / output rate at the i-th moment in the preset time period, n is the number of moments in the preset time period, and t i It is understood that the weighting factors corresponding to different moments may be different. i The system assigns values based on the fluctuation of power over time.

[0078] In some embodiments, the device utilization rate within a preset time period is determined based on the following formula:

[0079]

[0080] Among them, Sbly represents the equipment utilization rate within the preset time period, Tsjy represents the actual equipment running time within the preset time period, and Tkys represents the equipment available time within the preset time period.

[0081] In some embodiments, the average repair time of a device within a preset time period is determined based on the following formula:

[0082]

[0083] Among them, Xfsj represents the power efficiency within the preset time period, Repa k It represents the time when the kth fault of the device is repaired within the preset time period, N represents the number of times the device faults occur within the preset time period, and p represents the number of times the faults of the device are repaired within the preset time period.

[0084] In some embodiments, the power load forecast for a preset time period is determined based on the following formula:

[0085] Ycfh=β0+β1*Tm+β2*Hm+β3*Px+∈

[0086] Where Ycfh represents the predicted power load within the preset time period, β0, β1, β2, and β3 represent the preset regression coefficients, Tm represents temperature, Hm represents humidity, Px represents the power load within the preset time period, and ∈ represents the error term.

[0087] S103: Determine whether to send an early warning message based on the power quality index value.

[0088] Among them, the early warning information is used to indicate whether the power consumption of the power grid is abnormal.

[0089] In some embodiments, the power quality index value of the power grid is determined based on multidimensional evaluation indicators, including: determining the power quality index value of the power grid based on each multidimensional evaluation indicator in the multidimensional evaluation indicators, and the weighted value corresponding to each multidimensional evaluation indicator.

[0090] Exemplarily, the power quality index value Zlzb of the power grid is determined by the following formula:

[0091] Zlzb=a*Ydxl+b*Sbly+c*Xfsj+d*Ycfh

[0092] Where Ydxl represents the power efficiency during the preset time period, a represents the weighted value corresponding to Ydxl, Sbly represents the equipment utilization rate during the preset time period, b represents the weighted value corresponding to Sbly, Xfsj represents the power efficiency during the preset time period, c represents the weighted value corresponding to Xfsj, Ycfh represents the predicted power load during the preset time period, and d represents the weighted value corresponding to Ycfh. The sum of a, b, c, and d is 1. For example, a is 0.2, b is 0.4, c is 0.1, and d is 0.3.

[0093] In some embodiments, based on the power quality index value, determining whether to send a warning message includes: when the power quality index value is greater than or equal to a first threshold and less than or equal to a second threshold, determining not to send a warning message; or, when the power quality index value is less than the first threshold or greater than the second threshold, determining to send a warning message.

[0094] Exemplarily, the power quality compliance limit Dbxz is a closed interval [1, 112], where the first threshold is 50 and the second threshold is 112.

[0095] When the power quality index value Zlzb is in the left closed and right open interval [1, 50), it means that the power quality is weak and abnormal, and an early warning message is issued;

[0096] When the power quality index value Zlzb is in the closed interval [50, 112], it means that the power quality meets the standard and is in a normal state. At this time, no warning information is issued;

[0097] When the power quality index value Zlzb is in the open interval (112, +∞], it means that the power quality exceeds the limit and is in an abnormal state, and an early warning message is issued.

[0098] In some embodiments, the early warning information includes at least one of the above-mentioned power data, equipment operation data and energy consumption data.

[0099] In some embodiments, the warning information includes at least one of the above-mentioned power efficiency within the preset time period, equipment utilization within the preset time period, average equipment repair time within the preset time period, and power load forecast within the preset time period.

[0100] In some embodiments, the power grid is optimized for energy consumption based on the early warning information, and a power grid optimization report is generated and sent to the node display module.

[0101] For example, if the utilization rate of some equipment falls below a threshold within a preset time period, the operation of that equipment is stopped, and the grid optimization report can include the serial number of the stopped equipment. For another example, if the mean repair time of some equipment exceeds a preset threshold within a preset time period, the equipment is updated or repaired, and the grid optimization report can include the serial number of that equipment.

[0102] In some embodiments, the warning information includes at least one of the following: voltage deviation, three-phase voltage imbalance, voltage swell and sag, frequency leveling, and three-phase current imbalance.

[0103] In some embodiments, optimizing energy consumption of the power grid according to the early warning information includes at least one of the following:

[0104] When the grid voltage deviation drops or rises significantly, the on-load voltage regulation system can be used to adjust the voltage level and maintain the load side voltage unchanged.

[0105] When the power factor of the power grid decreases, the power factor can be optimized through the automatic switching of the reactive power compensation device;

[0106] In the event that one of the power lines in the grid loses power, the backup automatic switching device will provide power for another line.

[0107] Based on this, by acquiring multi-dimensional data generated during grid operation within a preset time period, including power data, equipment operation data, and energy consumption data, the power quality index value of the grid is determined, improving the accuracy and comprehensiveness of the power quality index value determination. Then, based on the power quality index value, whether to send an early warning message is determined, facilitating timely monitoring of abnormal power consumption on the grid. In the event of abnormal power consumption, a timely early warning message can be sent to optimize the grid and thereby improve grid operation efficiency.

[0108] It is understandable that the above method can be implemented by a business management device. In order to implement the above functions, the business management device includes a hardware structure or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments applied for herein, the embodiments of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in a hardware or computer software driven hardware manner depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the embodiments of the present application.

[0109] In the embodiments of the present application, the business management device and the like can be divided into functional modules according to the above-mentioned method examples. For example, each functional module can be divided according to each function. The above-mentioned integrated modules can be implemented in the form of hardware or software functional modules. It should be noted that the division of modules in the embodiments of the present application is schematic and is only a logical functional division. In actual implementation, other division methods may be used.

[0110] In the case of dividing each functional module into corresponding functional modules, Figure 4 FIG. 1 shows a possible structural diagram of the service management device involved in the above embodiment. Figure 4 As shown, the service management device 400 includes: an acquisition module 401 , a processing module 402 and an early warning module 403 .

[0111] The acquisition module 401 is configured to acquire multi-dimensional data generated during the operation of the power grid within a preset time period. The multi-dimensional data includes at least one of the following: power data, equipment operation data, and energy consumption data.

[0112] The processing module 402 is configured to determine a power quality index value of the power grid based on the multi-dimensional data.

[0113] The early warning module 403 is used to determine whether to send an early warning message based on the power quality indicator value.

[0114] In some embodiments, the processing module 402 is specifically configured to:

[0115] Determine multidimensional evaluation indicators of the power grid based on the multidimensional data; the multidimensional evaluation indicators include at least one of the following: power efficiency within a preset time period, equipment utilization within a preset time period, average equipment repair time within a preset time period, and power load forecast within a preset time period;

[0116] Based on multi-dimensional evaluation indicators, the power quality index value of the power grid is determined.

[0117] In some embodiments, the power data includes at least one of the following: power output power at each moment in a preset time period, and power input power at each moment in a preset time period.

[0118] In some embodiments, the power efficiency within a preset time period is determined based on the following formula:

[0119]

[0120] Among them, Ydxl represents the power efficiency within the preset time period, Px i Indicates the power output at the i-th moment in the preset time period, Pi irepresents the power input / output rate at the i-th moment in the preset time period, n is the number of moments in the preset time period, and t i Indicates the weighting factor corresponding to the i-th moment in the preset time period.

[0121] In some embodiments, the equipment operation data includes at least one of the following: the actual operation time of the equipment within a preset time period, the available time of the equipment within a preset time period, the number of equipment failures within a preset time period, the number of equipment failures repaired within a preset time period, and the time for each equipment failure repair within a preset time period.

[0122] In some embodiments, the device utilization rate within a preset time period is determined based on the following formula:

[0123]

[0124] Among them, Sbly represents the equipment utilization rate within the preset time period, Tsjy represents the actual equipment running time within the preset time period, and Tkys represents the equipment available time within the preset time period.

[0125] In some embodiments, the average repair time of a device within a preset time period is determined based on the following formula:

[0126]

[0127] Among them, Xfsj represents the power efficiency within the preset time period, Repa k It represents the time when the kth fault of the device is repaired within the preset time period, N represents the number of times the device faults occur within the preset time period, and p represents the number of times the faults of the device are repaired within the preset time period.

[0128] In some embodiments, the energy consumption data includes electricity load within a preset time period.

[0129] In some embodiments, the power load forecast for a preset time period is determined based on the following formula:

[0130] Ycfh=β0+β1*Tm+β2*Hm+β3*Px+∈

[0131] Where Ycfh represents the predicted power load within the preset time period, β0, β1, β2, and β3 represent the preset regression coefficients, Tm represents temperature, Hm represents humidity, Px represents the power load within the preset time period, and ∈ represents the error term.

[0132] For a detailed description of the acquisition module 401, processing module 402 and warning module 403, as well as a more detailed description of each technical feature and a description of the beneficial effects, please refer to the corresponding method embodiment section above and will not be repeated here.

[0133] Of course, the service management device 400 includes but is not limited to the unit modules listed above. Furthermore, the specific functions that can be implemented by the above functional units also include but are not limited to the functions corresponding to the method steps of the above examples. The detailed description of other modules of the service management device 400 can refer to the detailed description of the corresponding method steps, and will not be repeated here in this embodiment of the application.

[0134] In an exemplary embodiment, the embodiment of the present application further provides a computer program product, which, when executed on a computer, enables the computer to execute the above-mentioned related method steps to implement the method in the aforementioned method embodiment.

[0135] In an exemplary embodiment, the present application also provides a computer-readable storage medium including software instructions, which, when executed on an electronic device, enables the electronic device to execute any one of the methods provided in the above embodiments.

[0136] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware, or any combination thereof. When implemented using a software program, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer-executable instructions. When the computer-executable instructions are loaded and executed on a computer, all or part of the processes or functions according to the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer-executable instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer-executable instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0137] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other variations of the disclosed embodiments by reviewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple components. A single processor or other unit may implement several functions listed in the claims. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0138] Although the present application has been described with reference to specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the drawings are merely illustrative of the present application as defined by the appended claims and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, the present application is intended to include such modifications and variations as fall within the scope of the claims of the present application and their equivalents.

[0139] The above is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or replacements within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A business management method, characterized in that: The method comprises: Acquire multi-dimensional data generated during the operation of the power grid within a preset time period, the multi-dimensional data including power data, equipment operation data, and energy consumption data; Determining a power quality index value of the power grid based on the multi-dimensional data; Based on the power quality indicator value, it is determined whether to send an early warning message, where the early warning message is used to indicate whether the power consumption of the power grid is abnormal.

2. The method according to claim 1, characterized in that Determining the power quality index value of the power grid based on the multi-dimensional data includes: Determining a multidimensional evaluation index of the power grid based on the multidimensional data; the multidimensional evaluation index includes at least one of the following: power efficiency within the preset time period, equipment utilization within the preset time period, average equipment repair time within the preset time period, and power load forecast within the preset time period; Based on the multi-dimensional evaluation index, a power quality index value of the power grid is determined.

3. The method according to claim 2, characterized in that The power data includes at least one of the following: the power output power at each moment in the preset time period, and the power input power at each moment in the preset time period.

4. The method according to claim 3, characterized in that The power efficiency within the preset time period is determined based on the following formula: Among them, Ydxl represents the power efficiency in the preset time period, Px i Po represents the power output at the i-th moment in the preset time period. i represents the power input / output rate at the i-th moment in the preset time period, n is the number of moments in the preset time period, and t i represents the weighting factor corresponding to the i-th moment in the preset time period.

5. The method according to claim 2, characterized in that The equipment operation data includes at least one of the following: the actual operation time of the equipment within the preset time period, the available time of the equipment within the preset time period, the number of equipment failures within the preset time period, the number of equipment failures repaired within the preset time period, and the time for each equipment failure repair within the preset time period.

6. The method according to claim 5, characterized in that The equipment utilization rate within the preset time period is determined based on the following formula: Among them, Sbly represents the equipment utilization rate within the preset time period, Tsjy represents the actual operating time of the equipment within the preset time period, and Tkys represents the available time of the equipment within the preset time period.

7. The method according to claim 5, characterized in that The average repair time of the equipment within the preset time period is determined based on the following formula: Among them, Xfsj represents the power efficiency within the preset time period, Repa k represents the time when the kth fault of the device is repaired within the preset time period, N represents the number of times the device fails within the preset time period, and p represents the number of times the fault of the device is repaired within the preset time period.

8. The method according to claim 2, characterized in that The energy consumption data includes the power load within the preset time period.

9. The method according to claim 8, characterized in that The power load forecast within the preset time period is determined based on the following formula: Ycfh=β0+β1*Tm+β2*Hm+β3*Px+∈ Among them, Ycfh represents the predicted amount of power load in the preset time period, β0, β1, β2, and β3 represent preset regression coefficients, Tm represents temperature, Hm represents humidity, Px represents the power load in the preset time period, and ∈ represents an error term.

10. A business management system, characterized in that: The business management system includes a data acquisition module, a data analysis module and an early warning module; The data acquisition module is used to obtain multi-dimensional data generated during the operation of the power grid within a preset time period, wherein the multi-dimensional data includes at least one of the following: power data, equipment operation data, and energy consumption data; The data analysis module is used to determine the power quality index value of the power grid based on the multi-dimensional data; The early warning module is used to determine whether to send early warning information based on the power quality indicator value.

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