Data asset management system based on power metering

Abstract

The present invention relates to the technical field of electric power metering, and in particular to a data asset management system based on electric power metering, comprising an acquisition module: acquiring electric power data of equipment, and then analyzing the electric power data to obtain electric power analysis data; an energy consumption analysis module: judging the electric power consumption data of equipment, and outputting different energy consumption equipment; an impact analysis module: based on high-consumption equipment, acquiring the time-frequency value of the equipment, making comparison and judgment, and generating an impact signal; a management module: marking high-consumption and high-impact signals as risk asset equipment, obtaining risk assessment coefficients, and adjusting the supervision frequency of corresponding risk asset equipment; the present invention obtains the monitoring frequency of risk asset equipment that can be regulated in subsequent production processes through the power consumption transformation ratio and the impact ratio of the number of related equipment, so that the monitoring frequency of risk asset equipment is regulated appropriately, and the current supervision frequency of risk asset equipment is improved, thereby effectively improving the safety of risk asset supervision of electric power metering.

Description

Technical Field

[0001] The present invention relates to the technical field of power metering, and in particular to a data asset management system based on power metering. Background Art

[0002] Chinese patent CN114819582A discloses a metering asset management system based on electric energy meter data, which belongs to the technical field of electric energy meter management, and includes a metering asset statistics unit, a metering data acquisition unit, a metering data processing unit and a metering data analysis unit. The metering data processing unit is used to process the collected load data, and the metering data analysis unit is used to obtain a frequency domain indicator characteristic set for user classification based on discrete Fourier transform and frequency domain indicator characteristic parameters for the processed load data, and to evaluate the metering asset results of the classified users based on the electric energy meter data to which they belong.

[0003] The existing metering asset management system is equipped with a metering data analysis unit. After normalization preprocessing of the load data, the metering data analysis unit performs discrete Fourier transform on the load data to obtain a frequency domain index characteristic set, thereby realizing the classification of user load characteristics and providing assistance for the reasonable allocation of metering assets.

[0004] However, it cannot evaluate and judge the equipment used based on the measured electricity data, nor can it set up more reasonable and effective regulatory measures for high-energy-consuming and high-risk power asset equipment based on the results of the evaluation and judgment, so as to improve the efficiency of power asset equipment management. Summary of the invention

[0005] The purpose of the present invention is to provide a data asset management system based on electricity metering. The technical problem solved by the present invention is that it cannot evaluate and judge the equipment used according to the measured electricity data, and it cannot set more reasonable and effective supervision measures for high-energy consumption and high-risk power asset equipment based on the results of the evaluation and judgment, so as to improve the efficiency of power asset equipment management.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] Data asset management system based on power metering, including:

[0008] Acquisition module: obtains the power data of the equipment, analyzes the power data, and obtains power analysis data;

[0009] Among them, the power analysis data includes the year-on-year value, the month-on-month value, and the peak value;

[0010] Energy consumption analysis module: Based on the power analysis data, the power consumption data of the equipment is judged and the output is different energy consumption equipment;

[0011] Among them, different energy consumption equipment includes high-consumption equipment and low-consumption equipment;

[0012] Impact analysis module: Based on high-consumption equipment, obtain the time-frequency values ​​of the equipment, make comparisons and judgments, and generate impact signals;

[0013] Among them, the impact signal includes a high-consumption high-impact signal and a high-consumption low-impact signal;

[0014] Management module: Mark high-consumption and high-impact signals as risky asset equipment, obtain the current operation impact factor KDy and the current equipment impact factor KDs, and use the formula The regulatory frequency adjustment coefficient KT is calculated:

[0015] The regulatory frequency of the current risk asset equipment is obtained, and the regulatory frequency of the current risk asset equipment is multiplied by the regulatory frequency adjustment coefficient KT to obtain the regulatory frequency of the corresponding risk asset equipment.

[0016] As a further solution of the present invention: the processing process of the power ratio value is:

[0017] The power consumption value in the measurement period is calculated by comparing it with the power consumption value in the previous measurement period to obtain the power ratio value.

[0018] As a further solution of the present invention: the processing process of the year-on-year value of electricity is:

[0019] The power consumption value within the measurement period is calculated by comparing it with the power consumption value during the same period in history to obtain the power month-on-month value.

[0020] As a further solution of the present invention: the processing process of the power peak ratio is:

[0021] The maximum power consumption during the measurement period is calculated by comparing it with the historical maximum power consumption to obtain the power peak ratio.

[0022] As a further solution of the present invention: the process of judging the power consumption data of the equipment is as follows:

[0023] The power consumption ratio is calculated by adding up the power cycle value, the power year-on-year value and the power peak ratio.

[0024] If the power consumption ratio is greater than or equal to the power consumption ratio threshold, a high-consumption device signal is generated;

[0025] If the power consumption ratio is less than the power consumption ratio threshold, a low-consumption device signal is generated.

[0026] As a further solution of the present invention: the time-frequency value acquisition process of the device is:

[0027] The running time percentage and the running frequency percentage are added together to obtain the time-frequency value of the device.

[0028] As a further solution of the present invention: if the time-frequency value of the device is greater than or equal to the time-frequency threshold, a high-consumption and high-impact signal is generated;

[0029] If the time-frequency value of the device is less than the time-frequency threshold, a high-consumption and low-impact signal is generated.

[0030] As a further solution of the present invention, the process of obtaining the same-frequency ratio is as follows:

[0031] Obtain each high-consumption device, extract the power-consuming devices related to each high-consumption device, and mark them as related devices; obtain the number of related devices corresponding to each high-consumption device, and mark the number of related devices;

[0032] Calculate the ratio of the number of related devices to the total number of devices measured during the measurement period to obtain the proportion of co-frequency operation;

[0033] The process of obtaining the running time percentage is as follows:

[0034] The operating time of high-consumption equipment is obtained, and the ratio of the operating time of high-consumption equipment to the measurement period is calculated to obtain the allowable time ratio.

[0035] As a further solution of the present invention: the relevant equipment includes a connection device and a time association device;

[0036] All power-consuming devices connected in series with the high-consumption device are recorded as connected devices;

[0037] Obtain the start time and stop time of the high-consumption equipment during each operation, mark them as the start time and stop time of the high-consumption equipment, and then obtain the start time and stop time of all measured total equipment, mark them as the start time and stop time of the pre-association equipment;

[0038] The startup time of the high-consumption equipment is subtracted from the startup time of the pre-associated equipment and the average is taken to obtain the startup associated time; the shutdown time of the high-consumption equipment is subtracted from the shutdown time of the pre-associated equipment and the average is taken to obtain the shutdown associated time;

[0039] If the startup associated time is less than the startup associated time threshold, and the shutdown associated time is less than the shutdown associated time threshold, the corresponding power consuming device is marked as a time associated device.

[0040] As a further solution of the present invention: the process of obtaining the current operation impact factor is:

[0041] Get the power consumption ratio of risk asset equipment and mark it as the current operation impact factor KDy;

[0042] The process of obtaining the current device impact factor is as follows:

[0043] Get the total number of related equipment corresponding to the risk asset equipment, mark it as the total number of risk-related equipment, then get the number of risk asset equipment contained in the risk asset-related equipment, mark it as the number of related risk equipment, calculate the ratio of the number of related risk equipment to the total number of risk-related equipment, and get the current equipment impact factor KDs.

[0044] Beneficial effects of the present invention:

[0045] (1) The acquisition module of the present invention uses an electric power metering method to obtain the electric power data of the equipment, and then analyzes the electric power data to obtain electric power analysis data; the judgment module: based on the electric power analysis data, judges the electric power consumption data of the equipment, and outputs different energy consumption equipment; the present invention compares the electric power data of the current detection period from three dimensions: year-on-year, month-on-month and peak value, so as to judge the power consumption of the current electric power equipment, which is convenient for the subsequent key management of the electric power data of high-consumption equipment;

[0046] (2) The impact analysis module of the present invention is based on high-consumption equipment, obtains the time-frequency value of the equipment, makes comparison and judgment, and generates an impact signal; the present invention analyzes the impact degree of high-consumption equipment by the operating time proportion and the operating frequency proportion, so as to effectively and accurately evaluate the impact degree of each high-consumption equipment;

[0047] (3) The management module of the present invention: marks high-consumption and high-impact signals as risky asset equipment, obtains risk assessment coefficients, and adjusts the supervision frequency of the corresponding risky asset equipment; the present invention obtains the frequency of monitoring risky asset equipment in the subsequent production process through the power consumption ratio and the impact ratio of the number of related equipment, so that the monitoring frequency of risky asset equipment is adjusted appropriately, thereby increasing the current supervision frequency of risky asset equipment, thereby effectively improving the safety of risk asset supervision of electricity metering. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention will be further described below in conjunction with the accompanying drawings.

[0049] Figure 1 is a system block diagram of Embodiment 1 of the present invention;

[0050] Figure 2 is a system block diagram of Embodiment 2 of the present invention;

[0051] Figure 3 It is a system block diagram of embodiment 3 of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 are within the scope of protection of the present invention.

[0053] Example 1

[0054] See also Figure 1 As shown, the present invention is a data asset management system based on power metering, comprising:

[0055] Acquisition module: uses power metering to obtain power data of equipment, and then analyzes the power data to obtain power analysis data;

[0056] Among them, the electricity measurement method adopts the electric energy meter measurement, and the electricity analysis data includes the electricity year-on-year value, the electricity cycle value, and the electricity peak value;

[0057] In some implementation schemes, an electric energy meter is set to obtain the power consumption value of each device during the measurement period;

[0058] Then, the power consumption value in the measurement period is processed with the power consumption value in the previous measurement period, the power consumption value in the same period in history, and the historical power consumption peak value to obtain the power month-on-month value, power year-on-year value, and power peak ratio value;

[0059] Specifically, the processing process of the power cycle value is as follows:

[0060] Obtain the power consumption value in the measurement period and the power consumption value in the previous measurement period, calculate the ratio of the power consumption value in the measurement period to the power consumption value in the previous measurement period, and obtain the power ratio value;

[0061] The processing process of the year-on-year value of electricity is as follows:

[0062] Obtain the power consumption value within the measurement period and the power consumption value of the same period in history, calculate the ratio of the power consumption value within the measurement period to the power consumption value of the same period in history, and obtain the power cycle value;

[0063] The processing process of power peak ratio is as follows:

[0064] Obtaining the maximum power consumption value in the measurement period and the historical maximum power consumption value, calculating the ratio of the maximum power consumption value in the measurement period to the historical maximum power consumption value, and obtaining the power peak ratio;

[0065] Energy consumption analysis module: Based on the power analysis data, the power consumption data of the equipment is judged and the output is different energy consumption equipment;

[0066] Among them, different energy consumption equipment includes high-consumption equipment and low-consumption equipment;

[0067] In some embodiments, the power cycle value, the power year-on-year value, and the power peak ratio are obtained, and the power cycle value, the power year-on-year value, and the power peak ratio are added together to calculate the power consumption transformation ratio;

[0068] comparing the power consumption ratio with a power consumption ratio threshold;

[0069] If the power consumption ratio is greater than or equal to the power consumption ratio threshold, it means that the power performance of the electrical equipment measured during the detection period exceeds the performance of historical data, and a high-consumption equipment signal is generated;

[0070] If the power consumption ratio is less than the power consumption ratio threshold, it means that the power performance of the electrical equipment measured during the detection period does not exceed the performance of historical data, and a low-consumption equipment signal is generated;

[0071] The technical solution of the embodiment of the present invention is: an acquisition module: using an electric power metering method to obtain the electric power data of the equipment, and then analyzing the electric power data to obtain electric power analysis data; a judgment module: based on the electric power analysis data, judging the electric power consumption data of the equipment, and outputting different energy consumption equipment; the present invention compares the electric power data of the current detection period from three dimensions: year-on-year, month-on-month and peak value, so as to judge the power consumption of the current electric power equipment, which is convenient for the subsequent key management of the electric power data of high-consumption equipment.

[0072] Example 2

[0073] Based on the above Example 1, please refer to Figure 2 As shown, the present invention is a data asset management system based on power metering, and also includes:

[0074] Impact analysis module: Based on high-consumption equipment, obtain the time-frequency values ​​of the equipment, make comparisons and judgments, and generate impact signals;

[0075] Among them, the impact signal includes a high-consumption high-impact signal and a high-consumption low-impact signal;

[0076] In some embodiments, the operating time proportion and the operating same-frequency proportion of each high-power consumption device are obtained, and the operating time proportion and the operating same-frequency proportion are added together to obtain the time-frequency value of the device;

[0077] Compare the time-frequency value of the device with the time-frequency threshold;

[0078] If the time-frequency value of the device is greater than or equal to the time-frequency threshold, it means that the current high-consumption device has a high proportion in terms of operating time and the degree of correlation between devices, and a high-consumption high-impact signal is generated;

[0079] If the time-frequency value of the device is less than the time-frequency threshold, it means that the current high-consumption device has a low proportion in terms of operating time and the degree of correlation between devices, and a high-consumption low-impact signal is generated;

[0080] Specifically, the process of obtaining the running co-frequency ratio is as follows:

[0081] Obtain each high-consumption device, extract the power-consuming devices related to each high-consumption device, and mark them as related devices (related devices include connection devices and time-related devices); obtain the number of related devices corresponding to each high-consumption device, and mark the number of related devices;

[0082] Calculate the ratio of the number of related devices to the total number of devices measured during the measurement period to obtain the proportion of co-frequency operation;

[0083] The process of obtaining the running time percentage is as follows:

[0084] Obtain the operating time of high-consumption equipment, calculate the ratio of the operating time of high-consumption equipment to the measurement period, and obtain the allowable time ratio;

[0085] Exemplarily, the process of extracting power-consuming devices related to each high-consuming device is as follows:

[0086] Taking a certain high-consumption device as an example, all the power-consuming devices connected in series on the high-consumption device are recorded as connected devices;

[0087] Obtain the start time and stop time of the high-consumption equipment during each operation, mark them as the start time and stop time of the high-consumption equipment, and then obtain the start time and stop time of all measured total equipment, mark them as the start time and stop time of the pre-association equipment;

[0088] The startup time of the high-consumption equipment is subtracted from the startup time of the pre-associated equipment and the average is taken to obtain the startup associated time; the shutdown time of the high-consumption equipment is subtracted from the shutdown time of the pre-associated equipment and the average is taken to obtain the shutdown associated time;

[0089] Compare the startup-related time and the shutdown-related time with corresponding thresholds respectively;

[0090] If the startup associated time is less than the startup associated time threshold, and the shutdown associated time is less than the shutdown associated time threshold, the corresponding power consuming device is marked as a time associated device; otherwise, the corresponding power consuming device is not a time associated device;

[0091] The technical solution of the embodiment of the present invention is: impact analysis module: based on high-consumption equipment, obtain the time-frequency value of the equipment, make comparative judgments, and generate impact signals; the present invention analyzes the impact degree of high-consumption equipment through the proportion of operating time and the proportion of operating co-frequency, so as to effectively and accurately evaluate the impact degree of each high-consumption equipment.

[0092] Example 3

[0093] Based on the above Example 2, please refer to Figure 3 As shown, the present invention is a data asset management system based on power metering, and also includes:

[0094] Management module: Mark high-consumption and high-impact signals as risky asset equipment, obtain risk assessment coefficients, and adjust the supervision frequency of corresponding risky asset equipment;

[0095] In some implementation schemes, high-consumption and high-impact signals are marked as risky asset equipment, the current operation impact factor KDy and the current equipment impact factor KDs are obtained, and the current operation risk factor KDy and the current equipment impact factor KDs are processed and calculated to obtain the regulatory frequency adjustment coefficient KT; wherein the processing and calculation process is as follows:

[0096] Obtain the regulatory frequency of the current risk asset equipment, multiply the regulatory frequency of the current risk asset equipment by the regulatory frequency adjustment coefficient KT, and obtain the regulatory frequency of the corresponding risk asset equipment;

[0097] This enables subsequent staff to supervise the risk asset equipment according to the supervision frequency of the corresponding risk asset equipment;

[0098] Specifically, the process of obtaining the current operating impact factor is as follows:

[0099] Get the power consumption ratio of risk asset equipment and mark it as the current operation impact factor KDy;

[0100] The process of obtaining the current device impact factor is as follows:

[0101] Obtain the total number of related equipment corresponding to the risk asset equipment, mark it as the total number of risk-related equipment, then obtain the number of risk asset equipment in the risk asset-related equipment, mark it as the number of related risk equipment, calculate the ratio of the number of related risk equipment to the total number of risk-related equipment, and obtain the current equipment impact factor KDs;

[0102] The process of obtaining the regulatory frequency of current risk asset equipment is as follows:

[0103] Obtain the number of times the staff inspects the risk asset equipment during the measurement period, calculate the ratio of the number of inspections to the inspection period, and obtain the supervision frequency of the current risk asset equipment;

[0104] The technical solution of the embodiment of the present invention: Management module: Mark the high-consumption and high-impact signals as risk asset equipment, obtain the risk assessment coefficient, and adjust the supervision frequency of the corresponding risk asset equipment; the present invention obtains the ability to adjust the monitoring frequency of risk asset equipment in the subsequent production process through the power consumption ratio of embodiment 1 and the related equipment quantity impact ratio of embodiment 2, so that the monitoring frequency of risk asset equipment is adaptively regulated, and the current supervision frequency of risk asset equipment is increased, thereby effectively improving the safety of risk asset supervision of electricity metering; Therefore, the present invention solves the problem in the prior art that it cannot evaluate and judge the equipment used based on the measured electricity data, and it cannot set more reasonable and effective supervision measures for high-energy consumption and high-risk power asset equipment based on the results of the evaluation and judgment, so as to improve the management efficiency of power asset equipment.

[0105] Example 4

[0106] Based on the above embodiments 1-3, the present invention is a data asset management method based on power metering, comprising the following steps:

[0107] Step 1: Set up an energy meter to obtain the power consumption value of each device during the measurement period;

[0108] Then, the power consumption value in the measurement period is processed with the power consumption value in the previous measurement period, the power consumption value in the same period in history, and the historical power consumption peak value to obtain the power month-on-month value, power year-on-year value, and power peak ratio value;

[0109] Step 2: Obtain the power cycle value, the power year-on-year value, and the power peak ratio, add the power cycle value, the power year-on-year value, and the power peak ratio together to calculate the power consumption transformation ratio;

[0110] comparing the power consumption ratio with a power consumption ratio threshold;

[0111] If the power consumption ratio is greater than or equal to the power consumption ratio threshold, it means that the power performance of the electrical equipment measured during the detection period exceeds the performance of historical data, and a high-consumption equipment signal is generated;

[0112] If the power consumption ratio is less than the power consumption ratio threshold, it means that the power performance of the electrical equipment measured during the detection period does not exceed the performance of historical data, and a low-consumption equipment signal is generated;

[0113] Step 3: Obtain the operating time percentage and operating frequency percentage of each high-consumption device, add the operating time percentage and the operating frequency percentage to obtain the time-frequency value of the device;

[0114] Compare the time-frequency value of the device with the time-frequency threshold;

[0115] If the time-frequency value of the device is greater than or equal to the time-frequency threshold, it means that the current high-consumption device has a high proportion in terms of operating time and the degree of correlation between devices, and a high-consumption high-impact signal is generated;

[0116] If the time-frequency value of the device is less than the time-frequency threshold, it means that the current high-consumption device has a low proportion in terms of operating time and the degree of correlation between devices, and a high-consumption low-impact signal is generated;

[0117] Step 4: Mark the high-consumption and high-impact signal as a risk asset device, obtain the current operation impact factor KDy and the current equipment impact factor KDs, process and calculate the current operation risk factor KDy and the current equipment impact factor KDs, and obtain the regulatory frequency adjustment coefficient KT; the processing and calculation process is as follows:

[0118] Obtain the supervision frequency of the current risk asset equipment, multiply the supervision frequency of the current risk asset equipment by the supervision frequency adjustment coefficient KT, and adjust the supervision frequency of the corresponding risk asset equipment; so that subsequent staff can supervise the risk asset equipment according to the supervision frequency of the corresponding risk asset equipment.

[0119] Example 5

[0120] Schematic diagram of an embodiment of an electronic device provided by an embodiment of the present invention. An embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0121] Step 1: Set up an energy meter to obtain the power consumption value of each device during the measurement period;

[0122] Then, the power consumption value in the measurement period is processed with the power consumption value in the previous measurement period, the power consumption value in the same period in history, and the historical power consumption peak value to obtain the power month-on-month value, power year-on-year value, and power peak ratio value;

[0123] Step 2: Obtain the power cycle value, the power year-on-year value, and the power peak ratio, add the power cycle value, the power year-on-year value, and the power peak ratio together to calculate the power consumption transformation ratio;

[0124] comparing the power consumption ratio with a power consumption ratio threshold;

[0125] If the power consumption ratio is greater than or equal to the power consumption ratio threshold, it means that the power performance of the electrical equipment measured during the detection period exceeds the performance of historical data, and a high-consumption equipment signal is generated;

[0126] If the power consumption ratio is less than the power consumption ratio threshold, it means that the power performance of the electrical equipment measured during the detection period does not exceed the performance of historical data, and a low-consumption equipment signal is generated;

[0127] Step 3: Obtain the operating time percentage and operating frequency percentage of each high-consumption device, add the operating time percentage and the operating frequency percentage to obtain the time-frequency value of the device;

[0128] Compare the time-frequency value of the device with the time-frequency threshold;

[0129] If the time-frequency value of the device is greater than or equal to the time-frequency threshold, it means that the current high-consumption device has a high proportion in terms of operating time and the degree of correlation between devices, and a high-consumption high-impact signal is generated;

[0130] If the time-frequency value of the device is less than the time-frequency threshold, it means that the current high-consumption device has a low proportion in terms of operating time and the degree of correlation between devices, and a high-consumption low-impact signal is generated;

[0131] Step 4: Mark the high-consumption and high-impact signals as risky asset equipment, obtain the current operation impact factor KDy and the current equipment impact factor KDs, process and calculate the current operation risk factor KDy and the current equipment impact factor KDs, and obtain the regulatory frequency adjustment coefficient KT; the processing and calculation process is as follows:

[0132] Obtain the supervision frequency of the current risk asset equipment, multiply the supervision frequency of the current risk asset equipment by the supervision frequency adjustment coefficient KT, and adjust the supervision frequency of the corresponding risk asset equipment; so that subsequent staff can supervise the risk asset equipment according to the supervision frequency of the corresponding risk asset equipment.

[0133] Example 6

[0134] A schematic diagram of an embodiment of a computer-readable storage medium provided by an embodiment of the present invention. This embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0135] Step 1: Set up an energy meter to obtain the power consumption value of each device during the measurement period;

[0136] Then, the power consumption value in the measurement period is processed with the power consumption value in the previous measurement period, the power consumption value in the same period in history, and the historical power consumption peak value to obtain the power month-on-month value, power year-on-year value, and power peak ratio value;

[0137] Step 2: Obtain the power cycle value, the power year-on-year value, and the power peak ratio, add the power cycle value, the power year-on-year value, and the power peak ratio together to calculate the power consumption transformation ratio;

[0138] comparing the power consumption ratio with a power consumption ratio threshold;

[0139] If the power consumption ratio is greater than or equal to the power consumption ratio threshold, it means that the power performance of the electrical equipment measured during the detection period exceeds the performance of historical data, and a high-consumption equipment signal is generated;

[0140] If the power consumption ratio is less than the power consumption ratio threshold, it means that the power performance of the electrical equipment measured during the detection period does not exceed the performance of historical data, and a low-consumption equipment signal is generated;

[0141] Step 3: Obtain the operating time percentage and operating frequency percentage of each high-consumption device, add the operating time percentage and the operating frequency percentage to obtain the time-frequency value of the device;

[0142] Compare the time-frequency value of the device with the time-frequency threshold;

[0143] If the time-frequency value of the device is greater than or equal to the time-frequency threshold, it means that the current high-consumption device has a high proportion in terms of operating time and the degree of correlation between devices, and a high-consumption high-impact signal is generated;

[0144] If the time-frequency value of the device is less than the time-frequency threshold, it means that the current high-consumption device has a low proportion in terms of operating time and the degree of correlation between devices, and a high-consumption low-impact signal is generated;

[0145] Step 4: Mark the high-consumption and high-impact signals as risky asset equipment, obtain the current operation impact factor KDy and the current equipment impact factor KDs, process and calculate the current operation risk factor KDy and the current equipment impact factor KDs, and obtain the regulatory frequency adjustment coefficient KT; the processing and calculation process is as follows:

[0146] Obtain the supervision frequency of the current risk asset equipment, multiply the supervision frequency of the current risk asset equipment by the supervision frequency adjustment coefficient KT, and adjust the supervision frequency of the corresponding risk asset equipment; so that subsequent staff can supervise the risk asset equipment according to the supervision frequency of the corresponding risk asset equipment.

[0147] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0148] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0149] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0150] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0151] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0152] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0153] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0154] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. Data asset management system based on power metering, characterized in that: include: Acquisition module: obtains the power data of the equipment, analyzes the power data, and obtains power analysis data; Among them, the power analysis data includes the year-on-year value, the month-on-month value, and the peak value; Energy consumption analysis module: Based on the power analysis data, the power consumption data of the equipment is judged and the output is different energy consumption equipment; Among them, different energy consumption equipment includes high-consumption equipment and low-consumption equipment; Impact analysis module: Based on high-consumption equipment, obtain the time-frequency values ​​of the equipment, make comparisons and judgments, and generate impact signals; Among them, the impact signal includes a high-consumption high-impact signal and a high-consumption low-impact signal; Management module: Mark high-consumption and high-impact signals as risky asset equipment, obtain the current operation impact factor KDy and the current equipment impact factor KDs, and use the formula The regulatory frequency adjustment coefficient KT is calculated: Obtain the regulatory frequency of the current risk asset equipment, multiply the regulatory frequency of the current risk asset equipment by the regulatory frequency adjustment coefficient KT, and obtain the regulatory frequency of the corresponding risk asset equipment; The process of obtaining the time-frequency value of the device is as follows: Add the running time percentage and the running frequency percentage to get the time-frequency value of the device. The process of obtaining the running co-frequency ratio is as follows: Obtain each high-consumption device, extract the power-consuming devices related to each high-consumption device, and mark them as related devices; obtain the number of related devices corresponding to each high-consumption device, and mark the number of related devices; Calculate the ratio of the number of related devices to the total number of devices measured during the measurement period to obtain the proportion of co-frequency operation; The process of obtaining the running time percentage is as follows: Obtain the operating time of high-consumption equipment, calculate the ratio of the operating time of high-consumption equipment to the measurement period, and obtain the allowable time ratio; The current process of obtaining the impact factor is as follows: Get the power consumption ratio of risk asset equipment and mark it as the current operation impact factor KDy; The process of obtaining the current device impact factor is as follows: Get the total number of related equipment corresponding to the risk asset equipment, mark it as the total number of risk-related equipment, then get the number of risk asset equipment contained in the risk asset-related equipment, mark it as the number of related risk equipment, calculate the ratio of the number of related risk equipment to the total number of risk-related equipment, and get the current equipment impact factor KDs.

2. The data asset management system based on power metering according to claim 1 is characterized in that: The processing process of the power cycle value is as follows: The power consumption value in the measurement period is calculated by comparing it with the power consumption value in the previous measurement period to obtain the power ratio value.

3. The data asset management system based on power metering according to claim 2 is characterized in that: The processing process of the year-on-year value of electricity is as follows: The power consumption value within the measurement period is calculated by comparing it with the power consumption value during the same period in history to obtain the year-on-year value of electricity.

4. The data asset management system based on power metering according to claim 3 is characterized in that: The processing process of power peak ratio is as follows: The maximum power consumption during the measurement period is calculated by comparing it with the historical maximum power consumption to obtain the power peak ratio.

5. The data asset management system based on power metering according to claim 1 is characterized in that: The process of judging the power consumption data of the equipment is as follows: The power consumption ratio is calculated by adding up the power cycle value, the power year-on-year value and the power peak ratio. If the power consumption ratio is greater than or equal to the power consumption ratio threshold, a high-consumption device signal is generated; If the power consumption ratio is less than the power consumption ratio threshold, a low-consumption device signal is generated.

6. The data asset management system based on power metering according to claim 1 is characterized in that: If the time-frequency value of the device is greater than or equal to the time-frequency threshold, a high-consumption and high-impact signal is generated; If the time-frequency value of the device is less than the time-frequency threshold, a high-consumption and low-impact signal is generated.

7. The data asset management system based on power metering according to claim 6 is characterized in that: Related equipment includes connection equipment and time-related equipment; All power-consuming devices connected in series with the high-consumption device are recorded as connected devices; Obtain the start time and stop time of the high-consumption equipment during each operation, mark them as the start time and stop time of the high-consumption equipment, and then obtain the start time and stop time of all measured total equipment, mark them as the start time and stop time of the pre-association equipment; The startup time of the high-consumption equipment is subtracted from the startup time of the pre-associated equipment and the average is taken to obtain the startup associated time; the shutdown time of the high-consumption equipment is subtracted from the shutdown time of the pre-associated equipment and the average is taken to obtain the shutdown associated time; If the startup associated time is less than the startup associated time threshold, and the shutdown associated time is less than the shutdown associated time threshold, the corresponding power consuming device is marked as a time associated device.

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