Methods, apparatuses, devices, and media for calculating active power by current
Patent Information
- Application Number
- CN202610890813.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-18
- Publication Date
- 2026-11-03
AI Technical Summary
In industrial settings where voltage signals are lacking, existing technologies struggle to acquire the active power of equipment quickly and cost-effectively. Traditional methods require expensive voltage and current signal acquisition equipment, resulting in high costs and complex deployment.
By acquiring the static operating characteristics of the target device, a power factor inference model is constructed. Active power is calculated using current signals and operating characteristics, including operating current, voltage, and frequency characteristics. Power factor inference and calculation are then performed in conjunction with a machine learning model.
It enables rapid calculation of active power through current measurement under no voltage signal conditions, reducing equipment costs and improving calculation efficiency and accuracy, making it suitable for rapid inspection and low-cost renovation scenarios.
Smart Images
Figure CN123029258A_ABST
Abstract
Description
Technical Field
[0001] Embodiments of this disclosure relate to the field of electrical parameter calculation for industrial equipment, and more specifically, to a method, apparatus, device, and medium suitable for calculating the active power of an equipment by means of current. Background Technology
[0002] In numerous industrial settings (especially for rapid inspections and low-cost retrofits), current signal acquisition (CT / clamp meters) is convenient, readily available, and inexpensive. However, active power acquisition typically requires more comprehensive voltage and power metering circuits or smart power meters, resulting in significantly higher deployment timelines and costs. Consequently, scenarios with "current data but no power data" are common. Active power data is crucial for effective pump energy efficiency diagnosis and energy-saving reliability assessment, and accurately acquiring the active power of equipment is of paramount importance for industrial energy management.
[0003] In related technologies, it is usually necessary to simultaneously acquire voltage and current signals and perform power calculations using dedicated power analyzers or power quality monitoring devices. However, the computing equipment used in traditional methods is expensive and complex to install and deploy. If the site does not have complete voltage and power acquisition conditions, it is difficult to obtain the active power of the equipment quickly and at low cost. Summary of the Invention
[0004] The embodiments described herein provide a method, apparatus, device, and medium for calculating the active power of a device using current, overcoming the aforementioned problems.
[0005] In a first aspect, according to the present disclosure, a method for calculating the active power of a device using current is provided, comprising: Obtain the static operating characteristics of the target device; Based on the static operating characteristics of the target device, a set of matching devices that are associated with the target device is retrieved from a pre-constructed data sample set; Based on a set of matching devices that are associated with the target device, a power factor inference model corresponding to the target device is constructed; the power factor inference model is used to output the corresponding estimated power factor based on real-time operating characteristics; Acquire the field operation data of the target device, and extract the real-time operation features corresponding to the target device from the field operation data; wherein, the real-time operation features include: operating current features, or, operating current features and operating voltage features; when the target device is in a frequency conversion scenario, the real-time operation features also include operating frequency features and / or operating speed features; The real-time operating characteristics of the target device are input into the power factor inference model so that the estimated power factor of the target device can be calculated based on the real-time operating characteristics of the target device through the power factor inference model. Obtain the operating voltage characteristics corresponding to the target device, and calculate the active power of the target device based on the operating voltage characteristics, the estimated power factor, and the operating current characteristics.
[0006] Secondly, according to the present disclosure, an apparatus for calculating the active power of a device using current is provided, comprising: The acquisition module is used to acquire the static operating characteristics of the target device; The retrieval module is used to retrieve a set of matching devices that are associated with the target device from a pre-constructed data sample set based on the static operating characteristics of the target device. The construction module is used to construct a power factor inference model corresponding to the target device based on a set of matching devices that are associated with the target device; the power factor inference model is used to output the corresponding estimated power factor based on real-time operating characteristics; An extraction module is used to acquire the field operation data of the target device and extract the real-time operation features corresponding to the target device from the field operation data; wherein, the real-time operation features include: operating current features, or, operating current features and operating voltage features; when the target device is in a frequency conversion scenario, the real-time operation features also include operating frequency features and / or operating speed features; The estimation module is used to input the real-time operating characteristics of the target device into the power factor inference model, so as to estimate the power factor of the target device based on the real-time operating characteristics of the target device through the power factor inference model; The calculation module is used to obtain the operating voltage characteristics corresponding to the target device, and calculate the active power of the target device based on the operating voltage characteristics corresponding to the target device, the estimated power factor, and the operating current characteristics.
[0007] Thirdly, a computer device is provided, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method for calculating the active power of a device by current as described in any of the above embodiments.
[0008] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method for calculating the active power of a device by current as described in any of the above embodiments.
[0009] The method for calculating the active power of a device using current provided in this application includes: obtaining the static operating characteristics of the target device; retrieving a set of matching devices related to the target device from a pre-constructed data sample set based on the static operating characteristics of the target device; constructing a power factor inference model corresponding to the target device based on the set of matching devices related to the target device; the power factor inference model outputting the corresponding estimated power factor based on the real-time operating characteristics; obtaining the field operating data of the target device and extracting the corresponding real-time operating characteristics of the target device from the field operating data; wherein, the real-time operating characteristics include operating current characteristics, or operating current characteristics and operating voltage characteristics; when the target device is in a frequency conversion scenario, the real-time operating characteristics also include operating frequency characteristics and / or operating speed characteristics; inputting the corresponding real-time operating characteristics of the target device into the power factor inference model to infer the estimated power factor of the target device based on the corresponding real-time operating characteristics of the target device through the power factor inference model; obtaining the corresponding operating voltage characteristics of the target device, and calculating the active power of the target device based on the corresponding operating voltage characteristics, estimated power factor, and operating current characteristics of the target device. In this way, by combining the operating voltage characteristics and operating current characteristics to complete the active power calculation, a complete functional chain from current measurement to power output is realized. The calculation process does not require expensive equipment and can effectively calculate the active power of the equipment on site.
[0010] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more obvious and understandable, specific implementation methods of this application are described below. Attached Figure Description
[0011] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments will be briefly described below. It should be understood that the drawings described below only relate to some embodiments of this disclosure and are not intended to limit this disclosure, wherein: Figure 1 This is a flowchart illustrating a method for calculating the active power of a device using current, as provided in this disclosure.
[0012] Figure 2 This is a schematic diagram of a device for calculating the active power of an electrical current device provided in this disclosure.
[0013] Figure 3 This is a schematic diagram of the structure of a computer device provided in this disclosure.
[0014] It should be noted that the elements in the attached diagram are schematic and not drawn to scale. Detailed Implementation
[0015] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the described embodiments of this disclosure without creative effort are also within the scope of protection of this disclosure.
[0016] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this subject matter pertains. It will be further understood that terms such as those defined in commonly used dictionaries shall be interpreted as having the meaning consistent with their meaning in the context of the specification and in the relevant art, and shall not be interpreted in an idealized or overly formal form unless otherwise explicitly defined herein. As used herein, the statement of “connecting” or “coupling” two or more parts together shall mean that these parts are directly joined together or joined through one or more intermediate components.
[0017] The term "embodiment" as used herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of the phrase "embodiment" in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0018] In this document, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists, A and B exist simultaneously, or B exists. Additionally, the character " / " generally indicates that the preceding and following related objects have an "or" relationship. Terms such as "first" and "second" are only used to distinguish one component (or part of a component) from another component (or another part of a component).
[0019] In the description of this application, unless otherwise stated, "multiple" means two or more (including two), and similarly, "multiple groups" means two or more (including two groups).
[0020] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.
[0021] Figure 1 This is a flowchart illustrating a method for calculating the active power of a device using current, as provided in an embodiment of this disclosure. Figure 1As shown, the specific process of calculating the active power of a device using current includes: S110. Obtain the static operating characteristics of the target device; based on the static operating characteristics of the target device, retrieve a set of matching devices that are related to the target device from the pre-constructed data sample set.
[0022] The target equipment can be, for example, a three-phase motor driven by power frequency or variable frequency, and the equipment it drives. The static operating characteristics of the target equipment can be used to describe information that uniquely identifies the equipment, such as equipment model, equipment category, energy efficiency rating, rated power, etc.
[0023] Data sample sets can be generated by collecting on-site operating data from multiple devices. Each sample may include, but is not limited to: operating current characteristics: three-phase current I_a / I_b / I_c or I_rms, load current ratio r_I=I_rms / I_rated, fluctuation / imbalance characteristics, etc.; operating voltage characteristics: measured line voltage, rated voltage, long-term statistical voltage, or voltage characteristics at the corresponding frequency in a frequency conversion scenario, etc.; measured power factor cosφ_meas (from sample motors with power measurement capabilities); motor static / brand and category characteristics: model, energy efficiency rating, rated power P_rated, rated voltage / current, rated power factor cosφ_rated, number of pole pairs / synchronous speed, manufacturer or series, control method (power frequency / frequency conversion), industry / load type, etc.
[0024] In some embodiments, the static operating characteristics of the target device are used to describe the model of the target device. Based on the static operating characteristics of the target device, a set of matching devices associated with the target device is retrieved from a pre-built data sample set, including: retrieving multiple first candidate devices associated with the target device from the pre-built data sample set based on the model of the target device; if the number of first candidate devices meets a preset requirement, constructing a set of matching devices associated with the target device based on the multiple first candidate devices; if the number of first candidate devices does not meet the preset requirement, retrieving multiple second candidate devices associated with the target device from the pre-built data sample set according to a preset field of the target device; and constructing a set of matching devices associated with the target device based on the multiple first candidate devices and the multiple second candidate devices.
[0025] The preset fields include at least one of the following: model family, energy efficiency rating, power range, number of poles, voltage rating, control method, and load type. First, other devices with the same model as the target device can be matched from the data sample set. If the sample is insufficient, similarity measurements can be performed using methods such as rule filtering, weighted distance, clustering, or kNN based on fields such as model family / energy efficiency rating / power range / number of poles / voltage rating / control method / load type to select a set of matching devices Ω_sim that are related to the target device from the data sample set. This multi-level device matching strategy ensures the accuracy of device matching.
[0026] S120. Based on the set of matching devices that are related to the target device, construct a power factor inference model corresponding to the target device.
[0027] Among them, the power factor inference model is used to output the corresponding estimated power factor based on the real-time operating characteristics.
[0028] In some embodiments, a power factor inference model corresponding to the target device is constructed based on a set of matching devices that are associated with the target device. This includes: fitting the power factor curve / piecewise function of each device in the set of matching devices to generate a power factor inference model corresponding to the target device; or, using the historical operating characteristics of each device in the set of matching devices to perform regression prediction on a machine learning model to obtain a power factor inference model corresponding to the target device.
[0029] This involves fitting a regular curve / piecewise function of cosφ = f(r_I, f_out, …) to similar equipment samples to construct an empirical / curve fitting model, thus obtaining a power factor inference model. Alternatively, the model can input features [r_I, operating voltage characteristics, I fluctuation characteristics, brand characteristics, control method, load type, frequency f_out (if any)] and output cosφ_pred for model regression prediction. Another approach is to use a hybrid model, with empirical patterns as the framework and machine learning to correct for bias terms. Thus, through the flexible combination of various modeling methods, the power factor inference model can adapt to application scenarios with varying levels of data richness, improving the accuracy and robustness of power factor inference.
[0030] In some embodiments, the method further includes: collecting historical operating characteristics of the target device; inputting the historical operating characteristics into the power factor inference model to obtain the predicted active power; and adjusting the model parameters of the power factor inference model based on the deviation between the historical measured active power and the predicted active power of the target device, so that the prediction accuracy of the power factor inference model meets the preset convergence condition.
[0031] The model parameters can be adjusted using optimization strategies such as gradient descent, Bayesian optimization, or genetic algorithms, with the objective function being to minimize the mean square error or mean absolute percentage error between the predicted active power and the historical measured active power. When the decrease in verification error is less than a preset threshold or the maximum number of iterations is reached within several consecutive iterations, the model parameters are considered to have converged, and the current parameters are fixed as the final configuration of the power factor inference model.
[0032] Furthermore, the output of the power factor inference model can be dynamically corrected by incorporating the real-time operating conditions of the target equipment. For example, when the target equipment is detected to be in a startup transient or load change phase, a transient compensation coefficient is introduced to smooth the predicted active power, suppressing prediction distortion caused by drastic fluctuations in electrical quantities.
[0033] S130. Obtain the field operation data of the target equipment and extract the real-time operation characteristics of the target equipment from the field operation data.
[0034] The real-time operating characteristics include: operating current characteristics, or operating current characteristics and operating voltage characteristics; when the target equipment is in a frequency conversion scenario, the real-time operating characteristics also include operating frequency characteristics and / or operating speed characteristics.
[0035] Operating current characteristics may include three-phase current, RMS current, load current ratio, current fluctuation characteristics, and / or current imbalance characteristics; operating voltage characteristics may include measured line voltage, rated voltage, long-term statistical voltage, or voltage characteristics at the corresponding frequency in a frequency conversion scenario; operating frequency characteristics may include the inverter output frequency; and operating speed characteristics may include measured speed or estimated speed. It should be noted that the real-time operating characteristics of the target equipment may also include auxiliary characteristics such as operating condition switching quantities, start / stop status, and control mode.
[0036] S140. Input the real-time operating characteristics of the target device into the power factor inference model, so as to infer the estimated power factor of the target device based on the real-time operating characteristics of the target device through the power factor inference model.
[0037] The power factor inference model may include an input layer, a hidden layer, and an output layer. The input layer receives operating current characteristics, or operating current and operating voltage characteristics, or operating current, operating voltage, operating frequency, and / or operating speed characteristics, and normalizes the input characteristics. The hidden layer contains multiple fully connected sub-layers, which are nonlinearly mapped using activation functions to capture the complex nonlinear relationship between the input characteristics and the power factor. The output layer outputs the estimated power factor value and performs inverse normalization on the output result to obtain the power factor value in actual dimensions.
[0038] In some embodiments, the real-time operating characteristics of the target device are input into the power factor inference model to calculate the estimated power factor of the target device based on the real-time operating characteristics of the target device. This includes: inputting the operating current characteristics of the target device into the power factor inference model; or, inputting the operating current characteristics and operating voltage characteristics of the target device into the power factor inference model; or, inputting the operating current characteristics, operating voltage characteristics, operating frequency characteristics, and / or operating speed characteristics of the target device into the power factor inference model to calculate the estimated power factor of the target device based on the input real-time operating characteristics.
[0039] The power factor inference model is based on a pre-trained parameter mapping relationship. It takes the operating current feature in the real-time operating characteristics as the basic input variable, and can further combine the operating voltage feature, operating frequency feature and / or operating speed feature. Through the nonlinear transformation of a multi-layer neural network, it calculates and outputs the estimated power factor value of the target equipment under the current operating conditions.
[0040] S150. Obtain the operating voltage characteristics of the target device, and calculate the active power of the target device based on the operating voltage characteristics, estimated power factor, and operating current characteristics of the target device.
[0041] For the general form of three-phase power frequency / frequency conversion, the active power P_pred of the target equipment can be calculated according to the following formula (1). For frequency conversion scenarios, U_eff at the corresponding frequency can be used in the power formula (1).
[0042] P_pred = √3 U_eff I_rms cosφ_pred(1) In formula (1), U_eff represents the operating voltage characteristic, which can be the measured line voltage; if it cannot be measured, the rated voltage or long-term statistical voltage is used, and this uncertainty is reflected in the model confidence level Conf. I_rms represents the operating current characteristic; cosφ_pred represents the estimated power factor.
[0043] This embodiment can be applied to rapid inspection / rapid inspection boxes / mobile measurement: power and energy efficiency indicators can be quickly obtained by simply clamping the CT to collect current; low-cost digital transformation of old sites: current points are set up first, and power points are gradually added later; unified diagnosis of large-scale equipment: in areas with a large number of motors, such as steel and mining plants, energy efficiency profiles can be formed through current data; variable frequency speed control conditions: frequency / speed is incorporated as a feature into the inference to improve the accuracy of power estimation in the speed control section. After obtaining P_pred and Conf (output by the power factor inference model), it can be used for energy efficiency diagnosis, efficiency calculation, energy saving assessment, anomaly identification, and inspection report generation.
[0044] In some embodiments, obtaining the operating voltage characteristics corresponding to the target device includes: if the target device is in a power frequency scenario, then performing a voltage measurement on the target device; if the current line voltage of the target device is measured, then determining the current line voltage of the target device as the corresponding operating voltage characteristic; if the current line voltage of the target device cannot be measured, then determining the rated voltage or long-term statistical voltage of the target device as the corresponding operating voltage characteristic. If the target device is in a frequency conversion scenario, then determining the line voltage at the corresponding frequency of the target device as the corresponding operating voltage characteristic, or determining the rated voltage or long-term statistical voltage at the corresponding frequency of the target device as the corresponding operating voltage characteristic.
[0045] The real-time line voltage value at the target equipment terminal can be obtained through contact or non-contact sensing methods using voltage transformers or portable voltage measurement units. Considering that live-line safety distance restrictions, lack of reserved measurement terminals in older distribution cabinets, or the inability to open cabinets during rapid inspections may render actual voltage measurement impractical, the rated voltage value of the target equipment can be extracted from its historical operating records, or the average operating voltage of the target equipment over a past statistical period can be retrieved as a substitute. This facilitates rapid determination of the target equipment's operating voltage characteristics and improves power calculation efficiency.
[0046] In this embodiment, the static operating characteristics of the target device are obtained; based on the static operating characteristics of the target device, a set of matching devices with a relationship with the target device is retrieved from a pre-constructed data sample set; based on the set of matching devices with a relationship with the target device, a power factor inference model corresponding to the target device is constructed; the power factor inference model is used to output the corresponding estimated power factor based on the real-time operating characteristics; the field operating data of the target device is obtained, and the real-time operating characteristics corresponding to the target device are extracted from the field operating data; wherein, the real-time operating characteristics include: operating current characteristics, or, operating current characteristics and operating voltage characteristics; when the target device is in a frequency conversion scenario, the real-time operating characteristics also include operating frequency characteristics and / or operating speed characteristics; the real-time operating characteristics corresponding to the target device are input into the power factor inference model, so as to infer the estimated power factor corresponding to the target device based on the real-time operating characteristics corresponding to the target device through the power factor inference model; the operating voltage characteristics corresponding to the target device are obtained, and the active power of the target device is calculated based on the operating voltage characteristics, the estimated power factor, and the operating current characteristics corresponding to the target device. In this way, by combining the operating voltage characteristics and operating current characteristics to complete the active power calculation, a complete functional chain from current measurement to power output is realized. The calculation process does not require expensive equipment and can effectively calculate the active power of the equipment on site.
[0047] In summary, this embodiment does not use the fixed rated cosφ_rated when calculating the power factor, but instead uses the actual cosφ-current pattern of the same model or type of motor from history for transfer; it models the dynamic changes of cosφ through operating characteristics such as r_I, making the power estimation under medium and low loads significantly more accurate; even in cases of insufficient samples or unmeasurable voltage, P_pred can still be provided, along with Conf for the application layer to perform risk control. This effectively improves the credibility of energy efficiency diagnosis and energy-saving assessment, significantly reducing the deviation of power estimation under medium and low loads; key calculations can be completed using only current, shortening the deployment / diagnosis cycle and improving the speed of data acquisition and diagnosis; the more similar motor data there is, the more accurate the model becomes, forming a continuously enhancing scale effect and strong cross-site transfer capability; through confidence output, it avoids unusable results that are "black box" and unexplainable, ensuring engineering control.
[0048] Figure 2 This embodiment provides a schematic diagram of a device for calculating active power using current. The device for calculating active power using current may include: The acquisition module 210 is used to acquire the static operating characteristics of the target device.
[0049] The retrieval module 220 is used to retrieve a set of matching devices that are associated with the target device from a pre-built data sample set based on the static operating characteristics of the target device.
[0050] The construction module 230 is used to construct a power factor inference model corresponding to the target device based on a set of matching devices that are associated with the target device; the power factor inference model is used to output the corresponding estimated power factor based on real-time operating characteristics.
[0051] The extraction module 240 is used to acquire the field operation data of the target equipment and extract the real-time operation features corresponding to the target equipment from the field operation data; wherein, the real-time operation features include: operating current features, or operating current features and operating voltage features; when the target equipment is in a frequency conversion scenario, the real-time operation features also include operating frequency features and / or operating speed features.
[0052] The estimation module 250 is used to input the real-time operating characteristics of the target device into the power factor inference model, so as to estimate the power factor of the target device based on the real-time operating characteristics of the target device through the power factor inference model.
[0053] The calculation module 260 is used to obtain the operating voltage characteristics of the target device and calculate the active power of the target device based on the operating voltage characteristics, estimated power factor and operating current characteristics of the target device.
[0054] In some embodiments, the static operating characteristics of the target device are used to describe the model to which the target device belongs.
[0055] The retrieval module 220 is specifically used for: Based on the model of the target device, multiple first candidate devices that are related to the target device are retrieved from a pre-built data sample set. If the number of first candidate devices meets the preset requirement, a set of matching devices that are related to the target device is constructed based on the multiple first candidate devices. If the number of first candidate devices does not meet the preset requirement, multiple second candidate devices that are related to the target device are retrieved from the pre-built data sample set according to the preset fields of the target device. A set of matching devices that are related to the target device is constructed based on the multiple first candidate devices and the multiple second candidate devices. The preset fields include at least one of the following: model family, energy efficiency rating, power range, number of poles, voltage rating, control method, and load type.
[0056] In some embodiments, the calculation module 250 is specifically used for: Input the operating current characteristics of the target device into the power factor inference model; or, input the operating current characteristics and operating voltage characteristics of the target device into the power factor inference model; or, input the operating current characteristics, operating frequency characteristics, and / or operating speed characteristics of the target device into the power factor inference model; or, input the operating current characteristics, operating voltage characteristics, operating frequency characteristics, and / or operating speed characteristics of the target device into the power factor inference model, so as to infer the estimated power factor of the target device based on the input real-time operating characteristics through the power factor inference model.
[0057] In some embodiments, the calculation module 260 is specifically used for: If the target device is in a power frequency environment, the voltage of the target device is measured. If the current line voltage of the target device is measured, the current line voltage of the target device is determined as the corresponding operating voltage characteristic. If the current line voltage of the target device cannot be measured, the rated voltage or long-term statistical voltage of the target device is determined as the corresponding operating voltage characteristic.
[0058] In some embodiments, the calculation module 260 is specifically used for: If the target equipment is in a frequency conversion scenario, the line voltage at the corresponding frequency of the target equipment is determined as the corresponding operating voltage characteristic, or the rated voltage or long-term statistical voltage at the corresponding frequency of the target equipment is determined as the corresponding operating voltage characteristic.
[0059] In some embodiments, the construction module 230 is specifically used for: The power factor curve / piecewise function of each device in the matching device set is fitted to generate the power factor inference model corresponding to the target device; or, the historical operating characteristics of each device in the matching device set are used to perform regression prediction on the machine learning model to obtain the power factor inference model corresponding to the target device.
[0060] In some embodiments, an adjustment module is also included.
[0061] The adjustment module is used to collect historical operating characteristics of the target equipment; input the historical operating characteristics into the power factor inference model to obtain the predicted active power; and adjust the model parameters of the power factor inference model according to the deviation between the historical measured active power and the predicted active power of the target equipment so that the prediction accuracy of the power factor inference model meets the preset convergence conditions.
[0062] The apparatus for calculating active power of a device using current provided in this disclosure can execute the above-described method embodiments. For its specific implementation principle and technical effects, please refer to the above-described method embodiments, which will not be repeated here.
[0063] This application also provides a computer device. Please refer to the following for details. Figure 3 , Figure 3 This is a basic structural block diagram of the computer device in this embodiment.
[0064] The computer device includes a memory 310 and a processor 320 that are interconnected via a system bus. It should be noted that only a computer device with memory 310 and processor 320 is shown in the figure; however, it should be understood that it is not required to implement all the components shown, and more or fewer components may be implemented alternatively. Those skilled in the art will understand that the computer device described herein is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.
[0065] Computer devices can include desktop computers, laptops, handheld computers, and cloud servers. These devices allow for human-computer interaction with users through keyboards, mice, remote controls, touchpads, or voice-activated devices.
[0066] The memory 310 includes at least one type of readable storage medium, including non-volatile memory or volatile memory, such as flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, optical disk, etc. RAM may include static RAM or dynamic RAM. In some embodiments, the memory 310 may be an internal storage unit of a computer device, such as the hard disk or memory of the computer device. In other embodiments, the memory 310 may also be an external storage device of the computer device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, or flash card equipped on the computer device. Of course, the memory 310 may include both internal storage units and external storage devices of the computer device. In this embodiment, the memory 310 is typically used to store the operating system and various application software installed on the computer device, such as the program code of the method described above. In addition, the memory 310 can also be used to temporarily store various types of data that have been output or will be output.
[0067] Processor 320 is typically used to perform overall operations of a computer device. In this embodiment, memory 310 is used to store program code or instructions, including computer operation instructions, and processor 320 is used to execute the program code or instructions stored in memory 310 or process data, such as program code that runs the methods described above.
[0068] In this article, the bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. This bus system can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.
[0069] Another embodiment of this application also provides a computer-readable medium, which may be a computer-readable signal medium or a computer-readable medium. A processor in a computer reads computer-readable program code stored in the computer-readable medium, enabling the processor to execute the functional actions specified in each step or combination of steps in the above method; and to generate means for implementing the functional actions specified in each block or combination of blocks in the block diagram.
[0070] Computer-readable media include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared memory or semiconductor systems, devices or apparatuses, or any suitable combination thereof, wherein the memory is used to store program code or instructions, the program code including computer operation instructions, and the processor is used to execute the program code or instructions of the above-described methods stored in the memory.
[0071] The definitions of memory and processor can be found in the description of the foregoing computer device embodiments, and will not be repeated here.
[0072] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.
[0073] In the various embodiments of this application, the functional units or modules can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.
[0074] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0075] In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" as described in this application does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. This application can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims listing several means, several units of these means may be embodied by the same item of hardware. The use of "first," "second," and "third," etc., does not indicate any order and these words should be interpreted as names. Unless otherwise specified, the steps in the above embodiments should not be construed as limiting the order of execution.
[0076] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
Claims
1. A method for calculating the active power of a device using current, characterized in that, include: Obtain the static operating characteristics of the target device; Based on the static operating characteristics of the target device, a set of matching devices that are associated with the target device is retrieved from a pre-constructed data sample set; Based on a set of matching devices that are associated with the target device, a power factor inference model corresponding to the target device is constructed; the power factor inference model is used to output the corresponding estimated power factor based on real-time operating characteristics; Acquire the field operation data of the target device, and extract the real-time operation features corresponding to the target device from the field operation data; wherein, the real-time operation features include: operating current features, or, operating current features and operating voltage features; when the target device is in a frequency conversion scenario, the real-time operation features also include operating frequency features and / or operating speed features; The real-time operating characteristics of the target device are input into the power factor inference model so that the estimated power factor of the target device can be calculated based on the real-time operating characteristics of the target device through the power factor inference model. Obtain the operating voltage characteristics corresponding to the target device, and calculate the active power of the target device based on the operating voltage characteristics, the estimated power factor, and the operating current characteristics.
2. The method according to claim 1, characterized in that, The static operating characteristics of the target device are used to describe the model of the target device; based on the static operating characteristics of the target device, a set of matching devices that are associated with the target device is retrieved from a pre-constructed data sample set, including: Based on the model of the target device, multiple first candidate devices that are associated with the target device are retrieved from a pre-built data sample set; If the number of the first candidate devices meets the preset quantity requirement, then a set of matching devices that are associated with the target device is constructed based on the multiple first candidate devices; If the number of the first candidate devices does not meet the preset quantity requirement, then according to the preset fields of the target device, a number of second candidate devices that are associated with the target device are retrieved from the pre-constructed data sample set; a set of matching devices that are associated with the target device is constructed based on the number of first candidate devices and the number of second candidate devices; the preset fields include at least one of the following: model family, energy efficiency level, power range, number of poles, voltage level, control method, and load type.
3. The method according to claim 1, characterized in that, The real-time operating characteristics of the target device are input into the power factor inference model to calculate the estimated power factor of the target device based on the real-time operating characteristics of the target device, including: The operating current characteristics corresponding to the target device are input into the power factor inference model; or, the operating current characteristics and operating voltage characteristics corresponding to the target device are input into the power factor inference model; or, the operating current characteristics, operating frequency characteristics, and / or operating speed characteristics corresponding to the target device are input into the power factor inference model; or, the operating current characteristics, operating voltage characteristics, operating frequency characteristics, and / or operating speed characteristics corresponding to the target device are input into the power factor inference model, so as to infer the estimated power factor corresponding to the target device based on the input real-time operating characteristics through the power factor inference model.
4. The method according to claim 1, characterized in that, Obtaining the operating voltage characteristics corresponding to the target device includes: If the target device is in a power frequency environment, then the voltage of the target device shall be measured. If the current line voltage of the target device is measured, then the current line voltage of the target device is determined as the corresponding operating voltage characteristic; if the current line voltage of the target device cannot be measured, then the rated voltage or long-term statistical voltage of the target device is determined as the corresponding operating voltage characteristic.
5. The method according to claim 1, characterized in that, Obtaining the operating voltage characteristics corresponding to the target device includes: If the target device is in a frequency conversion scenario, the line voltage at the corresponding frequency of the target device is determined as the corresponding operating voltage characteristic, or the rated voltage or long-term statistical voltage at the corresponding frequency of the target device is determined as the corresponding operating voltage characteristic.
6. The method according to claim 1, characterized in that, Based on a set of matching devices associated with the target device, a power factor inference model corresponding to the target device is constructed, including: Fit the power factor curve / piecewise function of each device in the matching device set to generate the power factor inference model corresponding to the target device; Alternatively, the historical operating characteristics of each device in the matching device set can be used to perform regression prediction on the machine learning model to obtain the power factor inference model corresponding to the target device.
7. The method according to claim 1, characterized in that, Also includes: Collect historical operating characteristics of the target equipment; input the historical operating characteristics into the power factor inference model to obtain the predicted active power; Based on the deviation between the historical measured active power of the target device and the predicted active power, the model parameters of the power factor inference model are adjusted so that the prediction accuracy of the power factor inference model meets the preset convergence condition.
8. A device for calculating active power using current, characterized in that, include: The acquisition module is used to acquire the static operating characteristics of the target device; The retrieval module is used to retrieve a set of matching devices that are associated with the target device from a pre-constructed data sample set based on the static operating characteristics of the target device. The construction module is used to construct a power factor inference model corresponding to the target device based on a set of matching devices that are associated with the target device; the power factor inference model is used to output the corresponding estimated power factor based on real-time operating characteristics; An extraction module is used to acquire the field operation data of the target device and extract the real-time operation features corresponding to the target device from the field operation data; wherein, the real-time operation features include: operating current features, or, operating current features and operating voltage features; when the target device is in a frequency conversion scenario, the real-time operation features also include operating frequency features and / or operating speed features; The estimation module is used to input the real-time operating characteristics of the target device into the power factor inference model, so as to estimate the power factor of the target device based on the real-time operating characteristics of the target device through the power factor inference model; The calculation module is used to obtain the operating voltage characteristics corresponding to the target device, and calculate the active power of the target device based on the operating voltage characteristics corresponding to the target device, the estimated power factor, and the operating current characteristics.
9. A computer device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method for calculating the active power of a device by means of current as described in any one of claims 1 to 7.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When a computer program is executed by a processor, it implements the method for calculating the active power of a device by means of current as described in any one of claims 1 to 7.