Energy consumption data fusion management processing method and system based on intelligent lighting equipment

Abstract

The invention provides an energy consumption data fusion management processing method and system based on intelligent lighting equipment. The method comprises the following steps: acquiring reported energy consumption power of the intelligent lighting equipment; performing power calibration processing on the reported energy consumption power to obtain energy consumption calibration power; performing energy consumption fusion processing on the energy consumption calibration power to obtain a fused energy consumption value; performing fusion reliable processing on the fusion energy consumption value and a preset energy consumption value to obtain a fusion rollback difference; and sending a rollback loss signal to an energy consumption platform of the intelligent lighting equipment according to the fused rollback difference so as to adjust an output mode of energy consumption data fusion of all the intelligent lighting equipment. After the reported energy consumption power is collected, the current uploaded lighting power of the intelligent lighting equipment is determined, and finally the energy consumption rollback trigger state of each intelligent lighting equipment is adjusted according to the difference value, so that the output mode of energy consumption data fusion of each intelligent lighting equipment is optimized, and the energy consumption data fusion efficiency is improved. Therefore, the traceability of the energy consumption fusion data is improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of energy consumption data processing, and particularly to an energy consumption data fusion management and processing method and system based on intelligent lighting devices. Background Art

[0002] With the popularization of Internet of Things technology, the lighting industry is also undergoing informatization upgrading. At present, for the collection of energy consumption data of lighting devices in the lighting industry, the expression, transmission, calculation, etc. of energy consumption data are all different. Therefore, it is very difficult for any enterprise to statistically calculate the lighting energy consumption data within the scope of a park, company, etc. At present, the existing fusion solutions for energy consumption data of multi-vendor intelligent lighting devices have the following disadvantages: 1. The protocols of each vendor are privatized, and the system needs to be customized and developed with adaptation codes for each device; 2. The differences in energy consumption calculation algorithms lead to incomparable data, and the system cannot uniformly count; 3. When adding devices of new vendors, the system needs to be redeployed, with poor scalability. The adaptation complexity caused by the privatization of multi-vendor protocols. Different vendors' devices use privatized communication protocols and data formats (such as non-standard JSON structures, binary encodings, etc.), and the system needs to develop adaptation codes separately for each vendor, resulting in high development costs, long cycles, and inability to be reused. The incomparability of data caused by inconsistent energy consumption calculation logics. The energy consumption calculation algorithms of each vendor vary significantly, and the direct calculation results cannot be compared horizontally, making it difficult for the platform to accurately statistically analyze the global energy consumption. The operation and maintenance bottleneck of insufficient system scalability. When adding devices of new vendors, the system code needs to be modified and the system needs to be shut down for deployment, and the adaptation ability cannot be dynamically expanded, making it difficult to meet flexible access scenarios.

[0003] Moreover, there is a risk of lack of abnormal data processing mechanism. Traditional solutions lack cross-vendor data consistency verification and abnormal rollback mechanisms. When there are logical conflicts in the fusion data, it is easy to cause distorted statistical results and inability to trace and repair. Summary of the Invention

[0004] The purpose of the present disclosure is to overcome the deficiencies in the prior art and provide an energy consumption data fusion management and processing method and system based on intelligent lighting devices, which can improve the energy consumption fusion efficiency of multiple lighting devices and the traceability of energy consumption fusion data.

[0005] The purpose of the present disclosure is achieved through the following technical solutions: An energy consumption data fusion management and processing method based on intelligent lighting devices, the method comprising: Obtaining the reported energy consumption power of the intelligent lighting device; Performing power calibration processing on the reported energy consumption power to obtain calibrated energy consumption power; Performing energy consumption fusion processing on the calibrated energy consumption power to obtain a fused energy consumption value; Perform reliable processing on the fused energy consumption value and a preset energy consumption value to obtain a fused rollback difference quantity; Send a rollback loss signal to the energy consumption platform of the intelligent lighting device according to the fused rollback difference quantity to adjust the output mode of the energy consumption data fusion for all intelligent lighting devices.

[0006] In one embodiment, the power calibration process for the reported energy consumption power to obtain a calibrated energy consumption power includes: performing a dynamic calibration operation on the reported energy consumption power to obtain a dynamically calibrated power.

[0007] In one embodiment, after performing the dynamic calibration operation on the reported energy consumption power, it further includes: performing a time offset compensation operation on the dynamically calibrated power to obtain a calibrated energy consumption power; the calibrated energy consumption power satisfies the following formula: is the reported energy consumption power; is the calibrated energy consumption power; is a dynamic calibration factor for the dynamic calibration operation; is a time offset compensation factor for the time offset compensation operation; is the sampling interval.

[0008] where is the standard power reference value, for example, the laboratory calibration value; T is the calibration period; λ is the attenuation coefficient for reflecting the influence of device aging; t i is the current timestamp; is the average power within the period; Δt is the sampling interval.

[0009] In one embodiment, the energy consumption fusion process for the calibrated energy consumption power to obtain a fused energy consumption value includes: performing a temperature compensation operation on the calibrated energy consumption power to obtain a temperature-compensated fused energy consumption.

[0010] In one embodiment, after performing the temperature compensation operation on the calibrated energy consumption power, it further includes: performing a humidity compensation operation on the temperature-compensated fused energy consumption to obtain a humidity-compensated fused energy consumption.

[0011] In one embodiment, after performing the humidity compensation operation on the temperature-compensated fused energy consumption, it further includes: performing a light compensation operation on the humidity-compensated fused energy consumption to obtain a fused energy consumption value, The fused energy consumption value satisfies the following formula: is the power for energy consumption calibration; is the fused energy consumption value; is the environmental compensation factor; T env is the current ambient temperature; T 0 is the reference temperature; H env is the current ambient humidity; H 0 is the reference humidity; L env is the current ambient light intensity; L max is the maximum light intensity; k T , k H , k L are the compensation coefficients for temperature, humidity, and light respectively, which are dynamically optimized by device characteristics and machine learning models. For example, partial derivatives are calculated through historical data regression analysis.

[0012] k T satisfies the following formula: k H satisfies the following formula: k L satisfies the following formula: .

[0013] In one embodiment, the reliable processing of fusing the fused energy consumption value with a preset energy consumption value includes: obtaining the relative difference modulus between the fused energy consumption value and the preset energy consumption value; and sending a rollback enable signal to the energy consumption platform of intelligent lighting devices according to the fused rollback difference amount to adjust the output mode of the energy consumption data fusion for all intelligent lighting devices, including: detecting whether the fused rollback difference amount is greater than a preset rollback difference amount; when the fused rollback difference amount is greater than the preset rollback difference amount, sending a rollback enable signal to the energy consumption platform of intelligent lighting devices to trigger a rollback logic and exclude the fused energy consumption value.

[0014] An energy consumption data fusion management and processing system based on intelligent lighting devices, comprising: a lighting energy consumption acquisition module, a fusion energy consumption processing module, and a rollback adjustment module; the lighting energy consumption acquisition module is used to obtain the reported energy consumption power of the intelligent lighting devices; the fusion energy consumption processing module is used to perform power calibration processing on the reported energy consumption power to obtain a calibrated energy consumption power; perform energy consumption fusion processing on the calibrated energy consumption power to obtain a fused energy consumption value; perform fusion reliability processing on the fused energy consumption value and a preset energy consumption value to obtain a fusion rollback difference; the rollback adjustment module is used to send a rollback disable signal to the intelligent lighting device energy consumption platform according to the fusion rollback difference to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices.

[0015] A computer device, comprising a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented: Obtain the reported energy consumption power of the intelligent lighting devices; Perform power calibration processing on the reported energy consumption power to obtain a calibrated energy consumption power; Perform energy consumption fusion processing on the calibrated energy consumption power to obtain a fused energy consumption value; Perform fusion reliability processing on the fused energy consumption value and a preset energy consumption value to obtain a fusion rollback difference; Send a rollback disable signal to the intelligent lighting device energy consumption platform according to the fusion rollback difference to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices.

[0016] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Obtain the reported energy consumption power of the intelligent lighting devices; Perform power calibration processing on the reported energy consumption power to obtain a calibrated energy consumption power; Perform energy consumption fusion processing on the calibrated energy consumption power to obtain a fused energy consumption value; Perform fusion reliability processing on the fused energy consumption value and a preset energy consumption value to obtain a fusion rollback difference; Send a rollback disable signal to the intelligent lighting device energy consumption platform according to the fusion rollback difference to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices.

[0017] Compared with the prior art, the present disclosure has at least the following advantages: After collecting the reported energy consumption power, determine the current uploaded lighting power of the intelligent lighting device, and then calibrate and fuse the reported energy consumption power, so that the fusion of the lighting energy consumption of each intelligent lighting device is more accurate, so as to make the lighting fusion energy consumption of each intelligent lighting device more in line with the requirements, thereby improving the energy consumption fusion efficiency of multiple lighting devices. Then, compare the fused energy consumption value with the standard fused energy consumption to facilitate determining the difference between the current fused energy consumption of each intelligent lighting device and the specified fused energy consumption. Finally, according to the above difference value, adjust the energy consumption rollback trigger state of each intelligent lighting device to facilitate optimizing the output mode of the energy consumption data fusion of each intelligent lighting device, thereby improving the traceability of the energy consumption fusion data. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present disclosure, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0019] Figure 1 FIG. [FIG. NUMBER] is a flowchart of a method for managing and processing energy consumption data fusion based on intelligent lighting devices in an embodiment; Figure 2 FIG. [FIG. NUMBER] is a flowchart of a method for managing and processing energy consumption data fusion based on intelligent lighting devices in another embodiment; Figure 3 FIG. [FIG. NUMBER] is a flowchart of a method for managing and processing energy consumption data fusion based on intelligent lighting devices in yet another embodiment; Figure 4 FIG. [FIG. NUMBER] is an internal structure diagram of a computer device in an embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] To facilitate the understanding of the present disclosure, the present disclosure will be described more comprehensively below with reference to the relevant drawings. The preferred embodiments of the present disclosure are shown in the drawings. However, the present disclosure can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present disclosure more thorough and comprehensive.

[0021] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration and do not represent the only implementation.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this disclosure belongs. The terms used in the description of this disclosure herein are for the purpose of describing specific embodiments only and are not intended to limit this disclosure. The term "and / or" as used herein includes any and all combinations of one or more of the related listed items.

[0023] This disclosure relates to a method for energy consumption data fusion management and processing based on intelligent lighting devices. In one embodiment, the method for energy consumption data fusion management and processing based on intelligent lighting devices includes obtaining the reported energy consumption power of the intelligent lighting devices; performing power calibration processing on the reported energy consumption power to obtain calibrated energy consumption power; performing energy consumption fusion processing on the calibrated energy consumption power to obtain a fused energy consumption value; performing fusion reliability processing on the fused energy consumption value and a preset energy consumption value to obtain a fusion rollback difference; and sending a rollback failure signal to the energy consumption platform of the intelligent lighting devices according to the fusion rollback difference to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices. After collecting the reported energy consumption power, the current uploaded lighting power of the intelligent lighting devices is determined, and then the reported energy consumption power is calibrated and fused, so that the fusion between the lighting energy consumptions of each intelligent lighting device is more accurate, so as to obtain a lighting fusion energy consumption that better meets the requirements for each intelligent lighting device, thereby improving the energy consumption fusion efficiency of multiple lighting devices. Then, the fused energy consumption value is compared with the standard fused energy consumption to facilitate determining the difference between the current fused energy consumption of each intelligent lighting device and the specified fused energy consumption. Finally, according to the above difference value, the energy consumption rollback trigger state of each intelligent lighting device is adjusted to facilitate optimizing the output mode of the energy consumption data fusion of each intelligent lighting device, thereby improving the traceability of the energy consumption fusion data.

[0024] Please refer to Figure 1 , which is a flowchart of the method for energy consumption data fusion management and processing based on intelligent lighting devices according to an embodiment of this disclosure. The method for energy consumption data fusion management and processing based on intelligent lighting devices includes some or all of the following steps.

[0025] S100: Obtain the reported energy consumption power of the intelligent lighting devices.

[0026] In this embodiment, the reported energy consumption power is the energy consumption data uploaded by the intelligent lighting devices, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting devices, and also the reported energy consumption power corresponds to the current operating power of the intelligent lighting devices. By means of the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting devices, so as to determine the current energy consumption situation of each intelligent lighting device.

[0027] S200: Perform power calibration processing on the reported energy consumption power to obtain calibrated energy consumption power.

[0028] In this embodiment, the reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, which also means that the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By using the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration processing of the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so that the collection of the reported energy consumption power is more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device.

[0029] S300: Perform energy consumption fusion processing on the calibrated energy consumption power to obtain a fused energy consumption value.

[0030] In this embodiment, the calibrated energy consumption power is obtained after power calibration processing, that is, the calibrated energy consumption power is obtained based on the calibration of the reported energy consumption power. The reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, which also means that the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By using the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration processing of the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so that the collection of the reported energy consumption power is more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. Through the energy consumption fusion processing of the calibrated energy consumption power, the calibrated accurate energy consumption data of each intelligent lighting device are fused, making the energy consumption fusion of each intelligent lighting device more efficient, so as to improve the efficiency of the energy consumption data fusion of intelligent lighting devices from multiple manufacturers.

[0031] S400: Perform fusion reliability processing on the fused energy consumption value and a preset energy consumption value to obtain a fused rollback difference.

[0032] In this embodiment, the fused energy consumption value is the fused data obtained after calibrating each of the reported energy consumption powers. The energy consumption calibrated power is obtained after power calibration processing, that is, the energy consumption calibrated power is obtained by calibrating the reported energy consumption power. The reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, which also means that the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By using the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration processing of the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so as to make the acquisition of the reported energy consumption power more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. Through the energy consumption fusion processing of the energy consumption calibrated power, the accurate energy consumption data calibrated by each intelligent lighting device is fused, making the energy consumption fusion of each intelligent lighting device more efficient, so as to improve the efficiency of the energy consumption data fusion of intelligent lighting devices from multiple manufacturers. The preset energy consumption value is the standard fused energy consumption of each intelligent lighting device. By performing reliable fusion processing on the fused energy consumption value and the preset energy consumption value, it is convenient to determine the difference degree between the fused energy consumption of each intelligent lighting device and the standard fused energy consumption.

[0033] S500: Send a rollback loss signal to the intelligent lighting device energy consumption platform according to the fused rollback difference amount to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices.

[0034] In this embodiment, the fusion rollback difference is obtained based on the fusion energy consumption value and the preset energy consumption value. The fusion energy consumption value is the fused data after calibrating each reported energy consumption power. The energy consumption calibration power is obtained after power calibration processing, that is, the energy consumption calibration power is obtained by calibrating the reported energy consumption power. The reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, and also the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By sampling the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration processing of the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so as to make the collection of the reported energy consumption power more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. Through the energy consumption fusion processing of the energy consumption calibration power, the calibrated accurate energy consumption data of each intelligent lighting device are fused, so that the energy consumption fusion of each intelligent lighting device is more efficient, so as to improve the efficiency of the energy consumption data fusion of intelligent lighting devices of multiple manufacturers. The preset energy consumption value is the standard fusion energy consumption of each intelligent lighting device. By performing reliable fusion processing on the fusion energy consumption value and the preset energy consumption value, it is convenient to determine the difference degree between the fusion energy consumption of each intelligent lighting device and the standard fusion energy consumption. After determining the fusion rollback difference, the fusion energy consumption deviation situation of each intelligent lighting device is determined, which is convenient to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices, thereby improving the traceability of the energy consumption fusion data.

[0035] In this embodiment, after collecting the reported energy consumption power, the current uploaded lighting power of the intelligent lighting device is determined, and then the reported energy consumption power is calibrated and fused, so that the fusion between the lighting energy consumptions of each intelligent lighting device is more accurate, so as to make the lighting fusion energy consumption of each intelligent lighting device more in line with the requirements, thereby improving the energy consumption fusion efficiency of multiple lighting devices. Then, the fusion energy consumption value is compared with the standard fusion energy consumption, which is convenient to determine the difference between the current fusion energy consumption of each intelligent lighting device and the specified fusion energy consumption. Finally, according to the above difference value, the energy consumption rollback trigger state of each intelligent lighting device is adjusted, which is convenient to optimize the output mode of the energy consumption data fusion of each intelligent lighting device, thereby improving the traceability of the energy consumption fusion data.

[0036] In one embodiment, the power calibration process for the reported energy consumption power to obtain the calibrated energy consumption power includes: performing a dynamic calibration operation on the reported energy consumption power to obtain a dynamically calibrated power. In this embodiment, the reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, which also means that the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By means of the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration process for the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so that the acquisition of the reported energy consumption power is more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. The power calibration process includes performing a dynamic calibration operation on the reported energy consumption power. The dynamic calibration operation is a calibration operation based on a dynamic calibration factor for the reported energy consumption power, and it is to correct the reported energy consumption power through the dynamic correction factor to make the acquisition accuracy of the reported energy consumption power.

[0037] Further, after performing the dynamic calibration operation on the reported energy consumption power, it also includes: performing a time offset compensation operation on the dynamically calibrated power to obtain the calibrated energy consumption power. In this embodiment, the reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, which also means that the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By means of the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration process for the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so that the acquisition of the reported energy consumption power is more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. The power calibration process includes performing a dynamic calibration operation on the reported energy consumption power. The dynamic calibration operation is a calibration operation based on a dynamic calibration factor for the reported energy consumption power, and it is to correct the reported energy consumption power through the dynamic correction factor to make the acquisition accuracy of the reported energy consumption power. After the dynamic calibration operation, there is still a data upload time deviation in the dynamically calibrated power, and it is necessary to perform a time offset compensation on the reported energy consumption power to correct the influence brought by the sampling time deviation of the reported energy consumption power, and further improve the sampling accuracy of the reported energy consumption power.

[0038] In another embodiment, the calibrated energy consumption power is obtained through a dynamic calibration operation and a time offset compensation operation, and the calibrated energy consumption power satisfies the following formula: For reporting energy consumption power; For energy consumption calibration power; Is a dynamic calibration factor for dynamic calibration operations; Is a time offset compensation factor for time offset compensation operations; Is the sampling interval.

[0039] Among them, Is the standard power reference value, for example, the laboratory calibration value; T is the calibration period; λ is the attenuation coefficient used to reflect the impact of equipment aging; t i Is the current timestamp; Is the average power within the period; Δt is the sampling interval.

[0040] In one embodiment, the energy consumption fusion process for the energy consumption calibration power to obtain a fused energy consumption value includes: performing a temperature compensation operation on the energy consumption calibration power to obtain a temperature-compensated fused energy consumption. In this embodiment, the energy consumption calibration power is obtained after power calibration processing, that is, the energy consumption calibration power is obtained based on the calibration of the reported energy consumption power. The reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, which also corresponds to the current operating power of the intelligent lighting device. By sampling the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, thereby determining the current energy consumption situation of each intelligent lighting device. The power calibration process for the reported energy consumption power is to calibrate the original power of the reported energy consumption power to make the acquisition of the reported energy consumption power more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. Through the energy consumption fusion process for the energy consumption calibration power, the calibrated accurate energy consumption data of each intelligent lighting device is fused, making the energy consumption fusion of each intelligent lighting device more efficient, so as to improve the efficiency of the energy consumption data fusion of intelligent lighting devices from multiple manufacturers. The energy consumption fusion process for the energy consumption calibration power includes performing a temperature compensation operation on the energy consumption calibration power. The temperature compensation operation is a compensation operation for the energy consumption calibration power of the intelligent lighting device affected by the current ambient temperature to eliminate the sampling error of the ambient temperature on the energy consumption calibration power.

[0041] Further, after performing the temperature compensation operation on the energy consumption calibration power, the following steps are also included: performing a humidity compensation operation on the temperature-compensated integrated energy consumption to obtain the humidity-compensated integrated energy consumption. In this embodiment, the temperature-compensated integrated energy consumption is the energy consumption after temperature compensation, and the energy consumption calibration power is obtained after power calibration processing, that is, the energy consumption calibration power is obtained by calibrating the reported energy consumption power. The reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, and also the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By using the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration processing of the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so that the acquisition of the reported energy consumption power is more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. Through the energy consumption integration processing of the energy consumption calibration power, the calibrated accurate energy consumption data of each intelligent lighting device are integrated, making the energy consumption integration of each intelligent lighting device more efficient, so as to improve the efficiency of the energy consumption data integration of intelligent lighting devices from multiple manufacturers. The energy consumption integration processing of the energy consumption calibration power includes performing a temperature compensation operation on the energy consumption calibration power. The temperature compensation operation is a compensation operation for the energy consumption calibration power of the intelligent lighting device affected by the current ambient temperature to eliminate the sampling error of the ambient temperature on the energy consumption calibration power. During the use of the intelligent lighting device, it is not only easily affected by the ambient temperature, but also easily affected by the ambient humidity, resulting in the accuracy of the energy consumption calibration power of the intelligent lighting device being affected by different humidities during operation. Therefore, a humidity compensation operation is performed on the temperature-compensated integrated energy consumption, that is, while performing temperature compensation on the energy consumption calibration power, humidity compensation is also performed, taking into account the effects of both temperature and humidity on the energy consumption calibration power of the intelligent lighting device, making the integrated energy consumption of each intelligent lighting device more accurate, thus facilitating more accurate sampling of the energy consumption integration of the intelligent lighting device in the future to improve the accuracy of the integrated energy consumption.

[0042] Further, after performing the humidity compensation operation on the temperature-compensated integrated energy consumption, the following steps are also included: performing a light compensation operation on the humidity-compensated integrated energy consumption to obtain an integrated energy consumption value. In this embodiment, the humidity-compensated integrated energy consumption is obtained by performing temperature compensation and humidity compensation on the energy consumption calibration power. The energy consumption calibration power is obtained after power calibration processing, that is, the energy consumption calibration power is obtained based on the calibration of the reported energy consumption power. The reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, and also the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By using the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration processing of the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so that the collection of the reported energy consumption power is more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. Through the energy consumption integration processing of the energy consumption calibration power, the calibrated accurate energy consumption data of each intelligent lighting device are integrated, making the energy consumption integration of each intelligent lighting device more efficient, so as to improve the efficiency of the energy consumption data integration of intelligent lighting devices from multiple manufacturers. The energy consumption integration processing of the energy consumption calibration power includes performing a temperature compensation operation on the energy consumption calibration power. The temperature compensation operation is a compensation operation for the energy consumption calibration power of the intelligent lighting device affected by the current ambient temperature to eliminate the sampling error of the ambient temperature on the energy consumption calibration power. During the use of the intelligent lighting device, it is not only easily affected by the ambient temperature, but also easily affected by the ambient humidity, resulting in the accuracy of the energy consumption calibration power of the intelligent lighting device being affected by different humidities during operation. Therefore, a humidity compensation operation is performed on the temperature-compensated integrated energy consumption, that is, humidity compensation is also performed while performing temperature compensation on the energy consumption calibration power, taking into account the effects of temperature and humidity on the energy consumption calibration power of the intelligent lighting device, making the integrated energy consumption of each intelligent lighting device more accurate, thereby facilitating more accurate sampling of the energy consumption integration of the intelligent lighting device in the future to improve the accuracy of the integrated energy consumption. The light compensation operation on the humidity-compensated integrated energy consumption is a light compensation for the energy consumption calibration power to compensate for the impact caused by the current ambient light of the energy consumption calibration power of the intelligent lighting device, eliminating the error of the energy consumption calibration power of the intelligent lighting device caused by the light factor, and thus making the energy consumption integration of the intelligent lighting device more accurate. Among them, the integrated energy consumption value satisfies the following formula: is the energy consumption calibration power; is the environmental compensation factor; T env is the current ambient temperature; T 0 is the reference temperature; H env is the current ambient humidity; H 0 is the reference humidity; L env is the current ambient light intensity; L max is the maximum light intensity; k T , k H , k L are the compensation coefficients for temperature, humidity, and light, respectively, which are dynamically optimized by the device characteristics and machine learning model. For example, the partial derivatives are calculated through historical data regression analysis.

[0043] k T satisfies the following formula: k H satisfies the following formula: k L satisfies the following formula: .

[0044] In another embodiment, a light compensation operation is performed on the wet-complemented fusion energy consumption to obtain a fusion energy consumption value, and then global energy consumption processing is included to obtain a global energy consumption fusion value. The global energy consumption fusion value is the fusion of the energy consumption data of the intelligent lighting devices of each manufacturer, and the global energy consumption fusion value satisfies the following formula: is the global energy consumption fusion value; N is the number of manufacturer intelligent lighting devices connected; w i is the weight factor; is the variance of the energy consumption data of the i-th intelligent lighting device; is the smoothing coefficient; μ is the abnormal deviation penalty coefficient; is the average fusion energy consumption value of all intelligent lighting devices.

[0045] By sampling the global energy consumption fusion value, it is convenient to determine the total fusion energy consumption after the fusion of all intelligent lighting devices of each manufacturer, so as to facilitate the accurate monitoring of the comprehensive energy consumption of each manufacturer.

[0046] In one of the embodiments, the reliable processing of fusing the fused energy consumption value with the preset energy consumption value includes: obtaining the relative difference modulus between the fused energy consumption value and the preset energy consumption value; The sending of a rollback enable signal to the intelligent lighting device energy consumption platform according to the fused rollback difference amount to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices includes: detecting whether the fused rollback difference amount is greater than a preset rollback difference amount; When the fused rollback difference amount is greater than the preset rollback difference amount, a rollback enable signal is sent to the intelligent lighting device energy consumption platform to trigger a rollback logic to eliminate the fused energy consumption value. In this embodiment, the fused rollback difference amount is obtained based on the fused energy consumption value and the preset energy consumption value. The fused energy consumption value is the fused data after calibration of each reported energy consumption power. The energy consumption calibrated power is obtained after power calibration processing, that is, the energy consumption calibrated power is obtained based on the calibration of the reported energy consumption power. The reported energy consumption power is the energy consumption data uploaded by the intelligent lighting device, that is, the reported energy consumption power is the current energy consumption power value of the intelligent lighting device, that is, the reported energy consumption power corresponds to the current operating power of the intelligent lighting device. By sampling the reported energy consumption power, it is convenient to sample the energy consumption applicable to the current operation of the intelligent lighting device, so as to determine the current energy consumption situation of each intelligent lighting device. The power calibration processing of the reported energy consumption power is to calibrate the original power of the reported energy consumption power, so that the collection of the reported energy consumption power is more accurate, thereby improving the accuracy of the energy consumption data processing of the intelligent lighting device. Through the energy consumption fusion processing of the energy consumption calibrated power, the calibrated accurate energy consumption data of each intelligent lighting device are fused, so that the energy consumption fusion of each intelligent lighting device is more efficient, so as to improve the efficiency of the energy consumption data fusion of intelligent lighting devices from multiple manufacturers. The preset energy consumption value is the standard fused energy consumption of each intelligent lighting device. By the reliable processing of fusing the fused energy consumption value with the preset energy consumption value, it is convenient to determine the difference degree between the fused energy consumption of each intelligent lighting device and the standard fused energy consumption. After determining the fused rollback difference amount, the fused energy consumption deviation situation of each intelligent lighting device is determined, which is convenient to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices, thereby improving the traceability of the energy consumption fusion data. Among them, the fused energy consumption value is obtained after calibration compensation and environmental compensation. The fused energy consumption value is the total energy consumption fusion of each intelligent lighting device. The preset energy consumption value is the standard fused energy consumption of the intelligent lighting device. For example, the preset energy consumption value is the total energy consumption fusion of each intelligent lighting device fused by the traditional method, and the preset energy consumption value is used as a control group and recorded by a traditional electric meter.By obtaining the relative difference modulus between the fused energy consumption value and the preset energy consumption value, the difference between the fused energy consumption value and the fused energy consumption in the prior art is determined, so as to determine the error rate of the total fused energy consumption of each intelligent lighting device relative to the total fused energy consumption recorded by the traditional electric meter. Specifically, the fused rollback difference quantity satisfies the following formula: is the fused rollback difference quantity; E A is the preset energy consumption value; E B is the fused energy consumption value.

[0047] After determining the fused rollback difference quantity, by comparing it with the preset rollback difference quantity, the preset rollback difference quantity is the allowable error range between the fused energy consumption value and the fused energy consumption in the prior art. The fact that the fused rollback difference quantity is greater than the preset rollback difference quantity indicates that the error rate of the total fused energy consumption of each intelligent lighting device relative to the total fused energy consumption recorded by the traditional electric meter is too large, that is, it indicates that the currently compensated fused energy consumption deviates greatly from the actual fused energy consumption, belonging to the distorted fused energy consumption. At this time, a rollback enable signal is sent to the energy consumption platform of the intelligent lighting device to trigger the rollback logic and eliminate the fused energy consumption value, so as to avoid outputting the wrong fused energy consumption.

[0048] In another embodiment, when the fused rollback difference quantity is less than or equal to the preset rollback difference quantity, a rollback disable signal is sent to the energy consumption platform of the intelligent lighting device to output the fused energy consumption value as the current energy consumption, which is convenient for reporting the fused energy consumption to the platform system, specifically as Figure 2 shown.

[0049] In one of the embodiments, the present disclosure also relates to an energy consumption data fusion management and processing system based on intelligent lighting devices, including: a lighting energy consumption acquisition module, a fused energy consumption processing module, and a rollback adjustment module; the lighting energy consumption acquisition module is used to obtain the reported energy consumption power of the intelligent lighting device; the fused energy consumption processing module is used to perform power calibration processing on the reported energy consumption power to obtain the energy consumption calibrated power; perform energy consumption fusion processing on the energy consumption calibrated power to obtain the fused energy consumption value; perform fused reliability processing on the fused energy consumption value and the preset energy consumption value to obtain the fused rollback difference quantity; the rollback adjustment module is used to send a rollback disable signal to the energy consumption platform of the intelligent lighting device according to the fused rollback difference quantity to adjust the output mode of the energy consumption data fusion of all intelligent lighting devices.

[0050] In this embodiment, after the lighting energy consumption acquisition module collects the reported energy consumption power, the current uploaded lighting power of the intelligent lighting device is determined. Then, the fusion energy consumption processing module calibrates and fuses the reported energy consumption power, making the fusion of the lighting energy consumption of each intelligent lighting device more accurate, so as to obtain the lighting fusion energy consumption of each intelligent lighting device more in line with requirements, thereby improving the energy consumption fusion efficiency of multiple lighting devices. Then, the fused energy consumption value is compared with the standard fused energy consumption to facilitate determining the difference between the current fused energy consumption of each intelligent lighting device and the specified fused energy consumption. Finally, the rollback adjustment module adjusts the energy consumption rollback trigger state of each intelligent lighting device according to the above difference value, facilitating the optimization of the output mode of the energy consumption data fusion of each intelligent lighting device, thereby improving the traceability of the energy consumption fusion data.

[0051] In another embodiment, for the upload platform system of the fused energy consumption value, it needs to go through data collection, data parsing, data calculation, data fusion, and data statistics. For details, refer to the system architecture diagram corresponding to the energy consumption data fusion management processing system based on intelligent lighting devices, specifically as Figure 3 shown.

[0052] Among them, the energy consumption data standardization engine, as the core processing module, is responsible for format conversion and data modeling. It receives the raw data reported by the gateway and outputs the standardized data to the algorithm module. Its function is to dynamically identify the data format, support hot deployment to update the parsing rules, and ensure adaptability flexibility.

[0053] In the energy consumption algorithm module, the unified calculation of energy consumption data is realized, supporting the access and update of third-party algorithms. It receives the output data of the standardization engine, processes it, and then transmits it to the Kafka queue. Its function is to decouple the algorithm logic, provide an open API interface, and ensure the consistency of the calculation results.

[0054] The role of the Kafka message queue is to ensure the high performance and reliability of data transmission, support dynamic scaling, connect the standardization engine and the platform system, be responsible for data transfer, and be used to monitor the queue to complete data entry.

[0055] In one embodiment, a computer device is provided. This computer device can be a server, and its internal structure diagram can be as Figure 4As shown. The computer device includes a processor, a memory, and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as the operating state parameters of the battery cells, the unevenness of the battery cell operation, and the fan power adjustment signal. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements a method for energy consumption data fusion management and processing based on intelligent lighting devices.

[0056] Those skilled in the art can understand that Figure 4 the structure shown in is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0057] In one embodiment, the present application further provides a computer device, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the steps in the above method embodiments are implemented.

[0058] In one embodiment, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0059] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0060] The above-described embodiments merely represent several implementation manners of the present disclosure. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present disclosure, several modifications and improvements can still be made, and these all belong to the protection scope of the present disclosure. Therefore, the protection scope of the patent of the present disclosure shall be subject to the appended claims.

Claims

1. A method for fusion management and processing of energy consumption data based on intelligent lighting equipment, characterized in that: include: Obtain the reported energy consumption power of smart lighting equipment; Performing power calibration processing on the reported energy consumption power to obtain energy consumption calibration power; Performing energy consumption fusion processing on the energy consumption calibration power to obtain a fused energy consumption value; Reliably fusing the fused energy consumption value with the preset energy consumption value to obtain a fused rollback difference; A rollback failure signal is sent to the smart lighting device energy consumption platform according to the fusion rollback difference, so as to adjust the output mode of the energy consumption data fusion of all smart lighting devices.

2. The energy consumption data fusion management and processing method based on intelligent lighting equipment according to claim 1 is characterized in that: The performing power calibration processing on the reported energy consumption power to obtain energy consumption calibration power includes: A dynamic calibration operation is performed on the reported energy consumption power to obtain a dynamic calibration power.

3. The energy consumption data fusion management and processing method based on intelligent lighting equipment according to claim 2 is characterized in that: The dynamically calibrating the reported energy consumption power further comprises: Performing a time offset compensation operation on the dynamic calibration power to obtain an energy consumption calibration power; The energy consumption calibration power satisfies the following formula: To report energy consumption power; calibrate power for energy consumption; is the dynamic calibration factor, used for dynamic calibration operation; is the time offset compensation factor, used for time offset compensation operation; is the sampling interval; in, is the standard power reference value, for example, the laboratory calibration value; T is the calibration period; λ is the attenuation coefficient, which is used to reflect the aging effect of the equipment; t i is the current timestamp; is the average power within the period; Δt is the sampling interval.

4. The energy consumption data fusion management and processing method based on intelligent lighting equipment according to claim 1 is characterized in that: The performing energy consumption fusion processing on the energy consumption calibration power to obtain a fused energy consumption value includes: A temperature compensation operation is performed on the energy consumption calibration power to obtain temperature compensated fusion energy consumption.

5. The energy consumption data fusion management and processing method based on intelligent lighting equipment according to claim 4 is characterized in that: The temperature compensation operation is performed on the energy consumption calibration power, and then further includes: A humidity compensation operation is performed on the temperature compensation fusion energy consumption to obtain the moisture compensation fusion energy consumption.

6. The energy consumption data fusion management and processing method based on intelligent lighting equipment according to claim 5 is characterized in that: The humidity compensation operation is performed on the temperature compensation fusion energy consumption, and then further includes: Performing a light compensation operation on the wet compensation fusion energy consumption to obtain a fusion energy consumption value, The fusion energy consumption value satisfies the following formula: calibrate power for energy consumption; is the fusion energy consumption value; is the environmental compensation factor; T env is the current ambient temperature; T0 is the reference temperature; H env is the current ambient humidity; H0 is the reference humidity; L env is the current ambient light intensity; L max is the maximum light intensity; k T , k H , k L They are the compensation coefficients for temperature, humidity, and light, respectively, which are obtained by dynamic optimization of device characteristics and machine learning models, for example, by calculating partial derivatives through regression analysis of historical data; k T Satisfies the following formula: k H Satisfies the following formula: k L Satisfies the following formula: 。 7. The energy consumption data fusion management and processing method based on intelligent lighting equipment according to claim 1 is characterized in that: The step of reliably fusing the fused energy consumption value with the preset energy consumption value includes: Obtaining a relative difference between the fused energy consumption value and the preset energy consumption value; The sending of a rollback failure signal to the smart lighting device energy consumption platform according to the fusion rollback difference to adjust the output mode of energy consumption data fusion of all smart lighting devices includes: Detecting whether the fusion rollback difference is greater than a preset rollback difference; When the fused rollback difference is greater than the preset rollback difference, a rollback enable signal is sent to the smart lighting device energy consumption platform to trigger the rollback logic to eliminate the fused energy consumption value.

8. An energy consumption data fusion management and processing system based on intelligent lighting equipment, characterized in that: include: A lighting energy consumption collection module, which is used to obtain the reported energy consumption power of intelligent lighting equipment; A fusion energy consumption processing module, wherein the fusion energy consumption processing module is used to perform power calibration processing on the reported energy consumption power to obtain energy consumption calibration power; Performing energy consumption fusion processing on the energy consumption calibration power to obtain a fused energy consumption value; Reliably fusing the fused energy consumption value with the preset energy consumption value to obtain a fused rollback difference; A rollback adjustment module is used to send a rollback failure signal to the smart lighting device energy consumption platform according to the fused rollback difference, so as to adjust the output mode of the energy consumption data fusion of all smart lighting devices.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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