CN116132326B - Comprehensive energy efficiency data management method and system - Google Patents
Comprehensive energy efficiency data management method and system Download PDFInfo
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- CN116132326B CN116132326B CN202310058591.7A CN202310058591A CN116132326B CN 116132326 B CN116132326 B CN 116132326B CN 202310058591 A CN202310058591 A CN 202310058591A CN 116132326 B CN116132326 B CN 116132326B
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Abstract
The invention is suitable for a comprehensive energy efficiency data management method and a system, wherein the method comprises the following steps: acquiring gateway monitoring data; analyzing the intelligent equipment data, identifying the model and the operation mode of the intelligent equipment, and generating an intelligent equipment energy consumption curve; analyzing the data of the non-intelligent equipment, identifying the model of the non-intelligent equipment, and generating an energy consumption curve of the non-intelligent equipment; and carrying out energy efficiency evaluation based on the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve, judging whether the energy efficiency data are normal, and if not, sending out an energy efficiency data abnormal alarm. According to the comprehensive energy efficiency data management method provided by the embodiment of the invention, the gateway is used for carrying out data statistics on the equipment which is accessed to the gateway at present, the energy consumption of the equipment in each time period is calculated according to the data statistics on each equipment, the energy consumption is compared with the actual energy consumption, whether the energy efficiency is abnormal or not is judged, and when the energy efficiency is abnormal, prompt is carried out in time, so that the loss caused by the energy efficiency abnormality is reduced.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a comprehensive energy efficiency data management method and system.
Background
The data management is a process of effectively collecting, storing, processing and applying data by utilizing computer hardware and software technology, and aims to fully and effectively play a role of data, and the key for realizing effective management of the data is data organization.
The energy consumption information of each energy utilization system in the green building is collected, displayed, analyzed, diagnosed, maintained, controlled and optimally managed, and the system with real-time, global and systematic energy efficiency comprehensive function management functions is formed through resource integration.
In the current enterprises, a large amount of energy consumption equipment exists, but an effective energy consumption management system is lacked, so that accurate judgment on the energy efficiency of the enterprises cannot be performed.
Disclosure of Invention
The embodiment of the invention aims to provide a comprehensive energy efficiency data management method, which aims to solve the problems that a large amount of energy consumption equipment exists in the current enterprise, but an effective energy consumption management system is lacked, and the energy efficiency of the enterprise cannot be accurately judged.
The embodiment of the invention is realized in such a way that the comprehensive energy efficiency data management method comprises the following steps:
acquiring gateway monitoring data, wherein the gateway monitoring data comprises intelligent equipment data and non-intelligent equipment data;
analyzing the intelligent equipment data, identifying the model and the operation mode of the intelligent equipment, and generating an intelligent equipment energy consumption curve;
analyzing the data of the non-intelligent equipment, identifying the model of the non-intelligent equipment, and generating an energy consumption curve of the non-intelligent equipment;
and carrying out energy efficiency evaluation based on the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve, judging whether the energy efficiency data are normal, and if not, sending out an energy efficiency data abnormal alarm.
Preferably, the step of analyzing the data of the intelligent device, identifying the model and the operation mode of the intelligent device and generating the energy consumption curve of the intelligent device specifically includes:
analyzing the data of the intelligent equipment, and identifying the model of the intelligent equipment started at the same time;
inquiring a device database according to the model of the intelligent device, and determining real-time energy consumption parameters of the intelligent device under different environments;
and determining the energy consumption of the intelligent equipment in each time period according to the time sequence, and generating an intelligent equipment energy consumption curve.
Preferably, the step of analyzing the data of the non-intelligent device, identifying the model of the non-intelligent device and generating the energy consumption curve of the non-intelligent device specifically includes:
analyzing the data of the non-intelligent equipment, judging the type of the equipment which is accessed to the network at present, and determining the model of the equipment;
inquiring a device database according to the model of the non-intelligent device, and determining average energy consumption parameters of the non-intelligent device under different environmental conditions;
and determining the energy consumption of the non-intelligent equipment in each time period according to the time sequence, and generating an energy consumption curve of the non-intelligent equipment.
Preferably, the step of evaluating energy efficiency based on the intelligent device energy consumption curve and the non-intelligent device energy consumption curve to determine whether the energy efficiency data is normal specifically includes:
acquiring real-time energy consumption data, and intercepting the real-time energy consumption data to obtain segmented energy consumption data;
determining energy consumption analysis time information according to the segmented energy consumption data, and generating actual energy consumption data according to the intelligent equipment energy consumption curve, the non-intelligent equipment energy consumption curve and the energy consumption analysis time information;
and calculating the matching degree between the actual energy consumption data and the segmented energy consumption data, carrying out energy efficiency evaluation according to the matching degree, and judging whether the energy efficiency data are normal or not.
Preferably, when the energy efficiency data is determined to be abnormal, corresponding segmented energy consumption data is determined, and then the non-intelligent equipment and intelligent equipment which operate at the time are determined according to the segmented energy consumption data.
Preferably, the matching degree is the ratio of the actual energy consumption data to the segmented energy consumption data.
It is another object of an embodiment of the present invention to provide an integrated energy efficiency data management system, the system including:
the data acquisition module is used for acquiring gateway monitoring data, wherein the gateway monitoring data comprises intelligent equipment data and non-intelligent equipment data;
the first equipment analysis module is used for analyzing the intelligent equipment data, identifying the model and the operation mode of the intelligent equipment and generating an intelligent equipment energy consumption curve;
the second equipment analysis module is used for analyzing the data of the non-intelligent equipment, identifying the model of the non-intelligent equipment and generating an energy consumption curve of the non-intelligent equipment;
and the energy efficiency evaluation module is used for performing energy efficiency evaluation based on the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve, judging whether the energy efficiency data are normal or not, and if the energy efficiency data are abnormal, sending out an energy efficiency data abnormal alarm.
Preferably, the first device analysis module includes:
the first model identification unit is used for analyzing the data of the intelligent equipment and identifying the model of the intelligent equipment started at the same time;
the first parameter query unit is used for querying the equipment database according to the model of the intelligent equipment and determining real-time energy consumption parameters of the intelligent equipment in different environments;
the first curve generating unit is used for determining the energy consumption of the intelligent device in each time period according to the time sequence and generating an intelligent device energy consumption curve.
Preferably, the second device analysis module includes:
the second model identification unit is used for analyzing the data of the non-intelligent equipment, judging the type of the equipment currently accessed to the network and determining the model of the equipment;
the second parameter query unit is used for querying the equipment database according to the model of the non-intelligent equipment and determining the average energy consumption parameters of the non-intelligent equipment under different environmental conditions;
and the second curve generating unit is used for determining the energy consumption of the non-intelligent equipment in each time period according to the time sequence and generating a non-intelligent equipment energy consumption curve.
Preferably, the energy efficiency evaluation module includes:
the data interception unit is used for acquiring real-time energy consumption data and intercepting the real-time energy consumption data to obtain segmented energy consumption data;
the actual energy consumption calculation unit is used for determining energy consumption analysis time information according to the segmented energy consumption data and generating actual energy consumption data according to the intelligent equipment energy consumption curve, the non-intelligent equipment energy consumption curve and the energy consumption analysis time information;
and the abnormality judging unit is used for calculating the matching degree between the actual energy consumption data and the segmented energy consumption data, carrying out energy efficiency evaluation according to the matching degree, and judging whether the energy efficiency data are normal or not.
According to the comprehensive energy efficiency data management method provided by the embodiment of the invention, the gateway is used for carrying out data statistics on the equipment which is accessed to the gateway at present, the energy consumption of the equipment in each time period is calculated according to the data statistics on each equipment, the energy consumption is compared with the actual energy consumption, whether the energy efficiency is abnormal or not is judged, and when the energy efficiency is abnormal, prompt is carried out in time, so that the loss caused by the energy efficiency abnormality is reduced.
Drawings
Fig. 1 is a flowchart of a comprehensive energy efficiency data management method according to an embodiment of the present invention.
Fig. 2 is a flowchart of steps for analyzing data of an intelligent device, identifying a model and an operation mode of the intelligent device, and generating an energy consumption curve of the intelligent device according to an embodiment of the present invention.
Fig. 3 is a flowchart of a step of analyzing data of a non-intelligent device, identifying a model of the non-intelligent device, and generating an energy consumption curve of the non-intelligent device according to an embodiment of the present invention.
Fig. 4 is a flowchart of a step of performing energy efficiency evaluation based on an intelligent device energy consumption curve and a non-intelligent device energy consumption curve to determine whether energy efficiency data is normal or not according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of an integrated energy efficiency data management system according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of a first device analysis module according to an embodiment of the present invention.
Fig. 7 is a schematic diagram of a second device analysis module according to an embodiment of the present invention.
Fig. 8 is a schematic diagram of an energy efficiency evaluation module according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
It will be understood that the terms "first," "second," and the like, as used herein, may be used to describe various elements, but these elements are not limited by these terms unless otherwise specified. These terms are only used to distinguish one element from another element. For example, a first xx script may be referred to as a second xx script, and similarly, a second xx script may be referred to as a first xx script, without departing from the scope of the present application.
As shown in fig. 1, a flowchart of a comprehensive energy efficiency data management method according to an embodiment of the present invention is provided, where the method includes:
s100, gateway monitoring data are obtained, wherein the gateway monitoring data comprise intelligent equipment data and non-intelligent equipment data.
In this step, the gateway monitoring data is obtained, in the enterprise, the intelligent devices all have networking functions, all need to carry out data communication through the gateway, the intelligent devices comprise intelligent air conditioners, intelligent sound boxes, intelligent televisions and the like, the non-intelligent devices are various computers and other office devices such as printers and the like, the non-intelligent devices such as printers and computers also need to establish data connection with the gateway through wired channels or wireless channels, for example, data connection is carried out through network cables and the gateway, or data connection is carried out through wireless networks and the gateway, and whether the intelligent devices or the non-intelligent devices upload own working data through the gateway through the network.
And S200, analyzing the intelligent equipment data, identifying the model and the operation mode of the intelligent equipment, and generating an intelligent equipment energy consumption curve.
In this step, the intelligent device data is parsed, in the process of the intelligent device operation, the intelligent device uploads the mode data in which the intelligent device operates, that is, the intelligent device is in any working mode and records the working parameters in the operation mode, such as the intelligent air conditioner, in which the intelligent device uploads the working mode, such as heating mode, in which the intelligent device operates, and in which the intelligent device operates, the data, such as the temperature, the compressor operation time, the internal machine air volume and the like, set in heating are uploaded synchronously, a preset device database is queried, the corresponding power consumption of each intelligent device under different working conditions is recorded in the device database, such as 26 degrees of heating temperature, the compressor is started, the equal power is 2500W when the internal machine air volume is in three gears, then the intelligent device energy consumption curve can be obtained by recording according to the data in time sequence and recording in a two-dimensional coordinate system.
And S300, analyzing the data of the non-intelligent equipment, identifying the model of the non-intelligent equipment and generating an energy consumption curve of the non-intelligent equipment.
In this step, the data of the non-intelligent device is analyzed, for the non-intelligent device, the power of the non-intelligent device cannot be calculated, when the non-intelligent device runs, the working time and the running state of the non-intelligent device are uploaded, for example, for a computer, the model of the hardware of the non-intelligent device and the occupancy rate of the computer when the non-intelligent device runs are uploaded, the power of the hardware under each condition can be determined according to the model of the hardware, and the energy consumption requirement of the whole computer when the computer runs can be calculated and obtained, and likewise, the energy consumption curve of the non-intelligent device can be obtained by recording according to the time sequence.
S400, energy efficiency evaluation is carried out based on the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve, whether the energy efficiency data are normal or not is judged, and if the energy efficiency data are abnormal, an energy efficiency data abnormal alarm is sent.
In the step, energy efficiency evaluation is carried out based on an intelligent equipment energy consumption curve and a non-intelligent equipment energy consumption curve, after the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve are obtained, the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve are drawn in a two-dimensional coordinate system, the horizontal axes of the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve are both time, and the vertical axes of the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve are power, so that energy consumption in each time period can be calculated in an integral mode, and in an enterprise, in order to evaluate the actual consumption level of energy consumption, a corresponding energy consumption statistical device such as an ammeter is arranged, so that the actual consumed energy source in the current enterprise can be determined, the ratio between the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve is calculated, the evaluation can be carried out according to the ratio, whether energy efficiency data are normal or not can be judged, and if abnormal energy efficiency data abnormal alarms can be sent out; when the energy efficiency data is determined to be abnormal, corresponding segmented energy consumption data is determined, and then the non-intelligent equipment and intelligent equipment which operate at the time are determined according to the segmented energy consumption data.
As shown in fig. 2, as a preferred embodiment of the present invention, the steps of analyzing the data of the smart device, identifying the model and the operation mode of the smart device, and generating an energy consumption curve of the smart device specifically include:
s201, analyzing the intelligent device data, and identifying the model of the intelligent device started simultaneously.
In the step, the intelligent equipment data are analyzed, the model numbers, the operation parameters and the operation modes of all intelligent equipment are recorded in the intelligent equipment data, the intelligent equipment running at the current moment can be obtained through extraction, and the intelligent equipment is enumerated through a list.
S202, inquiring a device database according to the model of the intelligent device, and determining real-time energy consumption parameters of the intelligent device in different environments.
In the step, a device database is queried according to the model of the intelligent device, the intelligent device is queried one by one according to the model of the intelligent device, specifically, an intelligent device is determined first, then the operation mode and the operation parameters of the intelligent device are determined, at the moment, the device database is queried according to the model of the intelligent device to obtain corresponding matching items, the energy consumption conditions of the intelligent device operated under various different conditions are stored in the matching items, and the matching items are further screened according to the operation mode and the operation parameters of the current intelligent device in operation, so that the real-time energy consumption parameters of the current intelligent device under the current environment conditions are determined.
And S203, determining the energy consumption of the intelligent equipment in each time period according to the time sequence, and generating an intelligent equipment energy consumption curve.
In this step, the energy consumption of the intelligent device in each time period is determined according to the time sequence, specifically, the minimum time interval is divided, for example, 10 seconds is taken as a minimum time interval, then the time is divided according to the minimum time interval, further, the real-time energy consumption parameters corresponding to each minimum time interval are determined, and an intelligent device energy consumption curve is generated, for example, the real-time energy consumption parameter in the first minimum time interval is 2000W, and the real-time energy consumption parameter in the second minimum time interval is 2500W.
As shown in fig. 3, as a preferred embodiment of the present invention, the steps of analyzing the data of the non-intelligent device, identifying the model of the non-intelligent device, and generating an energy consumption curve of the non-intelligent device specifically include:
s301, analyzing the non-intelligent device data, judging the type of the device currently accessed to the network, and determining the model of the device.
In the step, the data of the non-intelligent equipment is analyzed, and in the non-intelligent equipment, the data is started to be sent to the gateway in the running process, so that the gateway can judge whether the gateway is started or not according to the data sent by the gateway and is in a working state, and the gateway can determine the model of the non-intelligent equipment according to the network address of the non-intelligent equipment.
S302, inquiring a device database according to the model of the non-intelligent device, and determining average energy consumption parameters of the non-intelligent device under different environmental conditions.
In this step, the device database is queried according to the model of the non-intelligent device, and similarly, the working energy consumption of all the non-intelligent devices is stored in the device database, where the working energy consumption is average energy consumption, and if the average working energy consumption of the printer is 2000W, the average working energy consumption is an average energy consumption parameter.
And S303, determining the energy consumption of the non-intelligent equipment in each time period according to the time sequence, and generating a non-intelligent equipment energy consumption curve.
In the step, the energy consumption of the non-intelligent equipment in each time period is determined according to the time sequence, a two-dimensional coordinate system is built, the time is taken as a horizontal axis, and the energy consumption is taken as a vertical axis to draw a curve so as to generate an energy consumption curve of the non-intelligent equipment.
As shown in fig. 4, as a preferred embodiment of the present invention, the step of evaluating energy efficiency based on the smart device energy consumption curve and the non-smart device energy consumption curve to determine whether the energy efficiency data is normal specifically includes:
s401, acquiring real-time energy consumption data, and intercepting the real-time energy consumption data to obtain segmented energy consumption data.
In this step, real-time energy consumption data is obtained, the real-time energy consumption data is obtained by statistics of an ammeter arranged inside a company, and the real-time energy consumption data is intercepted according to a preset interception interval, for example, one minute is taken as an interception interval, so that interception is performed, and a plurality of segmented energy consumption data are obtained.
S402, determining energy consumption analysis time information according to the segmented energy consumption data, and generating actual energy consumption data according to the intelligent equipment energy consumption curve, the non-intelligent equipment energy consumption curve and the energy consumption analysis time information.
In this step, energy consumption analysis time information is determined according to the segmented energy consumption data, if the starting time of the first segmented energy consumption data is 10:00 and the end time thereof is 10:01, corresponding time information can be obtained, actual energy consumption data is generated according to the intelligent device energy consumption curve, the non-intelligent device energy consumption curve and the energy consumption analysis time information, namely, the curves in the corresponding time periods in the intelligent device energy consumption curve and the non-intelligent device energy consumption curve are intercepted according to the energy consumption analysis time information, so that the actual energy consumption data is obtained through calculation.
S403, calculating the matching degree between the actual energy consumption data and the segmented energy consumption data, and carrying out energy efficiency evaluation according to the matching degree to judge whether the energy efficiency data are normal or not.
In the step, the matching degree between the actual energy consumption data and the sectional energy consumption data is calculated, the matching degree is the ratio of the actual energy consumption data to the sectional energy consumption data, the ratio is compared with a preset value, when the ratio is larger than the preset value, the energy efficiency data is judged to be normal, if the preset value is 0.9, and if the ratio of the actual energy consumption data to the sectional energy consumption data is larger than 0.9, the energy efficiency data is judged to be normal.
As shown in fig. 5, an integrated energy efficiency data management system according to an embodiment of the present invention includes:
the data acquisition module 100 is configured to acquire gateway monitoring data, where the gateway monitoring data includes smart device data and non-smart device data.
In this system, the data acquisition module 100 acquires gateway monitoring data, in enterprises, the intelligent devices all have a networking function and all need to perform data communication through the gateway, the intelligent devices include intelligent air conditioners, intelligent sound boxes, intelligent televisions and the like, the non-intelligent devices are various types of computers and other office devices such as printers, the non-intelligent devices such as printers and computers also need to establish data connection with the gateway through wired channels or wireless channels, for example, data connection is performed with the gateway through a network cable, or data connection is performed with the gateway through a wireless network, and whether the intelligent devices or the non-intelligent devices upload their working data through the gateway through the network.
The first device analysis module 200 is configured to analyze the data of the intelligent device, identify a model and an operation mode of the intelligent device, and generate an intelligent device energy consumption curve.
In the system, the first device analysis module 200 analyzes the data of the intelligent device, in the running process of the intelligent device, the intelligent device uploads the mode data of the intelligent device, namely, the intelligent device is in any working mode and records the working parameters of the intelligent device in the working mode, such as an intelligent air conditioner, in the running process, uploads the working modes of the intelligent device, such as a heating mode, and also uploads the working parameters of the intelligent device, such as the data of the temperature, the running time of a compressor, the air quantity of an internal machine and the like set in the heating process, synchronously uploads the data, such as the preset device database, records the corresponding power consumption of each intelligent device under different working conditions in the device database, such as 26 ℃ in the heating temperature, the compressor is started, the equal power of 2500W in the three-gear air quantity of the internal machine, records according to the data in time sequence, and records in a two-dimensional coordinate system, thus obtaining the energy consumption curve of the intelligent device.
And the second device analysis module 300 is used for analyzing the data of the non-intelligent device, identifying the model of the non-intelligent device and generating an energy consumption curve of the non-intelligent device.
In the system, the second device analysis module 300 analyzes the data of the non-intelligent device, for the non-intelligent device, it cannot calculate its own power, and when it runs, it uploads its working time and running state, for example, for a computer, it uploads its hardware model and its occupancy rate when running, according to the hardware model, it can determine the power of the hardware under each condition, and can calculate and obtain the energy consumption requirement that the whole computer will generate when running, and similarly, it records according to time sequence, and can obtain the energy consumption curve of the non-intelligent device.
The energy efficiency evaluation module 400 is configured to perform energy efficiency evaluation based on the intelligent device energy consumption curve and the non-intelligent device energy consumption curve, determine whether the energy efficiency data is normal, and if not, send out an abnormal alarm of the energy efficiency data.
In the system, the energy efficiency evaluation module 400 performs energy efficiency evaluation based on the intelligent device energy consumption curve and the non-intelligent device energy consumption curve, after the intelligent device energy consumption curve and the non-intelligent device energy consumption curve are obtained, the intelligent device energy consumption curve and the non-intelligent device energy consumption curve are drawn in a two-dimensional coordinate system, the horizontal axes of the intelligent device energy consumption curve and the non-intelligent device energy consumption curve are both time, the vertical axes of the intelligent device energy consumption curve and the non-intelligent device energy consumption curve are power, so that energy consumption in each time period can be calculated in an integral mode, in an enterprise, in order to evaluate the actual consumption level of energy consumption, corresponding energy consumption statistical equipment such as an ammeter is arranged, so that the actual consumed energy source in the current enterprise can be determined, the ratio between the intelligent device energy consumption curve and the non-intelligent device energy consumption curve is calculated, evaluation can be performed according to the ratio, whether energy efficiency data are normal or not can be judged, and if abnormal energy efficiency data alarm is sent; when the energy efficiency data is determined to be abnormal, corresponding segmented energy consumption data is determined, and then the non-intelligent equipment and intelligent equipment which operate at the time are determined according to the segmented energy consumption data.
As shown in fig. 6, as a preferred embodiment of the present invention, the first device analysis module 200 includes:
the first model identifying unit 201 is configured to parse the data of the smart device, and identify the model of the smart device that is started simultaneously.
In this module, the first model identifying unit 201 analyzes the data of the intelligent device, records the model, the operation parameter and the operation mode of each intelligent device in the data of the intelligent device, and extracts the model, the operation parameter and the operation mode of each intelligent device to obtain the intelligent device running at the current moment, and enumerates the intelligent device through a list.
The first parameter query unit 202 is configured to query the device database according to the model of the intelligent device, and determine real-time energy consumption parameters of the intelligent device in different environments.
In this module, the first parameter query unit 202 queries the device database according to the model of the intelligent device, queries one by one according to the model of the intelligent device, specifically, determines an intelligent device first, then determines an operation mode and operation parameters of the intelligent device, queries the device database according to the model of the intelligent device at this time to obtain corresponding matching items, stores energy consumption conditions of the intelligent device running under various different conditions in the matching items, and further screens the matching items according to the operation mode and operation parameters of the current intelligent device running to determine real-time energy consumption parameters of the current intelligent device under the current environmental conditions.
The first curve generating unit 203 is configured to determine energy consumption of the intelligent device in each time period according to a time sequence, and generate an energy consumption curve of the intelligent device.
In this module, the first curve generating unit 203 determines the energy consumption of the intelligent device in each time period according to the time sequence, specifically, divides the minimum time interval, for example, 10 seconds into one minimum time interval, then divides the time according to the minimum time interval, further determines the real-time energy consumption parameters corresponding to each minimum time interval, and generates the energy consumption curve of the intelligent device, for example, the real-time energy consumption parameter in the first minimum time interval is 2000W, and the real-time energy consumption parameter in the second minimum time interval is 2500W.
As shown in fig. 7, as a preferred embodiment of the present invention, the second device analysis module 300 includes:
the second model identifying unit 301 is configured to parse the non-intelligent device data, determine the type of the device currently accessing the network, and determine the model thereof.
In this module, the second model identifying unit 301 analyzes the data of the non-intelligent device, in the non-intelligent device, it starts to send data to the gateway in the running process, so the gateway can determine whether it starts according to the data sent by the gateway, whether it is in a working state, and the gateway can determine its model according to the network address of the non-intelligent device.
And the second parameter query unit 302 is configured to query the device database according to the model of the non-intelligent device, and determine average energy consumption parameters of the non-intelligent device under different environmental conditions.
In this module, the second parameter query unit 302 queries the device database according to the model of the non-intelligent device, and similarly, the device database stores all the working energy consumption of the non-intelligent device, where the working energy consumption is average energy consumption, and if the average working energy consumption of the printer is 2000W, the average working energy consumption is an average energy consumption parameter.
And the second curve generating unit 303 is configured to determine the energy consumption of the non-intelligent device in each time period according to the time sequence, and generate a non-intelligent device energy consumption curve.
In this module, the second curve generating unit 303 determines the energy consumption of the non-intelligent device in each time period according to the time sequence, and similarly, constructs a two-dimensional coordinate system, and draws a curve with time as the horizontal axis and energy consumption as the vertical axis, so as to generate an energy consumption curve of the non-intelligent device.
As shown in fig. 8, as a preferred embodiment of the present invention, the energy efficiency evaluation module 400 includes:
the data interception unit 401 is configured to obtain real-time energy consumption data, intercept the real-time energy consumption data, and obtain segmented energy consumption data.
In this step, the data interception unit 401 obtains real-time energy consumption data, where the real-time energy consumption data is obtained by statistics of electric meters disposed inside the company, and intercepts the real-time energy consumption data according to a preset interception interval, for example, an interception interval is taken as one minute, so as to intercept the real-time energy consumption data, and obtain a plurality of segment energy consumption data.
The actual energy consumption calculation unit 402 is configured to determine energy consumption analysis time information according to the segmented energy consumption data, and generate actual energy consumption data according to the intelligent device energy consumption curve, the non-intelligent device energy consumption curve and the energy consumption analysis time information.
In this step, the actual energy consumption calculating unit 402 determines energy consumption analysis time information according to the segment energy consumption data, for example, the starting time of the first segment energy consumption data is 10:00, the ending time thereof is 10:01, so as to obtain corresponding time information, and generates actual energy consumption data according to the intelligent device energy consumption curve, the non-intelligent device energy consumption curve and the energy consumption analysis time information, that is, intercepts the curves in the corresponding time periods in the intelligent device energy consumption curve and the non-intelligent device energy consumption curve according to the energy consumption analysis time information, so as to calculate and obtain the actual energy consumption data.
The anomaly determination unit 403 is configured to calculate a matching degree between the actual energy consumption data and the segmented energy consumption data, perform energy efficiency evaluation according to the matching degree, and determine whether the energy efficiency data is normal.
In this step, the anomaly determination unit 403 calculates a matching degree between the actual energy consumption data and the segment energy consumption data, where the matching degree is a ratio of the actual energy consumption data to the segment energy consumption data, compares the ratio with a preset value, and determines that the energy efficiency data is normal when the ratio is greater than the preset value, if the preset value is 0.9, and indicates that the energy efficiency data is normal when the ratio of the actual energy consumption data to the segment energy consumption data is greater than 0.9.
It should be understood that, although the steps in the flowcharts of the embodiments of the present invention are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in various embodiments may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.
Claims (2)
1. A method for integrated energy efficiency data management, the method comprising:
acquiring gateway monitoring data, wherein the gateway monitoring data comprises intelligent equipment data and non-intelligent equipment data;
analyzing the intelligent equipment data, identifying the model and the operation mode of the intelligent equipment, and generating an intelligent equipment energy consumption curve;
analyzing the intelligent equipment data, recording the model, the operation parameters and the operation modes of each intelligent equipment in the intelligent equipment data, extracting the operation parameters to determine the intelligent equipment which is running at the current moment, and enumerating through a list;
inquiring a device database according to the model of the intelligent device, inquiring one by one according to the model of the intelligent device, determining an operation mode and operation parameters of the intelligent device, inquiring the device database according to the model of the intelligent device to obtain corresponding matching items, storing energy consumption conditions of the intelligent device operated under various different conditions in the matching items, and further screening the matching items according to the operation mode and the operation parameters of the current intelligent device to determine real-time energy consumption parameters of the current intelligent device under the current environment conditions;
determining the energy consumption of the intelligent equipment in each time period according to the time sequence, dividing the minimum time interval, dividing the time according to the minimum time interval, further determining the real-time energy consumption parameters corresponding to each minimum time interval, and generating an intelligent equipment energy consumption curve;
analyzing the data of the non-intelligent equipment, identifying the model of the non-intelligent equipment, and generating an energy consumption curve of the non-intelligent equipment;
analyzing data of the non-intelligent equipment, in the non-intelligent equipment, starting to send the data to the gateway in the running process, judging whether the gateway is started or not according to the data sent by the gateway, and determining the model of the non-intelligent equipment according to the network address of the non-intelligent equipment;
inquiring a device database according to the model of the non-intelligent device, wherein the device database stores the working energy consumption of all the non-intelligent devices, and the working energy consumption is average energy consumption;
determining the energy consumption of the non-intelligent equipment in each time period according to the time sequence, constructing a two-dimensional coordinate system, and drawing a curve by taking time as a horizontal axis and the energy consumption as a vertical axis to generate an energy consumption curve of the non-intelligent equipment;
based on the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve, carrying out energy efficiency evaluation, judging whether actual energy consumption data are normal or not, and if not, sending out an energy efficiency data abnormal alarm;
the step of evaluating the energy efficiency based on the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve and judging whether the actual energy consumption data are normal or not specifically comprises the following steps:
acquiring real-time energy consumption data, and intercepting the real-time energy consumption data to obtain segmented energy consumption data;
determining energy consumption analysis time information according to the segmented energy consumption data, and generating actual energy consumption data according to the intelligent equipment energy consumption curve, the non-intelligent equipment energy consumption curve and the energy consumption analysis time information;
calculating the matching degree between the actual energy consumption data and the segmented energy consumption data, carrying out energy efficiency evaluation according to the matching degree, and judging whether the actual energy consumption data is normal or not;
the matching degree is the ratio of actual energy consumption data to segmented energy consumption data;
calculating the matching degree between the actual energy consumption data and the sectional energy consumption data, wherein the matching degree is the ratio of the actual energy consumption data to the sectional energy consumption data, comparing the ratio with a preset value, and judging that the energy efficiency data is normal when the ratio is larger than the preset value, otherwise, indicating that the energy efficiency data is abnormal;
intercepting curves in corresponding time periods in the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve according to the energy consumption analysis time information so as to calculate and obtain actual energy consumption data.
2. An integrated energy efficiency data management system, the system comprising:
the data acquisition module is used for acquiring gateway monitoring data, wherein the gateway monitoring data comprises intelligent equipment data and non-intelligent equipment data;
the first equipment analysis module is used for analyzing the intelligent equipment data, identifying the model and the operation mode of the intelligent equipment and generating an intelligent equipment energy consumption curve;
analyzing the intelligent equipment data, recording the model, the operation parameters and the operation modes of each intelligent equipment in the intelligent equipment data, extracting the operation parameters to determine the intelligent equipment which is running at the current moment, and enumerating through a list;
inquiring a device database according to the model of the intelligent device, inquiring one by one according to the model of the intelligent device, determining an operation mode and operation parameters of the intelligent device, inquiring the device database according to the model of the intelligent device to obtain corresponding matching items, storing energy consumption conditions of the intelligent device operated under various different conditions in the matching items, and further screening the matching items according to the operation mode and the operation parameters of the current intelligent device to determine real-time energy consumption parameters of the current intelligent device under the current environment conditions;
determining the energy consumption of the intelligent equipment in each time period according to the time sequence, dividing the minimum time interval, dividing the time according to the minimum time interval, further determining the real-time energy consumption parameters corresponding to each minimum time interval, and generating an intelligent equipment energy consumption curve;
the second equipment analysis module is used for analyzing the data of the non-intelligent equipment, identifying the model of the non-intelligent equipment and generating an energy consumption curve of the non-intelligent equipment;
analyzing data of the non-intelligent equipment, in the non-intelligent equipment, starting to send the data to the gateway in the running process, judging whether the gateway is started or not according to the data sent by the gateway, and determining the model of the non-intelligent equipment according to the network address of the non-intelligent equipment;
inquiring a device database according to the model of the non-intelligent device, wherein the device database stores the working energy consumption of all the non-intelligent devices, and the working energy consumption is average energy consumption;
determining the energy consumption of the non-intelligent equipment in each time period according to the time sequence, constructing a two-dimensional coordinate system, and drawing a curve by taking time as a horizontal axis and the energy consumption as a vertical axis to generate an energy consumption curve of the non-intelligent equipment;
the energy efficiency evaluation module is used for performing energy efficiency evaluation based on the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve, judging whether actual energy consumption data are normal or not, and if the actual energy consumption data are abnormal, sending out an energy efficiency data abnormal alarm;
the energy efficiency evaluation module comprises:
the data interception unit is used for acquiring real-time energy consumption data and intercepting the real-time energy consumption data to obtain segmented energy consumption data;
the actual energy consumption calculation unit is used for determining energy consumption analysis time information according to the segmented energy consumption data and generating actual energy consumption data according to the intelligent equipment energy consumption curve, the non-intelligent equipment energy consumption curve and the energy consumption analysis time information;
the abnormality judging unit is used for calculating the matching degree between the actual energy consumption data and the segmented energy consumption data, carrying out energy efficiency evaluation according to the matching degree and judging whether the actual energy consumption data is normal or not;
the matching degree is the ratio of actual energy consumption data to segmented energy consumption data;
calculating the matching degree between the actual energy consumption data and the sectional energy consumption data, wherein the matching degree is the ratio of the actual energy consumption data to the sectional energy consumption data, comparing the ratio with a preset value, and judging that the energy efficiency data is normal when the ratio is larger than the preset value, otherwise, indicating that the energy efficiency data is abnormal;
intercepting curves in corresponding time periods in the intelligent equipment energy consumption curve and the non-intelligent equipment energy consumption curve according to the energy consumption analysis time information so as to calculate and obtain actual energy consumption data.
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