CN114967887A - Energy consumption management method, device and equipment based on industrial intelligence and storage medium - Google Patents
Energy consumption management method, device and equipment based on industrial intelligence and storage medium Download PDFInfo
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Abstract
The invention discloses an energy consumption management method, device, equipment and storage medium based on industrial intelligence. The method comprises the following steps: acquiring actual operation energy consumption of the equipment to be detected; acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the equipment to be detected; comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result; and when judging that the equipment to be detected has abnormal energy consumption according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy. According to the invention, the actual operation energy consumption of the equipment to be detected is compared with the reference energy consumption in the historical energy consumption data, and the operation state of the equipment to be detected is adjusted according to the preset energy-saving strategy when the condition that the equipment to be detected has abnormal energy consumption is judged according to the comparison result. Compared with the existing mode of stopping equipment operation for maintenance when abnormal energy consumption is detected, the mode provided by the invention can improve the efficiency of energy consumption management, and further improve the operation efficiency of the equipment.
Description
Technical Field
The invention relates to the technical field of energy consumption management, in particular to an energy consumption management method, device, equipment and storage medium based on industrial intelligence.
Background
Energy has become an indispensable essential element of human society. With the increasing shortage of energy and the deterioration of environment, the acquisition of economical, convenient and environment-friendly energy becomes an urgent problem related to human survival and sustainable development. In public areas such as homes, offices, schools and the like, the consumption of energy such as water, electricity, gas, oil and the like is large, and based on this, energy consumption management is imperative. At present, when an existing energy consumption management system manages energy consumption data, the function is single, and an application function of the energy consumption data is lacked, so that the energy consumption management system has an application function of the energy consumption data, can dynamically manage and control energy consumption, and becomes a technical problem to be solved by technical staff in the field.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide an energy consumption management method, an energy consumption management device, energy consumption equipment and a storage medium based on industrial intelligence, and aims to solve the technical problem that the operation efficiency of the equipment is not high due to the lack of application of energy consumption data in the prior art.
In order to achieve the above object, the present invention provides an energy consumption management method based on industrial intelligence, the method comprising the steps of:
acquiring actual operation energy consumption of the equipment to be detected;
acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the equipment to be detected;
comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result;
and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy.
Optionally, the step of obtaining the reference energy consumption from the historical energy consumption data according to the environmental information and the production information of the device to be detected includes:
acquiring the current environmental information and production information of the equipment to be detected;
selecting a target scene where the equipment to be detected is currently located based on preset scene classification information according to the environment information and the production information, wherein the preset scene classification information comprises at least one scene and scene parameters corresponding to the scene;
and acquiring equipment energy consumption information in the historical energy consumption data under the target scene, and determining reference energy consumption according to the equipment energy consumption information.
Optionally, the step of comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result includes:
determining the actual total energy consumption of the equipment to be detected at each moment in a preset statistical period according to the actual operation energy consumption;
and comparing the actual total energy consumption with the corresponding total energy consumption in the reference energy consumption to obtain a comparison result.
Optionally, when it is determined that the equipment to be detected has abnormal energy consumption according to the comparison result, the step of adjusting the operating state of the equipment to be detected according to a preset energy-saving strategy includes:
determining an energy consumption difference value according to the comparison result;
judging whether the equipment to be detected has energy consumption abnormity or not according to the energy consumption difference value and a preset energy consumption fluctuation threshold value;
and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy.
Optionally, when it is determined that the equipment to be detected has abnormal energy consumption according to the comparison result, the step of adjusting the operating state of the equipment to be detected according to a preset energy-saving strategy includes:
when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, module energy consumption information of each module of the equipment to be detected is obtained;
acquiring a target energy consumption range of each module;
judging whether the energy consumption of the module is in the target energy consumption range or not according to the module energy consumption information;
if not, acquiring the function information of the module in the equipment to be detected;
selecting a replacement module matched with the function information from preset modules to be selected;
and adjusting the running state of the equipment to be detected according to the running parameters of the replacing module.
Optionally, after the step of obtaining module energy consumption information of each module of the device to be detected when it is determined that the device to be detected has abnormal energy consumption according to the comparison result, the method further includes:
acquiring the normal power of the module;
judging whether the module is abnormal or not according to the module energy consumption information and the normal power;
when the module is judged to be abnormal, operation and maintenance personnel are prompted to detect the module, and a detection result is obtained;
and judging whether the module is replaced or not according to the detection result and a preset judgment standard.
Optionally, the step of determining whether the module is abnormal according to the module energy consumption information and the normal power includes:
judging whether the actual power of the module is greater than the normal power or not according to the module energy consumption information;
when the actual power of the module is larger than the normal power and the module has no fault setting time, judging that the module is abnormal;
when the actual power of the module is larger than the normal power but the module has fault setting time, acquiring target duration that the actual power of the module is larger than the normal power;
and when the target duration is greater than or equal to the fault setting time of the module, judging that the module is abnormal.
In addition, to achieve the above object, the present invention also provides an energy consumption management apparatus based on industrial intelligence, the apparatus comprising:
the acquisition module is used for acquiring the actual operation energy consumption of the equipment to be detected;
the acquisition module is further used for acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the device to be detected;
the comparison module is used for comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result;
and the adjusting module is used for adjusting the running state of the equipment to be detected according to a preset energy-saving strategy when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result.
In addition, to achieve the above object, the present invention further provides an energy consumption management device based on industrial intelligence, the device comprising: a memory, a processor, and an industrial intelligence based energy consumption management program stored on the memory and executable on the processor, the industrial intelligence based energy consumption management program configured to implement the steps of the industrial intelligence based energy consumption management method as described above.
In addition, to achieve the above object, the present invention further provides a storage medium, on which an industrial intelligence-based energy consumption management program is stored, and the industrial intelligence-based energy consumption management program, when executed by a processor, implements the steps of the industrial intelligence-based energy consumption management method as described above.
The method comprises the steps of obtaining actual operation energy consumption of equipment to be detected; acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the equipment to be detected; comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result; and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy. According to the invention, the actual operation energy consumption of the equipment to be detected is compared with the reference energy consumption in the historical energy consumption data, and the operation state of the equipment to be detected is adjusted according to the preset energy-saving strategy when the condition that the equipment to be detected has abnormal energy consumption is judged according to the comparison result. Compared with the existing mode of stopping equipment operation for maintenance when abnormal energy consumption is detected, the mode provided by the invention can improve the efficiency of energy consumption management, and further improve the operation efficiency of the equipment.
Drawings
FIG. 1 is a schematic diagram of an industrial intelligence-based energy consumption management device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of the method for energy consumption management based on industrial intelligence according to the present invention;
FIG. 3 is a schematic flow chart of a second embodiment of the industrial intelligence-based energy consumption management method of the present invention;
FIG. 4 is a schematic flow chart of a third embodiment of the industrial intelligence-based energy consumption management method of the present invention;
FIG. 5 is a block diagram of a first embodiment of an industrial intelligence-based energy management device according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an industrial intelligence-based energy consumption management device of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the industrial intelligence-based energy consumption management apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (WI-FI) interface). The Memory 1005 may be a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation of an industrial intelligence based energy consumption management apparatus and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and an industrial intelligence-based energy consumption management program.
In the industrial intelligence-based energy consumption management apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the industrial intelligence based energy consumption management device may be disposed in the industrial intelligence based energy consumption management device, and the industrial intelligence based energy consumption management device invokes the industrial intelligence based energy consumption management program stored in the memory 1005 through the processor 1001 and executes the industrial intelligence based energy consumption management method provided by the embodiment of the present invention.
Based on the above energy consumption management device based on the industrial intelligence, an embodiment of the present invention provides an energy consumption management method based on the industrial intelligence, and referring to fig. 2, fig. 2 is a schematic flow diagram of a first embodiment of the energy consumption management method based on the industrial intelligence according to the present invention.
In this embodiment, the energy consumption management method based on industrial intelligence includes the following steps:
step S10: and acquiring the actual operation energy consumption of the equipment to be detected.
It should be noted that the execution subject of the embodiment may be a computing service device with data processing, network communication and program running functions, such as a mobile phone, a tablet computer, a personal computer, etc., or an electronic device or an energy consumption management device capable of implementing the above functions. The present embodiment and the following embodiments will be described below by taking the energy consumption management apparatus as an example.
It should be noted that the equipment to be detected can be equipment which needs energy consumption supervision, the equipment to be detected can be composed of a plurality of modules, and each module can play different functions. The actual operation energy consumption may be energy consumption information generated by the device to be detected in the operation process, for example, information such as power consumption and coal consumption at each time.
Step S20: and acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the equipment to be detected.
It should be noted that the environment information may be an environment parameter where the device to be detected is currently located, and may include: temperature, humidity, brightness, etc. The production information can be product information of a product currently produced by the equipment to be detected, and comprises information such as a product model, a product procedure and production parameters of the product, and the production parameters of the product can comprise information such as an ambient temperature, a humidity, an operation speed and efficiency of the equipment to be detected and the like required when the product is produced. The historical energy consumption data can be energy consumption information of the device to be detected in a historical operation process. The reference information may be energy consumption information matched with the environmental information and the production information in the historical energy consumption data. For example, if the environmental information is high temperature and the model number produced in the production information is a, the reference information may be energy consumption information corresponding to the product with the model number a produced at high temperature in the historical energy consumption data.
Step S30: and comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result.
It should be noted that, the comparing the actual operation energy consumption with the reference energy consumption may be determining an energy consumption difference between the actual operation energy consumption and the reference energy consumption in a preset period, and taking the energy consumption difference as the comparison result. The preset period may be a preset comparison period, for example, one day or several hours.
Further, in order to obtain a more accurate comparison result, the step S30 may include: determining the actual total energy consumption of the equipment to be detected at each moment in a preset statistical period according to the actual operation energy consumption; and comparing the actual total energy consumption with the corresponding total energy consumption in the reference energy consumption to obtain a comparison result.
It should be noted that the preset statistical period may be a preset statistical period, and may be a day or several hours, which is not limited herein. The actual total energy consumption may be the total energy consumption of the device under test at each moment, for example, the total energy consumption of the device under test between two points and three points is 200, and the total energy consumption between three points and four points is 300. The total energy consumption corresponding to each time point in the reference energy consumption may be total energy consumption corresponding to each time point in the reference energy consumption.
Step S40: and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy.
It should be noted that, when the energy consumption difference in the comparison result is greater than the preset energy consumption difference threshold, it may be determined that the equipment to be detected has energy consumption abnormality. The preset energy consumption difference threshold value can be a preset energy consumption difference value, the preset energy saving strategy can be energy consumption for closing unnecessary modules in the equipment to be detected, for example, when the temperature is lower than or in the normal operation temperature range of the equipment to be detected, the heat dissipation module of the equipment to be detected is closed, energy consumption is reduced, when the equipment to be detected works in the daytime, the illumination module in the equipment to be detected is closed, energy consumption is reduced, and when the equipment to be detected is in idle running or has no actual output, the equipment to be detected is closed.
Further, in order to accurately determine whether the device to be detected has an energy consumption abnormality, the step S40 may include: determining an energy consumption difference value according to the comparison result; judging whether the equipment to be detected has energy consumption abnormity or not according to the energy consumption difference value and a preset energy consumption fluctuation threshold value; and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy.
It should be noted that the preset energy consumption fluctuation threshold may be a preset energy consumption threshold, and is used to determine whether the equipment to be detected has energy consumption abnormality.
The embodiment acquires the actual operation energy consumption of the equipment to be detected; acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the equipment to be detected; comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result; and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy. According to the embodiment, the actual operation energy consumption of the equipment to be detected is compared with the reference energy consumption in the historical energy consumption data, and when the fact that the equipment to be detected is abnormal in energy consumption is judged according to the comparison result, the operation state of the equipment to be detected is adjusted according to the preset energy-saving strategy. Compared with the existing mode of stopping equipment operation for maintenance when abnormal energy consumption is detected, the mode of the embodiment can improve the efficiency of energy consumption management, and further improve the operation efficiency of the equipment.
Referring to fig. 3, fig. 3 is a schematic flow chart of a second embodiment of the energy consumption management method based on industrial intelligence according to the present invention.
Based on the first embodiment described above, in the present embodiment, the step S40 includes:
step S401: and when judging that the equipment to be detected has abnormal energy consumption according to the comparison result, acquiring the module energy consumption information of each module of the equipment to be detected.
It should be noted that the module can be each module that equipment to be detected contains, for example, equipment to be detected includes modules such as lighting module, heat dissipation module, transmission module, humidification module and welding. The module energy consumption information may be energy consumption information of each module in the device to be inspected.
Further, the energy consumption of the module increases, may be because the module ages or there is the energy consumption increase that the trouble leads to the module, consequently, in order to avoid leading to the energy consumption increase when the module moves because of the trouble of module, after step S401, still include: acquiring the normal power of the module; judging whether the module is abnormal or not according to the module energy consumption information and the normal power; when the module is judged to be abnormal, operation and maintenance personnel are prompted to detect the module, and a detection result is obtained; and judging whether the module is replaced or not according to the detection result and a preset judgment standard.
It should be noted that the normal power may be a power when the module normally operates, or a normal power of the module calculated according to the historical energy consumption information of the module. The step of judging whether the module is abnormal or not according to the module energy consumption information and the normal power can be that the actual power of the module is calculated according to the module energy consumption information, whether the actual power is larger than the normal power or not is judged, if so, when the module is judged to be abnormal, operation and maintenance personnel are prompted to detect the module, and a detection result is obtained; the determining whether to replace the module according to the detection result and the preset criterion may be determining whether to replace the module according to a module fault level in the detection result and a preset criterion, for example, if the preset criterion is that the fault level is below B, the module is not replaced for the moment, and if the fault level is above B, the module is replaced.
Further, in order to improve the accuracy of determining whether the module is abnormal, the step of determining whether the module is abnormal according to the module energy consumption information and the normal power includes: judging whether the actual power of the module is greater than the normal power or not according to the module energy consumption information; when the actual power of the module is larger than the normal power and the module has no fault setting time, judging that the module is abnormal; when the actual power of the module is larger than the normal power but the module has fault setting time, acquiring a target duration that the actual power of the module is larger than the normal power; and when the target duration is greater than or equal to the fault setting time of the module, judging that the module is abnormal.
It should be noted that the fault setting time may be a preset time length for accurately determining whether the module is faulty, for example, the fault setting time of the module is 10 seconds, when the actual power of the module is greater than the normal power, at this time, it is not directly determined that the module is faulty, but a preset timer is started to start timing, the actual power of the module is counted to be greater than the time length of the normal power, when the time length of the module that is greater than the normal power is equal to 10 seconds, it is determined that the module is faulty, within the 10 seconds, when the actual power of the module is less than or equal to the normal power, the preset timer is cleared, and when the actual power of the module is greater than the normal power, timing is restarted. The target duration may be a duration during which the actual power of the module is greater than the normal power.
Step S402: and acquiring the target energy consumption range of each module.
It should be noted that the target energy consumption range may be an energy consumption range calculated according to the normal power of the module when the module normally operates, or an energy consumption average value of the module is calculated according to historical energy consumption information of the module, and the target energy consumption range is determined according to the energy consumption average value and a preset fluctuation threshold, where the preset fluctuation threshold may be a preset energy consumption fluctuation value, for example, the energy consumption average value is 40, and the preset fluctuation threshold is 10, and the target energy consumption range is 30-50.
Step S403: and judging whether the energy consumption of the module is in the target energy consumption range or not according to the module energy consumption information.
It should be noted that, the determining, according to the module energy consumption information, whether the energy consumption of the module is within the target energy consumption range may be determining whether the energy consumption value at each time in the module energy consumption information of the module is within the target energy consumption range.
Step S404: if not, acquiring the functional information of the module in the equipment to be detected.
It should be noted that the function information may be a function of the module in the operation process of the device to be detected, for example, the module is used for heat dissipation, welding, transmission or humidification when the device to be detected operates.
Step S405: and selecting a replacement module matched with the function information from preset modules to be selected.
It should be noted that the preset candidate module may be a preset standby module. The replacement module may be a module having a function matching the function in the function information, for example, the currently used module has a function of lighting, and the replacement module may be an energy saving lamp; the function of the module that uses at present is the heat dissipation, and the replacement module can be the module that has the heat dissipation function and whole energy consumption is less than the energy consumption of current module such as air conditioner or fan.
Step S406: and adjusting the running state of the equipment to be detected according to the running parameters of the replacing module.
It should be noted that the operation parameters and the use efficiency of the replacement module and the replaced original module may be different, and therefore, after the original module is replaced by the replacement module in the equipment to be detected, in order not to affect the operation of the equipment to be detected, the operation state of the equipment to be detected needs to be adjusted according to the operation parameters of the replacement module. For example, the original module dissipates heat through a plurality of fans, but the replacement module dissipates heat through an air conditioner, the heat dissipation efficiency is improved, and the operation speed or the operation power of the equipment to be detected can be properly improved in order to improve the overall efficiency of the equipment to be detected.
According to the embodiment, when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, the module energy consumption information of each module of the equipment to be detected is obtained; acquiring a target energy consumption range of each module; judging whether the energy consumption of the module is in the target energy consumption range or not according to the module energy consumption information; if not, acquiring the function information of the module in the equipment to be detected; selecting a replacement module matched with the function information from preset modules to be selected; and adjusting the running state of the equipment to be detected according to the running parameters of the replacing module. The method comprises the steps of judging whether the energy consumption of a module is in a target energy consumption range of the module by acquiring module energy consumption information of each module of equipment to be detected, and if not, acquiring function information of the module in the equipment to be detected; selecting a replacement module matched with the function information from preset modules to be selected; and adjusting the running state of the equipment to be detected according to the running parameters of the replacing module. This embodiment reduces the energy consumption of waiting to detect equipment through replacing the unusual module of energy consumption in waiting to detect equipment with the replacement module, and then improves energy utilization.
Referring to fig. 4, fig. 4 is a schematic flow chart of a third embodiment of the energy consumption management method based on industrial intelligence according to the present invention.
Based on the foregoing embodiments, in this embodiment, the step S20 includes:
step S201: and acquiring the current environment information and production information of the equipment to be detected.
Step S202: and selecting a current target scene of the equipment to be detected based on preset scene classification information according to the environment information and the production information, wherein the preset scene classification information comprises at least one scene and scene parameters corresponding to the scene.
It should be noted that the preset scene classification information may be scene parameter information of each scene and scenario set in advance based on the historical environment and the historical production information of the device to be detected. For example, the preset scene classification information includes: high temperature scenario a: the corresponding scene parameter is that the temperature is more than 20 ℃, and the model of the produced product is A; low-temperature scene B: the corresponding scene parameter is that the temperature is less than 10 ℃, and the model of the produced product is B.
Step S203: and acquiring equipment energy consumption information in the historical energy consumption data under the target scene, and determining reference energy consumption according to the equipment energy consumption information.
It should be noted that the device energy consumption information may be energy consumption information in the historical energy consumption data in the target scenario, for example, the target scenario is a scenario in which the temperature is greater than 20 degrees celsius and the produced product model is a, and the energy consumption data corresponding to the scenario in which the temperature is greater than 20 degrees celsius and the produced product model is a is obtained from the historical energy consumption data and is used as the device energy consumption information. The determining of the reference energy consumption according to the equipment energy consumption information may be to perform processing such as filling, parsing or sorting on the equipment energy consumption information to obtain the reference energy consumption. The filling processing may be to fill missing data in the device energy consumption information with preset occupancy information.
The embodiment acquires the current environmental information and production information of the equipment to be detected; selecting a target scene where the equipment to be detected is currently located based on preset scene classification information according to the environment information and the production information, wherein the preset scene classification information comprises at least one scene and scene parameters corresponding to the scene; and acquiring equipment energy consumption information in the historical energy consumption data under the target scene, and determining reference energy consumption according to the equipment energy consumption information. According to the embodiment, the equipment energy consumption information corresponding to the current target scene is acquired from the historical energy consumption data through the current environment information and the current production information of the equipment to be detected, so that when the actual operation energy consumption is compared with the reference energy consumption, the acquired comparison result is more accurate, and the energy consumption management efficiency is improved.
Referring to fig. 5, fig. 5 is a block diagram illustrating a first embodiment of an energy consumption management device based on industrial intelligence according to the present invention.
As shown in fig. 5, the energy consumption management apparatus based on industrial intelligence according to an embodiment of the present invention includes:
the acquisition module 10 is used for acquiring the actual operation energy consumption of the equipment to be detected;
the obtaining module 10 is further configured to obtain reference energy consumption from historical energy consumption data according to the environmental information and the production information of the device to be detected;
the comparison module 20 is configured to compare the actual operation energy consumption with the reference energy consumption to obtain a comparison result;
and the adjusting module 30 is configured to adjust the operation state of the device to be detected according to a preset energy saving strategy when it is determined that the device to be detected has abnormal energy consumption according to the comparison result.
The method comprises the steps of obtaining actual operation energy consumption of a device to be detected; acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the equipment to be detected; comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result; and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy. According to the embodiment, the actual operation energy consumption of the equipment to be detected is compared with the reference energy consumption in the historical energy consumption data, and when the fact that the equipment to be detected is abnormal in energy consumption is judged according to the comparison result, the operation state of the equipment to be detected is adjusted according to the preset energy-saving strategy. Compared with the existing mode of stopping equipment operation for maintenance when abnormal energy consumption is detected, the mode of the embodiment can improve the efficiency of energy consumption management, and further improve the operation efficiency of the equipment.
It should be noted that the above-described work flows are only exemplary, and do not limit the scope of the present invention, and in practical applications, a person skilled in the art may select some or all of them to achieve the purpose of the solution of the embodiment according to actual needs, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may be referred to the energy consumption management method based on industrial intelligence provided in any embodiment of the present invention, and are not described herein again.
Based on the first embodiment of the energy consumption management device based on the industrial intelligence, a second embodiment of the energy consumption management device based on the industrial intelligence is provided.
In this embodiment, the obtaining module 10 is further configured to obtain environmental information and production information of the current location of the device to be detected; selecting a target scene where the equipment to be detected is currently located based on preset scene classification information according to the environment information and the production information, wherein the preset scene classification information comprises at least one scene and scene parameters corresponding to the scene; and acquiring equipment energy consumption information in the historical energy consumption data under the target scene, and determining reference energy consumption according to the equipment energy consumption information.
Further, the comparison module 20 is further configured to determine, according to the actual operating energy consumption, an actual total energy consumption of the device to be detected at each time within a preset statistical period; and comparing the actual total energy consumption with the corresponding total energy consumption in the reference energy consumption to obtain a comparison result.
Further, the adjusting module 30 is further configured to determine an energy consumption difference according to the comparison result; judging whether the equipment to be detected has energy consumption abnormity or not according to the energy consumption difference value and a preset energy consumption fluctuation threshold value; and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy.
Further, the adjusting module 30 is further configured to obtain module energy consumption information of each module of the device to be detected when it is determined that the device to be detected has abnormal energy consumption according to the comparison result; acquiring a target energy consumption range of each module; judging whether the energy consumption of the module is in the target energy consumption range or not according to the module energy consumption information; if not, acquiring the function information of the module in the equipment to be detected; selecting a replacement module matched with the function information from preset modules to be selected; and adjusting the running state of the equipment to be detected according to the running parameters of the replacing module.
Further, the adjusting module 30 is further configured to obtain a normal power of the module; judging whether the module is abnormal or not according to the module energy consumption information and the normal power; when the module is judged to be abnormal, operation and maintenance personnel are prompted to detect the module, and a detection result is obtained; and judging whether the module is replaced or not according to the detection result and a preset judgment standard.
Further, the adjusting module 30 is further configured to determine whether the actual power of the module is greater than the normal power according to the module energy consumption information; when the actual power of the module is larger than the normal power and the module has no fault setting time, judging that the module is abnormal; when the actual power of the module is larger than the normal power but the module has fault setting time, acquiring a target duration that the actual power of the module is larger than the normal power; and when the target duration is greater than or equal to the fault setting time of the module, judging that the module is abnormal.
Other embodiments or specific implementation manners of the energy consumption management device based on the industrial intelligence of the present invention may refer to the above method embodiments, and are not described herein again.
In addition, an embodiment of the present invention further provides a storage medium, where the storage medium stores an energy consumption management program based on industrial intelligence, and the energy consumption management program based on industrial intelligence, when executed by a processor, implements the steps of the energy consumption management method based on industrial intelligence described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., a rom/ram, a magnetic disk, an optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An energy consumption management method based on industrial intelligence is characterized by comprising the following steps:
acquiring actual operation energy consumption of the equipment to be detected;
acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the equipment to be detected;
comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result;
and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy.
2. The industrial intelligence-based energy consumption management method according to claim 1, wherein the step of obtaining the reference energy consumption from the historical energy consumption data according to the environmental information and the production information of the device under test comprises:
acquiring the current environmental information and production information of the equipment to be detected;
selecting a target scene where the equipment to be detected is currently located based on preset scene classification information according to the environment information and the production information, wherein the preset scene classification information comprises at least one scene and scene parameters corresponding to the scene;
and acquiring equipment energy consumption information in the historical energy consumption data under the target scene, and determining reference energy consumption according to the equipment energy consumption information.
3. The industrial intelligence-based energy consumption management method of claim 2, wherein the step of comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result comprises:
determining the actual total energy consumption of the equipment to be detected at each moment in a preset statistical period according to the actual operation energy consumption;
and comparing the actual total energy consumption with the corresponding total energy consumption in the reference energy consumption to obtain a comparison result.
4. The energy consumption management method based on industrial intelligence as claimed in claim 1, wherein said step of adjusting the operation status of the device to be tested according to a preset energy saving strategy when it is determined that the device to be tested has abnormal energy consumption according to the comparison result comprises:
determining an energy consumption difference value according to the comparison result;
judging whether the equipment to be detected has energy consumption abnormity or not according to the energy consumption difference value and a preset energy consumption fluctuation threshold value;
and when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, adjusting the running state of the equipment to be detected according to a preset energy-saving strategy.
5. The energy consumption management method based on the industrial intelligence as claimed in any one of claims 1-4, wherein the step of adjusting the operation state of the device to be detected according to a preset energy saving strategy when the device to be detected is judged to have the abnormal energy consumption according to the comparison result comprises:
when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result, module energy consumption information of each module of the equipment to be detected is obtained;
acquiring a target energy consumption range of each module;
judging whether the energy consumption of the module is in the target energy consumption range or not according to the module energy consumption information;
if not, acquiring the function information of the module in the equipment to be detected;
selecting a replacement module matched with the function information from preset modules to be selected;
and adjusting the running state of the equipment to be detected according to the running parameters of the replacing module.
6. The energy consumption management method based on industrial intelligence of claim 5, wherein after the step of obtaining the module energy consumption information of each module of the device to be detected when the device to be detected is determined to have abnormal energy consumption according to the comparison result, the method further comprises:
acquiring the normal power of the module;
judging whether the module is abnormal or not according to the module energy consumption information and the normal power;
when the module is judged to be abnormal, operation and maintenance personnel are prompted to detect the module, and a detection result is obtained;
and judging whether the module is replaced or not according to the detection result and a preset judgment standard.
7. The industrial intelligence-based energy consumption management method according to claim 6, wherein the step of determining whether the module has an abnormality according to the module energy consumption information and the normal power comprises:
judging whether the actual power of the module is greater than the normal power or not according to the module energy consumption information;
when the actual power of the module is larger than the normal power and the module has no fault setting time, judging that the module has abnormity;
when the actual power of the module is larger than the normal power but the module has fault setting time, acquiring a target duration that the actual power of the module is larger than the normal power;
and when the target duration is greater than or equal to the fault setting time of the module, judging that the module is abnormal.
8. An industrial intelligence-based energy consumption management apparatus, comprising:
the acquisition module is used for acquiring the actual operation energy consumption of the equipment to be detected;
the acquisition module is further used for acquiring reference energy consumption from historical energy consumption data according to the environmental information and the production information of the device to be detected;
the comparison module is used for comparing the actual operation energy consumption with the reference energy consumption to obtain a comparison result;
and the adjusting module is used for adjusting the running state of the equipment to be detected according to a preset energy-saving strategy when the energy consumption abnormality of the equipment to be detected is judged according to the comparison result.
9. An industrial intelligence-based energy consumption management device, the device comprising: a memory, a processor, and an industrial intelligence based energy consumption management program stored on the memory and executable on the processor, the industrial intelligence based energy consumption management program configured to implement the steps of the industrial intelligence based energy consumption management method of any of claims 1 to 7.
10. A storage medium having stored thereon an industrial intelligence based energy consumption management program, which when executed by a processor, performs the steps of the industrial intelligence based energy consumption management method of any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116205467A (en) * | 2023-04-28 | 2023-06-02 | 扬州市职业大学(扬州开放大学) | High-efficiency consumption management system and method based on industrial Internet of things |
| CN117408500A (en) * | 2023-12-15 | 2024-01-16 | 南京雅宸众联电力技术有限公司 | Substation energy management method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120072187A1 (en) * | 2010-09-21 | 2012-03-22 | Scott Irving | System for evaluating energy consumption |
| CN106444541A (en) * | 2016-11-23 | 2017-02-22 | 天津生态城绿色建筑研究院有限公司 | Intellectualized monitoring and operation optimization method and system of green building |
| WO2020107851A1 (en) * | 2018-11-29 | 2020-06-04 | 天津大学 | Low-cost commissioning method and system for air conditioning system based on existing large-scale public building |
| CN114110434A (en) * | 2021-11-23 | 2022-03-01 | 中海石油气电集团有限责任公司 | Online digital energy-saving diagnosis and regulation and control method and system for LNG receiving station |
-
2022
- 2022-08-01 CN CN202210913639.3A patent/CN114967887A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120072187A1 (en) * | 2010-09-21 | 2012-03-22 | Scott Irving | System for evaluating energy consumption |
| CN106444541A (en) * | 2016-11-23 | 2017-02-22 | 天津生态城绿色建筑研究院有限公司 | Intellectualized monitoring and operation optimization method and system of green building |
| WO2020107851A1 (en) * | 2018-11-29 | 2020-06-04 | 天津大学 | Low-cost commissioning method and system for air conditioning system based on existing large-scale public building |
| CN114110434A (en) * | 2021-11-23 | 2022-03-01 | 中海石油气电集团有限责任公司 | Online digital energy-saving diagnosis and regulation and control method and system for LNG receiving station |
Non-Patent Citations (1)
| Title |
|---|
| 李秀芳: "基于生产设备全要素能耗数据的挖掘与应用系统设计", 《信息与电脑(理论版)》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116205467A (en) * | 2023-04-28 | 2023-06-02 | 扬州市职业大学(扬州开放大学) | High-efficiency consumption management system and method based on industrial Internet of things |
| CN117408500A (en) * | 2023-12-15 | 2024-01-16 | 南京雅宸众联电力技术有限公司 | Substation energy management method |
| CN117408500B (en) * | 2023-12-15 | 2024-02-27 | 南京雅宸众联电力技术有限公司 | Substation energy management method |
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