CN114526537B - Equipment energy-saving control method and device - Google Patents
Equipment energy-saving control method and device Download PDFInfo
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- CN114526537B CN114526537B CN202111661488.9A CN202111661488A CN114526537B CN 114526537 B CN114526537 B CN 114526537B CN 202111661488 A CN202111661488 A CN 202111661488A CN 114526537 B CN114526537 B CN 114526537B
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- 238000000034 method Methods 0.000 title claims abstract description 43
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 83
- 238000005457 optimization Methods 0.000 claims abstract description 35
- 238000004378 air conditioning Methods 0.000 claims description 33
- 238000004146 energy storage Methods 0.000 claims description 31
- 238000004590 computer program Methods 0.000 claims description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 11
- 238000010438 heat treatment Methods 0.000 claims description 8
- 238000005057 refrigeration Methods 0.000 claims description 3
- 230000008569 process Effects 0.000 description 7
- 238000012545 processing Methods 0.000 description 7
- 238000005265 energy consumption Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
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- 238000013528 artificial neural network Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000001816 cooling Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000009423 ventilation Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/54—Control or safety arrangements characterised by user interfaces or communication using one central controller connected to several sub-controllers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/30—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring
- F24F11/49—Control or safety arrangements for purposes related to the operation of the system, e.g. for safety or monitoring ensuring correct operation, e.g. by trial operation or configuration checks
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/56—Remote control
- F24F11/58—Remote control using Internet communication
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
- F24F11/61—Control or safety arrangements characterised by user interfaces or communication using timers
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/65—Electronic processing for selecting an operating mode
- F24F11/67—Switching between heating and cooling modes
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/70—Control systems characterised by their outputs; Constructional details thereof
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F2110/00—Control inputs relating to air properties
- F24F2110/10—Temperature
- F24F2110/12—Temperature of the outside air
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
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- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
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- Human Computer Interaction (AREA)
- Physics & Mathematics (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The disclosure relates to the technical field of air conditioners, and provides an equipment energy-saving control method and device, wherein the method comprises the following steps: calculating water capacity based on the acquired basic parameters, and calculating average water temperature during starting based on the water capacity and the acquired internet of things data; determining the working mode of the equipment according to the average water temperature at the starting time; determining whether the working condition meets the standard or not based on the working mode; if the working condition meets the standard, acquiring an advanced shutdown time strategy; based on the advanced shutdown time strategy, the advanced shutdown optimization percentage is updated to adjust the advanced shutdown time of the equipment, so that the advanced shutdown time of the air conditioner is changed according to the load demand, the residual energy is fully utilized, the power consumption of the air conditioner is reduced, and the aim of saving the energy is achieved.
Description
Technical Field
The disclosure relates to the technical field of air conditioners, in particular to an equipment energy-saving control method and device.
Background
Building energy consumption, industrial energy consumption and traffic energy consumption are combined to form main aspects of energy consumption in China, the building energy consumption generally refers to operation consumption in buildings such as heating, air conditioning and lighting, most of the building energy consumption is concentrated on the application of air conditioning, and most of currently adopted air conditioning ventilation systems use heating ventilation air conditioning or central air conditioning systems, and after the air conditioning is stopped, residual energy enters the atmosphere, so that a large amount of energy is wasted.
In the prior art, a site control system controls an air conditioning system to set early shutdown time, and a cryopump operates according to the set time until the delay time is reached. However, once the time is set in this way, the time will be in a fixed state, the early shutdown time cannot be changed, and the energy storage of the air conditioning system is not fully utilized.
Disclosure of Invention
In view of this, the embodiments of the present disclosure provide a device energy-saving control method, device, electronic device, and computer readable storage medium, so as to solve the problem in the prior art that the device shutdown time can only be set fixedly in advance, and the energy storage of the air conditioning system is not fully utilized.
In a first aspect of an embodiment of the present disclosure, there is provided an apparatus power saving control method, including:
calculating water capacity based on the acquired basic parameters, and calculating average water temperature during starting based on the water capacity and the acquired internet of things data;
determining the working mode of the equipment according to the average water temperature at the starting time;
determining whether the working condition meets the standard or not based on the working mode;
if the working condition meets the standard, acquiring an advanced shutdown time strategy;
based on the advanced shutdown time strategy, the advanced shutdown optimization percentage is updated to adjust the advanced shutdown time of the device.
In a second aspect of the embodiments of the present disclosure, there is provided an apparatus for saving energy of a device, including:
the acquisition module is configured to calculate water capacity based on the acquired basic parameters and calculate average water temperature at starting based on the water capacity and the acquired internet of things data;
the working mode determining module is configured to determine the working mode of the equipment according to the average water temperature at the starting time;
the judging module is configured to determine whether the working condition meets the standard or not based on the working mode;
the strategy generation module is configured to acquire an advanced shutdown time strategy if the working condition meets the standard;
and the updating module is configured to update the advanced shutdown optimization percentage based on the advanced shutdown time strategy so as to adjust the advanced shutdown time of the equipment.
In a third aspect of the disclosed embodiments, an electronic device is provided, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the above method when the computer program is executed.
In a fourth aspect of the disclosed embodiments, a computer-readable storage medium is provided, which stores a computer program which, when executed by a processor, implements the steps of the above-described method.
Compared with the prior art, the beneficial effects of the embodiment of the disclosure at least comprise: according to the embodiment of the disclosure, the basic parameters are acquired, the water capacity is calculated, the average water temperature during starting is calculated based on the water capacity and the pre-acquired internet of things data, the equipment working mode is judged according to the average water temperature during starting, whether the working condition meets the standard is judged based on the working mode, the advanced shutdown time strategy is acquired under the condition that the working condition meets the standard is determined, the advanced shutdown time optimization percentage is updated based on the advanced shutdown time strategy, so that the advanced shutdown time of the air conditioner is adjusted, the advanced shutdown time of the air conditioner is changed according to the load demand, the residual energy is fully utilized, the power consumption of the air conditioner is reduced, and the purpose of saving the energy is achieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are required for the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.
Fig. 1 is a schematic flow chart of an apparatus energy-saving control method according to an embodiment of the disclosure;
fig. 2 is a schematic flowchart of an apparatus energy saving control method according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an energy-saving control device for equipment according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the disclosed embodiments. However, it will be apparent to one skilled in the art that the present disclosure may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail. All other embodiments, which are obtained by a person skilled in the art based on the described embodiments of the invention, fall within the scope of protection of the invention. The technical means used in the examples are conventional means well known to those skilled in the art unless otherwise indicated.
The technical scheme of the embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.
The air conditioner consumes energy, and because the air conditioner is directly stopped after running, the rest energy does not play a role in the air conditioning system before the next system running. The air conditioner can be operated in a delayed manner through the refrigerating pump, namely, the air conditioner is shut down in advance, and the air conditioner is influenced by a plurality of factors, such as the number of users, the water capacity, the indoor and outdoor temperature difference and the like, and the load requirements of the same system on different dates are different, so that the load requirements of the air conditioner are continuously changed, and the shut down time in advance is required to be adjusted according to the different load requirements.
However, in the prior art, the control method of the air conditioning system is single, the user selects to advance the shutdown time, the shutdown time is usually fixed after the setting, and after the air conditioning water system is shut down, the cryopump is operated according to the set time delay until the delay time expires. The air conditioner can not adjust the shutdown time in advance according to the load demand, so that energy waste is caused, and the power consumption is increased.
The embodiment of the disclosure provides an energy-saving control method for equipment, which comprises the steps of obtaining basic parameters, calculating water capacity, calculating average water temperature during starting based on the water capacity and pre-acquired internet of things data, judging an equipment working mode according to the average water temperature during starting, judging whether working conditions reach standards based on the working mode, determining whether the working conditions reach standards, obtaining an advanced shutdown time strategy, updating an advanced shutdown time optimization percentage based on the advanced shutdown time strategy, so as to adjust the advanced shutdown time of an air conditioner, enable the advanced shutdown time of the air conditioner to change according to load requirements, fully utilize residual energy, reduce the power consumption of the air conditioner and achieve the purpose of saving energy.
Fig. 1 is a schematic flow chart of an apparatus energy-saving control method according to an embodiment of the disclosure. As shown in fig. 1, the apparatus power saving control method includes:
step S101, calculating water capacity based on the acquired basic parameters, and calculating average water temperature at starting based on the water capacity and the acquired internet of things data.
The user inputs main use parameters according to the use requirement on a user interface provided by the air conditioning system, and the main use parameters at least comprise: air conditioning building area, original system downtime, algorithm start-up advance time. The input air conditioner building area refers to the building area occupied by the air conditioner position in the commodity room. The building area is generally about 85%, and the air-conditioning building area is contained within 85% of the building area. The building area of the air conditioner can be calculated according to the proportion of the occupied building area, and the proportion can be divided into: hotel restaurants account for 70-80%; office building, exhibition center accounting for 65-80%; theatre, club accounting for 75-85%; 15-35% of hospitals; 50-65% of shops. After the air-conditioning building area is obtained, the downtime of the original system is input, and the time is accurate to minutes. The algorithm start advance time is set as desired by the user, e.g., 10 minutes, 15 minutes, 30 minutes, 60 minutes, etc.
After inputting the basic parameters, the user can select whether to start the algorithm program, if so, the air conditioning system calculates the air conditioning water capacity according to the input use parameters, and the water capacity is divided into a use side water capacity and a cooling side water capacity, and in this embodiment, the use side water capacity is mainly calculated.
And acquiring the Internet of things data in real time through a data acquisition device, wherein the Internet of things data at least comprises measurement point data and equipment attribute information. The data of the measuring points can also change according to the different types of the equipment. The measurement point data includes, but is not limited to, at least one of average temperature, indoor temperature and water capacity of the intermediate carrier during shutdown, and the equipment attribute information can be equipment model, equipment type, heating capacity, refrigerating capacity and the like. The apparatus is exemplified by air conditioning apparatus, and the type of air conditioning includes, but is not limited to, a wall-mounted air conditioner, a cabinet air conditioner, a ceiling air conditioner, a window air conditioner, a central air conditioner, and the like.
And automatically selecting the required data of the Internet of things during calculation, and calculating by combining the obtained water capacity at the use side to obtain the average water temperature during starting.
Step S102, determining the working mode of the equipment according to the average water temperature at the starting time.
According to the average water temperature at the starting time, the air conditioning system judges whether the air conditioning system is in a refrigerating mode or a heating mode at the moment,
the specific judging process comprises the following steps:
when the outdoor temperature is more than or equal to T1, judging whether the air conditioner is refrigerated, if so, determining that the working mode of the air conditioner is a refrigeration mode;
wherein T1 may be 25 ℃;
and when the outdoor temperature is less than T2, judging whether the air conditioner heats, and if so, starting a heating mode.
Wherein T2 may be 15 ℃.
The temperature standard set for the air conditioning apparatus is different, and the conditions under which the cooling mode and the heating mode are turned on are different, which is not particularly limited herein.
Step S103, judging whether the working condition meets the standard or not based on the working mode.
After the working mode of the air conditioner is determined, the advanced shutdown time is obtained according to the algorithm prediction of the air conditioning system, if the advanced shutdown time is lower than the preset time, the advanced shutdown is not needed to be executed, the condition that the working condition does not reach the standard at the moment is judged, and the machine is shut down according to the original system shutdown time. If the advanced shutdown time accords with the set range of the advanced shutdown time of the air conditioner according to the algorithm prediction of the air conditioning system, judging that the working condition meets the standard at the moment.
The air conditioner is set in advance in the shutdown time range, so that the setting time is too long to avoid, and the optimization effect cannot be realized.
And step S104, if the working condition meets the standard, acquiring an advanced shutdown time strategy.
Firstly, according to the average water temperature during starting and the average water temperature during stopping, the energy storage temperature difference is calculated, and the water capacity of the use side is combined, so that the energy storage capacity is calculated. And calculating the system load rate and the load demand during the shutdown according to the collected internet of things data. Then, based on the stored energy and the load demand, a desired advanced shutdown time is calculated. Based on the advanced shutdown time optimization percentage, a recommended advanced shutdown time is calculated. And further, according to the expected advanced shutdown time and the recommended advanced shutdown time, obtaining an advanced shutdown time strategy, and generating the advanced shutdown time of the equipment.
Executing the advanced shutdown time strategy, and performing advanced shutdown according to the advanced shutdown time.
Step S105, based on the advanced power-off time strategy, updating the advanced power-off time optimization percentage to adjust the advanced power-off time of the equipment.
And calculating the average water temperature of the system after the shutdown, and calculating the actual energy storage temperature difference according to the average water temperature during the shutdown and the average water temperature during the startup. Based on the actual energy storage temperature difference and the expected energy storage temperature difference, calculating and updating the advanced shutdown optimization percentage, and based on the updated shutdown optimization percentage, determining new advanced shutdown time and ending the operation. The first default value of the advanced shutdown optimization percentage is 100%, and the later advanced shutdown optimization percentage is updated according to the actual running condition.
In this embodiment, the early shutdown optimization percentage is updated through algorithm self-learning, the algorithm adopts an intelligent self-learning model (such as a supervised neural network, an unsupervised neural network, etc.), and based on a historical database, the intelligent self-learning model is trained to obtain an updated early shutdown time percentage, and the intelligent self-learning model is obtained by combining an early shutdown strategy. After the historical advanced shutdown time record is obtained, the updated advanced shutdown optimization percentage is obtained through a self-learning model, the new advanced shutdown time is further obtained, and the new advanced shutdown strategy is determined based on the new advanced shutdown time. With the updating of the database and the improvement of the integrity, the obtained early shutdown time is more accurate. The application effect after the shutdown time is changed in advance can be compared in terms of the running efficiency of the refrigerating pump, the utilization rate of residual energy and the like, and the shutdown time strategy in advance is further improved in comparison.
In the embodiment of the disclosure, the adjustment of the advanced shutdown time of the air conditioning system can be realized through an algorithm and internet of things data, and also can be realized through a cloud edge combination mode. The current execution main body realizes operation through the cloud, calculates the advanced shutdown time by using the trained model, updates the advanced optimization percentage, and optimizes the advanced shutdown time. For edge computing, the edge device can only process local data, and cannot realize global computing. In practical application, information fusion still needs to be realized by means of a cloud platform. Therefore, cloud edge bonding is becoming an important support for industrial internet development. By having intelligent devices installed and connected in an edge computing environment, processing mission critical data and responding in real time, the device itself acts as a center to provide data, and analysis takes place on the device, so the delay is almost zero. With this newly added functionality, data processing becomes decentralized and network traffic is greatly reduced. The cloud may later collect these data for a second round of evaluation, processing, and in-depth analysis.
According to the energy saving method of the equipment, basic parameters are obtained, the water capacity is calculated, the average water temperature during starting is calculated based on the water capacity and the pre-collected internet of things data, the working mode of the equipment is judged according to the average water temperature during starting, whether the working condition meets the standard or not is judged based on the working mode, the working condition meets the standard or not is determined, an advanced shutdown time strategy is obtained, and the advanced shutdown optimization percentage is updated based on the advanced shutdown time strategy so as to adjust the advanced shutdown time. The air conditioner is powered off in advance and the time is changed according to the load demand, so that the residual energy is fully utilized, the power consumption of the air conditioner is reduced, and the purpose of saving the energy is achieved. Meanwhile, the calculated early shutdown time can be used for predicting the load demand of the user side after early shutdown, and different early shutdown time strategies are provided for the user according to the load demands of different air conditioning equipment. The early shutdown time strategy is not only applied to small hanging air conditioners in families, but also used for predicting the air conditioner load demands in large buildings such as markets, write buildings and the like, and reduces the power consumption cost. Meanwhile, excessive use of air conditioning equipment in extreme weather can be avoided, and the service life of the air conditioner is prolonged.
Further, the advanced shutdown time is obtained, the operation of executing the advanced shutdown can be closed according to the calculated advanced shutdown time in a manual mode, or the system can respond to the instruction of the advanced shutdown time according to the set advanced shutdown time and execute the advanced shutdown operation according to the set advanced shutdown time.
Further, the optimization percentage of shutdown in advance can be limited by setting an upper limit value and a lower limit value, so that parameter tuning is guaranteed to be in a certain range, normal operation of equipment is guaranteed, and the equipment is prevented from being damaged due to overlarge tuning time span.
In some embodiments, the method further comprises: after determining the strategy of the new shutdown time, executing the strategy of the advanced shutdown time, and if the air conditioning equipment is not shutdown on time according to the generated advanced shutdown time, detecting the air conditioning equipment, so as to ensure the normal operation of the air conditioning equipment; or after long-term operation, the air conditioning equipment acquires inaccurate data sensors, so that the calculated early shutdown time does not meet the actual load requirement of the air conditioner, and a prompt needs to be sent to a system to remind a worker to perform manual inspection or update a database, and an inherent algorithm model is optimized, so that the accuracy of early shutdown time calculation is realized.
Any combination of the above optional solutions may be adopted to form an optional embodiment of the present application, which is not described herein in detail.
Fig. 2 is a schematic flow chart of a specific embodiment of an apparatus energy-saving control method according to an embodiment of the disclosure. As shown in fig. 2, the method comprises the steps of:
s201, calculating water capacity based on the acquired basic parameters, and calculating average water temperature at starting based on the water capacity and the acquired internet of things data.
S202, determining the working mode of the equipment according to the average water temperature at the starting time.
When the outdoor temperature is more than or equal to T1, judging whether the air conditioner is refrigerated, if so, determining that the working mode of the air conditioner is a refrigeration mode;
and when the outdoor temperature is less than T2, judging whether the air conditioner heats, and if so, determining that the working mode of the air conditioner is a heating mode.
S203, based on the working mode, determining whether the working condition meets the standard.
If the early shutdown is not needed, the method comprises the following steps:
s204, determining that the working condition does not reach the standard, shutting down according to the original system downtime, and proceeding to step 209.
If the power-off is needed in advance, the method comprises the following steps:
s205, determining that the working condition meets the standard, and calculating the expected energy storage temperature difference, energy storage capacity, system load rate and load demand.
S206, calculating expected early shutdown time based on the energy storage amount and the load demand, and calculating recommended early shutdown time based on the early shutdown time optimization percentage.
S207, obtaining an advanced shutdown strategy based on the expected advanced shutdown time and the recommended advanced shutdown time.
S208, executing an early shutdown strategy and early shutdown.
S209, ending the operation.
S210, calculating the average water temperature of the system after shutdown;
s211, calculating an actual energy storage temperature difference based on the average water temperature during shutdown and the average water temperature during startup;
s212, calculating and updating the optimization percentage of the early shutdown based on the actual energy storage temperature difference and the expected energy storage temperature difference, and determining the new early shutdown time.
Fig. 3 is a schematic structural diagram of an apparatus for saving energy of a device according to an embodiment of the present disclosure. As shown in fig. 3, the energy saving device for early shutdown of the air conditioner includes an acquisition module 301, a working mode determination 302, a judgment module 303, a policy generation module 304 and an update module 305. Wherein the obtaining module 301 is configured to calculate the water capacity based on the obtained basic parameters, and calculate the average water temperature at the time of starting based on the water capacity and the collected internet of things data. The determination module 302 is configured to determine the operating mode of the device based on the average water temperature at start-up. The determine compliance module 303 is configured to determine whether the operating conditions are met based on the operating mode. The generation policy module 304 is configured to obtain the early shutdown time policy if the operating condition meets the criterion. The update module 305 is configured to update the early shutdown optimization percentage to adjust the early shutdown time of the device based on the early shutdown time policy.
Further, the acquisition module 301 is specifically configured to: the basic parameters are acquired, at least comprising: the building area of the air conditioner, the shutdown time of the original system and the starting advance time of the algorithm, and the water capacity is the water capacity at the use side; the pre-collected internet of things data at least comprises: measurement point data and equipment attribute information.
Further, the determine achievement module 303 is specifically configured to: the judging standard is whether the air conditioner needs to be shut down in advance according to the requirement of the air conditioner; if the machine needs to be powered off in advance, the working condition meets the standard; if the system does not need to be shut down in advance, the working condition is not up to standard, the working condition is determined to be not up to standard, and if the working condition is determined to be not up to standard, the system is shut down according to the original system downtime.
Further, the generation policy module 304 is specifically configured to: calculating expected energy storage temperature difference, energy storage amount, system load rate and load demand; calculating expected early shutdown time based on the energy storage capacity and the load demand; calculating recommended early shutdown time based on the early shutdown time optimization percentage; wherein, the optimization percentage of the early shutdown time is 100 percent, and the default value of the initial early shutdown optimization time is 100 percent; based on the expected advanced shutdown time and the recommended advanced shutdown time, an advanced shutdown strategy is obtained, the advanced shutdown strategy is executed, and the advanced shutdown is performed according to the advanced shutdown time.
Further, the update module 305 is specifically configured to: calculating data of a system after the shutdown, wherein the data of the system after the shutdown is average water temperature of the system after the shutdown, and calculating actual energy storage temperature difference based on the average water temperature during the shutdown and the average water temperature during the starting; based on the expected energy storage temperature difference and the actual energy storage temperature difference, the advanced shutdown optimization percentage is calculated and updated, and based on the updated shutdown optimization percentage, the new advanced shutdown time is determined.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not constitute any limitation on the implementation process of the embodiments of the disclosure.
Fig. 4 is a schematic structural diagram of an electronic device 4 provided in an embodiment of the present disclosure. As shown in fig. 4, the electronic apparatus 4 of this embodiment includes: a processor 401, a memory 402 and a computer program 403 stored in the memory 402 and executable on the processor 401. The steps of the various method embodiments described above are implemented by processor 401 when executing computer program 403. Alternatively, the processor 401, when executing the computer program 403, performs the functions of the modules/units in the above-described apparatus embodiments.
Illustratively, the computer program 403 may be partitioned into one or more modules/units, which are stored in the memory 402 and executed by the processor 401 to complete the present disclosure. One or more of the modules/units may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the computer program 403 in the electronic device 4.
The electronic device 4 may be a desktop computer, a notebook computer, a palm computer, a cloud server, or the like. The electronic device 4 may include, but is not limited to, a processor 401 and a memory 402. It will be appreciated by those skilled in the art that fig. 4 is merely an example of the electronic device 4 and is not meant to be limiting of the electronic device 4, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the electronic device may also include an input-output device, a network access device, a bus, etc.
The processor 401 may be a central processing unit (Central Processing Unit, CPU) or other general purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 402 may be an internal storage unit of the electronic device 4, for example, a hard disk or a memory of the electronic device 4. The memory 402 may also be an external storage device of the electronic device 4, for example, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the electronic device 4. Further, the memory 402 may also include both internal storage units and external storage devices of the electronic device 4. The memory 402 is used to store computer programs and other programs and data required by the electronic device. The memory 402 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
In the embodiments provided in the present disclosure, it should be understood that the disclosed apparatus/computer device and method may be implemented in other manners. For example, the apparatus/computer device embodiments described above are merely illustrative, e.g., the division of modules or elements is merely a logical functional division, and there may be additional divisions of actual implementations, multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present disclosure may implement all or part of the flow of the method of the above-described embodiments, or may be implemented by a computer program to instruct related hardware, and the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of the method embodiments described above. The computer program may comprise computer program code, which may be in source code form, object code form, executable file or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the jurisdiction's jurisdiction and the patent practice, for example, in some jurisdictions, the computer readable medium does not include electrical carrier signals and telecommunication signals according to the jurisdiction and the patent practice.
The above embodiments are merely for illustrating the technical solution of the present disclosure, and are not limiting thereof; although the present disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the disclosure, and are intended to be included in the scope of the present disclosure.
Claims (7)
1. A method for power saving control of a device, comprising:
calculating water capacity based on the acquired basic parameters, and calculating average water temperature at starting based on the water capacity and the acquired internet of things data;
determining the working mode of the equipment according to the average water temperature during starting;
determining whether the working condition meets the standard or not based on the working mode, wherein the judging standard is whether the air conditioner needs to be shut down in advance or not, if so, the working condition meets the standard, and if not, the working condition does not meet the standard;
if the working condition meets the standard, acquiring expected energy storage temperature difference, energy storage capacity, system load rate and load demand, calculating expected early shutdown time based on the energy storage capacity and the load demand, and calculating recommended early shutdown time based on the early shutdown time optimization percentage, wherein the default value of the initial early shutdown time optimization percentage is 100%; acquiring an advanced shutdown time strategy based on the expected advanced shutdown time and the recommended advanced shutdown time;
updating the advanced shutdown optimization percentage based on the advanced shutdown time strategy to adjust the advanced shutdown time of the equipment; the method specifically comprises the following steps:
acquiring the average water temperature of the system after shutdown;
calculating an actual energy storage temperature difference based on the average water temperature at the stop and the average water temperature at the start;
based on the expected energy storage temperature difference and the actual energy storage temperature difference, calculating and updating the optimization percentage of shutdown in advance,
and determining new advanced shutdown time based on the updated shutdown optimization percentage.
2. The method of claim 1, wherein the obtaining basic parameters, calculating a water volume, and calculating an average water temperature at start-up based on the water volume and the collected internet of things data, comprises:
obtaining basic parameters, wherein the basic parameters at least comprise: air conditioner building area, original system downtime and algorithm starting advance time;
collecting internet of things data, wherein the internet of things data at least comprises: measuring point data and equipment attribute information;
acquiring a water capacity of a use side based on the basic parameters and the internet of things data;
and calculating the average water temperature at the starting time based on the basic parameters, the Internet of things data and the water capacity at the using side.
3. The method of claim 1, wherein said determining the operating mode of the device based on said average water temperature at start-up comprises:
and judging that the current air conditioning system belongs to a refrigeration mode or a heating mode based on the average water temperature during starting.
4. The method of claim 1, wherein after the step of determining whether the operating condition meets the standard based on the operating mode, further comprises:
if the working condition does not reach the standard, the system is shut down according to the original system downtime.
5. An apparatus energy saving control device, characterized by comprising:
the acquisition module is configured to calculate water capacity based on the acquired basic parameters and calculate average water temperature at starting based on the water capacity and the acquired internet of things data;
the working mode determining module is configured to determine the working mode of the equipment according to the average water temperature during starting;
the judging module is configured to determine whether the working condition meets the standard or not based on the working mode, wherein the judging standard is whether the air conditioner needs to be shut down in advance or not, if the air conditioner needs to be shut down in advance, the working condition meets the standard, and if the air conditioner does not need to be shut down in advance, the working condition does not meet the standard;
the strategy generation module is configured to acquire expected energy storage temperature difference, energy storage capacity, system load rate and load demand if the working condition meets the standard, calculate expected early shutdown time based on the energy storage capacity and the load demand, and calculate recommended early shutdown time based on the early shutdown time optimization percentage, wherein the default value of the initial early shutdown optimization time percentage is 100%; acquiring an advanced shutdown time strategy based on the expected advanced shutdown time and the recommended advanced shutdown time;
the updating module is configured to update the advanced shutdown optimization percentage based on the advanced shutdown time strategy so as to adjust the advanced shutdown time of the equipment; the method specifically comprises the following steps: acquiring the average water temperature of the system after shutdown; calculating an actual energy storage temperature difference based on the average water temperature at the stop and the average water temperature at the start; and calculating and updating an advanced shutdown optimization percentage based on the expected energy storage temperature difference and the actual energy storage temperature difference, and determining a new advanced shutdown time based on the updated shutdown optimization percentage.
6. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 4 when the computer program is executed.
7. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 4.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012241948A (en) * | 2011-05-18 | 2012-12-10 | Panasonic Corp | Air conditioner |
| CN205783575U (en) * | 2016-05-31 | 2016-12-07 | 深圳市新环能科技有限公司 | Based on prediction central air conditioner system optimal downtime and the energy conserving system of analysis |
| CN106779321A (en) * | 2016-11-28 | 2017-05-31 | 新奥泛能网络科技股份有限公司 | A kind of energy supply control method and device based on energy supplying system |
| CN109084426A (en) * | 2018-08-14 | 2018-12-25 | 广东美的暖通设备有限公司 | The control method of air-conditioning system, the control device of air-conditioning system and air-conditioning system |
| CN113739390A (en) * | 2021-09-30 | 2021-12-03 | 上海美控智慧建筑有限公司 | Air conditioner control method and device and electronic equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130125572A1 (en) * | 2011-11-18 | 2013-05-23 | Cooper Technologies Company | Efficiency heating, ventilating, and air conditioning through indirect extension of compressor run times |
-
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012241948A (en) * | 2011-05-18 | 2012-12-10 | Panasonic Corp | Air conditioner |
| CN205783575U (en) * | 2016-05-31 | 2016-12-07 | 深圳市新环能科技有限公司 | Based on prediction central air conditioner system optimal downtime and the energy conserving system of analysis |
| CN106779321A (en) * | 2016-11-28 | 2017-05-31 | 新奥泛能网络科技股份有限公司 | A kind of energy supply control method and device based on energy supplying system |
| CN109084426A (en) * | 2018-08-14 | 2018-12-25 | 广东美的暖通设备有限公司 | The control method of air-conditioning system, the control device of air-conditioning system and air-conditioning system |
| CN113739390A (en) * | 2021-09-30 | 2021-12-03 | 上海美控智慧建筑有限公司 | Air conditioner control method and device and electronic equipment |
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