CN114995543B - Method and device for controlling environment regulating equipment through artificial intelligence AI - Google Patents
Method and device for controlling environment regulating equipment through artificial intelligence AI Download PDFInfo
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- CN114995543B CN114995543B CN202210604661.XA CN202210604661A CN114995543B CN 114995543 B CN114995543 B CN 114995543B CN 202210604661 A CN202210604661 A CN 202210604661A CN 114995543 B CN114995543 B CN 114995543B
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- G05D23/19—Control of temperature characterised by the use of electric means
- G05D23/1927—Control of temperature characterised by the use of electric means using a plurality of sensors
- G05D23/193—Control of temperature characterised by the use of electric means using a plurality of sensors sensing the temperaure in different places in thermal relationship with one or more spaces
- G05D23/1931—Control of temperature characterised by the use of electric means using a plurality of sensors sensing the temperaure in different places in thermal relationship with one or more spaces to control the temperature of one space
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Abstract
The application provides a method and a device for controlling environment regulating equipment through artificial intelligence AI, and relates to the technical field of energy-saving control. The method comprises the following steps: the method comprises the steps of obtaining a first parameter set, inputting the first parameter set and a first control strategy into a first model to obtain a second control strategy, wherein the first control strategy is obtained by inputting the second parameter set into the second model, the second control strategy is used for controlling each environmental conditioning device in a first room, the second parameter set is basic static data and does not change within a certain period of time in the same room, so that the first control strategy in the same room is unchanged, the first parameter set is environmental dynamic data and changes within a certain period of time in the same room, a more accurate second control strategy can be obtained according to the first parameter set and the first control strategy, and different second parameter sets and different first control strategies can be obtained in different rooms, so that the fine control of the environmental conditioning devices in different environments in different rooms is realized, and energy conservation and emission reduction are realized.
Description
Technical Field
The application belongs to the technical field of energy-saving control, and particularly relates to a method and a device for controlling environment regulating equipment through artificial intelligence AI.
Background
At present, for the problems of high energy consumption and 24h online operation of indoor environment adjusting equipment in some scenes, the energy-saving control method mainly adopted is as follows: the traditional frequency-fixing equipment is replaced by the frequency-conversion equipment by adopting the frequency conversion technology, and the frequency-conversion equipment automatically performs frequency conversion operation according to the indoor temperature condition, so that the indoor temperature adjustment is realized, and the environment adjustment equipment is prevented from being in high-frequency operation for a long time. However, in this way, after the indoor temperature is adjusted to the required range, the environment-adjusting device is operated at a low frequency, and the environment-adjusting device is in an operating state but has little effect on the temperature adjustment, so that the environment-adjusting device is in an ineffective operation, resulting in an increase in energy consumption. In this way, the environmental conditioning equipment can be controlled to start and stop through the temperature, but under the condition of frequent temperature change, the environmental conditioning equipment can be caused to start and stop frequently, so that the service life of the environmental conditioning equipment is influenced, meanwhile, the power consumption of the equipment can be increased in the process of frequent equipment starting, the energy-saving effect of indoor equipment cannot be well achieved, and the method for controlling the start and stop of the environmental conditioning equipment according to the temperature is single, the applicability is poor, and the control flexibility is poor.
Disclosure of Invention
The application provides a method and a device for controlling environment regulating equipment through artificial intelligence AI, which can realize the fine control of the environment regulating equipment in different indoor environments, thereby realizing energy conservation and emission reduction.
To achieve the above object, in a first aspect, the present application provides a method of controlling an environmental conditioning apparatus through an artificial intelligence AI, the method comprising:
The first device obtains a first set of parameters, the first set of parameters comprising: at least two of a current operation duration of each environment adjusting device in the M1 environment adjusting devices, a current season, a current indoor temperature in the first room, a corresponding outdoor current outdoor temperature in the first room, a current temperature of a heat radiating device in the first room, a current temperature in a cabinet in the first room or a current operation state of each environment adjusting device in the first room, wherein the M1 environment adjusting devices are used for adjusting the temperature in the first room, and M1 is a positive integer;
The first device inputs a first parameter set and a first control strategy into a first model to obtain a second control strategy, wherein the first control strategy is obtained by inputting a second parameter set into a second model, and the second parameter set comprises: at least one of an area in the first chamber, M1, a technical parameter of each environmental conditioning device in the first chamber, or a location of each environmental conditioning device in the first chamber, a second control strategy is used to control the M1 environmental conditioning devices, the first model and the second model being different artificial intelligence (ARTIFICIAL INTELLIGENCE, AI) models.
Optionally, the method further comprises:
The first equipment acquires a second parameter set;
The first device inputs the second parameter set into the second model to obtain a first control strategy.
Optionally, the method further comprises:
The method comprises the steps that first equipment obtains ith sample data, wherein the ith sample data comprises an ith parameter set, an ith control strategy, an ith 'parameter set and an ith' control strategy;
the first device determines an ith model according to the ith parameter set and the ith control strategy, wherein the ith model is used for obtaining a second model;
the first device determines an ith model according to an ith control strategy, an ith parameter set and an ith control strategy, wherein the ith model is used for obtaining the first model;
Wherein the i-th parameter set includes: at least one of an area in the ith chamber, a number Mi of environmental conditioning devices in the ith chamber, a technical parameter of each environmental conditioning device in the ith chamber, or a location of each environmental conditioning device in the ith chamber; the i' th parameter set includes: at least two of an operation duration of each environmental conditioning device in the Mi environmental conditioning devices, a season corresponding to the ith sample data, a current indoor temperature in the ith room, a current outdoor temperature corresponding to the ith room, a current temperature of a heat dissipating device in the ith room, a current temperature in a cabinet in the ith room, or a current operation state of each environmental conditioning device in the ith room.
Optionally, the method further comprises:
the first device sends a second control strategy to the second device;
The second device controls the M1 environmental conditioning devices according to the second control strategy.
Optionally, the second device controls the M1 environmental conditioning devices according to a second control policy, including:
The second device controls the M1 environmental conditioning devices to be turned on in a rotating way according to a second control strategy, or controls the M1 environmental conditioning devices to be turned on in a stepping way, or controls the M1 environmental conditioning devices to be turned on in a linkage way.
Optionally, after the second device controls the M1 environmental conditioning devices according to the second control policy, the method further includes:
The first device receives a third set of parameters from the second device, the third set of parameters comprising: at least two of a current operation duration of each environmental conditioning device, a current season, a current indoor temperature of the first room, a corresponding outdoor current outdoor temperature of the first room, a current temperature of a heat dissipating device in the first room, a current temperature in a cabinet in the first room, or a current operation state of each environmental conditioning device in the first room;
the first device updates the first model according to the third set of parameters and the first control strategy.
Optionally, after the second device controls the M1 environmental conditioning devices according to the second control policy, the method further includes:
The second device collects a third set of parameters, the third set of parameters comprising: at least two of a current operation duration of each environmental conditioning device, a current season, a current indoor temperature of the first room, a corresponding outdoor current outdoor temperature of the first room, a current temperature of a heat dissipating device in the first room, a current temperature in a cabinet in the first room, or a current operation state of each environmental conditioning device in the first room;
The second device determines a third control strategy according to the third parameter set and the second control strategy;
the second device controls the M1 environmental conditioning devices according to the third control strategy.
Optionally, the second device controls the M1 environmental conditioning devices according to a third control policy, including:
The second device controls the M1 environmental conditioning devices to be turned on in a rotating way according to a third control strategy, or controls the M1 environmental conditioning devices to be turned on in a stepping way, or controls the M1 environmental conditioning devices to be turned on in a linkage way.
Optionally, the environmental conditioning device is an air conditioning device.
In a second aspect, the present application provides an apparatus for controlling an environmental conditioning device through an artificial intelligence AI, the apparatus comprising:
an obtaining unit, configured to obtain a first parameter set, where the first parameter set includes: the current operation duration of each environment adjusting device in the M1 environment adjusting devices, the current season, the current indoor temperature in the first room, the corresponding outdoor current outdoor temperature in the first room, the current temperature of the heat radiating device in the first room, the current temperature in the cabinet in the first room or the current operation state of each environment adjusting device in the first room are at least two, the M1 environment adjusting devices are used for adjusting the temperature in the first room, and M1 is a positive integer.
The acquisition unit is further configured to acquire a second parameter set, where the second parameter set includes: at least one of an area in the first chamber, M1, a technical parameter of each environmental conditioning device in the first chamber, or a location of each environmental conditioning device in the first chamber.
The processing unit is used for inputting the first parameter set and the first control strategy into the first model to obtain a second control strategy, the first control strategy is obtained by inputting the second parameter set into the second model, the second control strategy is used for controlling M1 environment adjusting devices, and the first model and the second model are different AI models.
In a third aspect, an embodiment of the present application provides an apparatus for controlling an environmental conditioning device by an artificial intelligence AI, including a processor coupled to a memory, the processor configured to implement a method according to the first aspect or any implementation manner of the first aspect, when executing a computer program or instructions stored in the memory.
In a fourth aspect, an embodiment of the present application provides a computer storage medium, on which a computer program is stored, which when executed by a processor, implements the method of the first aspect or any implementation manner of the first aspect.
Compared with the prior art, the embodiment of the application has the beneficial effects that: the first device acquires a first parameter set, inputs the first parameter set and a first control strategy into the first model to obtain a second control strategy, wherein the first control strategy is obtained by inputting the second parameter set into the second model, and the second control strategy is used for controlling each environmental conditioning device in a first room. Different indoor second parameter sets can be obtained, different first control strategies can be obtained by the different second parameter sets, the same indoor environment is different, and the parameter values of the first parameter sets are different, so that different second control strategies can be obtained, and the fine control of the environment regulating equipment in different indoor environments can be realized, and energy conservation and emission reduction are realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in 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 application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a method for controlling an environmental conditioning device via an artificial intelligence AI provided in an embodiment of the application;
Fig. 2 is a schematic diagram of a method for controlling an air conditioner of a base station room through an artificial intelligence AI according to an embodiment of the present application;
FIG. 3 is a schematic block diagram of an apparatus for controlling an environmental conditioning device via an artificial intelligence AI provided in accordance with an embodiment of the application;
fig. 4 is a schematic block diagram of another apparatus for controlling an environmental conditioning device via an artificial intelligence AI provided by an embodiment of the application.
Detailed Description
The following describes the technical solution in the embodiment of the present application in detail in combination with the embodiment of the present application.
It should be understood that the manner, the case, the category, and the division of the embodiments of the present application are merely for convenience of description, and do not limit the present application in any way, and the various manners, the categories, the cases, and the features of the embodiments may be combined with each other without contradiction.
It should also be understood that the terms "first," "second," "third," "fourth," and "fifth" in the examples of this application are merely for the purpose of distinguishing, and do not constitute any limitation of this application. It should also be understood that, in the embodiments of the present application, the sequence number in each process does not mean the execution sequence of the steps, and the execution sequence of the steps is determined by the logic therein, which does not limit the execution process of the embodiments of the present application in any way.
For the problems of high energy consumption and 24h online operation of indoor environment adjusting equipment in some scenes, the problem of energy consumption caused by ineffective operation in the online operation of the environment adjusting equipment 24h can be solved by controlling the start and stop of the environment adjusting equipment through temperature, but the control method can cause frequent start and stop of the environment adjusting equipment under the condition of frequent temperature change, thereby influencing the service life of the environment adjusting equipment, and meanwhile, the energy consumption of the equipment can be increased in the frequent start process of the equipment, the energy-saving effect of the indoor environment adjusting equipment cannot be well achieved, the method for starting and stopping the environment adjusting equipment according to the temperature is single, the applicability is poor, and the control flexibility is poor.
For example, for the current situation of high energy consumption of a 5G base station room air conditioner, there are various energy saving methods currently, and the main stream method is as follows: the traditional fixed-frequency air conditioner is replaced by a variable-frequency air conditioner, and the variable-frequency air conditioner automatically performs variable-frequency operation according to the indoor temperature condition, so that the temperature of a machine room is adjusted, and the air conditioner is prevented from being in high-frequency operation for a long time. However, the scheme still does not change the current situation that the air conditioner 24h is on line, and can not completely solve the energy consumption problem of invalid operation of the air conditioner. Then, aiming at the current running situation of the air conditioner 24h of the base station room, an air conditioner control solution is provided, the air conditioner is controlled by adding a temperature acquisition device and a control system to the air conditioner of the room, the control solution is generally rough, the air conditioner is controlled only according to the indoor temperature value, the air conditioner is frequently started and stopped under the condition of frequent temperature change, the service life of the air conditioner is reduced, the power consumption of the air conditioner is increased due to the fact that the starting current is large in the starting process of the air conditioner, the energy saving effect of the air conditioner is not well achieved, meanwhile, the control method of the air conditioner is single, the air conditioner control strategy of all the base station rooms is the same, the control method is difficult to adjust according to on-site comprehensive factors, and the applicability is poor.
Based on the above problems, the present application provides a method and an apparatus for controlling an environmental conditioning device through an artificial intelligence AI, where a first device obtains a first parameter set, inputs the first parameter set and a first control policy into a first model to obtain a second control policy, where the first control policy is obtained by inputting the second parameter set into the second model, and the second control policy is used to control each environmental conditioning device in a first room, where the second parameter set is basic static data and does not change in a certain time in the same room, so that the first control policy is unchanged in the same room, and the first parameter set is environmental dynamic data and changes in a certain time in the same room, and the second control policy is more accurate. Different indoor conditions can be provided with different second parameter sets, different first control strategies can be provided for the different second parameter sets, the same indoor environment is different, and the first parameter sets are different, so that different second control strategies can be provided, and the fine control of the environment regulating equipment in different indoor conditions can be realized, thereby realizing energy conservation and emission reduction.
The technical scheme of the application is described in detail below by specific examples.
Fig. 1 is a schematic diagram of a method for controlling an environmental conditioning device through an artificial intelligence AI according to an embodiment of the present application, and as shown in fig. 1, the method 100 may include the following steps:
S110, a first device acquires a first parameter set, wherein the first parameter set comprises: at least two of a current operation duration of each environment adjusting device in the M1 environment adjusting devices, a current season, a current indoor temperature in the first room, a corresponding outdoor current outdoor temperature in the first room, a current temperature of a heat radiating device in the first room, a current temperature in a cabinet in the first room or a current operation state of each environment adjusting device in the first room, wherein the M1 environment adjusting devices are used for adjusting the temperature in the first room, and M1 is a positive integer.
Optionally, the first parameter set in S110 includes: at least two of the current operation duration of each environmental conditioning device of the M1 environmental conditioning devices, the current season, the current indoor temperature in the first room, the corresponding outdoor current outdoor temperature in the first room, the current temperature of the heat dissipating device in the first room, the current temperature in the cabinet in the first room, or the current operation state of each environmental conditioning device in the first room may be understood as: the first parameter set is any two of a current operation duration of each of the M1 environmental conditioning devices, a current season, a current indoor temperature of the first room, a corresponding outdoor current outdoor temperature of the first room, a current temperature of the heat sink device in the first room, a current temperature in the cabinet in the first room, or a current operation state of each of the environmental conditioning devices in the first room, or the first parameter set is any three of a current operation duration of each of the M1 environmental conditioning devices, a current season, a current indoor temperature in the first room, a corresponding outdoor current outdoor temperature in the first room, a current temperature of the heat sink device in the first room, a current temperature in the cabinet in the first room, or a current operation state of each of the environmental conditioning devices in the first room, or the first parameter set is any four of the current operation duration of each of the M1 environmental conditioning devices, the current season, the current indoor temperature of the first room, the corresponding outdoor current outdoor temperature of the first room, the current temperature of the heat dissipation device in the first room, the current temperature of the cabinet in the first room, or the current operation state of each of the environmental conditioning devices in the first room, or the first parameter set is any five of the current operation duration of each of the M1 environmental conditioning devices, the first parameter set is any six of a current season, a current indoor temperature in the first room, a corresponding outdoor current outdoor temperature in the first room, a current temperature in a heat dissipation device in the first room, a current temperature in a cabinet in the first room, or a current running state of each environment adjustment device in the first room, or the first parameter set is a current running time of each environment adjustment device in the M1 environment adjustment devices, a current season, a current indoor temperature in the first room, a corresponding outdoor current outdoor temperature in the first room, a current temperature in the heat dissipation device in the first room, a current temperature in the cabinet in the first room, and a current running state of each environment adjustment device in the first room.
Optionally, the current operation duration of each of the M1 environmental conditioning devices in S110 refers to an operation duration from the start time to the current time in the current start operation state of each environmental conditioning device.
Alternatively, the current season in S110 may be the season when the first set of parameters was acquired, e.g., the season may be spring, summer, autumn or winter.
Alternatively, the current season in S110 may be replaced with the current month, which is the month when the first parameter set was acquired, for example, the current month may be any month of 1 month to 12 months.
Alternatively, the current indoor temperature in the first room in S110 may be the current temperature of a specific location in the first room or the current average temperature of a plurality of locations in the first room.
Alternatively, the current outdoor temperature of the outdoor corresponding to the first indoor in S110 may be the current temperature of a specific location of the outdoor, or the current average temperature of a plurality of locations of the outdoor. The outdoor corresponding to the first room may be understood as the outdoor opposite to the first room.
Alternatively, the current temperature of the heat sink in the first room in S110 may be the current temperature of a specific location of the heat sink in the first room, or the current average temperature of a plurality of locations of the heat sink.
Alternatively, the current temperature within the cabinet in the first room in S110 may be the current temperature of a particular location within the cabinet, or the current average temperature of a plurality of locations within the cabinet.
Optionally, the current temperature of the heat dissipating device in the first room and/or the current temperature in the cabinet in the first room in S110 may be a condition for triggering the actions of the M1 environmental conditioning devices in the first room, for example, when the current temperature of the heat dissipating device in the first room exceeds a preset threshold, the M1 environmental conditioning devices are triggered to execute corresponding action instructions according to the second control policy, so as to reduce the temperature of the heat dissipating device and ensure the normal operation of the heat dissipating device. For another example, when the current temperature in the first indoor cabinet exceeds a preset threshold, triggering the M1 environmental conditioning devices to execute corresponding action instructions according to a second control strategy, so as to reduce the temperature in the first indoor cabinet and ensure the safety of the first indoor cabinet. It should be noted that the first room may include only M1 environmental conditioning devices, or the first room may include M1 environmental conditioning devices and a heat dissipating device, or the first room may include M1 environmental conditioning devices and a cabinet, or the first room may include M1 environmental conditioning devices, a heat dissipating device and a cabinet.
Alternatively, the current operation state of each environment adjustment device in the first room in S110 means that each environment adjustment device is operated or turned off. It should be noted that, the current operation states of any two environmental conditioning devices in the M1 environmental conditioning devices may be the same or different, and if the current operation state of any one environmental conditioning device in the M1 environmental conditioning devices is turned off, the current operation duration of the environmental conditioning device is zero.
Alternatively, the first parameter set in S110 may be acquired by the second device and uploaded to the first device, or may be acquired by the first device directly.
Alternatively, the first device may be a cloud server or a first indoor local server.
Alternatively, the second device may be a first indoor local server or an edge computing device.
Alternatively, the environmental conditioning device is an air conditioning device, or an air circulation device.
Alternatively, the device types of any two environmental conditioning devices of the M1 environmental conditioning devices may be the same or different. Alternatively, in the case where the device types of any two of the M1 environment adjustment devices are the same, the device manufacturers and/or the model numbers of any two of the M1 environment adjustment devices may be the same or different. For example, M1 environmental conditioning devices are each air conditioning devices, and the manufacturer and/or model of any two of the M1 air conditioning devices may be the same or different. For another example, M1 environmental conditioning devices are each air circulation devices, and the manufacturer and/or model of any two of the M1 air circulation devices may be the same or different. As another example, a part of the M1 environmental conditioning apparatuses may be an air conditioning apparatus part may be an air circulation apparatus.
S120, the first device inputs a first parameter set and a first control strategy into a first model to obtain a second control strategy, wherein the first control strategy is obtained by inputting a second parameter set into the second model, and the second parameter set comprises: at least one of an area in the first chamber, M1, a technical parameter of each environmental conditioning device in the first chamber, or a location of each environmental conditioning device in the first chamber, the second control strategy being for controlling the M1 environmental conditioning devices.
Optionally, the first device acquires a second parameter set, and the first device inputs the second parameter set into the second model to obtain the first control strategy.
Optionally, the second parameter set in S120 may be acquired by the second device and uploaded to the first device, or may be acquired by the first device directly.
Optionally, under the condition that the second parameter set is unchanged and the first parameter set is changed, the first device may perform only one time to input the second parameter set into the second model to obtain the first control policy, and perform multiple times to input the first parameter set and the first control policy into the first model to obtain the second control policy, so that a redundant calculation process of inputting the second parameter set into the second model to obtain the first control policy once every time the first device performs the first parameter set and the first control policy into the first model to obtain the second control policy is avoided. It should be noted that, the first control strategy obtained in the case where the second parameter set is unchanged is also unchanged.
Optionally, the second parameter set in S120 includes: at least one of the area in the first chamber, M1, a technical parameter of each environmental conditioning device in the first chamber or a position of each environmental conditioning device in the first chamber may be understood as: the second parameter set is any one of an area in the first room, M1, a technical parameter of each environmental conditioning device in the first room, or a position of each environmental conditioning device in the first room, or the second parameter set is any two of an area in the first room, M1, a technical parameter of each environmental conditioning device in the first room, or a position of each environmental conditioning device in the first room, or the second parameter set is any three of an area in the first room, M1, a technical parameter of each environmental conditioning device in the first room, or a position of each environmental conditioning device in the first room, or the second parameter set is an area in the first room, M1, a technical parameter of each environmental conditioning device in the first room, and a position of each environmental conditioning device in the first room.
Alternatively, in the case where each environmental conditioning apparatus is an air conditioning apparatus, the technical parameter of each environmental conditioning apparatus in the first room in S120 may be a technical parameter of the air conditioning apparatus, and the technical parameter of the air conditioning apparatus includes fixed frequency or variable frequency. Optionally, when the technical parameter of the air conditioning apparatus includes a fixed frequency, the technical parameter of the air conditioning apparatus may further include at least one of a cooling capacity corresponding to the fixed frequency, a heating capacity corresponding to the fixed frequency, a cooling power corresponding to the fixed frequency, a heating power corresponding to the fixed frequency, and the like. Optionally, in the case that the technical parameter of the air conditioning apparatus includes a frequency conversion, the technical parameter of the air conditioning apparatus may further include at least one of a cooling capacity corresponding to the frequency conversion, a heating capacity corresponding to the frequency conversion, a cooling power corresponding to the frequency conversion, a heating power corresponding to the frequency conversion, and the like.
Alternatively, the position of each of the environmental conditioning devices in the first room in S120 may indicate the arrangement layout condition of the M1 environmental conditioning devices in the first room.
Alternatively, the first model and the second model in S120 are different AI models.
Alternatively, the AI model may be a neural network model, for example, the first model and/or the second model may be a neural network model.
Alternatively, before S120, the first model and/or the second model may be determined by the first device, or determined by another device and sent to the first device.
Optionally, the first device acquires L sample data, where L is greater than a preset value. Each of the L sample data may include: the fourth parameter set, the fourth control policy, the fifth parameter set, and the fifth control policy may be different from any parameter value in the fourth parameter set included in the different sample data, the fourth control policy included in the different sample data may be different from any parameter value in the fifth parameter set included in the different sample data, and the fifth control policy included in the different sample data may be different from each other. The first device may determine a model using a fourth parameter set and a fourth control policy of a number of the L sample data, update the model using the fourth parameter set and the fourth control policy of the number of the L sample data, and so on, to finally obtain the second model. Alternatively, the first device may test the resulting second model using a fourth set of parameters and a fourth control strategy for a number of the L sample data. The first device may determine another model using a fourth control strategy of a number of the L sample data, the fifth parameter set and the fifth control strategy, and update the model using the fourth control strategy of the number of the L sample data, the fifth parameter set and the fifth control strategy, and so on, to finally obtain the first model. Alternatively, the first device may test the resulting first model with a fourth control strategy, a fifth set of parameters, and a fifth control strategy for several of the L sample data.
Wherein the fourth set of parameters comprises: at least one of an area in the room, a number M2 of environmental conditioning devices in the room, a technical parameter of each environmental conditioning device in the room, or a location of each environmental conditioning device in the room, the fifth set of parameters comprises: at least two of an operation duration of each environmental adjustment setting in the room corresponding to the fourth parameter set, a season when the fifth parameter set is acquired, a current indoor temperature in the room corresponding to the fourth parameter set, a current outdoor temperature in the room corresponding to the fourth parameter set, a current temperature of a heat dissipation device in the room corresponding to the fourth parameter set, a current temperature in a cabinet in the room corresponding to the fourth parameter set, or a current operation state of each environmental adjustment device in the room corresponding to the fourth parameter set.
The fourth parameter set and the fifth parameter set of each of the L sample data are parameter sets obtained by the first device from the same room. The fourth control strategy of each sample data in the L sample data is a rough strategy corresponding to indoor basic static parameters, and the fifth control strategy is a fine strategy corresponding to indoor fifth parameter sets.
The following describes, as an example, the i-th sample data among the L sample data:
the method comprises the steps that first equipment acquires ith sample data, wherein the ith sample data comprises an ith parameter set, an ith control strategy, an ith 'parameter set and an ith' control strategy, and the first equipment determines an ith model according to the ith parameter set and the ith control strategy, wherein the ith model is used for obtaining a second model; the first device determines an ith model according to an ith control strategy, an ith parameter set and an ith control strategy, wherein the ith model is used for obtaining a first model; wherein the i-th parameter set includes: at least one of an area in the ith chamber, a number Mi of environmental conditioning devices in the ith chamber, a technical parameter of each environmental conditioning device in the ith chamber, or a location of each environmental conditioning device in the ith chamber; the i' th parameter set includes: at least two of an operation duration of each environmental conditioning device in the Mi environmental conditioning devices, a season corresponding to the ith sample data, a current indoor temperature in the ith room, a current outdoor temperature corresponding to the ith room, a current temperature of a heat dissipating device in the ith room, a current temperature in a cabinet in the ith room, or a current operation state of each environmental conditioning device in the ith room.
The second device controls M1 environmental conditioning devices, described below in two cases.
Case one: the second device controls the M1 environmental conditioning devices according to the second control strategy.
Optionally, the second device controls the M1 environmental conditioning devices according to the second control policy, which may control the M1 environmental conditioning devices to turn on in a wheel manner, may control the M1 environmental conditioning devices to turn on in a step manner, may control the M1 environmental conditioning devices to turn on in a linkage manner, or control the M1 environmental conditioning devices to execute other action modes.
Optionally, the M1 environmental conditioning apparatuses are turned on in turn, that is, a first environmental conditioning apparatus of the M1 environmental conditioning apparatuses is turned on first, after a certain period of time, the first environmental conditioning apparatus is turned off, and then a second environmental conditioning apparatus is turned on, so that the M1 environmental conditioning apparatuses in the first room are turned on in turn until other mechanisms are triggered.
It should be noted that, after a certain period of time is elapsed in the process of turning on the M1 environmental conditioning devices, the first environmental conditioning device is turned off, and after the next period of time, the second environmental conditioning device is turned off, so that the corresponding mode of turning off the M1 environmental conditioning devices in the first room in turn is realized.
Specifically, the step-by-step opening of the M1 environmental conditioning apparatuses refers to opening a first environmental conditioning apparatus of the M1 environmental conditioning apparatuses, and after a certain period of time, opening a second environmental conditioning apparatus until the temperature in the first room drops to a preset temperature.
It should be noted that after the M1 environmental conditioning apparatuses are turned on step by step, until the temperature in the first room drops to the preset temperature, when N environmental conditioning apparatuses are in an on state, N on environmental conditioning apparatuses need to be turned off at this time, which may be the simultaneous turning off of N environmental conditioning apparatuses, or the alternate turning off of N environmental conditioning apparatuses, where N is a positive integer greater than zero and less than or equal to M1.
Specifically, the linkage turning on of M1 environmental conditioning apparatuses means that M1 environmental conditioning apparatuses are turned on simultaneously.
It should be noted that after the M1 environmental conditioning apparatuses are turned on in a linkage manner, until the temperature in the first room drops to a preset temperature, when the M1 environmental conditioning apparatuses are in an on state at this time, the M1 environmental conditioning apparatuses need to be turned off, which may be to turn off the M1 environmental conditioning apparatuses simultaneously or turn off the M1 environmental conditioning apparatuses in turn.
Optionally, after the first case, the second device collects a third parameter set, the second device sends the third parameter set to the first device, the first device receives the third parameter set from the second device, and the first device updates the first model according to the third parameter set and the first control policy.
Wherein the third set of parameters comprises: at least two of a current operation duration of each environment adjusting device in the M1 environment adjusting devices, a current season, a current indoor temperature in the first room, a corresponding outdoor current outdoor temperature in the first room, a current temperature of a heat radiating device in the first room, a current temperature in a cabinet in the first room or a current operation state of each environment adjusting device in the first room.
The parameters included in the third parameter set and the first parameter set are the same, but the values of the parameters in the third parameter set and the first parameter set are different. For example, the first parameter set is a current operation duration of each environmental conditioning device in the M1 environmental conditioning devices, a current season, a current indoor temperature in the first room, a corresponding outdoor current outdoor temperature in the first room, a current temperature of the heat dissipating device in the first room, a current temperature in the cabinet in the first room, and a current operation state of each environmental conditioning device in the first room, and the third parameter set is a current operation duration of each environmental conditioning device in the M1 environmental conditioning devices, a current season, a current indoor temperature in the first room, a corresponding outdoor current outdoor temperature in the first room, a current temperature of the heat dissipating device in the first room, a current temperature in the cabinet in the first room, and a current operation state of each environmental conditioning device in the first room, which are acquired after the preset duration.
Alternatively, the second device may be an edge computing device and the first device may be a cloud server.
And a second case: the second device controls the M1 environmental conditioning devices according to the third control strategy.
Optionally, the second device determines a third control policy according to the third parameter set and the second control policy, and the second device controls the M1 environmental conditioning devices to turn on according to the third control policy, or controls the M1 environmental conditioning devices to turn on in a stepping manner, or controls the M1 environmental conditioning devices to turn on in a linkage manner, or controls the M1 environmental conditioning devices to perform other actions.
Optionally, after the second device collects the third parameter set, the second device sends the third parameter set to the first device, the first device receives the third parameter set from the second device, and the first device updates the first model according to the third parameter set, the first control policy, and the third control policy.
Because the indoor and outdoor environment factors are complex and in a continuously changing state, the parameter values of the first parameter set or the third parameter set collected by the second equipment are dynamically changed, when the second equipment controls the M1 environment adjusting equipment according to the second control strategy, the second equipment can judge the collected third parameter set and adjust the second control strategy according to the mode in the second condition to obtain the third control strategy, and the second equipment controls the M1 environment adjusting equipment according to the third control strategy, so that the environment adjusting equipment can be controlled more accurately by combining the dynamic adjustment of the control strategy by the field factors.
The above steps realize fine control of M1 environmental conditioning apparatuses in the first room, and the control methods of the environmental conditioning apparatuses in different rooms are similar to the method 100 described above, so that detailed descriptions are omitted for avoiding redundant descriptions.
For better understanding of the solution of the present application, fig. 2 is a schematic diagram of a method for controlling an air conditioner of a base station room by using an artificial intelligence AI, and the embodiment is applied to control of the air conditioner of the base station room. As shown in fig. 2, the first device is a cloud server, and the second device is an edge station energy control unit.
S201, an edge station energy control unit collects base station data.
Specifically, the base station data includes: the number of the air conditioning equipment of the base station room, the area of the base station room and the technical parameters of the air conditioning equipment of the base station room.
For example, the second device in method 100 may be the edge station energy control unit of fig. 2 and the second set of parameters in method 100 may be the base station data of fig. 2.
S202, the edge station energy control unit sends base station data to the cloud server.
For example, the first device in method 100 may be the cloud server of fig. 2.
And S203, the cloud server inputs the base station data into an area and air-conditioning mathematical model and outputs the energy-saving control strategy range of the base station machine room.
For example, the second model in the method 100 may be the area & air conditioning algorithm model in fig. 2, and the first control strategy in the method 100 may be the energy saving control strategy range of the base station room in fig. 2.
S204, the edge station energy control unit collects base station environment data.
Specifically, the base station environment data includes: indoor temperature of the base station room, outdoor temperature of the base station room, operation time of the base station room air conditioning equipment and operation state of the base station room air conditioning equipment.
For example, the first set of parameters in method 100 may be the base station environment data in fig. 2.
S205, the edge station energy control unit sends base station environment data to the cloud server.
For example, the second device in the method 100 sending the first set of parameters to the first device may be S205 in fig. 2.
S206, the cloud server inputs the base station environment data into a season & temperature algorithm model, and outputs an optimal energy-saving control strategy of the base station machine room.
For example, the first model in method 100 may be the season & temperature algorithm model in fig. 2, and the second control strategy in method 100 may be the optimal energy-saving control strategy in fig. 2.
S207, the cloud server issues an optimal energy-saving control strategy to the edge station energy control unit.
For example, the first device in the method 100 sending the second control policy to the second device may be S207 in fig. 2.
S208, the edge station energy control unit controls the air conditioning equipment according to the optimal energy saving control strategy.
For example, the second device in the method 100 may control the environment adjustment device according to the second control policy to be S208 in fig. 2, and the environment adjustment device in the method 100 may be the air conditioning device in fig. 2.
S209, the edge station energy control unit collects the base station environment data at the next moment.
Specifically, the base station environment data at the next moment is the base station environment data collected by the edge station energy control unit after the preset time at the previous moment.
For example, the third set of parameters in method 100 may be the base station environment data for the next time instant in fig. 2.
S210, the edge station energy control unit sends base station environment data at the next moment to the cloud server.
For example, the second device in method 100 sending the third set of parameters to the first device may be S210 in fig. 2.
S211, the cloud server updates a season & temperature algorithm model according to the base station environment data at the next moment.
For example, the first device in the method 100 updating the first model according to the third parameter set and the first control strategy may be S211 in fig. 2.
S212, the energy control unit of the edge station judges the condition of the base station environment data at the next moment and issues a control instruction to the air conditioning equipment.
Specifically, the control instruction includes: the air conditioning equipment of the base station room is started in a linkage way, the air conditioning equipment of the base station room is started in a rotation way, or the air conditioning equipment of the base station room is started in a stepping way.
For example, the second device in method 100 outputting the third control strategy according to the third parameter set and the second control strategy may be S212 in fig. 2, and the third control strategy in method 100 may be the control instruction in fig. 2.
For example, in fig. 2, the optimal energy-saving control policy is that all air conditioning equipment of the base station room is not turned on, and if the collected base station environment data at the next moment is: the indoor temperature of the base station room is 33 ℃, the outdoor temperature of the base station room is 30 ℃, and the air conditioners of the base station room are all disconnected. The edge station energy control unit turns on an air conditioner closest to the base station electromechanical equipment or with the best cooling effect, and starts the judgment of the running time of the air conditioner.
If the indoor temperature of the base station room is higher than 34 ℃ within one hour, namely the on-site temperature is not reduced, and the temperature early warning value of the room is reached, at the moment, the edge station energy control unit issues a control instruction for linkage starting of air conditioning equipment of the base station room, namely all air conditioners in the room are rapidly opened, the temperature of the room is rapidly reduced, and the safety of the room is ensured.
If the indoor temperature of the base station room does not drop within one hour, and the indoor temperature is stabilized to be higher than 32 ℃, the edge station energy control unit issues a control instruction for step-by-step starting of the air conditioning equipment of the base station room at the moment, namely, the edge station energy control unit starts the air conditioner step by step according to the site condition and the running time of the air conditioner, and starts the next air conditioner at intervals for a certain time until the air conditioner is fully started or the temperature of the room is reduced.
If the indoor temperature of the base station room is reduced within one hour and stabilized to 28-32 ℃, the edge station energy control unit issues a control instruction for turning on the air conditioning equipment of the base station room at the moment, namely the edge station energy control unit performs turning control on the on-site air conditioner for a certain time interval, the air conditioning of the room is turned on in turn until other mechanisms are triggered, the running time of the air conditioner is reasonably distributed while the temperature of the room is ensured to be stable, and the service life of the air conditioner is prolonged.
If the indoor temperature of the base station machine room is lower than 28 ℃ within one hour, the edge station energy control unit judges whether the air conditioner is immediately turned off or not according to the operation time of the air conditioner and the temperature change rate of the machine room, and if the operation time is too short and the temperature change rate is large, the air conditioner is turned off in a delayed mode, so that the frequent start-stop phenomenon of the air conditioner is prevented.
It should be noted that, the execution sequence of S211 and S212 in fig. 2 is not limited, and S211 may be performed before or after S212 or simultaneously. It should be noted that the present application may include more steps or fewer steps than those of fig. 2, and the combination of the different steps in fig. 2 may form different embodiments, for example, S201 to S206 in fig. 2 may form an embodiment in which the first device acquires the first parameter set, the first device outputs the second control policy according to the first parameter set and the first control policy, S201 to S207 may form another embodiment in which the first device outputs the second control policy to the second device, S201 to S208 may form yet another embodiment in which the second device controls the environmental conditioning device according to the second control policy, S201 to S211 may form yet another embodiment in which the first device updates the first model according to the acquired third parameter set and the first control policy, and S201 to S209 and S212 may form yet another embodiment in which the second device controls the environmental conditioning device according to the third control policy.
Above, fig. 2 completes the fine control of the air conditioning equipment in the base station room, the obtained base station data is compared with the area & air conditioning number algorithm model in the cloud server to judge, the energy saving control policy range of the base station room is analyzed, based on the energy saving control policy range of the base station room, the cloud server inputs the obtained base station environment data into the season & temperature algorithm model to perform calculation and analysis, outputs the optimal energy saving control policy of the base station room and issues the optimal energy saving control policy to the edge station energy control unit, and the edge station energy control unit adjusts the optimal energy saving control policy according to the collected base station environment data at the next moment and issues a control instruction to perform fine control on the air conditioning equipment. Therefore, the fine control of the air conditioning equipment in different environments of the base station room is realized, and the energy conservation and emission reduction of the base station room are realized.
Fig. 3 is a schematic block diagram of an apparatus for controlling an environmental conditioning device through an artificial intelligence AI according to an embodiment of the present application, where, as shown in fig. 3, the apparatus provided in this embodiment includes:
An obtaining unit 310, configured to obtain a first parameter set, where the first parameter set includes: the current operation duration of each environment adjusting device in the M1 environment adjusting devices, the current season, the current indoor temperature in the first room, the corresponding outdoor current outdoor temperature in the first room, the current temperature of the heat radiating device in the first room, the current temperature in the cabinet in the first room or the current operation state of each environment adjusting device in the first room are at least two, the M1 environment adjusting devices are used for adjusting the temperature in the first room, and M1 is a positive integer.
The obtaining unit 310 is further configured to obtain a second parameter set, where the second parameter set includes: at least one of an area in the first chamber, M1, a technical parameter of each environmental conditioning device in the first chamber, or a location of each environmental conditioning device in the first chamber.
The processing unit 320 is configured to input a first parameter set and a first control policy into a first model to obtain a second control policy, where the first control policy is obtained by inputting the second parameter set into the second model, and the second control policy is used to control M1 environmental conditioning devices, and the first model and the second model are different AI models.
The apparatus shown in fig. 3 may perform the functions of the first device in the above method embodiments, which are not described in detail herein for avoiding redundancy.
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, the specific names of the functional units and modules are only for 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.
Based on the same inventive concept, fig. 4 is a schematic block diagram of another apparatus for controlling an environmental conditioning device by an artificial intelligence AI according to an embodiment of the application, including a processor coupled to a memory, the processor being configured to implement the method of the first aspect or any implementation manner of the first aspect when executing a computer program or instructions stored in the memory.
Based on the same inventive concept, the embodiment of the present application provides a computer storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the method of the first aspect or any implementation manner of the first aspect.
The integrated units described above may be stored in a device if implemented in the form of software functional units and sold or used as separate products. Based on such understanding, the present application may implement all or part of the flow of the method of the above-described embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a chip of a computer, and the computer program may implement the steps of the method embodiments described above when executed by a processor. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable storage medium may include at least: any entity or device capable of carrying computer program code to a photographing device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
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.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/device and method may be implemented in other manners. For example, the apparatus/device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units 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.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.
Claims (8)
1. A method for controlling an environmental conditioning device via an artificial intelligence AI, comprising:
the first device obtains a first set of parameters, the first set of parameters comprising: at least two of a current operation duration of each environmental conditioning device of M1 environmental conditioning devices, a current season, a current indoor temperature of a first room, a corresponding outdoor current outdoor temperature of the first room, a current temperature of a heat dissipating device of the first room, a current temperature in a cabinet of the first room, or a current operation state of each environmental conditioning device of the first room, wherein the M1 environmental conditioning devices are used for adjusting the temperature of the first room, and the M1 is a positive integer;
the first device inputs the first parameter set and a first control strategy into a first model to obtain a second control strategy, wherein the first control strategy is obtained by inputting a second parameter set into a second model, and the second parameter set comprises: at least one of an area in the first room, a number M1 of the environmental conditioning devices, a technical parameter of each environmental conditioning device in the first room, or a position of each environmental conditioning device in the first room, the second control strategy being for controlling the M1 environmental conditioning devices, the first model and the second model being different AI models, the AI models being neural network models;
the method further comprises the steps of:
the first device sends the second control strategy to a second device;
The second device controls the M1 environment adjusting devices according to the second control strategy;
Wherein after the second device controls the M1 environmental conditioning devices according to the second control policy, the first device receives a third parameter set from the second device, the third parameter set including: at least two of a current operation duration of each environment-adjusting device, a current season, a current indoor temperature of the first room, a corresponding outdoor current outdoor temperature of the first room, a current temperature of a heat-dissipating device in the first room, a current temperature in a cabinet in the first room, or a current operation state of each environment-adjusting device in the first room;
The first device updates the first model according to the third set of parameters and the first control strategy.
2. The method according to claim 1, wherein the method further comprises:
the first device obtains the second parameter set;
and the first device inputs the second parameter set into the second model to obtain the first control strategy.
3. The method according to claim 1, wherein the method further comprises:
The first device obtains ith sample data, wherein the ith sample data comprises an ith parameter set, an ith control strategy, an ith 'parameter set and an ith' control strategy;
The first device determines an ith model according to the ith parameter set and the ith control strategy, wherein the ith model is used for obtaining the second model;
The first device determines an ith model according to the ith control strategy, the ith parameter set and the ith control strategy, wherein the ith model is used for obtaining the first model;
Wherein the i-th parameter set includes: at least one of an area in an i-th room, a number Mi of environmental conditioning devices in the i-th room, a technical parameter of each environmental conditioning device in the i-th room, or a location of each environmental conditioning device in the i-th room; the i' th parameter set includes: at least two of an operation duration of each environmental conditioning device in the Mi environmental conditioning devices, a season corresponding to the ith sample data, a current indoor temperature in the ith room, a current outdoor temperature in the ith room, a current temperature of a heat dissipating device in the ith room, a current temperature in a cabinet in the ith room, or a current operation state of each environmental conditioning device in the ith room.
4. The method of claim 1, wherein the second device controlling the M1 environmental conditioning devices according to the second control strategy comprises:
The second device controls the M1 environmental conditioning devices to be turned on in a wheel motion mode according to the second control strategy, or controls the M1 environmental conditioning devices to be turned on in a stepping mode, or controls the M1 environmental conditioning devices to be turned on in a linkage mode.
5. The method of claim 1, wherein after the second device controls the M1 environmental conditioning devices according to the second control strategy, the method further comprises:
The second device collects a third set of parameters, the third set of parameters comprising: at least two of a current operation duration of each environment-adjusting device, a current season, a current indoor temperature of the first room, a corresponding outdoor current outdoor temperature of the first room, a current temperature of a heat-dissipating device in the first room, a current temperature in a cabinet in the first room, or a current operation state of each environment-adjusting device in the first room;
The second device determines a third control strategy according to the third parameter set and the second control strategy;
and the second equipment controls the M1 environment adjusting equipment according to the third control strategy.
6. The method of claim 5, wherein the second device controlling the M1 environmental conditioning devices according to the third control strategy comprises:
The second device controls the M1 environmental conditioning devices to be turned on in a wheel motion mode according to the third control strategy, or controls the M1 environmental conditioning devices to be turned on in a stepping mode, or controls the M1 environmental conditioning devices to be turned on in a linkage mode.
7. An apparatus for controlling an environmental conditioning device via an artificial intelligence AI, comprising a processor coupled to a memory, the processor for executing a computer program or instructions stored in the memory to implement a method as recited in any one of claims 1-6.
8. A computer storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, implements the method according to any of claims 1-6.
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