CN110873446B

CN110873446B - Method and device for controlling air conditioner, storage medium and processor

Info

Publication number: CN110873446B
Application number: CN201811012472.3A
Authority: CN
Inventors: 夏伟; 宋德超; 连圆圆; 陈翀; 秦萍; 万会; 冯德兵
Original assignee: Gree Electric Appliances Inc of Zhuhai
Current assignee: Gree Electric Appliances Inc of Zhuhai
Priority date: 2018-08-31
Filing date: 2018-08-31
Publication date: 2020-12-25
Anticipated expiration: 2038-08-31
Also published as: CN110873446A

Abstract

The invention discloses a method and a device for controlling an air conditioner, a storage medium and a processor. Wherein, the method comprises the following steps: acquiring first room information of a sample room and second room information of a target room; determining a room type of the target room according to the first room information and the second room information; and acquiring control information according to the room type, wherein the control information is used for controlling the cooling capacity and/or the heating capacity of the air conditioner in the target room. The invention solves the technical problem that the actual energy-saving effect of the air conditioner cannot be ensured by the energy-saving control mode of the air conditioner through experience in the prior art.

Description

Method and device for controlling air conditioner, storage medium and processor

Technical Field

The invention relates to the field of energy-saving control, in particular to a method and a device for controlling an air conditioner, a storage medium and a processor.

Background

The air conditioner is used as a device for adjusting the indoor environment temperature, and plays an important role in improving the living standard of people. However, the air conditioner is not efficient in using electric energy in daily use.

Because the domestic environments of each user are inconsistent, certain deviation exists between the domestic environments and theoretical conditions in the process of using the air conditioner, energy-saving control is carried out through traditional experience matching, the room requirements are possibly exceeded, waste is caused, or the room requirements are not met, the air conditioner is in full-load operation, and even the air conditioner is damaged due to overload. Moreover, the controlled factors influencing the overall operation of the air conditioner are not matched seriously, which can cause serious waste of energy and further influence the service life of the air conditioner.

Aiming at the problem that the actual energy-saving effect of the air conditioner cannot be ensured by the mode of carrying out energy-saving control on the air conditioner through experience in the prior art, an effective solution is not provided at present.

Disclosure of Invention

The embodiment of the invention provides a method and a device for controlling an air conditioner, a storage medium and a processor, which are used for at least solving the technical problem that the actual energy-saving effect of the air conditioner cannot be ensured in the prior art by performing energy-saving control on the air conditioner through experience.

According to an aspect of an embodiment of the present invention, there is provided a method of controlling an air conditioner, including: acquiring first room information of a sample room and second room information of a target room; determining a room type of the target room according to the first room information and the second room information; and acquiring control information according to the room type, wherein the control information is used for controlling the cooling capacity and/or the heating capacity of the air conditioner in the target room.

According to another aspect of the embodiments of the present invention, there is also provided an apparatus for controlling an air conditioner, including: the acquisition module is used for acquiring first room information of the sample room and second room information of the target room; a determining module, configured to determine a room type of the target room according to the first room information and the second room information; and the acquisition module is used for acquiring control information according to the room type, wherein the control information is used for controlling the refrigerating capacity and/or the heating capacity of the air conditioner in the target room.

According to another aspect of the embodiments of the present invention, there is also provided a storage medium, where the storage medium includes a stored program, and when the program runs, the apparatus where the storage medium is located is controlled to perform the following steps: acquiring first room information of a sample room and second room information of a target room; determining a room type of the target room according to the first room information and the second room information; and acquiring control information according to the room type, wherein the control information is used for controlling the cooling capacity and/or the heating capacity of the air conditioner in the target room.

According to another aspect of the embodiments of the present invention, there is also provided a processor, configured to execute a program, where the program executes the following steps: acquiring first room information of a sample room and second room information of a target room; determining a room type of the target room according to the first room information and the second room information; and acquiring control information according to the room type, wherein the control information is used for controlling the cooling capacity and/or the heating capacity of the air conditioner in the target room.

In the embodiment of the invention, first room information of a sample room and second room information of a target room are acquired; determining a room type of the target room according to the first room information and the second room information; the control information is obtained according to the room type, wherein the control information is used for controlling the refrigerating capacity and/or the heating capacity of the air conditioner in the target room, and the purpose of solving the problem of the refrigerating/heating demand of the actual living environment of a user is achieved, so that the technical effect of avoiding the situation that the refrigerating capacity and/or the heating capacity are output blindly and derailed from the actual demand is achieved, and the technical problem that the actual energy-saving effect of the air conditioner cannot be guaranteed due to the mode of carrying out energy-saving control on the air conditioner through experience in the prior art is solved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

fig. 1 is a flowchart of a method of controlling an air conditioner according to an embodiment of the present invention;

FIG. 2 is a graphical illustration of an alternative sample room in accordance with an embodiment of the present invention;

FIG. 3 is a graphical illustration of an alternative sample room in accordance with an embodiment of the present invention;

FIG. 4 is a schematic diagram of an alternative reinforcement learning algorithm control framework in accordance with an embodiment of the present invention;

fig. 5 is a schematic diagram of an alternative air conditioner energy saving control process according to an embodiment of the present invention;

fig. 6(a) is a schematic diagram of an alternative monte carlo algorithm simulation control flow in a virtual air conditioner according to an embodiment of the present invention;

fig. 6(b) is a schematic diagram of an alternative monte carlo algorithm simulation control flow in a virtual air conditioner according to an embodiment of the present invention;

fig. 7 is a schematic structural diagram of an apparatus for controlling an air conditioner according to an embodiment of the present invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the above-described figures are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

In accordance with an embodiment of the present invention, there is provided an embodiment of a method of controlling an air conditioner, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that herein.

Fig. 1 is a flowchart of a method of controlling an air conditioner according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:

step S102, first room information of the sample room and second room information of the target room are collected.

In step S102, the first room information includes at least one of: room type, room area, room cooling capacity, and/or heating capacity; the second room information includes at least one of: room area, room cooling capacity, and/or heating capacity.

In the embodiment of the application, a refrigeration capacity database of a sample room may be further provided, and the first room information of the sample room may be stored in the refrigeration capacity database in advance, so that the first room information may be obtained from the refrigeration capacity database.

Step S104, determining the room type of the target room according to the first room information and the second room information.

The factors such as room type, heat dissipation coefficient, area, height, floor and directional (to the shade or to the sun) house materials of a room in a user family have large influence on the refrigeration and heating of the room, but in real life, the user simply purchases heating and ventilation equipment according to the room area, and each manufacturer gives a rough reference standard according to an experimental result when designing the heating and ventilation equipment, but the difference between the actual room environment of the user and the laboratory environment is large, so that the refrigeration and heating effects are not ideal.

Therefore, in the embodiment of the present application, the room type of the target room needs to be determined, so as to improve the cooling and heating effects, and the energy saving range of the air conditioner can be limited according to the room type of the room, so that the requirement for cooling/heating can be reduced in a proper amount under the condition that the reduction comfort is not obvious, thereby reducing the energy consumption and meeting the energy saving requirement of the user.

It should be noted that the cooling capacity and/or the heating capacity of different room types are different, and the above-mentioned various influencing factors have a large heating and cooling effect in the room due to the inconsistency of the room types.

Since the first room information in the sample room already contains: the room type, the room area, the room cooling capacity and/or the heating capacity, and the respective first room information of each room is corresponding. The room type of the target room may be determined according to the room area, the room cooling capacity, and/or the heating capacity in the target room.

And step S106, acquiring control information according to the room type, wherein the control information is used for controlling the cooling capacity and/or the heating capacity of the air conditioner in the target room.

The embodiment of the application can control the refrigerating capacity and/or the heating capacity of the air conditioner in the target room by determining the room type of the room, limits the energy-saving range of the air conditioner, specifically can be the refrigerating capacity and/or the heating capacity, and further can reduce the refrigerating/heating capacity requirement in a proper amount under the condition that the reduction comfort is not obvious, thereby reducing the energy consumption and meeting the energy-saving requirement of a user.

Moreover, based on the reinforcement learning control algorithm based on the Monte Carlo tree search provided by the embodiment of the application, the independent optimization of the operation parameters on the existing heating and ventilation equipment can be realized, so that the optimal internal adaptation strategy is realized, the controlled factors of the air conditioner are accurately optimized on the premise of the same refrigeration demand, and the energy consumption is reduced.

In the above embodiment, the heating and ventilating apparatus may include: the heating direction is mainly provided with a boiler, a heat exchanger, a water pump, a radiator and the like; for the ventilation direction, the main equipment is a fan; for the air conditioning direction, the main equipment is cooling tower, water chilling unit, water pump, air handler, fan coil etc..

In an alternative embodiment, the first room information includes at least one of: room type, room area, room cooling capacity, and/or heating capacity; collecting first room information of a sample room, comprising:

step S202, acquiring the room type of the sample room;

step S204, measuring the room area of each sample room according to the room type of the sample room;

and step S206, calculating the power consumption and the energy consumption ratio of the air conditioners in the sample rooms based on the room area of each sample room to obtain the refrigerating capacity and/or the heating capacity of the air conditioners in the sample rooms.

In the above alternative embodiment, the sample room and the target room may each be a bedroom, living room, kitchen, classroom, hospital, etc., and in an alternative embodiment, the room types include at least one of: house type structure, building material, position orientation, environmental floor, thermal-insulated effect.

Since different room types have great influence on the cooling capacity and the heating capacity of the room, the room types of the sample rooms can be determined in the sample rooms, the room area of the sample room of each room type can be measured according to the room types of the sample rooms, and the cooling capacity and/or the heating capacity of the air conditioner in the sample room can be obtained by calculating the power consumption and the energy consumption ratio of the air conditioner in the sample room based on the room area of each sample room.

In an optional embodiment, calculating the power consumption and the energy consumption ratio of the air conditioners in the sample room to obtain the cooling capacity and/or the heating capacity of the air conditioners in the sample room includes:

step S302, obtaining the energy consumption ratio of the air conditioners in the sample room;

step S304, detecting the power consumption of the air conditioner, and calculating to obtain the power consumption of the air conditioner;

step S306, calculating the power consumption of the air conditioner and the energy consumption ratio to obtain the cooling capacity and/or the heating capacity.

In the embodiment of the present application, the energy consumption ratio may be obtained according to the following calculation formula: the energy consumption ratio is the cooling capacity/power consumption, or the energy consumption ratio is the heating capacity/power consumption, and may also be preset during the production of the air conditioner, and the energy consumption ratio may be obtained according to factory setting parameters. It should be noted that the real-time cooling capacity and/or heating capacity is calculated according to the real-time power consumption of the air conditioner.

In an alternative embodiment, if the type of the target room is not a standard sample room, the heating and ventilation device calculates the actual cooling and/or heating demand of the room through its own sensor during the operation.

In an optional embodiment, before determining the room type of the target room according to the first room information and the second room information, the method further includes:

step S402, determining the room area of each sample room according to the room type of the sample room;

step S404, determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of each sample room;

step S406, determining a graph of each sample room by using the room area of the sample room as an abscissa of a coordinate system and using the cooling capacity and/or the heating capacity of the sample room as an ordinate of the coordinate system.

In this embodiment of the application, after the first room information of the sample room is acquired, a graph of the sample room of each room type may be further drawn on the rectangular coordinate system, specifically, the room area of each sample room may be determined and listed on the rectangular coordinate system according to the room type of the sample room, the maximum value and the minimum value of the cooling capacity and/or the heating capacity of each sample room may be determined on the rectangular coordinate system according to the room area of the sample room and the cooling capacity and/or the heating capacity of each sample room may be determined on the rectangular coordinate system, the room area of the sample room is used as the abscissa of the coordinate system, and the cooling capacity and/or the heating capacity of the sample room is used as the ordinate of the coordinate system, so as to determine the graph of each sample room.

In an alternative embodiment, the graph of the sample room may be, but is not limited to, as shown in fig. 2 and 3, and t is a rectangular coordinate system shown in fig. 2 and 3₀Is the origin of a coordinate system, t_cCooling capacity (the cooling capacity is taken as an example in the embodiment and can also be expressed as heating capacity) s of a coordinate system₁、s₂、s₃、s₄The room areas of the sample rooms for different room types, the three solid lines in fig. 2 are: room type I maximum (i.e., maximum amount of cooling for room type I); room type II maximum (i.e., maximum amount of cooling for room type II); room type III maximum (i.e., maximum cooling capacity for room type III).

In an optional embodiment, the second room information includes at least one of: room area, room cooling capacity and/or heating capacity; collecting second room information of a target room, comprising:

step S502, acquiring the room area of the target room;

step S504, detecting the power consumption of the air conditioner in the target room, and calculating to obtain the power consumption of the air conditioner;

and step S506, calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity of the air conditioner in the target room.

In the embodiment of the present application, the room area of the target room may be obtained by measurement, or may be obtained by other methods, for example, querying room information corresponding to the target room.

And detecting the power consumption of the air conditioner in the target room, calculating the power consumption of the air conditioner through a power consumption calculation formula, and further calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity of the air conditioner in the target room.

In an optional embodiment, determining the room type of the target room according to the first room information and the second room information includes:

step S602, determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of the corresponding sample room in the curve chart according to the room area of the target room;

step S604, calculating the maximum value and the minimum value to obtain the average value of the refrigerating capacity and/or the heating capacity;

step S606, determining the room type of the sample room corresponding to the average value of the cooling capacity and/or the heating capacity as the room type of the target room.

In the present applicationIn the embodiment, according to the room area of the target room, the maximum value of the cooling capacity and the minimum value of the cooling capacity of the sample room in the sample room graph shown in fig. 3 are selected, wherein the maximum value t of the cooling capacity of the sample room corresponding to the room type II is selected_maxAnd minimum value t of refrigerating capacity of sample room_min(ii) a Maximum refrigerating capacity t of sample room corresponding to room type III_rnAnd minimum value t of refrigerating capacity of sample room_rm(ii) a The maximum and minimum cooling capacity values of the sample room corresponding to the room type I are not shown in fig. 3, and the room area is s_rThe actual cooling/heating demand is t_r，t_rAnd s_rThe point A is the average value of the refrigerating capacity and/or the heating capacity, and the average value is the average value calculated by the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of each type of room.

Obtaining room types I to III through calculation, wherein the current area s of the three room types_rAnd actual refrigeration demand t_rF below. By finding the smallest two f-values, the smaller the f-value, the greater the likelihood that the actual refrigeration demand will likely fall within a certain room type. From the results of the graph, it can be seen that the current possibility of falling between room type II and room type III is high.

And, when f tends to 0, t_rApproximately equal to t_maxAnd t_minThe average value of the average values is obtained through data analysis, when the actual refrigerating capacity falls on the midpoint position of the maximum value and the minimum value of the area, the effect of determining the type of the target room to which the target room belongs is best, and the closer the distance between the falling point and the center of the area is, the more uniform the falling point is, and the better the attribution effect is. The purpose of the calculation formula is to determine the midpoint positions of the three regions, which two positions are closest to the actual cooling capacity, and which two regions the actual cooling capacity belongs to. And judging the difference between the distance from the actual refrigerating capacity to the upper limit and the distance from the actual refrigerating capacity to the lower limit through the formula so as to judge the condition that the actual refrigerating capacity falls on the corresponding position.

In an alternative embodiment, f | | | t is calculated for each sample room type_max-t_r|-|t_r-t_minL; results obtained in ascending order: f1, f2, f3 … … fn; selecting a sample room corresponding to the minimum value f1 and the second minimum value f 2; determination of t_rClosest to t_max1 and t_min1、t _max2 and t _min2, average value of the total. With t_rJudging the room type, selecting 2 room types, and recording t_minGraph is shown.

As an alternative embodiment, since the cooling capacity and the heating capacity are the largest factors of energy saving or not, the obvious energy saving effect can be directly realized by reducing the heating capacity or the cooling capacity within a proper and reasonable range.

Therefore, in the embodiment of the present application, the actual heating capacity and/or cooling capacity demand of the air conditioner may be set to be a flexible variable interval, and a certain value fixed in the past may be changed as the actual indoor cooling and heating capacity: [ t ] of_rm+0.9λ|t_min-t_rm|,t_r-0.1λ|t_min-t_rm|](ii) a Wherein, the λ is an adjustable parameter, and the value range can be but not limited to [0.2,0.5 ]]Or [0,1 ]]By optimizing the operation parameters of the heating and ventilation equipment, the refrigerating and heating quantity falls within the reasonable range of the calculation formula, and the energy conservation and the consumption reduction are facilitated.

In the embodiment of the application, the actual refrigerating capacity t can be obtained_rThe cooling capacity is adjusted from a fixed value to a flexible interval value, and the maximum value of the interval is a little smaller than the actual cooling capacity.

In the above calculation formula, t_rm<t_minThe value range of λ is [0,1 ]]In the case of (2), when the value of λ tends to 1, the value range of the above calculation formula may be approximated to [0.1t ]_rm+0.9t_min,t_r-0.1|t_min-t_rm|]. When the value of λ tends to 0, the value range of the above calculation formula can be approximated as [ t [ ]_rm,t_r]. The value range of the lambda is [0,1 ]]In the case of (2), when the value of λ tends to 0.5, the value range of the above calculation formula may be approximated to [0.55t [ ]_rm+0.45t_min,t_r-0.05|t_min-t_rm|]。

In addition, since in the embodiment of the present application, the lower limit when the value of λ tends to 1: t is t_rm＜0.1t_rm+0.9t_min＜t_min(ii) a Lower limit when λ tends to be 0.5: t is t_rm＜0.55t_rm+0.45t_min＜t_min(ii) a Lower limit when λ tends to be 0: t is t_rm；

0.1t_rm+0.9t_min-(0.55t_rm+0.45t_min)＝0.45t_min-0.45t_rm＝0.45(t_min-t_rm)>0

Therefore 0.1t_rm+0.9t_min>0.55t_rm+0.45t_min>t_rm；

Upper limit when λ tends to 1: t is t_r-0.1|t_min-t_rm|；

Upper limit when λ tends to be 0.5: t is t_r-0.05|t_min-t_rm|；

Upper limit when λ tends to 0: t is t_r；

t_r-0.1|t_min-t_rm|＜t_r-0.05|t_min-t_rm|＜t_r；

According to the above calculation formula, it can be determined that when the value of λ is decreased, the lower limit is decreased and the upper limit is increased.

In an optional embodiment, the method further includes:

step S702, collecting the operating parameters of the air conditioners in the target room.

In step S702, the operating parameters include at least one of the following: setting temperature value, electronic expansion valve opening degree, compressor frequency and fan rotating speed.

Step S704, collecting the state data of the target room.

In step S704, the status data includes at least one of: indoor temperature, indoor humidity, outdoor humidity.

Step S706, combining the working parameters and the status data to obtain a status database of the target room.

In this embodiment, combining the operating parameters and the status data means to establish a corresponding relationship between the operating parameters and the status data, and store the operating parameters and the status data in a status database, where the operating parameters of the air conditioner are controlled factors of the air conditioner.

In the embodiment of the application, the controlled factors of the air conditioner are accurately optimized through the reinforcement learning control algorithm based on the Monte Carlo tree search, and reinforcement learning of the air conditioner can be realized. Through judging the heating capacity and/or the refrigerating capacity demand in user's room, avoid blind output, under the prerequisite that satisfies the travelling comfort, suitably reduce the output of heating capacity and/or refrigerating capacity, in time deal with the change in the room, make the room remain stable state, through reinforceing study, make the air conditioner make the action with the mode that the energy consumption is the lowest, saved power consumption, improved air conditioner work efficiency.

In an optional embodiment, after obtaining the status database of the target room, the method further includes:

step S802, taking the working parameters and the state data as Monte Carlo nodes, describing a state database by a Monte Carlo tree, and establishing a corresponding relation between the working parameters and the state data of the air conditioner in the sample room through a Monte Carlo algorithm.

Step S804, using any one monte carlo node as a starting point, determining a route to another monte carlo node through the monte carlo algorithm, so as to traverse all nodes in the monte carlo tree, and recording the traversed route and the traversed data, where the another monte carlo node is a node on the monte carlo tree except for the any one monte carlo node.

In the embodiment of the application, the corresponding relation between the sample air conditioner working parameters and the room state information can be established, and the Monte Carlo algorithm is adopted to describe the corresponding relation; simulating sample air conditioner switching and room change to a stable state; recording energy consumption of switching all states to a stable state; detecting whether a target room is in a stable state; instructing the air conditioner to switch to a stable state with the lowest energy consumption; and updating the algorithm according to the switching result.

Optionally, collecting air conditioner working parameters and room state information, keeping a value unchanged, measuring changes of other values, recording all value combinations, and establishing a corresponding relation.

In the above alternative embodiment, each set of values is combined as a node of the monte carlo algorithm; selecting two value combinations, wherein only one value is changed and the change is directly realized; and connecting all numerical value combinations according to the standard, drawing a Monte Carlo tree, traversing all states according to a Monte Carlo algorithm, and recording steps, routes and data combinations.

The Monte Carlo algorithm is a Monte Carlo tree search control algorithm, is a depth-first-based search algorithm, is simulated in a large number of random ways, finds a certain rule, and gives a statistical result for a decision maker to refer to. The monte carlo algorithm is described with reference to fig. 4, 5, 6(a) and 6(b) and the heating and ventilation device, and the heating and ventilation device is described as an air conditioner:

the reinforcement learning algorithm control framework for air conditioner energy saving is shown in fig. 4, and as shown in fig. 4, a large number of simulations are used in the reinforcement learning process based on the monte carlo tree search control algorithm in the air conditioner, so that the optimal decision is obtained for the air conditioner to use. Therefore, it can be assumed that one air conditioner is running, the virtual air conditioner does not exist objectively, but can be embodied in the air conditioner in the form of an algorithm, and the algorithm can be burnt in a chip on an air conditioner control mainboard in the form of codes/programs for solidification, and is mainly used for simulating an air conditioner regulation and control strategy, so that the optimal control strategy can be obtained and the real air conditioner is referenced and executed.

In operation, the actual air conditioner shown in fig. 4 may first obtain current air conditioner state information and environmental state, that is, information of indoor environment temperature, outdoor environment humidity, indoor environment humidity, user set temperature, electronic expansion valve opening, compressor frequency, fan rotation speed, and the like shown in fig. 5, through the state obtaining module.

In addition, in fig. 4, the current state may be determined by the state determining module to determine whether the current state reaches the stable state. If the state reaches the stable state, the environment state and the air conditioner state information are continuously acquired after waiting for time t, and then state judgment is carried out; and if the stable state is not reached, regulating and controlling the air conditioner, entering a virtual air conditioner, performing action simulation to finally obtain an optimized decision, controlling the air conditioner through a strategy execution module, judging whether the expected energy-saving effect is reached or not through the environmental state information after the time delay delta t, and if not, circulating the steps.

As shown in fig. 5, the virtual air conditioner is composed of a monte carlo algorithm and an evaluation system, the monte carlo algorithm is mainly used for simulating the execution action of the air conditioner, the evaluation system is mainly used for judging whether the expected energy-saving effect is achieved after the execution of the relevant action reaches a stable state, if not, a certain negative reward (i.e., punishment) is given, and if so, a certain reward is given. Therefore, the virtual air conditioner selects the execution strategy with high reward according to the intention of the control algorithm and transmits the execution strategy to the real air conditioner.

It should be noted that the monte carlo algorithm is mainly divided into four stages: selection, expansion, simulation and backtracking. And acquiring the current environmental state, namely acquiring the state information through a state acquisition module in the running process of the air conditioner, judging the state, and synchronizing the current state information into the virtual air conditioner if the environmental state stable state condition is not met.

In an optional embodiment, after recording the traversal route and the traversal data, the method further includes:

step S902, simulating a switching process of switching the state of the working parameter of the air conditioner in the sample room to a first stable state and switching the state of the state data of the sample room to a second stable state;

and step S904, recording the energy consumption of the air conditioner in the sample room during the switching process.

In the embodiment of the present application, the switching process of simulating the state of the operating parameter of the air conditioner in the sample room to switch to the first stable state and the state of the sample room state data to switch to the second stable state, for example, simulating the change of the operating parameter of the air conditioner, simulating the change of the room state information, recording the state change and the switching route.

Calculating an air conditioner state switching route according to the state of each room; according to the air conditioner state switching route and steps, finding out corresponding temperature, electronic expansion valve opening degree, compressor frequency and fan rotating speed changes; and measuring and recording the energy consumption of the air conditioner switching temperature, the opening of the electronic expansion valve, the frequency of the compressor and the rotating speed of the fan, and calculating the air conditioner switching energy consumption.

step S1002, detecting whether the state of the target room is a stable state;

step S1004, if the state of the target room is not the stable state, switching the state of the target room to the stable state when controlling the air conditioner in the target room to switch to the lowest energy consumption;

step S1006, updating the monte carlo algorithm.

In the embodiment of the application, the room states can be substituted into the air conditioner to act, the room state information is added, all the states are traversed by the Monte Carlo algorithm, and the stable state of each room state information is obtained.

In the embodiment of the present application, the monte carlo algorithm may be updated by the following method: setting a priority for each switching route according to the switching energy consumption from low to high; if the energy consumption is less than the theoretical value, updating the energy consumption record and improving the priority of the switching route; measuring actual switching energy consumption, and if the actual switching energy consumption is larger than a theoretical value, reducing the priority of the switching route; and detecting whether the room reaches a stable state or not, and deleting the switching route if the room does not reach the stable state.

In an alternative embodiment, whether the state of the target room is a stable state is detected as follows:

step S1102, detecting whether a state of an operating parameter of an air conditioner in the target room is the first stable state and whether a state of state data in the target room is the second stable state;

step S1104, performing the above detection step again after a predetermined time interval;

step S1106, determining that the state of the target room is a stable state if the two detection results are completely consistent;

in step S1108, if the two detection results are not completely consistent, it is determined that the state of the target room is an unstable state.

In step S1102, the operating parameters of the air conditioner in the target room and the status data in the target room are detected to determine whether the status of the operating parameters of the air conditioner in the target room is the first stable status and whether the status of the status data in the target room is the second stable status.

Optionally, the predetermined time may be half an hour, for example, the detecting step may be executed again at intervals of half an hour, if the room status data of two times completely match, the state of the target room is determined to be a stable state, and if the room status data of two times do not completely match, the state of the target room is determined to be an unstable state.

In an alternative embodiment, recording the energy consumption of the air conditioner in the sample room during the switching process includes:

step S1202, determining working parameters of the air conditioner in the sample room according to the switching process and a switching route corresponding to the switching process;

step S1204, measuring energy consumption generated by the air conditioner when the operating parameter changes, and calculating to obtain total energy consumption of the air conditioner.

In the embodiment of the present application, according to the switching process and the switching route corresponding to the switching process, the operating parameters of the air conditioner in the sample room are determined, and the total energy consumption of the air conditioner is obtained by measuring the energy consumption generated by the air conditioner at each operating parameter and calculating the sum of the energy consumption at each time.

In an alternative embodiment, switching the state of the target room to the stable state includes:

step S1302, detecting whether a node of the working parameter and the state data exists in the monte carlo tree;

step S1304, if the nodes of the working parameters and the state data exist in the monte carlo tree, determining the energy consumption of the air conditioner according to a route where the nodes reach a stable state;

step S1304, if the monte carlo tree does not have the node of the working parameter and/or the state data, simulating to obtain a simulated switching route according to the monte carlo algorithm, and calculating energy consumption corresponding to the simulated switching route;

step S1304, switching the state of the target room to the stable state according to the switching route corresponding to the energy consumption with the lowest energy consumption value.

In the embodiment of the application, the current working parameters of the air conditioner and the current state information of the room can be collected and substituted into the Monte Carlo trees of the sample air conditioner and the target room; detecting whether nodes of the working parameters and the state data exist in the Monte Carlo tree or not, and if the nodes of the working parameters and the state data exist in the Monte Carlo tree, obtaining corresponding switching energy consumption according to a route reaching a stable state; if the Monte Carlo tree has no node of the numerical combination, simulating a switching route from a room to a stable state by using a Monte Carlo algorithm, and calculating energy consumption corresponding to the simulated switching route; and switching the state of the target room to the stable state according to a switching route corresponding to the energy consumption with the lowest energy consumption value, and indicating the air conditioner to implement the action.

In the embodiment of the present application, assuming that the air conditioner has two control actions (actually, there may be many kinds) in each state, assuming that the air conditioner state information and the environmental state information are collectively referred to as the operating parameters of the air conditioner, the following describes a control method of the air conditioner with reference to fig. 6(a) and 6 (b):

in an alternative embodiment, as shown in fig. 6(a), any state of the air conditioner operating parameter is S₁Change 2 kinds of data, and perform 2 actions A_1,1And A_1,2To obtain 2 room states S_1,1To S_2,1And S is_1,1And S_2,1Each of the 2 actions A_1,1,1、A_2,1,1、A_1,2,1、A_2,2,1To obtain 4 room states S_1,1,1、S_2,1,1、S_1,2,1、S_2,2,1(ii) a By analogy, all the states are traversed by using the Monte Carlo algorithm, and the stable state which is finally reached by each room state is calculated.

As shown in FIG. 6(a), the current state information is S₁Under which there are two actions

And

after the two actions are executed, two states S are provided_2,1And S_2,2. By analogy, the state can be represented as S_L1,L2L1 indicates that L1-1 actions have been performed, and L2 is a sequence indicating the selected branch routes, e.g., L2 is 1,1,2, indicating that the first route is selected for the first time, the first route is selected for the second time, and the second route is selected for the third time. As shown in FIG. 6(a), S₁To S via a route selected from 1-1-2_4,1,1,2。

According to the Monte Carlo algorithm, when the air conditioner is in the state S₁Now, a decision needs to be madeAfter the virtual air conditioner performs N simulations using the monte carlo algorithm, it is known that the red route in fig. 6(a) is the optimal route. The virtual air conditioner outputs the next action as

The real air conditioner acts according to the virtual air conditioner

After a delay of Δ t, the status information S is obtained_2,1Will S₂When the current state is switched to, the air conditioner needs to execute the next action, and the control process is called again, as shown in fig. 6(b), the next action is assumed to be

Then the next status information is obtained as S_3,2And the rest can be done in the same way until the environment stable state is reached. And the air conditioner keeps continuously acquiring the state so as to be in case of breaking the environment stable state, and the Monte Carlo tree search control algorithm is required to be applied again to calculate the strategy.

In the embodiment of the application, energy consumption from one state to another state can be used as feedback, and then energy consumption of some strategies can be judged, the Monte Carlo algorithm simulates the experimental schemes before leaving factory by a random means to obtain energy consumption feedback values, and after N times of simulation in the virtual air conditioner, the optimal route (the total energy consumption value of one set of routes is the lowest) is judged according to the energy consumption feedback value of each route.

Regarding the monte carlo optimal route, the selected policy information (branch route) and the corresponding energy consumption information, and information before and after state transition can be burned into the chip as prior knowledge (known information) through codes according to pre-acquired experimental data, such as from one state to another state. In practical application of a user family, the generated environmental state information is far wider than the information covered by an experimental scheme, the Monte Carlo algorithm has two functions of utilization and exploration, the prior information is utilized, prior knowledge is preferentially adopted for simulation, and if the prior knowledge does not exist, simulation exploration is carried out, so that an optimal route is selected.

In an optional embodiment, the method for limiting the energy saving range may be firstly applied to adjust the amount of cooling and heating of the room, that is, the cooling and heating amount is appropriately reduced from a fixed point to an elastic area, which is beneficial to reducing the energy saving range under the condition of unobvious reduction of comfort, and then the monte carlo tree search control algorithm is applied to continue optimization within the energy saving range.

Based on the embodiment of the application, the problem of balance among all controlled factors of the air conditioner can be solved, the phenomenon of incongruity of 'big horse pulling a trolley' is avoided, the problem of refrigerating/heating requirements of the actual living environment of a user can be solved, and the phenomenon of derailment between the refrigerating capacity output blindly and the actual requirements is avoided.

Example 2

According to an embodiment of the present invention, there is also provided an apparatus for implementing the method for controlling an air conditioner, fig. 7 is a schematic structural diagram of an apparatus for controlling an air conditioner according to an embodiment of the present invention, and as shown in fig. 7, the apparatus for controlling an air conditioner includes: an acquisition module 70, a determination module 72, and an acquisition module 74, wherein:

the acquisition module 70 is used for acquiring first room information of the sample room and second room information of the target room; a determining module 72, configured to determine a room type of the target room according to the first room information and the second room information; and an obtaining module 74, configured to obtain control information according to the room type, where the control information is used to control a cooling amount and/or a heating amount of an air conditioner in the target room.

It should be noted that the above modules may be implemented by software or hardware, for example, for the latter, the following may be implemented: the modules can be located in the same processor; alternatively, the modules may be located in different processors in any combination.

It should be noted that the above-mentioned acquisition module 70, determination module 72 and acquisition module 74 correspond to steps S102 to S106 in embodiment 1, and the above-mentioned modules are the same as the examples and application scenarios realized by the corresponding steps, but are not limited to the disclosure of embodiment 1. It should be noted that the modules described above may be implemented in a computer terminal as part of an apparatus.

It should be noted that, reference may be made to the relevant description in embodiment 1 for alternative or preferred embodiments of this embodiment, and details are not described here again.

The above-mentioned device for controlling an air conditioner may further include a processor and a memory, and the above-mentioned collecting module 70, determining module 72, obtaining module 74, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to implement corresponding functions.

The processor comprises a kernel, and the kernel calls a corresponding program unit from the memory, wherein one or more than one kernel can be arranged. The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.

According to the embodiment of the application, the embodiment of the storage medium is also provided. Optionally, in this embodiment, the storage medium includes a stored program, and the device on which the storage medium is located is controlled to execute any one of the above methods for controlling the air conditioner when the program runs.

Optionally, in this embodiment, the storage medium may be located in any one of a group of computer terminals in a computer network, or in any one of a group of mobile terminals, and the storage medium includes a stored program.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: acquiring first room information of a sample room and second room information of a target room; determining a room type of the target room according to the first room information and the second room information; and acquiring control information according to the room type, wherein the control information is used for controlling the cooling capacity and/or the heating capacity of the air conditioner in the target room.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: acquiring the room type of the sample room; measuring the room area of each sample room according to the room type of the sample room; and calculating the power consumption and the energy consumption ratio of the air conditioners in the sample rooms based on the room area of each sample room to obtain the refrigerating capacity and/or the heating capacity of the air conditioners in the sample rooms.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: acquiring the energy consumption ratio of the air conditioner in the sample room; detecting the power consumption of the air conditioner, and calculating to obtain the power consumption of the air conditioner; and calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: determining the room area of each sample room according to the room type of the sample room; determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of each sample room; and determining a curve graph of each sample room by taking the room area of the sample room as an abscissa of a coordinate system and taking the refrigerating capacity and/or the heating capacity of the sample room as an ordinate of the coordinate system.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: acquiring the room area of the target room; detecting the power consumption of the air conditioner in the target room, and calculating to obtain the power consumption of the air conditioner; and calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity of the air conditioner in the target room.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of the corresponding sample room in the curve chart according to the room area of the target room; calculating the maximum value and the minimum value to obtain the average value of the refrigerating capacity and/or the heating capacity; and determining the room type of the sample room corresponding to the average value of the cooling capacity and/or the heating capacity as the room type of the target room.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: collecting working parameters of an air conditioner in the target room, wherein the working parameters comprise at least one of the following parameters: setting a temperature value, the opening of an electronic expansion valve, the frequency of a compressor and the rotating speed of a fan; collecting state data of the target room, wherein the state data comprises at least one of the following: indoor temperature, indoor humidity, outdoor humidity; and obtaining a state database of the target room by combining the working parameters and the state data.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: taking the working parameters and the state data as Monte Carlo nodes, describing a state database by a Monte Carlo tree, and establishing a corresponding relation between the working parameters and the state data of the air conditioner in the sample room through a Monte Carlo algorithm; and determining routes to other Monte Carlo nodes by using any Monte Carlo node as a starting point through the Monte Carlo algorithm, traversing all the nodes in the Monte Carlo tree, and recording the traversed routes and the traversed data, wherein the other Monte Carlo nodes are the nodes on the Monte Carlo tree except the Monte Carlo node.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: simulating a switching process of switching the state of the working parameters of the air conditioner in the sample room to a first stable state and switching the state of the state data of the sample room to a second stable state; and recording the energy consumption of the air conditioner in the sample room in the switching process.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: detecting whether the state of the target room is a stable state; if the state of the target room is not the stable state, switching the state of the target room to the stable state when controlling the air conditioner in the target room to switch to the lowest energy consumption; the monte carlo algorithm described above is updated.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: a detection step of detecting whether a state of an operating parameter of an air conditioner in the target room is the first stable state and whether a state of state data in the target room is the second stable state; after a predetermined time interval, executing the detection step again; if the two detection results are completely consistent, determining that the state of the target room is a stable state; and if the two detection results are not completely consistent, determining that the state of the target room is an unstable state.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: determining working parameters of the air conditioner in the sample room according to the switching process and a switching route corresponding to the switching process; and measuring the energy consumption generated by the air conditioner when the working parameters are changed every time, and calculating to obtain the total energy consumption of the air conditioner.

Optionally, the program controls the device on which the storage medium is located to perform the following functions when running: detecting whether nodes of the working parameters and the state data exist in the Monte Carlo tree or not; if the Monte Carlo tree has the nodes of the working parameters and the state data, determining the energy consumption of the air conditioner according to the route of the nodes to the stable state; if the Monte Carlo tree does not have the nodes of the working parameters and/or the state data, simulating to obtain a simulated switching route according to the Monte Carlo algorithm, and calculating energy consumption corresponding to the simulated switching route; and switching the state of the target room to the stable state according to a switching route corresponding to the energy consumption with the lowest energy consumption value.

According to the embodiment of the application, the embodiment of the processor is also provided. Optionally, in this embodiment, the processor is configured to execute a program, where the program executes any one of the above methods for controlling an air conditioner.

The embodiment of the application provides equipment, the equipment comprises a processor, a memory and a program which is stored on the memory and can run on the processor, and the following steps are realized when the processor executes the program: acquiring first room information of a sample room and second room information of a target room; determining a room type of the target room according to the first room information and the second room information; and acquiring control information according to the room type, wherein the control information is used for controlling the cooling capacity and/or the heating capacity of the air conditioner in the target room.

Optionally, when the processor executes the program, the room type of the sample room may be obtained; measuring the room area of each sample room according to the room type of the sample room; and calculating the power consumption and the energy consumption ratio of the air conditioners in the sample rooms based on the room area of each sample room to obtain the refrigerating capacity and/or the heating capacity of the air conditioners in the sample rooms.

Optionally, when the processor executes the program, the energy consumption ratio of the air conditioner in the sample room may also be obtained; detecting the power consumption of the air conditioner, and calculating to obtain the power consumption of the air conditioner; and calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity.

Optionally, when the processor executes the program, the room area of each sample room may be determined according to the room type of the sample room; determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of each sample room; and determining a curve graph of each sample room by taking the room area of the sample room as an abscissa of a coordinate system and taking the refrigerating capacity and/or the heating capacity of the sample room as an ordinate of the coordinate system.

Optionally, when the processor executes a program, the room area of the target room may also be obtained; detecting the power consumption of the air conditioner in the target room, and calculating to obtain the power consumption of the air conditioner; and calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity of the air conditioner in the target room.

Optionally, when the processor executes a program, the maximum value and the minimum value of the cooling capacity and/or the heating capacity of the corresponding sample room in the graph may be determined according to the room area of the target room; calculating the maximum value and the minimum value to obtain the average value of the refrigerating capacity and/or the heating capacity; and determining the room type of the sample room corresponding to the average value of the cooling capacity and/or the heating capacity as the room type of the target room.

Optionally, when the processor executes a program, the processor may further collect an operating parameter of an air conditioner in the target room, where the operating parameter includes at least one of: setting a temperature value, the opening of an electronic expansion valve, the frequency of a compressor and the rotating speed of a fan; collecting state data of the target room, wherein the state data comprises at least one of the following: indoor temperature, indoor humidity, outdoor humidity; and obtaining a state database of the target room by combining the working parameters and the state data.

Optionally, when the processor executes a program, the working parameters and the state data may be used as monte carlo nodes, a state database is described by a monte carlo tree, and a corresponding relationship between the working parameters and the state data of the air conditioner in the sample room is established by a monte carlo algorithm; and determining routes to other Monte Carlo nodes by using any Monte Carlo node as a starting point through the Monte Carlo algorithm, traversing all the nodes in the Monte Carlo tree, and recording the traversed routes and the traversed data, wherein the other Monte Carlo nodes are the nodes on the Monte Carlo tree except the Monte Carlo node.

Optionally, when the processor executes a program, a switching process of switching the state of the operating parameter of the air conditioner in the sample room to a first stable state and switching the state of the state data of the sample room to a second stable state may also be simulated; and recording the energy consumption of the air conditioner in the sample room in the switching process.

Optionally, when the processor executes a program, it may further detect whether the state of the target room is a stable state; if the state of the target room is not the stable state, switching the state of the target room to the stable state when controlling the air conditioner in the target room to switch to the lowest energy consumption; the monte carlo algorithm described above is updated.

Optionally, when the processor executes a program, the processor may further execute a detecting step of detecting whether a state of an operating parameter of an air conditioner in the target room is the first stable state, and whether a state of state data in the target room is the second stable state; after a predetermined time interval, executing the detection step again; if the two detection results are completely consistent, determining that the state of the target room is a stable state; and if the two detection results are not completely consistent, determining that the state of the target room is an unstable state.

Optionally, when the processor executes a program, the processor may further determine an operating parameter of the air conditioner in the sample room according to the switching process and a switching route corresponding to the switching process; and measuring the energy consumption generated by the air conditioner when the working parameters are changed every time, and calculating to obtain the total energy consumption of the air conditioner.

Optionally, when the processor executes a program, it may further detect whether a node of the working parameter and the state data exists in the monte carlo tree; if the Monte Carlo tree has the nodes of the working parameters and the state data, determining the energy consumption of the air conditioner according to the route of the nodes to the stable state; if the Monte Carlo tree does not have the nodes of the working parameters and/or the state data, simulating to obtain a simulated switching route according to the Monte Carlo algorithm, and calculating energy consumption corresponding to the simulated switching route; and switching the state of the target room to the stable state according to a switching route corresponding to the energy consumption with the lowest energy consumption value.

The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: acquiring first room information of a sample room and second room information of a target room; determining a room type of the target room according to the first room information and the second room information; and acquiring control information according to the room type, wherein the control information is used for controlling the cooling capacity and/or the heating capacity of the air conditioner in the target room.

Optionally, when the computer program product executes a program, the room type of the sample room may also be obtained; measuring the room area of each sample room according to the room type of the sample room; and calculating the power consumption and the energy consumption ratio of the air conditioners in the sample rooms based on the room area of each sample room to obtain the refrigerating capacity and/or the heating capacity of the air conditioners in the sample rooms.

Optionally, when the computer program product executes a program, the energy consumption ratio of the air conditioner in the sample room may also be obtained; detecting the power consumption of the air conditioner, and calculating to obtain the power consumption of the air conditioner; and calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity.

Optionally, when the computer program product executes a program, the room area of each sample room may be determined according to the room type of the sample room; determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of each sample room; and determining a curve graph of each sample room by taking the room area of the sample room as an abscissa of a coordinate system and taking the refrigerating capacity and/or the heating capacity of the sample room as an ordinate of the coordinate system.

Optionally, when the computer program product executes a program, the room area of the target room may also be obtained; detecting the power consumption of the air conditioner in the target room, and calculating to obtain the power consumption of the air conditioner; and calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity of the air conditioner in the target room.

Optionally, when the computer program product executes a program, the maximum value and the minimum value of the cooling capacity and/or the heating capacity of the corresponding sample room in the graph may be determined according to the room area of the target room; calculating the maximum value and the minimum value to obtain the average value of the refrigerating capacity and/or the heating capacity; and determining the room type of the sample room corresponding to the average value of the cooling capacity and/or the heating capacity as the room type of the target room.

Optionally, when the computer program product executes a program, the operating parameters of the air conditioner in the target room may be collected, where the operating parameters include at least one of: setting a temperature value, the opening of an electronic expansion valve, the frequency of a compressor and the rotating speed of a fan; collecting state data of the target room, wherein the state data comprises at least one of the following: indoor temperature, indoor humidity, outdoor humidity; and obtaining a state database of the target room by combining the working parameters and the state data.

Optionally, when the computer program product executes a program, the operating parameters and the state data may be used as monte carlo nodes, a state database is described by a monte carlo tree, and a corresponding relationship between the operating parameters and the state data of the air conditioner in the sample room is established by a monte carlo algorithm; and determining routes to other Monte Carlo nodes by using any Monte Carlo node as a starting point through the Monte Carlo algorithm, traversing all the nodes in the Monte Carlo tree, and recording the traversed routes and the traversed data, wherein the other Monte Carlo nodes are the nodes on the Monte Carlo tree except the Monte Carlo node.

Optionally, when the computer program product executes a program, a switching process of switching the state of the operating parameter of the air conditioner in the sample room to a first stable state and switching the state of the state data of the sample room to a second stable state may also be simulated; and recording the energy consumption of the air conditioner in the sample room in the switching process.

Optionally, when the computer program product executes a program, it may further detect whether the state of the target room is a stable state; if the state of the target room is not the stable state, switching the state of the target room to the stable state when controlling the air conditioner in the target room to switch to the lowest energy consumption; the monte carlo algorithm described above is updated.

Optionally, when the computer program product executes a program, the method may further include detecting whether a state of an operating parameter of an air conditioner in the target room is the first stable state, and whether a state of state data in the target room is the second stable state; after a predetermined time interval, executing the detection step again; if the two detection results are completely consistent, determining that the state of the target room is a stable state; and if the two detection results are not completely consistent, determining that the state of the target room is an unstable state.

Optionally, when the computer program product executes a program, determining operating parameters of the air conditioner in the sample room according to the switching process and a switching route corresponding to the switching process; and measuring the energy consumption generated by the air conditioner when the working parameters are changed every time, and calculating to obtain the total energy consumption of the air conditioner.

Optionally, when the computer program product executes a program, it may further detect whether a node of the working parameter and the state data exists in the monte carlo tree; if the Monte Carlo tree has the nodes of the working parameters and the state data, determining the energy consumption of the air conditioner according to the route of the nodes to the stable state; if the Monte Carlo tree does not have the nodes of the working parameters and/or the state data, simulating to obtain a simulated switching route according to the Monte Carlo algorithm, and calculating energy consumption corresponding to the simulated switching route; and switching the state of the target room to the stable state according to a switching route corresponding to the energy consumption with the lowest energy consumption value.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims

1. A method of controlling an air conditioner, comprising:

acquiring first room information of a sample room and second room information of a target room;

determining the room type of the target room according to the first room information and the second room information;

acquiring control information according to the room type, wherein the control information is used for controlling the refrigerating capacity and/or the heating capacity of an air conditioner in the target room;

wherein determining the room type of the target room according to the first room information and the second room information comprises:

determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of the corresponding sample room in the curve graph according to the room area of the target room;

calculating the maximum value and the minimum value to obtain the average value of the refrigerating capacity and/or the heating capacity;

determining the room type of the sample room corresponding to the average value of the refrigerating capacity and/or the heating capacity as the room type of the target room;

the area of the sample room is taken as the abscissa of a coordinate system, and the refrigerating capacity and/or the heating capacity of the sample room are/is taken as the ordinate of the coordinate system to obtain the curve graph; and calculating the power consumption and the energy consumption ratio of the air conditioner in the sample room to obtain the refrigerating capacity and/or the heating capacity based on the room area of the sample room.

2. The method of claim 1, wherein the first room information comprises at least one of: room type, room area, room cooling capacity, and/or heating capacity; collecting first room information of a sample room, comprising:

acquiring a room type of the sample room;

measuring the room area of the sample room according to the room type of the sample room;

and calculating the power consumption and the energy consumption ratio of the air conditioner in the sample room based on the room area of the sample room to obtain the refrigerating capacity and/or the heating capacity of the air conditioner in the sample room.

3. The method of claim 2, wherein calculating the power consumption and the energy consumption ratio of the air conditioners in the sample room to obtain the cooling capacity and/or the heating capacity of the air conditioners in the sample room comprises:

acquiring the energy consumption ratio of the air conditioner in the sample room;

detecting the power consumption of the air conditioner, and calculating to obtain the power consumption of the air conditioner;

and calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity.

4. The method of claim 1, wherein prior to determining the room type of the target room from the first room information and the second room information, the method further comprises:

determining the room area of the sample room according to the room type of the sample room;

determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of the sample room;

and determining a curve graph of the sample room by taking the room area of the sample room as an abscissa of a coordinate system and taking the refrigerating capacity and/or the heating capacity of the sample room as an ordinate of the coordinate system.

5. The method of claim 4, wherein the second room information comprises at least one of: room area, room cooling capacity and/or heating capacity; collecting second room information of a target room, comprising:

acquiring the room area of the target room;

detecting the power consumption of an air conditioner in the target room, and calculating to obtain the power consumption of the air conditioner;

and calculating the power consumption and the energy consumption ratio of the air conditioner to obtain the refrigerating capacity and/or the heating capacity of the air conditioner in the target room.

6. The method of any one of claims 1 to 5, wherein the room type comprises at least one of: house type structure, building material, position orientation, environmental floor, thermal-insulated effect.

7. The method according to any one of claims 1 to 5, further comprising:

collecting operating parameters of an air conditioner in the target room, wherein the operating parameters comprise at least one of the following: setting a temperature value, the opening of an electronic expansion valve, the frequency of a compressor and the rotating speed of a fan;

acquiring status data of the target room, wherein the status data comprises at least one of: indoor temperature, indoor humidity, outdoor humidity;

and obtaining a state database of the target room by combining the working parameters and the state data.

8. The method of claim 7, wherein after obtaining the status database of the target room, the method further comprises:

taking the working parameters and the state data as Monte Carlo nodes, describing a state database by a Monte Carlo tree, and establishing a corresponding relation between the working parameters and the state data of the air conditioner in the sample room by a Monte Carlo algorithm;

and determining routes reaching other Monte Carlo nodes by using any Monte Carlo node as a starting point through the Monte Carlo algorithm, traversing all nodes in the Monte Carlo tree, and recording the traversed routes and traversed data, wherein the other Monte Carlo nodes are nodes except any Monte Carlo node on the Monte Carlo tree.

9. The method of claim 8, wherein after recording the traversal route and the traversal data, the method further comprises:

simulating a switching process of switching the state of the working parameters of the air conditioner in the sample room to a first stable state and switching the state of the sample room state data to a second stable state;

recording the energy consumption of the air conditioner in the sample room during the switching process.

10. The method of claim 9, wherein after recording the traversal route and the traversal data, the method further comprises:

detecting whether the state of the target room is a stable state;

if the state of the target room is not the stable state, switching the state of the target room to the stable state when the air conditioner in the target room is controlled to be switched to the lowest energy consumption;

and updating the Monte Carlo algorithm.

11. The method according to claim 10, characterized by detecting whether the state of the target room is a steady state by:

detecting whether the state of the working parameter of the air conditioner in the target room is the first stable state and whether the state of the state data in the target room is the second stable state;

after a predetermined time interval, the detecting step is executed again;

if the two detection results are completely consistent, determining that the state of the target room is a stable state;

and if the two detection results are not completely consistent, determining that the state of the target room is an unstable state.

12. The method of claim 9, wherein recording energy consumption of air conditioners in the sample room during the switching process comprises:

determining working parameters of the air conditioner in the sample room according to the switching process and a switching route corresponding to the switching process;

and measuring the energy consumption generated by the air conditioner when the working parameters are changed every time, and calculating to obtain the total energy consumption of the air conditioner.

13. The method of claim 10, wherein switching the state of the target room to the steady state comprises:

detecting whether nodes of the working parameters and the state data exist in the Monte Carlo tree or not;

if the nodes of the working parameters and the state data exist in the Monte Carlo tree, determining the energy consumption of the air conditioner according to the route of the nodes to a stable state;

if the nodes of the working parameters and/or the state data do not exist in the Monte Carlo tree, simulating to obtain a simulated switching route according to the Monte Carlo algorithm, and calculating energy consumption corresponding to the simulated switching route;

and switching the state of the target room to the stable state according to a switching route corresponding to the energy consumption with the lowest energy consumption value.

14. An apparatus for controlling an air conditioner, comprising:

the acquisition module is used for acquiring first room information of the sample room and second room information of the target room;

a determining module, configured to determine a room type of the target room according to the first room information and the second room information;

the acquisition module is used for acquiring control information according to the room type, wherein the control information is used for controlling the refrigerating capacity and/or the heating capacity of an air conditioner in the target room;

wherein the apparatus is further configured to determine the room type of the target room by: determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of the corresponding sample room in the curve graph according to the room area of the target room; calculating the maximum value and the minimum value to obtain the average value of the refrigerating capacity and/or the heating capacity; determining the room type of the sample room corresponding to the average value of the refrigerating capacity and/or the heating capacity as the room type of the target room;

15. A storage medium comprising a stored program, wherein the program, when executed, controls an apparatus on which the storage medium is located to perform the steps of: acquiring first room information of a sample room and second room information of a target room; determining the room type of the target room according to the first room information and the second room information; acquiring control information according to the room type, wherein the control information is used for controlling the refrigerating capacity and/or the heating capacity of an air conditioner in the target room; wherein determining the room type of the target room according to the first room information and the second room information comprises: determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of the corresponding sample room in the curve graph according to the room area of the target room; calculating the maximum value and the minimum value to obtain the average value of the refrigerating capacity and/or the heating capacity; determining the room type of the sample room corresponding to the average value of the refrigerating capacity and/or the heating capacity as the room type of the target room; the area of the sample room is taken as the abscissa of a coordinate system, and the refrigerating capacity and/or the heating capacity of the sample room are/is taken as the ordinate of the coordinate system to obtain the curve graph; and calculating the power consumption and the energy consumption ratio of the air conditioner in the sample room to obtain the refrigerating capacity and/or the heating capacity based on the room area of the sample room.

16. A processor, wherein the processor is configured to execute a program, wherein the program executes to perform the following steps: acquiring first room information of a sample room and second room information of a target room; determining the room type of the target room according to the first room information and the second room information; acquiring control information according to the room type, wherein the control information is used for controlling the refrigerating capacity and/or the heating capacity of an air conditioner in the target room; wherein determining the room type of the target room according to the first room information and the second room information comprises: determining the maximum value and the minimum value of the refrigerating capacity and/or the heating capacity of the corresponding sample room in the curve graph according to the room area of the target room; calculating the maximum value and the minimum value to obtain the average value of the refrigerating capacity and/or the heating capacity; determining the room type of the sample room corresponding to the average value of the refrigerating capacity and/or the heating capacity as the room type of the target room; the area of the sample room is taken as the abscissa of a coordinate system, and the refrigerating capacity and/or the heating capacity of the sample room are/is taken as the ordinate of the coordinate system to obtain the curve graph; and calculating the power consumption and the energy consumption ratio of the air conditioner in the sample room to obtain the refrigerating capacity and/or the heating capacity based on the room area of the sample room.