CN116859768A

CN116859768A - Energy scheduling method and device applied to smart home

Info

Publication number: CN116859768A
Application number: CN202311023623.6A
Authority: CN
Inventors: 陈小平; 孙欢
Original assignee: Foshan Viomi Electrical Technology Co Ltd
Current assignee: Foshan Viomi Electrical Technology Co Ltd
Priority date: 2023-08-14
Filing date: 2023-08-14
Publication date: 2023-10-10

Abstract

The invention discloses an energy scheduling method and device applied to intelligent home, wherein the method comprises the following steps: determining operation energy consumption information of each intelligent home device in the intelligent home scene; judging whether all intelligent household devices meet preset operation energy consumption conditions according to all operation energy consumption information; if not, inputting all the operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result; and executing regulation and control operation on all the intelligent household devices according to the energy scheduling result. Therefore, the intelligent household equipment energy scheduling method and system can realize the intelligent household equipment energy scheduling function, are beneficial to improving the comprehensiveness and rationality of the energy scheduling mode of the intelligent household equipment, and are beneficial to improving the regulation accuracy and the regulation reliability of the intelligent household equipment, so that the energy scheduling accuracy and the energy scheduling reliability of the intelligent household equipment are beneficial to improving, and the energy consumption of the intelligent household equipment is further beneficial to reducing.

Description

Energy scheduling method and device applied to smart home

Technical Field

The invention relates to the technical field of energy scheduling, in particular to an energy scheduling method and device applied to intelligent home.

Background

Energy is the basis of survival and development of modern society, and in order to cope with energy crisis and environmental pollution, research on energy scheduling is performed in addition to research on new energy; the energy scheduling of smart home is also a big research hotspot.

At present, the energy scheduling mode of the existing intelligent home mainly carries out energy scheduling on the intelligent home according to self subjective consciousness by staff, and the energy scheduling result obtained by manual operation is easily influenced by subjective factors, so that the energy scheduling accuracy and reliability of the intelligent home are low. Therefore, it is important to provide a new energy scheduling method for smart home to improve the accuracy and reliability of energy scheduling.

Disclosure of Invention

The technical problem to be solved by the invention is to provide the energy scheduling method and the device applied to the intelligent home, which can improve the accuracy and the reliability of energy scheduling.

In order to solve the technical problems, the first aspect of the invention discloses an energy scheduling method applied to intelligent home, which comprises the following steps:

determining operation energy consumption information of each intelligent home device in the intelligent home scene;

Judging whether all the intelligent household devices meet preset operation energy consumption conditions according to all the operation energy consumption information;

when judging that not all the intelligent household devices meet the operation energy consumption conditions, inputting all the operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result;

and executing regulation and control operation on all the intelligent household devices according to the energy scheduling result.

In an optional implementation manner, in a first aspect of the present invention, the inputting all the operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result includes:

analyzing the current control parameters of each intelligent household device according to all the operation energy consumption information and the operation configuration information of each intelligent household device;

analyzing the intelligent home scene based on the processing operation requirement and the processing effect requirement corresponding to the intelligent home equipment according to the current control parameters of all the intelligent home equipment;

and carrying out energy scheduling operation on all the operation energy consumption information according to the processing operation requirement, the processing effect requirement and the operation configuration information of each intelligent household device to obtain an energy scheduling result.

In an optional implementation manner, in a first aspect of the present invention, performing an energy scheduling operation on all the operation energy consumption information according to the processing operation requirement, the processing effect requirement, and the operation configuration information of each smart home device to obtain an energy scheduling result, where the energy scheduling operation includes:

screening at least one core home device from all the intelligent home devices according to the processing operation requirement and the processing effect requirement;

for each core home device, at least one auxiliary home device matched with the core home device is selected from all the intelligent home devices according to the processing operation requirement, the processing effect requirement and the function configuration information of each intelligent home device;

determining auxiliary energy consumption requirements corresponding to all auxiliary household devices according to the operation energy consumption information of the core household devices, and analyzing the replacement feasibility corresponding to all the auxiliary household devices according to the auxiliary energy consumption requirements, the operation configuration information and the function configuration information corresponding to each auxiliary household device and the processing effect requirements;

when the replacement feasibility is larger than or equal to a preset replacement feasibility threshold, analyzing equipment replacement schemes corresponding to all the auxiliary household equipment according to the auxiliary energy consumption requirements, the operation configuration information and the function configuration information corresponding to each auxiliary household equipment and the processing effect requirements;

And determining the consumable energy information of each intelligent household device according to the device alternative scheme and the operation configuration information of all the intelligent household devices, and determining an energy scheduling result according to the consumable energy information of each intelligent household device.

As an optional implementation manner, in the first aspect of the present invention, the auxiliary home device includes a first auxiliary home device that is currently operating and/or a second auxiliary home device that may be used to replace the first auxiliary home device;

and for each core home device, analyzing device alternatives corresponding to all the auxiliary home devices according to the auxiliary energy consumption requirement, the operation configuration information and the function configuration information corresponding to each auxiliary home device, and the processing effect requirement, including:

determining the achievable effect condition of the first auxiliary home equipment according to the auxiliary energy consumption requirement and the operation configuration information corresponding to the first auxiliary home equipment;

judging whether the first auxiliary household equipment meets preset energy consumption and treatment effect conditions according to the treatment effect requirements and the achievable effect conditions;

When the first auxiliary household equipment meets the energy consumption and treatment effect conditions, determining first operation regulation and control information of the first auxiliary household equipment according to the auxiliary energy consumption requirements, the achievable effect conditions and the treatment effect requirements so as to determine equipment alternatives corresponding to all the auxiliary household equipment;

when the first auxiliary household equipment is judged to not meet the energy consumption and processing effect conditions, at least one target second auxiliary household equipment is selected from all the second auxiliary household equipment according to the auxiliary energy consumption requirements and the operation configuration information corresponding to each second auxiliary household equipment;

determining second operation regulation and control information of the target second auxiliary home equipment according to the auxiliary energy consumption requirement, the operation configuration information and the function configuration information corresponding to each second auxiliary home equipment and the processing effect requirement so as to determine equipment alternatives corresponding to all the auxiliary home equipment;

the first operation regulation information and the second operation regulation information comprise operation duration regulation information and/or operation mode regulation information and/or operation grade regulation information.

In an optional implementation manner, in the first aspect of the present invention, after the inputting all the operation energy consumption information into a preset energy scheduling model, the method further includes:

determining expected energy scheduling results corresponding to all the operation energy consumption information, and judging whether the expected energy scheduling results are matched with the energy scheduling results or not;

and when the judgment result is negative, executing self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result.

In a first aspect of the present invention, the performing a self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result includes:

determining scheduling difference information according to the expected energy scheduling result and the energy scheduling result;

according to the scheduling difference information, training adjustment information corresponding to the energy scheduling model is determined, and according to the training adjustment information, the operation energy consumption information and the intelligent home scene, a first self-learning operation is executed on the energy scheduling model;

Determining at least one difference type corresponding to the scheduling difference information, and analyzing a difference occurrence reason set corresponding to each difference type according to all the difference types and historical training adjustment data corresponding to the energy scheduling model;

analyzing operation adjustment information of energy scheduling analysis aiming at each difference type according to the difference occurrence reason set corresponding to each difference type;

and executing a second self-learning operation on the energy scheduling model according to the operation adjustment information corresponding to all the difference types.

In an optional implementation manner, in a first aspect of the present invention, the determining, according to all the operation energy consumption information, whether all the smart home devices meet a preset operation energy consumption condition includes:

according to all the operation energy consumption information, calculating comprehensive energy consumption values corresponding to all the intelligent household devices, and judging whether the comprehensive energy consumption values are larger than or equal to a preset comprehensive energy consumption value threshold;

when the comprehensive energy consumption value is judged to be larger than or equal to the comprehensive energy consumption value threshold, determining that not all the intelligent household devices meet preset operation energy consumption conditions;

When the comprehensive energy consumption value is judged to be smaller than the comprehensive energy consumption value threshold, for each intelligent household device, according to the operation energy consumption information of the intelligent household device, the operation information of the intelligent household device aiming at different energy consumption judging parameters is analyzed; judging whether the intelligent household equipment meets the judging conditions corresponding to all the energy consumption judging parameters or not according to the operation information of each energy consumption judging parameter;

when judging that not all the intelligent household devices meet the evaluation conditions, determining that not all the intelligent household devices meet preset operation energy consumption conditions;

when all the intelligent household devices are judged to meet the evaluation conditions, analyzing the corresponding operation energy consumption trend of all the intelligent household devices according to all the operation energy consumption information, and judging whether the operation energy consumption trend is matched with a preset expected operation energy consumption trend or not;

when the operation energy consumption trend is judged to be matched with the expected operation energy consumption trend, determining that all intelligent household equipment meets preset operation energy consumption conditions;

and when the operation energy consumption trend is not matched with the expected operation energy consumption trend, determining that all the intelligent household devices do not meet the preset operation energy consumption condition.

The second aspect of the invention discloses an energy scheduling device applied to intelligent home, which is characterized in that the device comprises:

the determining module is used for determining the operation energy consumption information of each intelligent home device in the intelligent home scene;

the judging module is used for judging whether all the intelligent household devices meet preset operation energy consumption conditions according to all the operation energy consumption information;

the energy scheduling module is used for inputting all the operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result when the judging module judges that not all the intelligent household devices meet the operation energy consumption conditions;

and the regulation and control module is used for executing regulation and control operation on all the intelligent household devices according to the energy scheduling result.

In a second aspect of the present invention, as an optional implementation manner, the energy scheduling module inputs all the operation energy consumption information into a preset energy scheduling model, and a manner of obtaining an energy scheduling result specifically includes:

In a second aspect of the present invention, as an optional implementation manner, the energy scheduling module performs an energy scheduling operation on all the operation energy consumption information according to the processing operation requirement, the processing effect requirement and the operation configuration information of each smart home device, and a manner of obtaining an energy scheduling result specifically includes:

As an optional implementation manner, in the second aspect of the present invention, the auxiliary home device includes a first auxiliary home device that is currently operating and/or a second auxiliary home device that may be used to replace the first auxiliary home device;

And for each core home device, the energy scheduling module analyzes device alternatives corresponding to all the auxiliary home devices according to the auxiliary energy consumption requirement, operation configuration information and function configuration information corresponding to each auxiliary home device, and the processing effect requirement, where the method specifically includes:

In a second aspect of the present invention, the determining module is further configured to determine, after the energy scheduling module inputs all the operation energy consumption information to a preset energy scheduling model to obtain an energy scheduling result, an expected energy scheduling result corresponding to all the operation energy consumption information;

the judging module is further used for judging whether the expected energy scheduling result is matched with the energy scheduling result or not;

and, the apparatus further comprises:

and the model self-learning module is used for executing self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result when the judging module judges that the expected energy scheduling result is not matched with the energy scheduling result.

In a second aspect of the present invention, the mode for the model self-learning module to perform a self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result specifically includes:

In a second aspect of the present invention, the determining module determines, according to all the operation energy consumption information, whether all the smart home devices meet a preset operation energy consumption condition, by specifically including:

The third aspect of the invention discloses another energy scheduling device applied to intelligent home, which comprises:

a memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program codes stored in the memory to execute the energy scheduling method applied to the intelligent home disclosed in the first aspect of the invention.

The fourth aspect of the present invention discloses a computer storage medium, where computer instructions are stored, and when the computer instructions are called, the computer instructions are used to execute an energy scheduling method applied to smart home disclosed in the first aspect of the present invention.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

in the embodiment of the invention, the operation energy consumption information of each intelligent home device in the intelligent home scene is determined; judging whether all the intelligent household devices meet preset operation energy consumption conditions according to all the operation energy consumption information; when the judgment result is negative, inputting all the operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result; and executing regulation and control operation on all the intelligent household equipment according to the energy scheduling result. Therefore, the intelligent household equipment energy scheduling method and the intelligent household equipment energy scheduling system can determine the energy scheduling result according to the operation energy consumption information, execute the regulation and control operation on the intelligent household equipment according to the energy scheduling result, realize the intelligent household equipment energy scheduling function, and are beneficial to improving the comprehensiveness and rationality of the energy scheduling mode of the intelligent household equipment, further beneficial to improving the regulation and control accuracy and the regulation and control reliability of the intelligent household equipment, further beneficial to improving the energy scheduling accuracy and the reliability of the intelligent household equipment and further beneficial to reducing the energy consumption of the intelligent household equipment.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a schematic view of a scene to which an energy scheduling method applied to an intelligent home is applicable, which is disclosed in an embodiment of the present invention;

fig. 2 is a schematic flow chart of an energy scheduling method applied to smart home according to an embodiment of the present invention;

fig. 3 is a schematic flow chart of another energy scheduling method applied to smart home according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of an energy scheduling device applied to smart home according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of another energy scheduling device applied to smart home according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of another energy scheduling device applied to smart home according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or article.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The invention discloses an energy scheduling method and device applied to intelligent home, which can determine an energy scheduling result according to operation energy consumption information, execute regulation and control operation on intelligent home equipment according to the energy scheduling result, realize an intelligent home equipment energy scheduling function, and are beneficial to improving the comprehensiveness and rationality of an energy scheduling mode of the intelligent home equipment, further beneficial to improving the regulation accuracy and reliability of the intelligent home equipment, and further beneficial to improving the energy scheduling accuracy and reliability of the intelligent home equipment and further beneficial to reducing the energy consumption of the intelligent home equipment. The following will describe in detail.

In order to better understand the energy scheduling method and device for the smart home described in the present invention, first, a scene architecture to which the energy scheduling method for the smart home is applied is described, specifically, the scene architecture may be as shown in fig. 1, and a scene to which the energy scheduling method for the smart home is applied may include an intelligent cloud, a communication module, a sensing module, a switch module, a first smart home and/or a traditional home device end, a second smart home and/or a traditional home device end, and the like, where the intelligent cloud receives operation energy consumption information corresponding to the first smart home and/or the traditional home device end through the communication module, determines an energy scheduling result, and the intelligent cloud performs corresponding operations based on the energy scheduling result and controls the switch module, the second smart home and/or the traditional home device end through the communication module. Illustrating: when the intelligent air conditioner is started, the intelligent humidifier also needs to be started, the intelligent cloud obtains operation energy consumption information of the intelligent air conditioner and the intelligent humidifier (namely, a first intelligent home and/or a traditional household appliance end) through the communication module, and when the total energy consumption value of the intelligent air conditioner and the intelligent humidifier is higher than a preset bearable energy consumption value, the intelligent cloud determines the expected scene condition of the intelligent home scene through the sensing module, the intelligent cloud performs energy scheduling analysis on the operation energy consumption information to obtain an energy scheduling result, the intelligent cloud determines control parameters of the intelligent switch (namely, the switch module) according to the energy scheduling result, the intelligent cloud transmits the control parameters of the intelligent switch to the intelligent switch through the communication module, the intelligent switch reduces operation time based on the control parameters, or the intelligent switch selects another humidifier (namely, a second intelligent home appliance end and/or a traditional household appliance end) with lower energy consumption and similar dehumidification effect to perform humidification operation based on the control parameters, and the intelligent home equipment in the intelligent home scene meets the operation energy consumption condition through intelligent energy scheduling.

It should be noted that, the schematic view of the scenario shown in fig. 1 is only for showing a scenario suitable for an energy scheduling method applied to smart home, and the related smart devices are only schematically shown, and specific structures/sizes/shapes/positions/installation manners, and communication manners between the smart devices may be adaptively adjusted according to actual scenarios, which are not limited by the scenario shown in fig. 1.

Example 1

Referring to fig. 2, fig. 2 is a flow chart of an energy scheduling method applied to smart home according to an embodiment of the present invention. The method described in fig. 2 may be applied to an energy scheduling device of an intelligent home, where the device may include a server, where the server includes a local server or a cloud server, and embodiments of the present invention are not limited. As shown in fig. 2, the energy scheduling method applied to the smart home comprises the following operations:

101. and determining the operation energy consumption information of each intelligent home device in the intelligent home scene.

Optionally, the operation energy consumption information of the smart home device may include, but is not limited to, one or more of an operation energy consumption value, an operation energy consumption change amplitude, an operation energy consumption change frequency, and other operation energy consumption conditions of the smart home device, which is not limited by the embodiment of the present invention.

102. And judging whether all the intelligent household devices meet preset operation energy consumption conditions according to all the operation energy consumption information.

Further optionally, when it is determined that all the smart home devices meet the preset operation energy consumption condition, step 101 is executed again, which is not limited by the embodiment of the present invention.

103. When judging that not all intelligent household devices meet the operation energy consumption conditions, inputting all operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result.

Optionally, the energy scheduling result may include, but is not limited to, one or more of an expected energy consumption value of each smart home device, an expected operation parameter of each smart home device, an expected energy consumption allocation situation corresponding to all smart home devices, a required energy scheduling amplitude of each smart home device, other energy scheduling related information of the smart home device, and the like, which is not limited in the embodiment of the present invention.

104. And executing regulation and control operation on all the intelligent household devices according to the energy scheduling result.

Further optionally, executing the regulation and control operation on all the smart home devices according to the energy scheduling result may include:

determining the expected energy consumption condition of each intelligent household device according to the energy scheduling result and the current energy consumption condition of each intelligent household device, and determining the expected operation parameter of each intelligent household device according to the expected energy consumption condition and the current operation parameter of each intelligent household device;

And for each intelligent household device, controlling the intelligent household device to execute corresponding operation according to the expected operation parameters of the intelligent household device.

determining target intelligent home equipment to be regulated and controlled and demand regulation information of each target intelligent home equipment from all intelligent home equipment according to an energy scheduling result;

determining an intelligent switch associated with each target intelligent home device according to the demand regulation information of each target intelligent home device and each target intelligent home device, and generating control parameters of the intelligent switch according to the demand regulation information of each target intelligent home device;

the control parameters of the intelligent switch comprise switch control parameters of the target intelligent household equipment and/or operation control parameters of the target intelligent household equipment.

Optionally, the performing a regulation operation on the smart home device may include, but is not limited to, one or more of performing a regulation operation on an energy consumption related parameter of the smart home device, performing a regulation operation on an operation parameter of the smart home device, performing a regulation operation on a control parameter of the smart home device, performing another regulation operation on the smart home device that can enable the smart home device to meet an operation energy consumption condition, and the like.

Therefore, the energy scheduling method applied to the intelligent home described by the embodiment of the invention can determine the energy scheduling result according to the operation energy consumption information, and execute the regulation and control operation on the intelligent home equipment according to the energy scheduling result, thereby realizing the energy scheduling function of the intelligent home equipment, being beneficial to improving the comprehensiveness and rationality of the energy scheduling mode of the intelligent home equipment, further being beneficial to improving the regulation and control accuracy and reliability of the intelligent home equipment, further being beneficial to improving the energy scheduling accuracy and reliability of the intelligent home equipment and further being beneficial to reducing the energy consumption of the intelligent home equipment.

In an optional embodiment, the inputting all the operation energy consumption information into the preset energy scheduling model to obtain the energy scheduling result may include:

according to the current control parameters of all intelligent home equipment, analyzing the intelligent home scene based on the processing operation requirement and the processing effect requirement corresponding to the intelligent home equipment;

Optionally, the operation configuration information of the smart home device may be understood as data conditions related to device configuration parameters corresponding to different operation effects and different operation energy consumption conditions of the smart home device, and the embodiment of the present invention is not limited.

Optionally, the operation energy consumption information, the operation configuration information and the current control parameters of the smart home device are illustrated by: when the intelligent household equipment is an intelligent air conditioner, the running energy consumption information of the intelligent air conditioner is 0.893 degree of power consumption per hour, the running configuration information of the intelligent air conditioner indicates that the corresponding prescribed energy consumption is 0.893 degree of power consumption per hour when the intelligent air conditioner is in a dehumidification mode, the current control parameters of the intelligent air conditioner are used for indicating that the intelligent air conditioner is in the dehumidification mode, other conditions are available in the same way, and no further description is given here by way of example.

Optionally, the processing operation requirement of the smart home scenario may include, but is not limited to, one or more of an operation behavior of the processing operation, an operation behavior of the processing operation that must be avoided, an operator related requirement of the processing operation, an execution subject requirement of the processing operation, a processing object requirement of the processing operation, an operation smart home device energy consumption requirement of the processing operation, other requirements related to the processing operation, and the like.

Optionally, the processing effect requirement of the smart home scene may include, but is not limited to, one or more of an effect required by the smart home device for a scene area corresponding to the smart home scene, an effect required by a scene environment corresponding to the smart home scene, a somatosensory effect required by a related person corresponding to the smart home scene, an effect required by other devices corresponding to the smart home scene, an effect required by other processing objects related to the smart home scene, and the like.

Therefore, according to the optional embodiment, the energy scheduling result of the intelligent household equipment can be determined according to the determined processing operation requirement, the determined processing effect requirement and the determined operation configuration information of each intelligent household equipment, so that the comprehensiveness and rationality of the determining mode of the energy scheduling result can be improved, the diversity and pertinence of the determining parameters of the energy scheduling result can be improved, and the accuracy and reliability of the determined energy scheduling result can be improved.

In another optional embodiment, performing the energy scheduling operation on all the operation energy consumption information according to the processing operation requirement, the processing effect requirement and the operation configuration information of each smart home device to obtain an energy scheduling result may include:

Screening at least one core home device from all intelligent home devices according to the processing operation requirement and the processing effect requirement;

for each core home equipment, screening at least one auxiliary home equipment matched with the core home equipment from all intelligent home equipment according to the processing operation requirement, the processing effect requirement and the function configuration information of each intelligent home equipment;

determining auxiliary energy consumption requirements corresponding to all auxiliary household equipment according to the operation energy consumption information of the core household equipment, and analyzing the substitution feasibility corresponding to all the auxiliary household equipment according to the auxiliary energy consumption requirements, the operation configuration information, the function configuration information and the processing effect requirements corresponding to each auxiliary household equipment;

when the replacement feasibility is larger than or equal to a preset replacement feasibility threshold value, analyzing equipment replacement schemes corresponding to all auxiliary household equipment according to the auxiliary energy consumption requirement, the operation configuration information, the function configuration information and the processing effect requirement corresponding to each auxiliary household equipment;

according to the equipment alternative scheme and the operation configuration information of all the intelligent household equipment, the consumable energy information of each intelligent household equipment is determined, and according to the consumable energy information of each intelligent household equipment, an energy scheduling result is determined.

Optionally, the core home device and the auxiliary home device may be understood that the home device used for coping with the main scene requirement in the smart home scene is a core home device, and the home device used for providing the auxiliary functional effect is an auxiliary home device; further, by way of example: when the main scene requirement of the intelligent home scene is to reduce the ambient temperature, the core home equipment can be an intelligent air conditioner, the auxiliary home equipment can be a humidifier, and other conditions are similarly available, and the details are not repeated here.

Optionally, the device replacement scheme corresponding to all auxiliary home devices may be used to determine one or more of home devices to be replaced in all auxiliary home devices, new control parameters for replacing home devices, device replacement execution time, device replacement execution mode, required duration of device replacement, front and rear energy consumption information of device replacement, device replacement execution requirement, device replacement related personnel information, other information related to device replacement operation, and the like, which is not limited in the embodiment of the present invention.

Optionally, determining the auxiliary energy consumption requirements corresponding to all the auxiliary home devices according to the operation energy consumption information of the core home devices can be understood as: on the basis of the operation energy consumption which must be generated by the core home equipment, the maximum operation energy consumption which can be generated by all the auxiliary home equipment is determined, so that the total operation energy consumption which corresponds to the core home equipment and the auxiliary home equipment meets the energy consumption condition, and the core home equipment and the auxiliary home equipment can meet the scene requirement of the intelligent home scene on the basis of meeting the energy consumption condition.

Optionally, the alternative feasibility corresponding to all the auxiliary home devices can be understood as: on the basis of meeting the energy consumption condition of the intelligent household equipment and meeting the scene requirement of the intelligent household scene, the feasibility of carrying out the substitution operation on the auxiliary household equipment is not limited.

Optionally, the foregoing consumable energy information of each smart home device may include, but is not limited to, one or more of maximum energy consumption requirement information (i.e. maximum energy consumption) of each smart home device, a requirement energy consumption range, basic energy consumption requirement information (i.e. energy consumption required for achieving a basic operation effect), specific requirement energy consumption data, and the embodiment of the present invention is not limited.

Therefore, the intelligent household equipment can be divided into the core household equipment and the auxiliary household equipment by the optional embodiment, more specific energy scheduling result determining operation is executed based on the core household equipment and the auxiliary household equipment, the rationality, the comprehensiveness and the feasibility of an energy scheduling result determining mode are improved, the accuracy and the reliability of the determined energy scheduling result are improved, and the influence of energy scheduling on the operation effect of the household equipment is reduced on the basis of energy scheduling.

In yet another alternative embodiment, the auxiliary home devices include a first auxiliary home device that is currently operating and/or a second auxiliary home device that is available to replace the first auxiliary home device;

further optionally, for each core home device, analyzing device alternatives corresponding to all auxiliary home devices according to the auxiliary energy consumption requirement, the operation configuration information and the function configuration information corresponding to each auxiliary home device, and the processing effect requirement may include:

when the first auxiliary household equipment meets the energy consumption and processing effect conditions, determining first operation regulation information of the first auxiliary household equipment according to the auxiliary energy consumption requirements, the achievable effect conditions and the processing effect requirements so as to determine equipment substitution schemes corresponding to all the auxiliary household equipment;

when the first auxiliary household equipment is judged to not meet the energy consumption and processing effect conditions, at least one target second auxiliary household equipment is screened out from all the second auxiliary household equipment according to the auxiliary energy consumption requirements and the operation configuration information corresponding to each second auxiliary household equipment;

Determining second operation regulation information of the target second auxiliary home equipment according to the auxiliary energy consumption requirement, the operation configuration information corresponding to each second auxiliary home equipment, the function configuration information and the processing effect requirement so as to determine equipment alternatives corresponding to all the auxiliary home equipment;

Optionally, the achievable effect status of the first auxiliary home device is illustrated by: the embodiment of the invention is not limited by the functional effect which can be realized by the first auxiliary home equipment by combining the configuration energy consumption condition corresponding to different operation parameters and control parameters of the first auxiliary home equipment on the basis of the maximum bearable energy consumption corresponding to the auxiliary energy consumption requirement.

Optionally, the above determining whether the first auxiliary home device meets the preset energy consumption and treatment effect conditions according to the treatment effect requirement and the achievable effect condition may be understood as: whether the effect condition of the first auxiliary home equipment, which can be achieved on the basis of meeting the auxiliary energy consumption requirement, meets the processing effect requirement or not is not limited by the embodiment of the invention; further alternatively, the energy consumption and treatment effect conditions and equipment alternatives described above are exemplified: when the energy consumption and treatment effect conditions are met, the operation parameters of the first auxiliary household equipment are directly regulated, and when the energy consumption and treatment effect conditions are not met, new auxiliary household equipment (namely target second auxiliary household equipment) is determined and the operation parameters of the second auxiliary household equipment are regulated; further, for example, when the intelligent air conditioner (i.e., the core home equipment) is turned on, the humidifier (i.e., the first auxiliary home equipment) is also turned on, and whether the first auxiliary home equipment can meet the energy consumption and treatment effect conditions after the operation duration, the operation mode, the humidification strength and the like of the humidifier in current use are adjusted is analyzed, if not, the humidifier in current use is replaced by another humidifying equipment (i.e., the target second auxiliary home equipment) with lower energy consumption and similar effect, and the embodiment of the invention is not limited.

Therefore, the optional embodiment can be respectively matched with corresponding equipment alternative determining modes according to the condition that the first auxiliary household equipment meets the energy consumption and processing effect conditions and the condition that the first auxiliary household equipment does not meet the energy consumption and processing effect conditions, thereby being beneficial to improving the comprehensiveness and feasibility of the equipment alternative determining modes, improving the diversity, flexibility, selectivity and pertinence of the equipment alternative determining modes, and further being beneficial to improving the accuracy and reliability of the determined equipment alternative.

In still another optional embodiment, the determining, according to the all operation energy consumption information, whether all the smart home devices meet the preset operation energy consumption condition may include:

when the comprehensive energy consumption value is judged to be greater than or equal to the comprehensive energy consumption value threshold, determining that not all intelligent household equipment meets the preset operation energy consumption condition;

When judging that not all the intelligent household devices meet the judging conditions, determining that not all the intelligent household devices meet the preset operation energy consumption conditions;

when all the intelligent household devices are judged to meet the judging conditions, analyzing the corresponding operation energy consumption trend of all the intelligent household devices according to all the operation energy consumption information, and judging whether the operation energy consumption trend is matched with a preset expected operation energy consumption trend or not;

when the operation energy consumption trend is judged to be matched with the expected operation energy consumption trend, determining that all intelligent household equipment meets the preset operation energy consumption condition;

and when the operation energy consumption trend is not matched with the expected operation energy consumption trend, determining that all intelligent household equipment does not meet the preset operation energy consumption condition.

Optionally, the above energy consumption evaluation parameters may include, but are not limited to, one or more of a super-energy consumption long parameter, a super-energy consumption frequency parameter, a super-energy consumption amplitude parameter, a super-energy consumption specific value parameter, a super-energy consumption frequency parameter, a super-energy consumption acceptable degree parameter (for example, the energy consumption may be small, the energy consumption may not be super-energy consumption at all), etc. of the smart home device, and the embodiment of the present invention is not limited.

Optionally, the operation energy consumption trend may include, but is not limited to, one or more of a change trend of an operation energy consumption specific value of the smart home device, a change trend of a difference value before and after operation energy consumption of the smart home device, a change trend of an operation energy consumption change frequency of the smart home device, a change trend of an operation energy consumption change interval duration of the smart home device, a change trend of other parameters related to operation energy consumption change, and the like.

Therefore, the optional embodiment can determine that the operation energy consumption condition meets the condition according to the comprehensive energy consumption value, the judgment condition and the operation energy consumption trend, is favorable for improving the comprehensiveness and rationality of the operation energy consumption condition meeting the condition determining mode, and further is favorable for improving the layer-by-layer progressive property of the operation energy consumption condition meeting the condition determining mode and improving the diversity and flexibility of the determined parameters of the operation energy consumption condition meeting the condition, so that the accuracy and reliability of the determined operation energy consumption condition meeting the condition are favorable.

Example two

Referring to fig. 3, fig. 3 is a flow chart of another energy scheduling method applied to smart home according to an embodiment of the present invention. The method described in fig. 3 may be applied to an energy scheduling device of an intelligent home, where the device may include a server, where the server includes a local server or a cloud server, and embodiments of the present invention are not limited. As shown in fig. 3, the energy scheduling method applied to the smart home comprises the following operations:

201. And determining the operation energy consumption information of each intelligent home device in the intelligent home scene.

202. And judging whether all the intelligent household devices meet preset operation energy consumption conditions according to all the operation energy consumption information.

203. When judging that not all intelligent household devices meet the operation energy consumption conditions, inputting all operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result.

204. And executing regulation and control operation on all the intelligent household devices according to the energy scheduling result.

205. And determining an expected energy scheduling result corresponding to all the operation energy consumption information.

206. And judging whether the expected energy scheduling result is matched with the energy scheduling result.

Further optionally, when it is determined that the expected energy scheduling result matches the energy scheduling result, step 201 is executed again, which is not limited in the embodiment of the present invention.

207. And when the expected energy scheduling result is not matched with the energy scheduling result, executing self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result.

Alternatively, the self-learning scheme of the energy scheduling model corresponding to the above steps 205-207 may be between the step 203 and the step 204, or may be after the step 204, which is not limited in the embodiment of the present invention.

In the embodiment of the present invention, for other descriptions of step 201 to step 204, please refer to other detailed descriptions of step 101 to step 104 in the first embodiment, and the description of the embodiment of the present invention is omitted.

Therefore, the embodiment of the invention can determine the energy scheduling result according to the operation energy consumption information, execute the regulation and control operation on the intelligent household equipment according to the energy scheduling result, realize the energy scheduling function of the intelligent household equipment, and be beneficial to improving the comprehensiveness and rationality of the energy scheduling mode of the intelligent household equipment, further be beneficial to improving the regulation and control accuracy and reliability of the intelligent household equipment, thereby being beneficial to improving the energy scheduling accuracy and reliability of the intelligent household equipment and further be beneficial to reducing the energy consumption of the intelligent household equipment; and the self-learning mode of the energy scheduling model can be provided, when the expected energy scheduling result is not matched with the energy scheduling result, the self-learning operation of the energy scheduling model is carried out, the comprehensiveness and the integrity of the energy scheduling mode applied to the intelligent home are improved, the self-learning timeliness and the self-learning reliability of the energy scheduling model are improved, the running reliability and the running accuracy of the energy scheduling model are improved, and the accuracy and the reliability of the energy scheduling result output by the energy scheduling model are improved.

In an optional embodiment, the performing a self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result may include:

Optionally, the performing the first self-learning operation on the energy scheduling model may be understood as performing shallow adjustment on the energy scheduling model directly according to the scheduling difference information, so that when the same operation energy consumption information is input again to perform energy scheduling and/or perform energy scheduling for the current smart home scene again, the energy scheduling result output by the energy scheduling model is matched with the expected energy scheduling result, and the self-learning effect brought by the first self-learning operation is one-sided and more specific.

Optionally, the performing the second self-learning operation on the energy scheduling model may be understood as performing deep adjustment on the energy scheduling model according to scheduling difference information, historical training adjustment data, a set of reasons for occurrence of differences corresponding to each difference type, and the like, so that the energy scheduling model improves energy scheduling accuracy from the overall energy scheduling level, and self-learning effects brought by the second self-learning operation are comprehensive and more superior, which is not limited by embodiments of the present invention.

Optionally, the difference types may include, but are not limited to, one or more of a scheduling object difference type, an energy consumption value scheduling difference type, an energy consumption variation degree scheduling difference type, a scheduling frequency difference type, a scheduling time difference type, a device operation mode scheduling difference type, a device operation parameter scheduling difference type, a device operation grade scheduling difference type, and the like, which are not limited in the embodiment of the present invention.

Optionally, the operation adjustment information of the energy scheduling analysis for each difference type can be understood as: for each difference type, the energy scheduling analysis operation of the energy scheduling model is adjusted, so that the scheduling result outputted by the energy scheduling model does not have the scheduling result difference condition corresponding to the difference type.

Therefore, the optional embodiment can execute the first self-learning operation and the second self-learning operation on the energy scheduling model to realize self-learning of the energy scheduling model, which is beneficial to improving the comprehensiveness and rationality of the self-learning mode of the energy scheduling model, and further beneficial to improving the self-learning rationality and self-learning accuracy of the energy scheduling model, thereby being beneficial to improving the energy scheduling accuracy and the energy scheduling reliability of the energy scheduling model.

Example III

Referring to fig. 4, fig. 4 is a schematic structural diagram of an energy scheduling device for smart home according to an embodiment of the present invention. The apparatus described in fig. 4 may include a server, where the server includes a local server or a cloud server, and embodiments of the present invention are not limited. As shown in fig. 4, the energy scheduling device applied to the smart home may include:

the determining module 301 is configured to determine operation energy consumption information of each smart home device in the smart home scene.

The judging module 302 is configured to judge whether all the smart home devices meet the preset operation energy consumption conditions according to all the operation energy consumption information.

The energy scheduling module 303 is configured to input all operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result when the judging module 302 judges that not all intelligent home devices meet the operation energy consumption condition.

And the regulation and control module 304 is configured to execute regulation and control operations on all intelligent home devices according to the energy scheduling result.

It can be seen that implementing the energy scheduling device for smart home described in fig. 4 can determine an energy scheduling result according to the operation energy consumption information, and execute a regulation and control operation on the smart home device according to the energy scheduling result, so as to implement an energy scheduling function of the smart home device, thereby being beneficial to improving the comprehensiveness and rationality of an energy scheduling mode of the smart home device, further being beneficial to improving the regulation and control accuracy and reliability of the smart home device, and further being beneficial to improving the energy scheduling accuracy and reliability of the smart home device, and further being beneficial to reducing the energy consumption of the smart home device.

In an alternative embodiment, the energy scheduling module 303 inputs all the operation energy consumption information into a preset energy scheduling model, and the manner of obtaining the energy scheduling result specifically includes:

Therefore, the device described in fig. 5 can determine the energy scheduling result of the intelligent home equipment according to the determined processing operation requirement, the determined processing effect requirement and the determined operation configuration information of each intelligent home equipment, which is beneficial to improving the comprehensiveness and rationality of the determination mode of the energy scheduling result, improving the diversity and pertinence of the determination parameters of the energy scheduling result, and further improving the accuracy and reliability of the determined energy scheduling result.

In another alternative embodiment, the energy scheduling module 303 performs an energy scheduling operation on all the operation energy consumption information according to the processing operation requirement, the processing effect requirement and the operation configuration information of each smart home device, and a manner of obtaining an energy scheduling result specifically includes:

It can be seen that the device described in fig. 5 can also divide the smart home device into a core home device and an auxiliary home device, and execute a more specific energy scheduling result determining operation based on the core home device and the auxiliary home device, which is beneficial to improving the rationality, comprehensiveness and feasibility of the energy scheduling result determining mode, further is beneficial to improving the accuracy and reliability of the determined energy scheduling result, and is also beneficial to reducing the influence of energy scheduling on the operation effect of the home device on the basis of realizing energy scheduling.

further optionally, for each core home device, the energy scheduling module 303 specifically includes, according to the auxiliary energy consumption requirement, the operation configuration information and the function configuration information corresponding to each auxiliary home device, and the processing effect requirement, a manner of analyzing the device alternatives corresponding to all the auxiliary home devices:

It can be seen that the apparatus described in fig. 5 can also be matched with corresponding equipment alternative determining modes according to the situation that the first auxiliary home equipment meets the energy consumption and processing effect conditions and the first auxiliary home equipment does not meet the energy consumption and processing effect conditions, which is beneficial to improving the comprehensiveness and feasibility of the equipment alternative determining modes, and is also beneficial to improving the diversity, flexibility, selectivity and pertinence of the equipment alternative determining modes, thereby being beneficial to improving the accuracy and reliability of the determined equipment alternative.

In yet another alternative embodiment, the determining module 301 is further configured to determine an expected energy scheduling result corresponding to all the operation energy consumption information after the energy scheduling module 303 inputs all the operation energy consumption information to a preset energy scheduling model to obtain the energy scheduling result.

The judging module 302 is further configured to judge whether the expected energy scheduling result matches the energy scheduling result.

And, as shown in fig. 5, the apparatus may further include:

the model self-learning module 305 is configured to perform a self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result when the judging module 302 judges that the expected energy scheduling result does not match the energy scheduling result.

Therefore, the device described in fig. 5 can also provide a self-learning mode of the energy scheduling model, and when the expected energy scheduling result is not matched with the energy scheduling result, the self-learning operation of the energy scheduling model is performed, so that the comprehensiveness and the integrity of the energy scheduling mode applied to the intelligent home are improved, the self-learning timeliness and the self-learning reliability of the energy scheduling model are improved, the running reliability and the running accuracy of the energy scheduling model are improved, and the accuracy and the reliability of the energy scheduling result output by the energy scheduling model are improved.

In yet another alternative embodiment, the model self-learning module 305 performs the self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result, which specifically includes:

It can be seen that the device described in fig. 5 can also perform the first self-learning operation and the second self-learning operation on the energy scheduling model to realize self-learning of the energy scheduling model, which is beneficial to improving the comprehensiveness and rationality of the self-learning mode of the energy scheduling model, and further beneficial to improving the self-learning rationality and self-learning accuracy of the energy scheduling model, thereby being beneficial to improving the energy scheduling accuracy and the energy scheduling reliability of the energy scheduling model.

In yet another alternative embodiment, the determining module 302 determines, according to all the operation energy consumption information, whether all the smart home devices meet the preset operation energy consumption condition specifically includes:

It can be seen that the device described in fig. 5 can also determine that the operation energy consumption condition meets the situation according to the comprehensive energy consumption value, the evaluation condition and the operation energy consumption trend, which is favorable for improving the comprehensiveness and rationality of the operation energy consumption condition meeting the situation determining mode, further favorable for improving the layer-by-layer progressive property of the operation energy consumption condition meeting the situation determining mode and improving the diversity and flexibility of the determined parameters of the operation energy consumption condition meeting the situation, thereby being favorable for improving the accuracy and reliability of the determined operation energy consumption condition meeting the situation.

Example IV

Referring to fig. 6, fig. 6 is a schematic structural diagram of another energy scheduling device for smart home according to an embodiment of the present invention. The apparatus described in fig. 6 may include a server, where the server includes a local server or a cloud server, and embodiments of the present invention are not limited. As shown in fig. 6, the apparatus may include:

A memory 401 storing executable program codes;

a processor 402 coupled with the memory 401;

further, an input interface 403 and an output interface 404 coupled to the processor 402 may be included;

the processor 402 invokes executable program codes stored in the memory 401, for executing the steps in the energy scheduling method applied to smart home described in the first or second embodiment.

Example five

The embodiment of the invention discloses a computer storage medium which stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps in the energy scheduling method applied to intelligent home described in the first embodiment or the second embodiment.

Example six

An embodiment of the present invention discloses a computer program product, where the computer program product includes a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the energy scheduling method applied to smart home described in the first embodiment or the second embodiment.

The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.

Finally, it should be noted that: the embodiment of the invention discloses an energy scheduling method and device applied to intelligent home, which are disclosed by the embodiment of the invention only for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims

1. An energy scheduling method applied to intelligent home, which is characterized by comprising the following steps:

2. The energy scheduling method applied to the smart home according to claim 1, wherein the step of inputting all the operation energy consumption information into a preset energy scheduling model to obtain an energy scheduling result includes:

3. The energy scheduling method for smart home according to claim 2, wherein the performing energy scheduling operation on all the operation energy consumption information according to the processing operation requirement, the processing effect requirement and the operation configuration information of each smart home device to obtain an energy scheduling result includes:

4. The energy scheduling method applied to smart home according to claim 3, wherein the auxiliary home devices include a first auxiliary home device currently operating and/or a second auxiliary home device available to replace the first auxiliary home device;

5. The energy scheduling method applied to smart home according to any one of claims 1 to 4, wherein after the inputting all the operation energy consumption information into a preset energy scheduling model, the method further comprises:

6. The energy scheduling method applied to smart home according to claim 5, wherein the performing a self-learning operation on the energy scheduling model according to the expected energy scheduling result and the energy scheduling result includes:

7. The energy scheduling method for smart home according to any one of claims 1 to 4, wherein the determining, according to all the operation energy consumption information, whether all the smart home devices meet a preset operation energy consumption condition includes:

8. An energy scheduling device for smart home, the device comprising:

9. An energy scheduling device for smart home, the device comprising:

a memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program code stored in the memory to perform the energy scheduling method of any one of claims 1-7 for use in smart home.

10. A computer storage medium storing computer instructions which, when invoked, are adapted to perform the energy scheduling method of any one of claims 1-7 for use in smart homes.