CN114738827A - Household electric heating intelligent group control method and system based on user habits - Google Patents
Household electric heating intelligent group control method and system based on user habits Download PDFInfo
- Publication number
- CN114738827A CN114738827A CN202210382396.5A CN202210382396A CN114738827A CN 114738827 A CN114738827 A CN 114738827A CN 202210382396 A CN202210382396 A CN 202210382396A CN 114738827 A CN114738827 A CN 114738827A
- Authority
- CN
- China
- Prior art keywords
- user
- electric
- instantaneous
- power
- different rooms
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000005485 electric heating Methods 0.000 title claims abstract description 64
- 238000000034 method Methods 0.000 title claims abstract description 51
- 238000010438 heat treatment Methods 0.000 claims description 29
- 238000004364 calculation method Methods 0.000 claims description 28
- 238000004590 computer program Methods 0.000 claims description 14
- 238000003860 storage Methods 0.000 claims description 11
- 238000004422 calculation algorithm Methods 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 6
- 230000005540 biological transmission Effects 0.000 claims description 5
- 238000013528 artificial neural network Methods 0.000 claims description 4
- 238000005065 mining Methods 0.000 claims description 4
- 230000006399 behavior Effects 0.000 claims description 3
- 238000013500 data storage Methods 0.000 claims description 3
- 230000009467 reduction Effects 0.000 abstract description 4
- 229910052799 carbon Inorganic materials 0.000 abstract description 3
- 238000004134 energy conservation Methods 0.000 abstract description 3
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 12
- 230000006870 function Effects 0.000 description 5
- 238000011217 control strategy Methods 0.000 description 3
- 230000001276 controlling effect Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007774 longterm Effects 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1096—Arrangement or mounting of control or safety devices for electric heating systems
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D2200/00—Heat sources or energy sources
- F24D2200/08—Electric heater
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D2220/00—Components of central heating installations excluding heat sources
- F24D2220/04—Sensors
- F24D2220/042—Temperature sensors
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Thermal Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Central Heating Systems (AREA)
Abstract
The invention provides a household electric heating intelligent group control method and system based on user habits. The scheme comprises the steps of collecting indoor temperature expected values of different rooms of a user, identifying the use habits of the user, intelligently pushing a set mode, and identifying the indoor temperature requirement at the next moment; collecting the instantaneous total electric power of a user and the instantaneous electric power of an electric heater group, identifying the instantaneous electric power of other electric equipment, comparing the instantaneous electric power with a preset total power limit value, and identifying the available instantaneous power at the next moment; the method comprises the steps of collecting actual indoor temperatures of different rooms of a user at the current moment, predicting electric heating requirements of different rooms at the next moment according to indoor temperature requirements of different rooms at the next moment, combining available instantaneous power of an electric heater group, and intelligently adjusting electric heaters of all rooms. According to the scheme, the intelligent group control of the electric heater is carried out by acquiring the different room temperatures and the instantaneous available electric power of the user and comparing the obtained electric power with the expected temperature value, and the energy conservation, the cost reduction and the carbon reduction are realized on the premise of ensuring that the user demand and the power do not exceed the limit.
Description
Technical Field
The invention relates to the technical field of heating, in particular to a household electric heating intelligent group control method and system based on user habits.
Background
The electric heating is a high-quality comfortable environment-friendly heating mode for converting clean electric energy into heat energy, and long-term practical application proves that the electric heating has incomparable advantages of other heating modes and is accepted and accepted by more and more users. The household electric heating system mainly utilizes the mode of directly converting electric energy into household heat energy to heat indoors.
The main principle of the existing household electric heating system is that the electric heating equipment is regulated and controlled to heat by means of preset temperature of a user, and in addition, partial peak clipping and valley filling strategies are considered in part of schemes, and electric heating is carried out through balancing supply and demand of electric energy. However, the existing technology cannot identify the habit of the user to carry out intelligent pushing in a control mode, and meanwhile, the intelligent pushing cannot carry out unlimited control according to the electric power requirements of different rooms of the user, so that better use experience of the user and no limit value of the power of electric equipment cannot be guaranteed.
Disclosure of Invention
In view of the above problems, the invention provides a user habit-based household electric heating intelligent group control method and system, which can be used for formulating an indoor electric heater group control strategy by acquiring heating habits of different rooms of a user, and realizing energy conservation, cost reduction, green and low carbon in the heating process on the premise of ensuring that the user requirement and the instantaneous total power are not over-limit.
According to the first aspect of the embodiment of the invention, the intelligent group control method for household electric heating based on the user habits is provided.
In one or more embodiments, preferably, the user heating intelligent group control method based on user habits includes:
collecting indoor temperature expected values of different rooms of a user, identifying the use habits of the user, intelligently pushing a set mode, and identifying indoor temperature requirements of the different rooms at the next moment;
collecting the instantaneous total electric power of a user and the instantaneous electric power of an electric heater group, identifying the instantaneous electric power of other electric equipment except the electric heater group by the user, comparing the instantaneous electric power with a preset user total electric power limit value, and identifying the available instantaneous power of the electric heater group at the next moment;
the actual indoor temperature of different rooms of the user at the current moment is collected, the electric heating requirements of different rooms at the next moment are predicted according to the indoor temperature requirements of different rooms at the next moment, the available instantaneous power of the electric heater group is combined, the electric heaters in each room are started, stopped and intelligently judged, and a control instruction is sent to the electric heaters.
In one or more embodiments, preferably, the collecting the expected indoor temperature values of different rooms of the user, identifying the use habits of the user, intelligently pushing a setting mode, and identifying the indoor temperature requirements of the different rooms at the next time includes:
collecting the indoor temperature expected values of different rooms of a user, and storing the indoor temperature expected values as expected temperature data;
carrying out online processing on the expected temperature data, establishing a corresponding relation table between different time periods of different rooms of a user and the expected temperature data, identifying the use habits of the user, and storing the use habits as first data;
pushing a setting mode according with the use habit of the user according to the room and the time period of the setting state to be adjusted by the user, identifying the expected temperature data of different rooms in different time periods at the next moment selected by the user, and storing the expected temperature data as second data;
extracting the temperature, the time and the room number corresponding to each second data, and calculating expected temperature habits of each first data at different times and different room numbers by using a first calculation formula;
predicting user behavior according to the historical expected temperature habits through polynomial fitting or through the combination of an LSTM neural network cooperation algorithm and a rule mining algorithm to generate the expected temperature habits in a future period of time, and pushing the expected temperature habits to different rooms of the user at the next moment; automatically identifying the final set expected temperature of different rooms of a user at the next moment, and generating the indoor temperature requirements of the different rooms at the next moment;
the first calculation formula is:
where t "(i, τ) is the expected temperature habit of the user i room at time τ, τ is the time value, t ' (i, τ -1) is the set expected temperature of the i room at time τ -1, t ' (i, τ -2) is the set expected temperature of the i room at time τ -2, and t ' (i, τ -n) is the set expected temperature of the i room at time τ -n.
In one or more embodiments, preferably, the collecting the user's instantaneous total electric power and the electric heater group's instantaneous electric power, identifying the user's other electric consumers instantaneous electric power, comparing with the preset user's total electric power limit, and identifying the available instantaneous power of the electric heater group at the next moment, specifically includes:
acquiring instantaneous electric power of a user through an intelligent electric meter;
acquiring the preset user total electric power limit value, and comparing the relation between the user instantaneous electric power and the preset user total electric power limit value;
if the instantaneous electric power of the user is larger, sending a power-limiting operation command, and setting the set power of the electric heater group to be 0 at the next moment;
if the preset user total electric power limit value is larger or equal to the preset user total electric power limit value, sending an available instantaneous power calculation command;
and after receiving an available instantaneous power calculation command, taking the difference value of the user instantaneous electric power and the instantaneous electric power of the electric heater group as the instantaneous electric power of other electric devices of the user, and taking the difference value of the preset user total electric power limit value and the instantaneous electric power of other electric devices of the user as the available instantaneous power of the electric heater group.
In one or more embodiments, preferably, the acquiring actual indoor temperatures of different rooms of the user at the current time, and predicting the different room electric heating demands at the next time according to the indoor temperature demands at the next time of the different rooms specifically includes:
acquiring actual indoor temperatures of different rooms of a user at the current moment through a sensor;
acquiring the final set expected temperature of different rooms of a user at the next moment, and comparing the magnitude relation between the actual indoor temperature of the different rooms and the final set expected temperature at the next moment;
if the actual indoor temperature of the room is higher, sending a power-limiting operation command, and setting the power of the electric heater to be 0 at the next moment;
if the final set expected temperature at the next moment is larger or equal to the final set expected temperature at the next moment, calculating the electric power demands of different rooms by using a second calculation formula as the electric heating demands of the different rooms at the next moment;
the second calculation formula is:
N′(i,τ+1)=A*(t′(i,τ+1)-t(i,τ))
where N '(i, τ +1) is the power demand of i room τ +1, a is the power coefficient corresponding to the desired temperature difference per unit of room, t' (i, τ +1) is the set desired temperature of i room at τ +1, and t (i, τ) is the actual indoor temperature of i room at τ.
In one or more embodiments, preferably, the available instantaneous power of the electric heater group is combined, the on-off and adjustment of the electric heaters in each room are intelligently determined, and a control instruction is sent to the electric heater, which specifically includes:
identifying available instantaneous power of the electric heater group, and calculating the set power of the electric heaters in each room by using a third calculation formula according to the electric heating requirements of different rooms at the next moment;
performing power control on all the electric heaters according to the set power of the electric heaters in each room;
the third calculation formula is:
wherein, N (i, τ +1) is the electric power set value at the moment of i room τ +1, m is the number of rooms, and N (τ +1) is the available instantaneous power of the electric heater group at the moment of τ + 1.
In one or more embodiments, it is preferable to further include: and transmitting the set power of the user electric heater through a ZigBee, Wifi or ZigBee plus Wifi wireless network.
In one or more embodiments, preferably, the method further includes classifying and saving the expected indoor temperature values of the different rooms of the user, specifically including:
acquiring the indoor temperature expected values of all the rooms;
extracting source positions of all the indoor temperature expected values;
adding room number data to the indoor temperature expected value according to the source position to generate first intermediate position data;
adding an electric heater number to the first intermediate position data according to the source position to generate second intermediate data;
and reading the expected indoor temperature at the next moment, and storing the expected indoor temperature at the next moment and the second intermediate data together as real-time storage data in a memory.
According to the second aspect of the embodiment of the invention, the household electric heating intelligent group control system based on the user habits is provided.
In one or more embodiments, preferably, the household heating intelligent group control system based on user habits comprises:
the demand analysis module is used for acquiring indoor temperature expected values of different rooms of a user, identifying the use habits of the user, intelligently pushing a set mode and identifying indoor temperature demands of different rooms at the next moment;
the state analysis module is used for acquiring the instantaneous total electric power of the user and the instantaneous electric power of the electric heater group, identifying the instantaneous electric power of other electric equipment of the user, comparing the instantaneous electric power with a preset user total electric power limit value, and identifying the available instantaneous power of the electric heater group;
the intelligent control module is used for acquiring the actual indoor temperatures of different rooms of a user at the current moment, predicting the electric heating requirements of different rooms at the next moment according to the indoor temperature requirements of different rooms at the next moment, intelligently judging the start and stop and adjustment of each room electric heater by combining the available instantaneous power of the electric heater group, and sending a control instruction to the electric heaters;
the wireless transmission module is used for transmitting the instantaneous electric power of the user through a ZigBee, Wifi or ZigBee plus Wifi wireless network;
and the data storage module is used for classifying and storing the indoor temperature expected values of different rooms of the user.
According to a third aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method according to any one of the first aspect of embodiments of the present invention.
According to a fourth aspect of embodiments of the present invention, there is provided an electronic device, including a memory and a processor, the memory being configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of the first aspect of embodiments of the present invention.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
1) in the embodiment of the invention, the user habit is intelligently identified, the power consumption of the user is monitored in real time, the automatic optimization control of the electric heater group is realized, the overload of a power grid caused by the overlarge instantaneous power of the user electric heater is prevented on the premise of meeting the comfort level of the user, and the heating power consumption and the cost of the user are saved;
2) according to the embodiment of the invention, the heating habits of different rooms of the user are obtained, and the setting mode is intelligently pushed, so that the electric heating control of the user is more intelligent and convenient.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
Fig. 1 is a flowchart of a household heating intelligent group control method based on user habits according to an embodiment of the present invention.
Fig. 2 is a flowchart of collecting expected indoor temperature values of different rooms of a user, identifying the usage habits of the user, intelligently pushing a setting mode, and identifying indoor temperature requirements of the different rooms at the next time in the user electric heating intelligent group control method based on the user habits according to an embodiment of the present invention.
Fig. 3 is a flowchart of collecting the instantaneous total electric power of the user and the instantaneous electric power of the electric heater group, identifying the instantaneous electric power of other electric devices of the user, and comparing the instantaneous electric power with the preset total electric power limit value to identify the available instantaneous power of the electric heater group at the next moment in the user electric heating intelligent group control method based on the user habits according to an embodiment of the present invention.
Fig. 4 is a flowchart of a method for controlling a household intelligent group for heating by users based on user habits, according to an embodiment of the present invention, the method collects actual indoor temperatures of different rooms of the user at a current time, and predicts electric heating demands of different rooms at a next time according to the indoor temperature demands of different rooms at the next time.
Fig. 5 is a flowchart of an embodiment of the present invention, which combines the available instantaneous power of the electric heater group, to intelligently determine the start and stop of the electric heaters in each room and to send a control instruction to the electric heaters, in the household electric heating intelligent group control method based on user habits.
Fig. 6 is a flowchart of classifying and saving the expected indoor temperature values of different rooms of the user in an intelligent group control method for household heating based on user habits according to an embodiment of the present invention.
Fig. 7 is a block diagram of an intelligent group control system for household heating based on user habits according to an embodiment of the present invention.
Fig. 8 is a block diagram of an electronic device in one embodiment of the invention.
Detailed Description
In some of the flows described in the present specification and claims and in the above figures, a number of operations are included that occur in a particular order, but it should be clearly understood that these operations may be performed out of order or in parallel as they occur herein, with the order of the operations being indicated as 101, 102, etc. merely to distinguish between the various operations, and the order of the operations by themselves does not represent any order of performance. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.
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.
The electric heating is a high-quality comfortable environment-friendly heating mode for converting clean electric energy into heat energy, and long-term practical application proves that the electric heating has incomparable advantages of other heating modes and is accepted and accepted by more and more users. The household electric heating system mainly utilizes the mode of directly converting electric energy into household heat energy to heat the indoor.
The main principle of the existing household electric heating system is that the electric heating equipment is regulated and controlled to heat by means of preset temperature of a user, and in addition, partial peak clipping and valley filling strategies are considered in part of schemes, and electric heating is carried out through balanced electric energy supply. However, the existing technology cannot identify the habit of the user to carry out intelligent pushing of the control mode, and meanwhile, can not carry out non-overrun control according to the electric power requirements of different rooms of the user, and can not ensure better use experience of the user and non-overrun of the power of electric equipment.
The embodiment of the invention provides a household electric heating intelligent group control method and system based on user habits. According to the scheme, the indoor electric heater group control strategy is formulated by acquiring heating habits of different rooms of a user, and on the premise that the user demand and the instantaneous total power are not exceeded, energy conservation and cost reduction in the heating process are realized, and the indoor electric heater group control strategy is green and low-carbon.
According to the first aspect of the embodiment of the invention, the intelligent group control method for household electric heating based on the user habits is provided.
Fig. 1 is a flowchart of a household heating intelligent group control method based on user habits according to an embodiment of the present invention.
In one or more embodiments, preferably, the user heating intelligent group control method based on user habits includes:
s101, collecting indoor temperature expected values of different rooms of a user, identifying the use habits of the user, intelligently pushing a set mode, and identifying indoor temperature requirements of the different rooms at the next moment;
s102, acquiring the instantaneous total electric power of a user and the instantaneous electric power of an electric heater group, identifying the instantaneous electric power of other electric equipment except the electric heater group of the user, comparing the instantaneous electric power with a preset user total electric power limit value, and identifying the available instantaneous power of the electric heater group at the next moment;
s103, collecting actual indoor temperatures of different rooms of a user at the current moment, predicting electric heating requirements of different rooms at the next moment according to the indoor temperature requirements of different rooms at the next moment, combining available instantaneous power of an electric heater group, intelligently judging the starting and stopping and adjusting of each room electric heater, and sending a control instruction to the electric heaters.
In the embodiment of the invention, the indoor temperatures of different rooms are collected in different areas according to the requirements of users, the use habits of the users are automatically established by combining the current control habits of the users on electric heating, the comfort level judgment is further completed, the prediction is realized according to the use habits, and the intelligent pushing user setting mode is achieved. The method comprises the steps of identifying the instantaneous total electric power of a user, the instantaneous total electric power limit value and the instantaneous electric power of an electric heater group, finishing judgment of available instantaneous power of the electric heater group, analyzing heating requirements of different rooms by combining set indoor temperatures of different rooms of the user, and finally finishing power distribution according to needs under the power limit value of the electric heater group.
Fig. 2 is a flowchart of collecting expected indoor temperature values of different rooms of a user, identifying the usage habits of the user, intelligently pushing a setting mode, and identifying indoor temperature requirements of the different rooms at the next time in the user electric heating intelligent group control method based on the user habits according to an embodiment of the present invention.
As shown in fig. 2, the collecting the expected indoor temperature values of different rooms of the user, identifying the use habits of the user, intelligently pushing the setting mode, and identifying the indoor temperature requirements of the different rooms at the next moment specifically includes:
s201, collecting the indoor temperature expected values of different rooms of a user, and storing the indoor temperature expected values as expected temperature data;
s202, carrying out online processing on the expected temperature data, establishing a corresponding relation table between different time periods of different rooms of a user and the expected temperature data, identifying the use habits of the user, and storing the use habits as first data;
s203, pushing a setting mode according with the use habit of the user according to the room and the time period of the setting state to be adjusted by the user, identifying the expected temperature data of different rooms at different time periods at the next moment selected by the user, and storing the expected temperature data as second data;
s204, extracting the temperature, the time and the room number corresponding to each second data, and calculating expected temperature habits of each first data at different times and different room numbers by using a first calculation formula;
s205, predicting user behaviors of each first data according to historical expected temperature habits through polynomial fitting or through the combination of an LSTM neural network cooperation algorithm and a rule mining algorithm, generating the expected temperature habits in a period of time in the future, and pushing the expected temperature habits to different rooms of a user at the next moment; automatically identifying the final set expected temperature of different rooms of a user at the next moment, and generating the indoor temperature requirements of the different rooms at the next moment;
the first calculation formula is:
where t "(i, τ) is the expected temperature habit of the user i room at time τ, τ is the time value, t ' (i, τ -1) is the set expected temperature of the i room at time τ -1, t ' (i, τ -2) is the set expected temperature of the i room at time τ -2, and t ' (i, τ -n) is the set expected temperature of the i room at time τ -n.
In the embodiment of the invention, the expected temperature habits of different rooms are analyzed, the historical data of the user is further utilized to generate the indoor temperature demand forecast of the different rooms at the next moment, each first data is forecasted by polynomial fitting according to the expected temperature habits of the history or by the combination of an LSTM neural network cooperative algorithm and a rule mining algorithm, and the generated temperature demand at the next moment is a basic parameter for carrying out subsequent control mode intelligent pushing. In addition, expected temperature set values of different rooms of a user are identified, and indoor temperature requirements of the different rooms at the next moment are generated.
Fig. 3 is a flowchart of collecting the instantaneous total electric power of the user and the instantaneous electric power of the electric heater group, identifying the instantaneous electric power of other electric devices of the user, and comparing the instantaneous electric power with the preset total electric power limit value to identify the available instantaneous power of the electric heater group at the next moment in the user electric heating intelligent group control method based on the user habits according to an embodiment of the present invention.
As shown in fig. 3, the method includes collecting the instantaneous total electric power of the user and the instantaneous electric power of the electric heater group, identifying the instantaneous electric power of other electric devices of the user, comparing the instantaneous electric power with the preset total electric power limit value of the user, and identifying the available instantaneous power of the electric heater group at the next moment, and specifically includes:
s301, acquiring instantaneous electric power of a user through an intelligent electric meter;
s302, acquiring the preset user total electric power limit value, and comparing the relation between the user instantaneous electric power and the preset user total electric power limit value;
s303, if the instantaneous electric power of the user is higher, sending a power-limiting operation command, and setting the set power of the electric heater group at the next moment to be 0;
s304, if the preset user total electric power limit value is larger or equal to the preset user total electric power limit value, sending an available instantaneous power calculation command;
s305, after receiving an available instantaneous power calculation command, taking the difference value of the user instantaneous electric power and the instantaneous electric power of the electric heater group as instantaneous electric power of other electric devices of the user, and taking the difference value of the preset user total electric power limit value and the instantaneous electric power of other electric devices of the user as the available instantaneous power of the electric heater group.
In the embodiment of the invention, in order to realize the control of the user on the total electric power of the users of the electric heater group, the available instantaneous power values under different conditions are calculated, and a data basis is further provided for the subsequent control.
Fig. 4 is a flowchart of collecting actual indoor temperatures of different rooms of a user at a current time and predicting electric heating requirements of different rooms at a next time according to the indoor temperature requirements of the different rooms at the next time in the user electric heating intelligent group control method based on user habits according to an embodiment of the present invention.
As shown in fig. 4, acquiring actual indoor temperatures of different rooms of a user at a current time, and predicting electric heating requirements of different rooms at a next time according to indoor temperature requirements of different rooms at the next time, specifically including:
s401, acquiring actual indoor temperatures of different rooms of a user at the current moment through a sensor;
s402, acquiring the final set expected temperature of different rooms of the user at the next moment, and comparing the magnitude relation between the actual indoor temperature of the different rooms and the final set expected temperature at the next moment;
s403, if the actual indoor temperature of the room is higher, a power-limiting operation command is sent out, and the set power of the electric heater at the next time is set to be 0;
s404, if the final set expected temperature at the next moment is larger or equal to the final set expected temperature at the next moment, calculating the electric power requirements of different rooms by using a second calculation formula to serve as the electric heating requirements of the different rooms at the next moment;
the second calculation formula is:
N′(i,τ+1)=A*(t′(i,τ+1)-t(i,τ))
where N '(i, τ +1) is the power demand of i room τ +1, a is the power coefficient corresponding to the desired temperature difference per unit of room, t' (i, τ +1) is the set desired temperature of i room at τ +1, and t (i, τ) is the actual indoor temperature of i room at τ.
In an embodiment of the invention, the electric power demand of each room is further automatically calculated and used as the electric heating demand of different rooms at the next moment.
Fig. 5 is a flowchart of an embodiment of the present invention, which combines the available instantaneous power of the electric heater group, and intelligently determines the start-stop and adjustment of the electric heaters in each room, and sends a control instruction to the electric heaters, in the household electric heating intelligent group control method based on the user habits.
As shown in fig. 5, the available instantaneous power of the electric heater group is combined, the electric heater in each room is started and stopped and is intelligently judged by regulation, and a control instruction is sent to the electric heater, and the method specifically comprises the following steps:
s501, identifying available instantaneous power of the electric heater group, and calculating the set power of the electric heaters in each room by using a third calculation formula according to the electric heating requirements of different rooms at the next moment;
s502, controlling the power of all the electric heaters according to the set power of the electric heaters in each room;
the third calculation formula is:
wherein, N (i, τ +1) is the electric power set value at the moment of i room τ +1, m is the number of rooms, and N (τ +1) is the available instantaneous power of the electric heater group at the moment of τ + 1.
The household electric heating intelligent group control method based on user habits further comprises the following steps: and carrying out data transmission on the set power of the user electric heater through ZigBee, Wifi or ZigBee + Wifi wireless network.
Fig. 6 is a flowchart of classifying and saving the expected indoor temperature values of different rooms of the user in an intelligent group control method for household heating based on user habits according to an embodiment of the present invention.
As shown in fig. 6, the method for controlling a household intelligent group heating system based on user habits further includes classifying and storing the expected indoor temperature values of different rooms of the user, which specifically includes:
s601, acquiring the indoor temperature expected values of all the rooms;
s602, extracting source positions of all the indoor temperature expected values;
s603, adding room number data to the indoor temperature expected value according to the source position to generate first intermediate position data;
s604, adding an electric heater number to the first intermediate position data according to the source position to generate second intermediate data;
and S605, reading the expected indoor temperature at the next moment, storing the expected indoor temperature at the next moment and the second intermediate data together into real-time storage data, and storing the real-time storage data in a memory.
In the embodiment of the invention, the corresponding temperature expected value is set by combining the control information, and the combination storage of different source positions and the control information is realized, so that the temperature control method is further used for the subsequent temperature control of the intelligent group control of electric heating.
In order to realize the functions, automatic information synchronization needs to be carried out on a plurality of electric heating devices, but because the acquisition information quantity of a large amount of electric heating devices and other power supply devices is large, and the real-time transmission data quantity is also large, time-sharing and segmented self-adaptive information synchronization is carried out aiming at the problem, flexible setting of control information and temperature expected information is realized through the synchronization mode, too many resources cannot be occupied, information congestion of intelligent group control is avoided, and the specific process is as follows:
setting a first preset measurement coefficient and a second preset measurement coefficient;
extracting historical data of user operation frequency, predicting possible operation frequency at the current moment, and using the possible operation frequency as a user regulation index of the current time;
extracting historical data of system operation frequency, predicting the system operation frequency at the current moment, and taking the system operation frequency as a system regulation and control index at the current moment;
calculating the system operation degree at the current moment by using a fourth calculation formula;
judging whether a fifth calculation formula is met, and if so, sending a classification operation instruction;
after receiving the classification operation instruction, sending an edge processing command to all the electric heating equipment, wherein all the electric heating equipment only upload the change operation, and the unchanged information is not transmitted;
after the classification operation instruction is received, the missing data in all the read information is automatically supplemented with the data of the electric heating equipment at the previous moment, and the group control command is continuously executed;
the fourth calculation formula is:
Zt=K1Z1+K2Z2
wherein ,ZtFor the degree of system operation at the present moment, Z1For the user at the current time, Z2Is the system regulation index at the current moment, K1Is a first predetermined measure coefficient, K2Is a second preset measure coefficient;
wherein ,K1 and K2Is set to 0.5.
The fifth calculation formula is:
Zt/Zt_max>60%
wherein ,Zt_maxIs the maximum system operating margin at time t.
According to the second aspect of the embodiment of the invention, the household heating intelligent group control system based on the user habits is provided.
Fig. 7 is a block diagram of an intelligent group control system for household heating based on user habits according to an embodiment of the present invention.
In one or more embodiments, preferably, the household heating intelligent group control system based on user habits comprises:
the demand analysis module 701 is used for acquiring indoor temperature expected values of different rooms of a user, identifying the use habits of the user, intelligently pushing a set mode, and identifying indoor temperature demands of different rooms at the next moment;
the state analysis module 702 is used for acquiring the instantaneous total electric power of the user and the instantaneous electric power of the electric heater group, identifying the instantaneous electric power of other electric equipment of the user, comparing the instantaneous electric power with a preset user total electric power limit value, and identifying the available instantaneous power of the electric heater group;
the intelligent control module 703 is used for acquiring actual indoor temperatures of different rooms of a user at the current moment, predicting electric heating requirements of different rooms at the next moment according to the indoor temperature requirements of different rooms at the next moment, intelligently judging the start and stop and adjustment of each room electric heater by combining the available instantaneous power of the electric heater group, and sending a control instruction to the electric heaters;
the wireless transmission module 704 is used for transmitting the instantaneous electric power of the user through a ZigBee, Wifi or ZigBee + Wifi wireless network;
and the data storage module 705 is configured to store the indoor temperature expected values of the different rooms of the user in a classified manner.
According to a third aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method according to any one of the first aspect of embodiments of the present invention.
According to a fourth aspect of the embodiments of the present invention, there is provided an electronic apparatus. Fig. 8 is a block diagram of an electronic device in one embodiment of the invention. The electronic device shown in fig. 8 is a universal heating control device, which includes a general-purpose computer hardware structure, which includes at least a processor 801 and a memory 802. The processor 801 and the memory 802 are connected by a bus 803. The memory 802 is adapted to store instructions or programs executable by the processor 801. Processor 801 may be a stand-alone microprocessor or a collection of one or more microprocessors. Thus, the processor 801 implements the processing of data and the control of other devices by executing instructions stored by the memory 802 to perform the method flows of embodiments of the present invention as described above. The bus 803 connects the above components together, and also connects the above components to a display controller 804 and a display device and an input/output (I/O) device 805. Input/output (I/O) devices 805 may be a mouse, keyboard, modem, network interface, touch input device, motion sensing input device, printer, and other devices known in the art. Typically, the input/output devices 805 are coupled to the system through input/output (I/O) controllers 806.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
1) in the embodiment of the invention, the user habit is intelligently identified, the power consumption of the user is monitored in real time, the automatic optimization control of the electric heater group is realized, the overload of a power grid caused by the overlarge instantaneous power of the user electric heater is prevented on the premise of meeting the comfort level of the user, and the heating power consumption and the cost of the user are saved;
2) according to the embodiment of the invention, the heating habits of different rooms of the user are obtained, and the setting mode is intelligently pushed, so that the electric heating control of the user is more intelligent and convenient.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A household electric heating intelligent group control method based on user habits is characterized by comprising the following steps:
collecting indoor temperature expected values of different rooms of a user, identifying the use habits of the user, intelligently pushing a set mode, and identifying indoor temperature requirements of the different rooms at the next moment;
collecting the instantaneous total electric power of a user and the instantaneous electric power of an electric heater group, identifying the instantaneous electric power of other electric equipment except the electric heater group by the user, comparing the instantaneous electric power with a preset user total electric power limit value, and identifying the available instantaneous power of the electric heater group at the next moment;
the actual indoor temperature of different rooms of the user at the current moment is collected, the electric heating requirements of different rooms at the next moment are predicted according to the indoor temperature requirements of different rooms at the next moment, the available instantaneous power of the electric heater group is combined, the electric heaters in each room are started, stopped and intelligently judged, and a control instruction is sent to the electric heaters.
2. The intelligent group control method for household electric heating based on user habits according to claim 1, wherein the collecting the expected indoor temperature values of different rooms of the user, identifying the user habits, intelligently pushing the setting mode, and identifying the indoor temperature requirements of the different rooms at the next moment specifically comprises:
collecting the indoor temperature expected values of different rooms of a user, and storing the indoor temperature expected values as expected temperature data;
carrying out online processing on the expected temperature data, establishing a corresponding relation table between different time periods of different rooms of a user and the expected temperature data, identifying the use habits of the user, and storing the use habits as first data;
pushing a setting mode according with the use habit of the user according to the room and the time period of the setting state to be adjusted by the user, identifying the expected temperature data of different rooms in different time periods at the next moment selected by the user, and storing the expected temperature data as second data;
extracting the temperature, the time and the room number corresponding to each second data, and calculating expected temperature habits of each first data at different times and different room numbers by using a first calculation formula;
predicting user behavior according to the historical expected temperature habits through polynomial fitting or through the combination of an LSTM neural network cooperative algorithm and a rule mining algorithm, generating the expected temperature habits in a period of time in the future, and pushing the expected temperature habits to the user at the next moment in different rooms; automatically identifying the final set expected temperature of different rooms of a user at the next moment, and generating the indoor temperature requirements of the different rooms at the next moment;
the first calculation formula is:
where t "(i, τ) is the expected temperature habit of the user i room at time τ, τ is the time value, t ' (i, τ -1) is the set expected temperature of the i room at time τ -1, t ' (i, τ -2) is the set expected temperature of the i room at time τ -2, and t ' (i, τ -n) is the set expected temperature of the i room at time τ -n.
3. The intelligent group control method for household electric heating based on user habits as claimed in claim 1, wherein the method comprises the steps of collecting the instantaneous total electric power of the user and the instantaneous electric power of the electric heater group, identifying the instantaneous electric power of other electric devices of the user, comparing the instantaneous electric power with the preset total electric power limit value of the user, and identifying the available instantaneous power of the electric heater group at the next moment, and specifically comprises the following steps:
acquiring instantaneous electric power of a user through an intelligent electric meter;
acquiring the preset user total electric power limit value, and comparing the relation between the user instantaneous electric power and the preset user total electric power limit value;
if the instantaneous electric power of the user is larger, sending a power-limiting operation command, and setting the set power of the electric heater group to be 0 at the next moment;
if the preset user total electric power limit value is larger or equal to the preset user total electric power limit value, sending an available instantaneous power calculation command;
and after receiving an available instantaneous power calculation command, taking the difference value of the user instantaneous electric power and the instantaneous electric power of the electric heater group as the instantaneous electric power of other electric devices of the user, and taking the difference value of the preset user total electric power limit value and the instantaneous electric power of other electric devices of the user as the available instantaneous power of the electric heater group.
4. The intelligent group control method for household electric heating based on user habits according to claim 1, wherein the method for collecting actual indoor temperatures of different rooms of a user at a current time and predicting electric heating requirements of different rooms at a next time according to the indoor temperature requirements of different rooms at the next time specifically comprises the following steps:
acquiring actual indoor temperatures of different rooms of a user at the current moment through a sensor;
acquiring the final set expected temperature of different rooms of a user at the next moment, and comparing the magnitude relation between the actual indoor temperature of the different rooms and the final set expected temperature at the next moment;
if the actual indoor temperature of the room is higher, sending a power-limiting operation command, and setting the power of the electric heater to be 0 at the next moment;
if the final set expected temperature at the next moment is larger or equal to the final set expected temperature at the next moment, calculating the electric power demands of different rooms by using a second calculation formula as the electric heating demands of the different rooms at the next moment;
the second calculation formula is:
N′(i,τ+1)=A*(t′(i,τ+1)-t(i,τ))
where N '(i, τ +1) is the power demand of i room τ +1, a is the power coefficient corresponding to the desired temperature difference per unit of room, t' (i, τ +1) is the set desired temperature of i room at τ +1, and t (i, τ) is the actual indoor temperature of i room at τ.
5. The intelligent group control method for household electric heating based on user habits as claimed in claim 1, wherein the method for intelligently judging the start and stop of each room electric heater and adjusting the electric heater and sending a control instruction to the electric heater in combination with the available instantaneous power of the electric heater group specifically comprises:
identifying available instantaneous power of the electric heater group, and calculating the set power of the electric heaters in each room by using a third calculation formula according to the electric heating requirements of different rooms at the next moment;
performing power control on all the electric heaters according to the set power of the electric heaters in each room;
the third calculation formula is:
wherein, N (i, τ +1) is the electric power set value at the moment of i room τ +1, m is the number of rooms, and N (τ +1) is the available instantaneous power of the electric heater group at the moment of τ + 1.
6. The intelligent group control method for household heating based on user habits according to claim 1, further comprising: and transmitting the set power of the user electric heater through a ZigBee, Wifi or ZigBee plus Wifi wireless network.
7. The intelligent group control method for household electric heating based on user habits according to claim 1, further comprising classifying and storing the expected indoor temperature values of different rooms of the user, specifically comprising:
acquiring the indoor temperature expected values of all rooms;
extracting source positions of all the indoor temperature expected values;
adding room number data to the indoor temperature expected value according to the source position to generate first intermediate position data;
adding an electric heater number to the first intermediate position data according to the source position to generate second intermediate data;
and reading the expected indoor temperature at the next moment, and storing the expected indoor temperature at the next moment and the second intermediate data together as real-time storage data in a memory.
8. The utility model provides a family is with electric heating intelligence group control system based on user's custom which characterized in that, this system includes:
the demand analysis module is used for acquiring indoor temperature expected values of different rooms of a user, identifying the use habits of the user, intelligently pushing a set mode and identifying indoor temperature demands of different rooms at the next moment;
the state analysis module is used for acquiring the instantaneous total electric power of the user and the instantaneous electric power of the electric heater group, identifying the instantaneous electric power of other electric equipment of the user, comparing the instantaneous electric power with a preset user total electric power limit value, and identifying the available instantaneous power of the electric heater group;
the intelligent control module is used for acquiring the actual indoor temperatures of different rooms of a user at the current moment, predicting the electric heating requirements of different rooms at the next moment according to the indoor temperature requirements of different rooms at the next moment, intelligently judging the start and stop and adjustment of each room electric heater by combining the available instantaneous power of the electric heater group, and sending a control instruction to the electric heaters;
the wireless transmission module is used for transmitting the instantaneous electric power of the user through a ZigBee, a Wifi or a ZigBee plus Wifi wireless network;
and the data storage module is used for classifying and storing the indoor temperature expected values of different rooms of the user.
9. A computer-readable storage medium on which computer program instructions are stored, which, when executed by a processor, implement the method of any one of claims 1-7.
10. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method of any of claims 1-7.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210382396.5A CN114738827B (en) | 2022-04-12 | 2022-04-12 | User habit-based intelligent group control method and system for heating by using electricity |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210382396.5A CN114738827B (en) | 2022-04-12 | 2022-04-12 | User habit-based intelligent group control method and system for heating by using electricity |
Publications (2)
Publication Number | Publication Date |
---|---|
CN114738827A true CN114738827A (en) | 2022-07-12 |
CN114738827B CN114738827B (en) | 2023-09-26 |
Family
ID=82280627
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210382396.5A Active CN114738827B (en) | 2022-04-12 | 2022-04-12 | User habit-based intelligent group control method and system for heating by using electricity |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN114738827B (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115000990A (en) * | 2022-08-04 | 2022-09-02 | 建科环能科技有限公司 | Peak regulation control method and system for power storage system in intelligent group control electric heating power grid |
CN115218270A (en) * | 2022-08-18 | 2022-10-21 | 建科环能科技有限公司 | Intelligent group control method and system for distributed electric heating of terminal substation level |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104181898A (en) * | 2014-09-01 | 2014-12-03 | 东北电力大学 | Intelligent control method and system for interactive home appliances on basis of time-of-use electricity price response |
WO2017008322A1 (en) * | 2015-07-10 | 2017-01-19 | 西安交通大学 | Smart home energy management method based on social networking behavior detection |
CN110864414A (en) * | 2019-10-30 | 2020-03-06 | 郑州电力高等专科学校 | Air conditioner power utilization load intelligent control scheduling method based on big data analysis |
US20200355387A1 (en) * | 2018-08-20 | 2020-11-12 | Grid4C | Method and system for hvac inefficiency prediction using household electrical smart meter data |
CN112050383A (en) * | 2019-06-06 | 2020-12-08 | 青岛海尔空调器有限总公司 | Control method of air conditioner under refrigeration working condition |
CN112050438A (en) * | 2019-06-06 | 2020-12-08 | 青岛海尔空调器有限总公司 | Control method of air conditioner under refrigeration working condition |
CN112161322A (en) * | 2020-09-24 | 2021-01-01 | 深圳市合信达控制***有限公司 | Heating equipment and control method thereof |
-
2022
- 2022-04-12 CN CN202210382396.5A patent/CN114738827B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104181898A (en) * | 2014-09-01 | 2014-12-03 | 东北电力大学 | Intelligent control method and system for interactive home appliances on basis of time-of-use electricity price response |
WO2017008322A1 (en) * | 2015-07-10 | 2017-01-19 | 西安交通大学 | Smart home energy management method based on social networking behavior detection |
US20200355387A1 (en) * | 2018-08-20 | 2020-11-12 | Grid4C | Method and system for hvac inefficiency prediction using household electrical smart meter data |
CN112050383A (en) * | 2019-06-06 | 2020-12-08 | 青岛海尔空调器有限总公司 | Control method of air conditioner under refrigeration working condition |
CN112050438A (en) * | 2019-06-06 | 2020-12-08 | 青岛海尔空调器有限总公司 | Control method of air conditioner under refrigeration working condition |
CN110864414A (en) * | 2019-10-30 | 2020-03-06 | 郑州电力高等专科学校 | Air conditioner power utilization load intelligent control scheduling method based on big data analysis |
CN112161322A (en) * | 2020-09-24 | 2021-01-01 | 深圳市合信达控制***有限公司 | Heating equipment and control method thereof |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115000990A (en) * | 2022-08-04 | 2022-09-02 | 建科环能科技有限公司 | Peak regulation control method and system for power storage system in intelligent group control electric heating power grid |
CN115218270A (en) * | 2022-08-18 | 2022-10-21 | 建科环能科技有限公司 | Intelligent group control method and system for distributed electric heating of terminal substation level |
CN115218270B (en) * | 2022-08-18 | 2023-09-29 | 建科环能科技有限公司 | Distributed electric heating intelligent group control method and system for terminal substation level |
Also Published As
Publication number | Publication date |
---|---|
CN114738827B (en) | 2023-09-26 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Wei et al. | A bi-level scheduling model for virtual power plants with aggregated thermostatically controlled loads and renewable energy | |
CN114738827B (en) | User habit-based intelligent group control method and system for heating by using electricity | |
Hao et al. | Aggregate flexibility of thermostatically controlled loads | |
US9310792B2 (en) | Scheduling and modeling the operation of controllable and non-controllable electronic devices | |
EP2494736B1 (en) | Method of controlling network system | |
CN102142062A (en) | Method and apparatus for controlling operations of devices based on information about power consumption of the devices | |
CN102375443A (en) | Thermal time constraints for demand response applications | |
CN104122819A (en) | User habit based intelligent household electricity utilization method and system thereof | |
KR20120086979A (en) | Electrical instrument, power management apparatus, power management system and method for controlling the same | |
CN106096747B (en) | Solar energy auxiliary household energy management method for taking various uncertain factors into account in real-time electricity price environment | |
CN104833038A (en) | Multi-split air conditioner centralized control method and centralized controller | |
CN111598478B (en) | Comprehensive energy demand response quantity calculation method | |
CN215724029U (en) | Central air conditioning adaptive control system | |
CN110503461B (en) | Demand response method based on residential user clustering in smart power grid | |
CN104408663A (en) | User demand response dispatching system and method of smart grid | |
JP6471751B2 (en) | Energy control system, energy control device, energy control method and program | |
CN111947276A (en) | Control method, server, control equipment and storage medium of air conditioner | |
CN111679573A (en) | Household energy consumption optimization method and device for residents | |
CN113935856A (en) | Method and device for controlling electric energy, processor and computer readable storage medium | |
CN206370695U (en) | A kind of photovoltaic plant | |
CN110535143B (en) | Energy management method and device facing intelligent residence dynamic demand response | |
US9407114B2 (en) | Network system and control method thereof | |
CN106779321A (en) | A kind of energy supply control method and device based on energy supplying system | |
CN114936460B (en) | User electricity utilization time sequence optimization method and system | |
CN115051374B (en) | Control method, device and storage medium for electric heating equipment to participate in electric peak regulation |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |