Device control method, electronic device, computer readable medium, and program product

Abstract

The invention relates to the technical field of computers, in particular to an equipment control method, electronic equipment, a computer readable medium and a program product. At least one electric device included in a target area of a building is determined through an electronic device, and device parameters of the electric device included in the target area are adjusted based on people flow data in the target area and / or weather data of an external environment. The current environment of the target area can meet the comfort requirement based on the adjusted electric equipment, and energy conservation and consumption reduction are achieved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a device control method, electronic equipment, computer-readable medium, and program product. Background Art

[0002] Currently, to achieve automatic control of electrical equipment in buildings such as office buildings and apartments, a pre-set control scheme for these electrical equipment can be used. Based on this pre-set control scheme, electrical equipment such as air conditioners, lighting, and elevators within the building can be automatically controlled. For example, the pre-set control scheme can be used to control the building's air conditioners to operate at a higher temperature for heating in the winter and a lower temperature for cooling in the summer.

[0003] However, the lack of flexibility in automatically controlling electrical devices based on preset control schemes can make it difficult to achieve optimal electricity usage in some scenarios, thereby reducing energy consumption and carbon emissions from building operations. For example, in winter, high outdoor temperatures and / or high traffic volume may obviate the need for air conditioning to heat the building. In such scenarios, if the building's air conditioning continues to heat according to the preset control scheme, this would result in unnecessary energy waste and could potentially worsen comfort levels within the building. Summary of the Invention

[0004] The present application provides a device control method, electronic device, computer-readable medium, and program product, which can adjust device parameters of electrical devices based on changes in the number of people.

[0005] In a first aspect, the present application provides a device control method, applied to a first electronic device, the method comprising: determining at least one second electronic device within a first target area, and a first device parameter value corresponding to the second electronic device; obtaining environmental parameters of the first target area; detecting that a first parameter in the environmental parameters changes to a first parameter value, wherein the first parameter is used to represent the number of people in the first target area; adjusting the first device parameter value to a second device parameter value based on the first parameter value; and controlling the second electronic device based on the second device parameter value.

[0006] Here, the first electronic device may be the control device mentioned below. The first target area may be the target area mentioned below. The second electronic device may be the electrical device mentioned below. The environmental parameters may include the structural data of the building mentioned below, the electrical device data in the building, the climate data and the flow of people data. The first parameter used to represent the number of people in the first target area may be the flow of people or the flow of people data mentioned below. The first parameter value may be a specific flow of people value (or, the number of people value). The first device parameter value and the second device parameter value may be the parameter values ​​of the device parameters mentioned below.

[0007] After detecting that the number of people in the first target area has changed to a first parameter value, the device parameters of the second electronic device can be adjusted to a second device parameter value based on the first parameter value. Furthermore, the device parameters are parameters that control the operating state of the second electronic device. Therefore, based on this solution, the operating state of the second electronic device can be adjusted according to changes in the number of people.

[0008] In a possible implementation of the first aspect, detecting that a first parameter among the environmental parameters changes to a first parameter value includes: determining at a first moment that the first parameter will change to the first parameter value at a second moment, wherein the first moment is earlier than the second moment.

[0009] Here, the first electronic device can predict at the first moment that the first parameter will change to the first parameter value at the second moment in the future, and then, the device parameter of the second electronic device can be adjusted to the second device parameter value according to the first parameter value at the first moment, and the second electronic device can be controlled according to the second device parameter value at the first moment. In this way, the operating state of the second electronic device can be adjusted in advance. For example, with reference to the following, the first target area can be a conference room, the second electronic device can be an air conditioner, and the first device parameter value and the second device parameter value can be the parameter values ​​of the air conditioning parameters of the air conditioner. Therefore, the air conditioning parameters of the air conditioner in the conference room can be adjusted in advance based on this method to preheat the conference room.

[0010] For another example, as described below, the first target area may be an office, the second electronic device may be a lighting device, and the first and second device parameter values ​​may be device parameter values ​​of the lighting device. The device parameters of the lighting device can be described in detail in 200 below and are not detailed here. Using this approach, the office lighting can be turned on in advance, ensuring that the office is already illuminated when employees enter.

[0011] For another example, as described below, the first target area may be the first floor lobby, the second electronic device may be an elevator, and the first and second device parameter values ​​may be parameter values ​​of the elevator's device parameters. The elevator's device parameters are described in detail in 200 below and are not detailed here. This approach allows elevators that are idle at the first moment to be dispatched to the first lobby in advance, reducing the time users in the first floor lobby need to wait for elevators.

[0012] In a possible implementation of the first aspect, detecting that a first parameter among the environmental parameters changes to a first parameter value includes: detecting that the first parameter changes to the first parameter value at a third moment.

[0013] Here, when the first electronic device detects that the first parameter changes to the first parameter value at the third moment, it can determine the second device parameter value of the second electronic device based on the first parameter value, thereby realizing real-time adjustment of the operating state of the second electronic device. For example, with reference to the following, the first target area can be a safety passage, the second electronic device can be the lighting of the safety passage, and the first device parameter value and the second device parameter value can be the parameter values ​​of the device parameters of the lighting device. Based on this method, when it is detected that there is someone in the safety passage at the third moment (the first parameter value is not 0), the lighting of the safety passage can be controlled to turn on; conversely, when it is detected that there is no one in the safety passage at the third moment (the first parameter value is 0), the lighting of the safety passage can be controlled to turn off.

[0014] In a possible implementation of the first aspect, controlling the second electronic device based on the second device parameter value includes: corresponding to the first parameter value being greater than 0, controlling the first category of devices in the second electronic device to be in a first state based on the second device parameter value; corresponding to the first parameter value being equal to 0, controlling the first category of devices in the second electronic device to be in a second state based on the second device parameter value; wherein the energy consumption value of the first category of devices in the first state is greater than the energy consumption value of the first category of devices in the second state.

[0015] Here, the first type of equipment may be the first type of electronic equipment mentioned below, for example, it may include at least any one of a lighting device, an escalator, and an elevator.

[0016] Here, a first parameter value greater than 0 indicates that someone is present in the first target area; conversely, a first parameter value equal to 0 indicates that no one is present in the first target area. Therefore, based on determining whether there is someone in the first target area, the first type of device in the first target area can be controlled to adjust its operating state. For a specific example, see the detailed description of step 202 below and will not be repeated here.

[0017] Here, the first state may be the operating state of the first type of electronic device controlled by the switch parameter (as an example of the device parameter), and correspondingly, the second state may be the non-operating state of the first type of electronic device controlled by the switch parameter; the first state may be the high lighting brightness state of the lighting device controlled by the gear parameter (as an example of the device parameter), and correspondingly, the second state may be the low lighting brightness state of the lighting device controlled by the gear parameter; the first state may be the high-speed operating state of the elevator controlled by the speed parameter (as an example of the device parameter), and correspondingly, the second state may be the low-speed operating state of the elevator controlled by the speed parameter.

[0018] In a possible implementation of the first aspect, adjusting the first device parameter value to the second device parameter value based on the first parameter value includes: determining the heat production (including sensible heat and latent heat) of the first target area based on the first parameter value; determining the heat dissipation of the first target area based on the first device parameter value; adjusting the first device parameter value to the second device parameter value based on the heat production and the heat dissipation, and controlling the second type of device in the second electronic device based on the second device parameter value; wherein the second type of electronic device is used to adjust the temperature of the first target area.

[0019] The heat generated in the first target area includes sensible heat and latent heat. Sensible heat can include a temperature rise in the first target area; latent heat can include sweat evaporation from people in the first target area corresponding to the flow of people in the first target area, as well as an increase in air humidity in the first target area caused by other humidifying equipment. Sensible heat and latent heat can generally be collectively expressed as heat generation.

[0020] Here, the second type of electronic equipment can be the second type of electrical equipment mentioned below. For example, central air conditioning (as an example of air conditioning), floor heating system, etc. It can be understood that the heat production of the first target area determined based on the first parameter value is positive, indicating that the temperature of the first target area has increased due to the increase in the number of people. At this time, the cooling capacity of the first target area determined based on the first device parameter value is positive, which means that cooling is performed based on the second type of electrical equipment in the first target area. The heat production of the first target area determined based on the first parameter value is negative, indicating that the temperature of the first target area has decreased due to the decrease in the number of people. At this time, the cooling capacity of the first target area determined based on the first device parameter value is negative, which means that heating is performed based on the second type of electrical equipment in the first target area.

[0021] In a possible implementation of the first aspect, the heat generation of the first target area is determined based on the first parameter value, including: determining the heat generation of the first target area based on spatial data of the first target area, the first parameter value, and a third parameter value of a second parameter in the environmental parameters, wherein the second parameter includes at least one or more of the following: the amount of light in the first target area, the heat dissipation of electrical equipment in the first target area, and the heat transfer coefficient of the enclosure structure of the first target area.

[0022] Here, the spatial data of the first target area may be the spatial size of the target area, the ventilation volume, etc. The first parameter value may be the flow of people data in the first target area. The third parameter value of the second parameter in the environmental parameters may be the amount of light in the first target area, that is, the heat generated by light in the first target area; it may be the heat dissipation of the electrical equipment in the first target area, that is, the heat generated by the running electrical equipment in the first target area; it may be the heat transfer coefficient of the enclosure structure of the first target area. Here, the enclosure structure of the first target area may include the walls, doors, windows and other structures of the first target area that may have heat preservation and moisture retention functions. Here, no restrictive description is made on the enclosure structure of the first target area. Here, the process of calculating the heat generation of the first target area can refer to the specific description in the following step 405, which will not be repeated here.

[0023] In a possible implementation of the first aspect, determining the cooling capacity of the first target area based on the first device parameter value includes: determining the cooling capacity corresponding to the first target area based on the spatial data of the first target area and the first device parameter value, wherein the spatial data includes at least one or more of the following: the ventilation volume of the first target area, the heat transfer coefficient of the enclosure structure of the first target area, and the spatial size of the first target area; wherein the first device parameter value is a default parameter value preset for the second type of electronic equipment.

[0024] Here, the first device parameter value may be the default device parameter value in step 400 below. The specific method for generating the first device parameter value can be found in the detailed description of step 400 and is not further described here. The method for determining the cooling capacity corresponding to the first target area based on the spatial data of the first target area and the first device parameter value can be found in the detailed description of step 406 below and is not further described here.

[0025] In a possible implementation of the first aspect, adjusting the first device parameter value to the second device parameter value based on heat production and heat dissipation includes: determining a first indicator value based on heat production, heat dissipation, and the first device parameter value; using the first device parameter value as the second device parameter value corresponding to the first target area when the first indicator value satisfies the target indicator corresponding to the first target area; adjusting the first device parameter value to the second device parameter value when the first indicator value does not satisfy the target indicator corresponding to the first target area, wherein the second indicator value determined based on heat production, heat dissipation, and the second device parameter value satisfies the target indicator.

[0026] In a possible implementation of the first aspect, the target indicators include: at least any one or more of an energy consumption indicator, a comfort indicator, and an energy cost indicator; wherein the first indicator value determined based on the heat production, heat dissipation, and the first device parameter value includes: determining the first energy consumption value based on the second device parameter value and the power consumption parameter value of the second type of equipment; determining the first energy cost value based on the second device parameter value, the power consumption parameter value of the second type of equipment, and the energy price value; determining the first comfort value based on the first temperature value and a preset comfort indicator, wherein the first temperature value is determined based on spatial data, heat production, and heat dissipation; and determining the first indicator value based on the first energy consumption value, the first comfort value, and the first energy cost value.

[0027] Here, the energy consumption index may be the default energy consumption value described below, and correspondingly, the first energy consumption value may be the energy consumption value described below in step 402. The comfort index may be the comfort index described below in step 408, and correspondingly, the first comfort value may be the comfort parameter described below in step 407, and the first temperature value may be the temperature of the target area described below in step 407. The energy cost index may be the preset energy cost threshold described below in step 408.

[0028] Here, the first device parameter value is a default device parameter value. Furthermore, a second device parameter value can be generated based on the first device parameter value and the optimization algorithm. In this case, the second device parameter value can be the test device parameter value described below. The process of generating the second device parameter value based on the first device parameter value can be described in detail in step 401 below and is not further described here.

[0029] Furthermore, it is possible to first determine whether the first indicator value corresponding to the first device parameter value meets the target indicator. If so, the second electronic device can be controlled based on the first device parameter value. Conversely, if not, the second device parameter value is repeatedly generated based on the first device parameter value until the second device parameter value meets the target indicator. The process of repeatedly generating the second device parameter value is described in detail in steps 401 to 408 below and is not further elaborated here.

[0030] In a possible implementation of the first aspect, the method further includes: inputting the first target area into a preset first model; determining the spatial data of the first target area based on the output of the first model, wherein the training samples of the first model include: the construction data of the building corresponding to the first target area; wherein the construction data of the building includes: the construction data of one or more typical floors of the building; the typical floors include at least any one of the above-ground floor, the ground floor and the underground floor.

[0031] Here, the first model may be the building geometry model mentioned below. The process of establishing the building geometry model based on the building construction data may be referred to the detailed description in step 201 below, which will not be described in detail here.

[0032] In a possible implementation of the first aspect, after controlling the second type of equipment based on the second device parameter value, it also includes: obtaining the energy consumption value corresponding to the second type of equipment; when the energy consumption value is outside the first indicator value range corresponding to the energy consumption indicator, determining the fourth device parameter value through an optimization algorithm based on the second device parameter value.

[0033] Here, the second device parameter value may be the device parameter value of the first category of electrical users or the device parameter value of the second category of electrical users in step 504 below. The energy consumption value corresponding to the second electronic device may be the actual energy consumption value of the first category of electrical users or the second category of electrical users in step 503 below, as well as the first simulated energy consumption value of the first category of electrical users or the second simulated energy consumption value of the second category of electrical users in step 504 below.

[0034] The energy consumption value outside the first indicator value interval corresponding to the energy consumption index may be that the difference between the actual energy consumption value of the first type of electrical equipment or the second type of electrical equipment and the first simulated energy consumption value or the second simulated energy consumption value is greater than a preset threshold. The fourth device parameter value may be the first optimized parameter value or the second optimized parameter value in step 505 below. Here, the specific process of generating the fourth device parameter value can be referred to the specific description in steps 500 to 508 below, and will not be repeated again. It can be understood that based on this method, optimization can be performed based on the actual application effect of the adjusted second device parameter value.

[0035] In a possible implementation of the first aspect, the method further includes: inputting the first target area and time into a preset second model; determining the number of people in the first target area based on the output of the second model; wherein the number of people includes a first parameter value; wherein the training sample of the second model includes: the parameter value of the first parameter at each time in each area of ​​the building corresponding to the first target area.

[0036] Here, the second model can be the pedestrian flow model described below. The moments include a first moment, a second moment, and a third moment. The parameter value of the first parameter is the pedestrian flow data for each area of ​​the building at each moment. The details of the second model can be found in the detailed description of step 200 below and are not detailed here.

[0037] In a second aspect, the present application provides an electronic device comprising: one or more processors; one or more memories; and one or more programs stored in the one or more memories. When the one or more programs are executed by the one or more processors, the electronic device performs the device control method provided in the first aspect and various possible implementations of the first aspect. The electronic device may include a first electronic device.

[0038] In a third aspect, the present application provides a computer-readable medium having instructions stored thereon. When the instructions are executed on a computer, the computer executes the device control method provided by the first aspect and various possible implementations of the first aspect.

[0039] In a fourth aspect, the present application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the device control method provided by the above-mentioned first aspect and various possible implementations of the above-mentioned first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 The figure shows a scenario diagram of an air conditioner provided by the present application performing winter heating based on a preset control scheme;

[0041] Figure 2 FIG2 is a flow chart of adjusting device parameters of an electrical device according to an embodiment of the present application;

[0042] Figure 3 Shown is a schematic diagram of the structure of a building provided in an embodiment of the present application;

[0043] Figure 4 The figure shows a flow chart of adjusting the device parameter value of the second type of electrical equipment provided by an embodiment of the present application;

[0044] Figure 5 The figure shows a schematic diagram of an optimization process of a device parameter value provided by an embodiment of the present application;

[0045] Figure 6 Shown is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0047] Figure 1 A schematic diagram of a scenario in which an air conditioner performs winter heating based on a preset control scheme is shown.

[0048] In some embodiments, see Figure 1, the building's control device 100 establishes a communication connection with the electrical equipment in the building, and the control device 100 includes the aforementioned preset control scheme, which can control the electrical equipment based on the preset control scheme. However, the control device 100 can only control the electrical equipment based on a single or fixed preset control scheme and cannot be adaptively adjusted according to the needs of the actual scenario. For example, the control device 100 can control the air conditioner 101 to heat the office area 102 according to the preset temperature in winter based on the preset control scheme. However, due to the large flow of people in the office area 102, the high heat generated by the flow of people may result in the temperature of the office area 102 being stabilized within a more suitable range without the need for air conditioning. Obviously, in this scenario, if the air conditioner 101 still heats according to the preset temperature, the temperature of the office area 102 will be too high, and the comfort level will be greatly reduced. At the same time, it will cause a large waste of electricity.

[0049] Therefore, to solve the above-mentioned problems, the present application provides an electrical equipment control method, which is applied to an electronic device. The electronic device determines at least one electrical device included in a target area of ​​a building, and adjusts the device parameters of the electrical devices included in the target area based on pedestrian flow data in the target area and / or weather data of the external environment, so that the current environment of the target area can meet the comfort requirements based on the adjusted electrical devices.

[0050] It is understood that the electronic devices in the embodiments of the present application may include, but are not limited to, mobile phones, tablet computers, desktop computers, laptop computers, handheld computers, netbooks, terminal devices, servers, and other electronic devices capable of controlling electrical devices within a building. For example, the electronic devices may be control devices for smart buildings.

[0051] The following describes the embodiments of the present application by taking an electronic device as an example of a control device for controlling various electrical devices in a building.

[0052] In some embodiments, the target area may include a portion of a building. For example, in an office building, the target area may include meeting rooms, office areas, lobbies, elevators, stairwells, and other areas. Alternatively, the building may be a hotel, shopping mall, hospital, or any other type of building where electrical equipment can be centrally controlled. This application does not limit the specific types of buildings or the specific types of target areas within them.

[0053] Below, the application scenarios and application effects of the control method provided in this application will be illustrated with examples in combination with different types of electrical equipment.

[0054] This example illustrates an office deployment scenario, assuming that electrical equipment such as air conditioners are temperature control devices, and the target area for air conditioner deployment is an office. In winter, the air conditioner may heat the target area at a higher temperature. However, when the flow of people in the target area remains high, the heat generated by the flow of people may cause the temperature in the target area to rise. In this scenario, when increased flow of people in the target area is detected, the air conditioning parameters of the air conditioner in the target area can be adjusted, causing the air conditioner to lower the heating temperature or stop heating, so that the current environment in the target area continues to meet the comfort requirements based on the adjusted air conditioning parameters.

[0055] For example, in winter, if a target area is currently unoccupied, it may be predicted that traffic will increase in the target area over time. For example, if a conference room is currently unoccupied, and based on a traffic forecast, it is determined that traffic will increase to 20 people in half an hour, the air conditioning parameters in the conference room can be adjusted to preheat the target area at a higher temperature. This will ensure that the conference room meets the required comfort level half an hour later based on the adjusted air conditioning parameters, improving the user experience.

[0056] Taking lighting as an example, the control method provided by this application can achieve pre-emptive lighting of target areas. For example, if the target area is an office, and it is predicted that someone will enter the office in five minutes, the lighting parameters in the office can be adjusted at that moment to turn on the lighting. This ensures that the office is already illuminated when the employee enters, improving the user experience.

[0057] Taking the example of an elevator as an electrical equipment, the control method provided by this application can realize the advance dispatch of elevators to the target area. Take the first floor lobby as an example. If the elevators parked on other floors are idle at the current moment, and it is predicted that the flow of people in the lobby on the first floor will increase significantly in ten minutes, the elevator parameters can be adjusted at the current moment to dispatch the elevator to the first floor. This can realize the pre-dispatch of the elevator, reduce the waiting time for users in the lobby on the first floor, and improve the user experience.

[0058] Below, the specific process of adjusting the equipment parameters of the electrical equipment based on the control method provided in this application will be described in detail with reference to the accompanying drawings.

[0059] Figure 2 A schematic diagram of a process for adjusting device parameters of an electrical device is shown.

[0060] Understandably, implementation Figure 2The electronic device of each step of the process shown can be the aforementioned control device. For the sake of convenience of description, the control device is used as the execution subject when introducing each step below, and the execution subject will not be described in detail below.

[0061] Specifically, the implementation process of the control method provided in the embodiment of the present application may include the following steps:

[0062] 200: Obtain building structural data, electrical equipment data in the building, climate data, and pedestrian flow data.

[0063] For example, the building's structural data can be obtained based on the building's design drawings or design models. The structural data may include structural data for each floor of the building, such as design data and building envelope data for each floor's rooms and / or areas. The design data includes spatial data and location data, and the exterior wall envelope data includes heat transfer coefficient data for the exterior and interior wall envelopes.

[0064] The aforementioned electrical equipment data includes location data, energy consumption parameter data, equipment parameter data, etc. of the electrical equipment in the building.

[0065] Here, the location data of the electric device may be used to indicate the specific location of the electric device in the building.

[0066] Energy consumption parameter data for electrical equipment can be power parameters. For example, for air conditioners, this data may include cooling input power, cooling output power, heating input power, and heating output power. For lighting equipment, this data may include power parameters for different lighting brightness levels. For elevators, this data may include power parameters for different operating states.

[0067] The device parameter data of the electric device may be parameter data required during the operation of the electric device.

[0068] Taking the cooling scenario of a central air conditioner as an example, a central air conditioner might include a fan coil unit (FCU) that uses fans and chilled water to circulate indoor air and adjust temperature and humidity; a fresh air system that draws in outdoor air; a chiller that uses a compressor refrigeration cycle to cool the chilled water; and a cooling tower that uses fans to dissipate heat from the cooling water. Correspondingly, the central air conditioner's equipment parameter data might include parameters such as the FCU's fan speed and flow rate; the fresh air system's fan speed and flow rate; the cooling tower's fan speed and fan baffle position; and the chiller's chilled water temperature and flow rate.

[0069] Taking lighting equipment as an example, the equipment parameters of the lighting equipment may be switch parameters for controlling the switch state, gear parameters for controlling the lighting brightness, and the like.

[0070] Taking an elevator as an example, the equipment parameters of an elevator may be switch parameters for controlling the switch state, speed parameters for controlling the running speed, and elevator dispatch parameters for controlling the floors to which the elevator is dispatched.

[0071] Here, the climate data may be acquired historical weather data, including temperature, humidity, light intensity, wind speed, etc.

[0072] Here, the pedestrian flow data can be obtained based on a preset pedestrian flow model. Specifically, the pedestrian flow model is constructed based on the structural data of the building and the historical pedestrian flow in each area of ​​the building at different times. When the target area and target time are input into the pedestrian flow model, the pedestrian flow data of the target area at the target time can be predicted. For example, the pedestrian flow in the cafeteria during meal times can be predicted based on the pedestrian flow model. The pedestrian flow data can also be obtained based on sensors in the building for real-time detection of pedestrian flow, such as infrared sensors. Here, this application does not provide a restrictive description of the specific method of obtaining pedestrian flow data.

[0073] It can be understood that the aforementioned acquired data is merely an example, and this application does not provide any restrictive description of the specific data content required to adjust the equipment parameters of the electrical equipment.

[0074] 201: Establishing a building geometry model based on the building's structural data.

[0075] For example, the control device may establish an architectural geometric model of the building based on the construction data of the building.

[0076] It is understood that the structures of floors of the same type in a building are usually the same. Therefore, for floors of the same type, only one of them can be modeled. Specifically, floors can be divided into three typical types: underground floors, ground floors, and above-ground floors based on their external environments.

[0077] It's understood that a building can be constructed based on one or more typical floors. Therefore, after modeling the basement, ground floor, and above-ground floor to obtain three typical floor models, the geometric model of the entire building can be derived by reusing one or more of these typical floor models. This approach effectively reduces the time and resource costs associated with modeling each floor of a building.

[0078] For example, Figure 3 A schematic diagram of the structure of a building is shown.

[0079] See also Figure 3Building 30 may include three typical floors: the ground floor 300 (also known as "floor 2"), the ground floor 301 (also known as "floor 1"), and the basement 302 (also known as "basement -1"). Furthermore, each typical floor can be modeled based on the structural data of building 30 to obtain a building geometry model of building 30. The building geometry model of building 30 can be derived by combining the ground floor model, the ground floor model, and the basement model. Based on the building geometry model of building 30, structural data such as the location, spatial dimensions, and heat transfer coefficient of the building envelope can be determined for any room or area in building 30.

[0080] For example, based on the architectural geometric model of the building 30 , structural data such as the location, space size, and heat transfer coefficient of the enclosure structure of rooms or areas such as the conference room 304 , office 305 , or hall 306 on the ground floor 300 can be known.

[0081] It is understood that the building geometric model can also be determined in combination with the location data of the electrical equipment. Furthermore, all the electrical equipment included in any room or area can also be determined based on the building geometric model.

[0082] 202: Determine equipment parameter values ​​of the first type of electrical equipment in the target area based on the building geometry model and the pedestrian flow data.

[0083] For example, the first category of electrical equipment may include lighting equipment, elevators, and other electrical equipment whose operation can be determined based on pedestrian flow data. For example, if the lighting equipment is a light in a safety passage, the light can be turned on when the pedestrian flow in the safety passage is not zero; conversely, the light can be turned off when the pedestrian flow in the safety passage is zero.

[0084] Here, based on the aforementioned step 200, it can be seen that pedestrian flow data can be obtained based on sensors in the building for real-time pedestrian flow detection. Based on the aforementioned step 201, it can be seen that all electrical devices included in the target area can be determined based on the aforementioned building geometric model, including the aforementioned first category of electrical devices.

[0085] Furthermore, based on the acquired pedestrian flow data in the target area, the device parameter values ​​of the first type of electrical equipment at the target time can be determined.

[0086] Specifically, taking lighting as an example, if the pedestrian flow data within the target area is non-zero at the target time, the lighting device's on / off parameters can be adjusted to the values ​​corresponding to the on state. Conversely, if the pedestrian flow data within the target area is zero at the target time, the lighting device's on / off parameters can be adjusted to the values ​​corresponding to the off state. This approach effectively reduces lighting device energy consumption.

[0087] Furthermore, if the traffic flow data in the target area is zero at the target time, and the traffic flow model predicts that the traffic flow data in the target area will not be zero after a preset time interval, the lighting device's on / off parameters can be adjusted to the parameter value corresponding to the on state at the target time. For example, if the traffic flow model predicts that someone will enter the hall in ten minutes, the on / off parameters of the hall lights can be adjusted to the parameter value corresponding to the on state at the current time. This method can preemptively turn on the lights before someone enters the hall, improving the user experience.

[0088] For example, if the first type of electrical equipment is an escalator, if the flow of people in the target area is zero at the target time and for a period of time thereafter, the escalator's on / off parameters can be adjusted to the parameter value corresponding to the stopped state, or the escalator's speed parameters can be adjusted to a lower setting. Conversely, if the flow of people in the target area is not zero at the target time, the escalator's on / off parameters can be adjusted from the stopped state to the parameter value corresponding to the running state, or the escalator's speed parameters can be adjusted from a lower setting to a higher setting. This approach effectively reduces the escalator's energy consumption.

[0089] For example, if elevators are the first type of electrical equipment, and traffic in a target area increases rapidly within a period of time after a target time, the dispatch parameters of idle elevators can be adjusted to the floors of the target area at the target time. This approach allows for optimal elevator allocation, reduces wait times, and improves the user experience.

[0090] It is understood that the specific details of the aforementioned first-category electrical equipment are merely examples, and this application does not limit the specific types of first-category electrical equipment. Furthermore, the aforementioned method for adjusting the device parameters of first-category electrical equipment is merely an example. It is understood that any parameter adjustment method that can adjust the device parameters of first-category electrical equipment based on foot traffic data to reduce power consumption and / or improve the user experience is within the scope of protection of this application.

[0091] 203: Control the first type of electrical equipment in the target area based on the equipment parameter values ​​of the first type of electrical equipment.

[0092] Exemplarily, the control device may adjust the device parameter value of the first type of electrical equipment to the device parameter value to achieve the application effect shown in the aforementioned step 202 .

[0093] 204: Determine device parameter values ​​of the second type of electrical equipment in the target area based on the building geometry model, electrical equipment data in the building, climate data, and pedestrian flow data.

[0094] For example, the following will be combined with Figure 4The process of the control device adjusting the device parameters of the second type of electrical equipment is specifically described and will not be repeated here. Here, the second type of electrical equipment may be an electrical equipment capable of adjusting the temperature of the target area.

[0095] 205: Control the second type of electrical equipment in the target area based on the equipment parameter values ​​of the second type of electrical equipment.

[0096] For example, the control device may adjust the device parameter value of the central air conditioner to the first device parameter value, so that the central air conditioner can operate based on the first device parameter value to meet energy consumption requirements, comfort indicators and cost control requirements.

[0097] It can be understood that based on the above content, multi-objective optimization of electrical equipment can be achieved, so that the operation of electrical equipment can simultaneously meet energy consumption requirements, comfort indicators and cost control requirements, thereby achieving energy conservation and emission reduction, saving operating costs, and ensuring multiple comfort needs.

[0098] Furthermore, the control device can integrate the device parameter adjustment process shown in steps 200 to 205 into a building energy model for the building. The control device can then periodically invoke this building energy model to adaptively adjust the parameters of electrical equipment within the building based on the flow of people and / or climate conditions during different cycles. For example, during a period of time in winter, heating by air conditioning may not be necessary due to relatively comfortable outside temperatures. The control device's periodic adjustment strategy can then adapt to the current scenario, adjusting the air conditioning control parameters based on the aforementioned building energy model so that the adjusted air conditioning stops heating or starts cooling.

[0099] Exemplarily, the period may be daily, weekly, monthly, etc., and this application does not provide any restrictive description on the specific adjustment period.

[0100] Figure 4 A schematic diagram of a process for adjusting the device parameter value of the second type of electrical equipment is shown below. Figure 4 The process of determining the device parameter values ​​of the second type of electrical equipment in the target area in the aforementioned step 204 is described in detail.

[0101] Understandably, implementation Figure 4 The electronic device of each step of the process shown can be the aforementioned control device. For the sake of convenience of description, the control device is used as the execution subject when introducing each step below, and the execution subject will not be described in detail below.

[0102] The following describes in detail the process by which a control device determines device parameter values ​​for a second-category electrical device, using a central air conditioner as an example. It is understood that the second-category electrical device may also include other types of air conditioners, such as split-type air conditioners, or other temperature control devices, such as floor heating systems. This application does not restrict the specific types of the second-category electrical device.

[0103] Specifically, the implementation process of controlling the device to adjust the device parameter value of the second type of electrical equipment may include the following steps:

[0104] 400: Get the default device parameter values ​​of the second type of electrical equipment.

[0105] For example, the central air conditioner may have a default device parameter value. Before the control device adjusts the device parameter of the central air conditioner, the second type of electrical equipment may perform a temperature adjustment operation on the target area based on the default device parameter value.

[0106] Specifically, taking the cooling scenario of a central air conditioner as an example, the central air conditioner's equipment parameters may include the fan speed and flow parameters of the FCU, the fan speed and flow parameters of the fresh air system, the fan speed and baffle position parameters of the cooling tower, and the chilled water temperature and flow parameters of the chiller. Each of the aforementioned equipment parameters may have a corresponding default equipment parameter value.

[0107] 401: Generate test device parameter values ​​based on default device parameter values.

[0108] Here, the second type of electrical equipment may have a default device parameter value. The default device parameter value may be a factory setting value of the second type of electrical equipment, or a parameter value determined based on the aforementioned preset control scheme. Figure 1 As can be seen from the description, the default device parameter values ​​may not be suitable for specific application scenarios. Therefore, the control device can generate a set of test device parameter values ​​based on the default device parameter values ​​through a preset optimization algorithm or random method. And based on the following steps 402 to 408, it is judged whether the test device parameter values ​​can meet specific application requirements, such as energy consumption requirements, comfort requirements, cost control requirements, etc. If not, this step 401 can be repeated to update and optimize the test device parameter values ​​until the test device parameter values ​​that meet the application requirements are determined. And based on the following step 409, the test device parameter values ​​that meet the application requirements are applied.

[0109] Taking the second category of electrical equipment, such as a central air conditioner, as an example, the control device can generate test device parameter values ​​based on the default device parameter values ​​of the central air conditioner using a preset optimization algorithm or a random method. The optimization algorithm may be a genetic algorithm, a simulated annealing algorithm, an ant colony algorithm, a differential algorithm, or the like. The specific method for generating test device parameter values ​​based on the default device parameter values ​​is not limited herein.

[0110] Specifically, the control device can generate test equipment parameter values ​​for multiple equipment parameters, such as the fan speed parameters and flow parameters of the FCU, the fan speed parameters and flow parameters of the fresh air system, the fan speed parameters and fan baffle position parameters of the cooling tower, and the cooling water temperature parameters and flow parameters of the chiller.

[0111] 402: Determine the energy consumption value of the second type of electrical equipment in the target area based on the test equipment parameter value and the electrical equipment data.

[0112] For example, after the control device generates the test device parameter values ​​of each device parameter of the central air conditioner, the energy consumption value of the central air conditioner can be calculated based on the test device parameter values ​​of each device parameter, the energy consumption parameter data of the central air conditioner (as an example of electrical equipment data) and the operating time.

[0113] 403: Determine whether the energy consumption value meets the preset energy consumption requirement.

[0114] For example, if the energy consumption value meets the preset energy consumption requirement, the following step 404 is executed; otherwise,

[0115] If the energy consumption value does not meet the preset energy consumption requirement, the above step 401 is repeated.

[0116] Specifically, the control device may precalculate a default energy consumption value for the central air conditioner in a default operating state. Here, the default energy consumption value may be the energy consumption value when the central air conditioner is operated based on the default device parameter values ​​for each device parameter. Specifically, the energy consumption value for the central air conditioner may be calculated based on the default device parameter values ​​for each device parameter, energy consumption parameter data for the central air conditioner, and operating time.

[0117] Furthermore, the control device may determine whether the energy consumption value corresponding to the parameter value of the test device is less than the default energy consumption value.

[0118] If the energy consumption value corresponding to the test equipment parameter value is less than the default energy consumption value, it means that the energy consumption value meets the preset energy consumption requirement. Then, based on the following steps 404 to 408, it can be further determined whether the central air conditioner control based on the test equipment parameter value can meet the comfort requirement.

[0119] If the energy consumption value corresponding to the test equipment parameter value is greater than or equal to the default energy consumption value, it means that the energy consumption value cannot meet the preset energy consumption requirement. The above step 401 can be repeated to update the test equipment parameter value, and the process is repeated until the updated test equipment parameter value can meet the preset energy consumption requirement.

[0120] It can be understood that based on this method, it can be ensured that the adjusted equipment parameters of the central air conditioner can bring lower power consumption, so as to achieve the purpose of energy conservation and emission reduction.

[0121] 404: Determine the spatial size of the target area based on the building geometric model.

[0122] For example, if it is determined based on the aforementioned step 403 that the energy consumption value corresponding to the parameter value of the test equipment meets the preset energy consumption requirement, the controllable device can determine the spatial size of the target area based on the building geometric model to execute the following step 405 based on the spatial size.

[0123] Here, the specific content of determining the spatial size of the target area based on the building geometric model can be found in the relevant description in the aforementioned step 201, which will not be repeated here.

[0124] 405: Determine the heat generation in the target area based on the space size, electrical equipment data, climate data, and pedestrian flow data of the target area.

[0125] For example, the heat generation sources in the target area may mainly be human traffic, climate, and electrical equipment.

[0126] Specifically, based on the target area's spatial size, pedestrian flow data, and the human body's unit heat production index, a thermodynamic formula can be used to calculate the heat production caused by pedestrian flow within the target area. This pedestrian flow data can be derived from the aforementioned pedestrian flow model. Because this pedestrian flow model outputs time-varying predicted data rather than fixed values, the heat production calculated based on this pedestrian flow data is more consistent with the heat production caused by pedestrian flow in actual scenarios.

[0127] Based on the spatial size of the target area and climate data, the heat generated by light in the target area can be calculated using thermodynamic formulas. Here, climate data may include light intensity, temperature, wind speed, etc. This application does not provide a restrictive description of climate data.

[0128] Based on the target area's spatial size, test equipment parameters, and electrical equipment data, thermodynamic formulas can be used to calculate the heat generated by the operating electrical equipment within the target area. This electrical equipment data includes, for example, power parameters, and this application does not restrict this data.

[0129] Furthermore, by adding up the above three parts of heat production, the total heat production of the target area can be obtained.

[0130] It will be understood that the aforementioned method of calculating heat production based on human traffic, climate, and electronic equipment is merely an example. In other exemplary methods, the control device may also calculate heat production based on one or more of human traffic, climate, electronic equipment, and other heat-producing factors. It will be understood that the more heat-producing factors used to calculate heat production, the more accurate the calculated total heat production. For example, the heat transfer coefficient of the enclosure structure in the aforementioned structural data will affect the thermal insulation, moisture retention, heat insulation, and moisture-proof properties of the target area, and thus, will also affect the total heat production of the target area. Therefore, the aforementioned other heat-producing factors may also include the heat transfer coefficient of the enclosure structure.

[0131] 406: Calculate the cooling capacity or heating capacity of the second-category electrical equipment in the target area based on the space size of the target area, the parameter value of the test equipment, and the electrical equipment data of the second-category electrical equipment.

[0132] For example, based on the target area's spatial size, central air conditioner test equipment parameter values, and the central air conditioner's electrical equipment data, thermodynamic formulas can be used to calculate the central air conditioner's cooling capacity or heating capacity in the target area. Here, the electrical equipment data for the second category of electrical equipment may include unit cooling capacity parameters or unit heating capacity parameters. This application does not restrict the central air conditioner's electrical equipment data.

[0133] Furthermore, in step 404, the heat transfer coefficient of the target area's enclosure structure can be obtained based on the aforementioned building geometry model. Because the heat transfer coefficient of the enclosure structure can affect the target area's insulation, this heat transfer coefficient can be combined with thermodynamic formulas to calculate the target area's heat production and the central air conditioning's cooling or heating capacity, ensuring that the resulting heat production, cooling, or heating capacity more closely resembles actual conditions.

[0134] 407: Determine a comfort parameter of the target area based on the heat production in the target area and the cooling capacity or heating capacity of the second type of electrical equipment in the target area.

[0135] For example, after determining the heat production in the target area and the cooling or heating capacity of the central air conditioner in the target area, comfort parameters such as temperature and humidity in the target area can be determined based on heat transfer-related formulas. These heat transfer-related formulas include, but are not limited to, thermodynamic formulas, energy conservation formulas, and heat balance formulas.

[0136] 408: Determine whether the target area meets a preset comfort index based on the comfort parameter of the target area.

[0137] For example, if the target area meets the preset comfort index, the following step 409 is executed; otherwise,

[0138] If the target area does not meet the preset comfort index, the above step 401 is repeated.

[0139] Specifically, the control device may calculate the comfort level of the target area based on the target area's temperature, humidity, and other comfort parameters determined in step 407, using a preset comfort index calculation formula. If the difference between the comfort level and the preset comfort index is less than a preset threshold, the target area is determined to meet the preset comfort index, and step 409 is then executed.

[0140] Conversely, if the difference between the comfort level and the preset comfort index is greater than or equal to a preset threshold, it can be determined that the target area does not meet the preset comfort index. Therefore, the above step 401 can be repeated to update the test device parameter value. This process is repeated until the updated test device parameter value meets the preset comfort index.

[0141] It can be understood that based on this method, it can be ensured that the adjusted equipment parameters of the central air conditioner can achieve lower power consumption while ensuring the comfort of the target area.

[0142] In addition, it is understood that the control device can also calculate the energy cost that may be generated when the central air conditioner is operated based on the test device parameter value, and the energy cost that may be generated when the central air conditioner is operated based on the aforementioned default device parameter value (which may be referred to as "default energy cost") based on the energy consumption value determined in the aforementioned step 403. The control device can also determine whether the test device parameter value meets the cost control requirements based on the energy cost and the default energy cost.

[0143] Specifically, if the energy cost is less than the default energy cost, it is determined that the test equipment parameter value can meet the cost control requirements. Then, the following step 409 can be executed; otherwise,

[0144] If the energy cost is greater than or equal to the default energy cost, it is determined that the test equipment parameter value cannot meet the cost control requirements. Then, the above step 401 can be repeated to update the test equipment parameter value. This process is repeated until the updated test equipment parameter value can meet the cost control requirements.

[0145] It can be understood that based on this method, it can be ensured that the adjusted central air-conditioning equipment parameters can achieve lower power consumption and ensure the comfort of the target area while achieving the effect of cost control and reducing operating costs.

[0146] Furthermore, it is understood that each device parameter value of an electrical device has a corresponding adjustable range. Therefore, after determining that the test device parameter value for the second type of electrical device can simultaneously meet the energy consumption requirements, comfort indicators, and cost control requirements, it is again determined whether the test device parameter value is within the adjustable range of the corresponding device parameter. If it is not within the adjustable range, step 401 must be repeated to update the test device parameter value.

[0147] Furthermore, it is understood that for the device parameter values ​​of the first category of electrical equipment determined in step 202, the energy consumption value and / or energy cost during operation can also be calculated based on the operating time and power consumption parameter value (as an example of electrical equipment data), so as to determine whether to adopt the current device parameter value based on the preset energy consumption index and / or energy cost index. Similarly, the determination of whether to adopt the current device parameter value can be made based on the adjustable range of the device parameter of the first category of electrical equipment.

[0148] Here, the aforementioned energy consumption index may be a preset energy consumption value threshold, and the aforementioned energy cost index may be a preset energy cost threshold.

[0149] 409: Use the test device parameter value as the device parameter value of the second type of electrical equipment in the target area.

[0150] Based on the aforementioned steps, it can be determined that the test device parameter values ​​meet energy consumption requirements, comfort indicators, and cost control requirements. Therefore, the control device can adjust the device parameters of the second type of electrical equipment in the target area based on the test device parameter values. For example, the test device parameter values ​​can be used as the device parameter values ​​for a central air conditioner.

[0151] In addition, it can be understood that the controller can optimize the device parameter value according to the actual application effect of the adjusted device parameter value.

[0152] Specifically, Figure 5 A schematic diagram of an optimization process for equipment parameter values ​​is shown.

[0153] Understandably, implementation Figure 5 The electronic device of each step of the process shown can be the aforementioned control device. For the sake of convenience of description, the control device is used as the execution subject when introducing each step below, and the execution subject will not be described in detail below.

[0154] Specifically, the device parameter value optimization process provided in the embodiment of the present application may include the following steps:

[0155] 500: Obtain device parameter values ​​of the first category of electric devices and / or device parameter values ​​of the second category of electric devices.

[0156] For example, the device parameter values ​​of the first category of electrical devices acquired by the control device may be generated based on the aforementioned step 202, and the device parameter values ​​of the second category of electrical devices acquired may be generated based on the aforementioned step 409. The process of generating the device parameter values ​​of the first category of electrical devices and the device parameter values ​​of the second category of electrical devices will not be further described herein.

[0157] 501: Determine whether the building has the detection equipment required to implement the device parameter value.

[0158] If the judgment result is yes, it means that the building has the detection equipment required to implement the equipment parameter value, then the following step 503 is executed; otherwise,

[0159] If the determination result is no, it means that the building does not have the detection equipment required to implement the equipment parameter value, and then the following step 502 is executed.

[0160] If the control device determines that the building does not have the detection device required to implement the device parameter value, the detection device may be installed in the target area based on the following step 502.

[0161] On the contrary, if the control device determines that the building has the detection equipment required to implement the equipment parameter values, it can implement the equipment parameter values ​​of the first category of electrical equipment and the equipment parameter values ​​of the second category of electrical equipment based on the following step 503 and monitor their actual energy consumption.

[0162] For example, when the device parameter values ​​of the first type of electrical equipment and the device parameter values ​​of the second type of electrical equipment are actually applied, it may be necessary to have corresponding detection equipment in the building.

[0163] For example, as can be seen from step 202 above, the control device needs to adjust the device parameter values ​​of the first category of electrical devices based on infrared sensors used to detect real-time pedestrian flow in the building. Therefore, before adjusting the device parameter values ​​of the first category of electrical devices in step 203 above, it is possible to pre-determine whether infrared sensors used for real-time pedestrian flow detection are present in the target area of ​​the building. It should be understood that the infrared sensors used as detection devices are merely examples, and this application does not limit the specific type of detection device.

[0164] 502: Install additional testing equipment.

[0165] For example, if the control device determines, based on step 501, that the building does not have the detection equipment required to implement the device parameter values, it may install the detection equipment in the target area to proceed to step 503. For example, the control device may notify relevant building personnel to install the aforementioned infrared sensor for real-time pedestrian flow detection.

[0166] 503: Monitoring actual energy consumption values ​​based on the optimization module.

[0167] For example, after the control device applies the device parameter values ​​for the first category of electrical users in step 203 and the device parameter values ​​for the second category of electrical users in step 205, the actual energy consumption values ​​of the first category of electrical users and the second category of electrical users within a preset time range can be directly read from the monitoring elements of the first category of electrical users and the second category of electrical users. The monitoring elements may be, for example, electric meters for the first category of electrical users and the second category of electrical users.

[0168] It can be understood that, here, the optimization module can be a software module in the control device, or a software module in other electronic devices that have established a communication connection with the control device.

[0169] 504: Determine whether the device parameter value meets the energy consumption requirement based on the actual energy consumption value and the simulated energy consumption value.

[0170] If the judgment result is yes, it means that the device parameter value meets the energy consumption requirement, then the following step 508 is executed; otherwise,

[0171] If the judgment result is no, it means that the device parameter value does not meet the energy consumption requirement, and then the following step 505 is executed.

[0172] Exemplarily, the simulated energy consumption value may include a first simulated energy consumption value for a first category of electrical equipment and a second simulated energy consumption value for a second category of electrical equipment. The first simulated energy consumption value may be the energy consumption value of the first category of electrical equipment within a preset time range, calculated based on device parameter values ​​and power parameters of the first category of electrical equipment. The second simulated energy consumption value may be the energy consumption value of the second category of electrical equipment within a preset time range, calculated based on device parameter values ​​and power parameters of the second category of electrical equipment.

[0173] Furthermore, the aforementioned optimization module may determine whether the difference between the actual energy consumption value and the simulated energy consumption value is less than a preset threshold.

[0174] Specifically, the optimization module can determine whether the difference between the actual energy consumption value of the first type of electrical equipment and the first simulated energy consumption value is less than a preset threshold, and whether the difference between the actual energy consumption value of the second type of electrical equipment and the second simulated energy consumption value is less than a preset threshold.

[0175] If the difference between the actual energy consumption value and the simulated energy consumption value is greater than or equal to the preset threshold, it means that the device parameter value has a large deviation in actual application, resulting in a large difference between the actual energy consumption and the energy consumption in simulation.

[0176] Therefore, the optimization module may execute the following step 505 to optimize the device parameter values ​​of the first type of electrical equipment and / or the device parameter values ​​of the second type of electrical equipment during actual application.

[0177] If the difference between the actual energy consumption value and the simulated energy consumption value is smaller than the preset threshold, it means that the difference between the actual energy consumption of the device parameter value in actual application and the energy consumption in simulation is relatively small.

[0178] Therefore, the optimization module may execute step 508 described below to implement the first optimization parameter value and / or the second optimization parameter value.

[0179] 505: Generate a first optimized parameter value based on the device parameter value of the first type of electrical equipment, and / or generate a second optimized parameter value based on the device parameter value of the second type of electrical equipment.

[0180] For example, for the first type of electrical equipment, taking the first type of electrical equipment as a lighting device, if the device parameter value is the parameter value of the switch parameter corresponding to the aforementioned open state, the lighting brightness parameter value representing lower lighting brightness can be used as the first optimized parameter value.

[0181] Taking the first type of electrical equipment as an escalator as an example, if the equipment parameter value is the parameter value of the switch parameter corresponding to the aforementioned operating state, the speed parameter value indicating a slower operating speed can be used as the first optimized parameter value.

[0182] Here, no restrictive description is given to the first optimized parameter value of the first category of electrical equipment, and any device parameter value that can reduce the power consumption of the first category of electrical equipment can be used as the first optimized parameter value of the device.

[0183] The process of the optimization module generating the second optimized parameter value based on the device parameter value of the second type of electrical equipment is substantially the same as the process of the control device generating the first device parameter value based on the default device parameter value in the aforementioned step 401, and is not repeated here.

[0184] 506: Monitor the actual energy consumption value after applying the first optimized parameter value and / or the second optimized parameter value.

[0185] For example, the optimization module may send the first optimization parameter value and / or the second optimization parameter value to the control device, causing the control device to apply the first optimization parameter value and / or the second optimization parameter value. Furthermore, the optimization module may monitor the actual energy consumption value after applying the first optimization parameter value and / or the second optimization parameter value. The process of monitoring the actual energy consumption value is substantially the same as that described in step 503 above and is not further described here.

[0186] 507: Determine whether the device parameter value meets the energy consumption requirement based on the actual energy consumption value and the simulated energy consumption value.

[0187] If the judgment result is yes, it means that the device parameter value meets the energy consumption requirement, then the following step 508 is executed; otherwise,

[0188] If the judgment result is no, it means that the device parameter value does not meet the energy consumption requirement, and then the above-mentioned step 505 is executed.

[0189] Exemplarily, the optimization module may determine whether a difference between an actual energy consumption value after applying the first optimization parameter value and / or the second optimization parameter value and the aforementioned simulated energy consumption value is less than a preset threshold.

[0190] If the judgment result is no, it means that the difference between the actual energy consumption value after applying the first optimization parameter value and / or the second optimization parameter value and the aforementioned simulated energy consumption value is greater than or equal to the preset threshold.

[0191] This indicates that the energy consumption after applying the first and / or second optimized parameter values ​​is high and does not meet the energy consumption requirements. Therefore, step 505 may be repeated to update the first and / or second optimized parameter values ​​until the difference between the actual energy consumption after applying the first and / or second optimized parameter values ​​and the simulated energy consumption value is less than a preset threshold.

[0192] If the judgment result is yes, it means that the difference between the actual energy consumption value after applying the first optimization parameter value and / or the second optimization parameter value and the aforementioned simulated energy consumption value is less than the preset threshold.

[0193] This indicates that the energy consumption after applying the first optimized parameter value and / or the second optimized parameter value meets the energy consumption requirement. Therefore, the following step 508 may be executed.

[0194] 508: Adjust the first category of electrical devices and / or the second category of electrical devices based on the first optimization parameter value and / or the second optimization parameter value.

[0195] For example, when the control device determines based on the aforementioned step 507 that the energy consumption after applying the first optimization parameter value and / or the second optimization parameter value meets the energy consumption requirements, the first optimization parameter value can be stably applied to the first type of electrical equipment, and / or the second optimization parameter value can be applied to the second type of electrical equipment without updating the first optimization parameter value and / or the second optimization parameter value.

[0196] under, Figure 6 FIG2 shows a schematic structural diagram of an electronic device 100. The electronic device 100 may include the aforementioned control device.

[0197] The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0198] It should be understood that the structure illustrated in the embodiments of the present invention does not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown, or may combine or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0199] The processor 110 may include one or more processing units. For example, the processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU). The different processing units may be independent devices or integrated into one or more processors.

[0200] The controller can generate operation control signals according to the instruction operation code and timing signal to complete the control of instruction fetching and execution.

[0201] Processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in processor 110 is a cache memory. This memory can store instructions or data that have just been used or are being recycled by processor 110. If processor 110 needs to use the same instruction or data again, it can directly access the memory. This avoids duplicate accesses, reduces processor 110 latency, and thus improves system efficiency.

[0202] The wireless communication function of the electronic device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

[0203] Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In other embodiments, the antennas can be used in conjunction with a tuning switch.

[0204] The mobile communication module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G applied to the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the same device as at least some of the modules of the processor 110.

[0205] The wireless communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), etc., which are applied to the electronic device 100. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110. The wireless communication module 160 can also receive the signal to be sent from the processor 110, frequency modulate it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2.

[0206] Electronic device 100 implements display functionality through a GPU, display screen 194, and an application processor. A GPU is a microprocessor for image processing that connects display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs that execute program instructions to generate or modify display information.

[0207] The embodiments of the present application also provide a computer program product for implementing the control methods provided in the above embodiments.

[0208] The various embodiments of the mechanisms disclosed in this application can be implemented in hardware, software, firmware, or a combination of these implementation methods. The embodiments of the present application can be implemented as computer program modules or module codes executed on a programmable system, which includes at least one processor, a storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device.

[0209] A computer program module or module code can be applied to input instructions to perform the functions described herein and generate output information. The output information can be applied to one or more output devices in a known manner. For the purposes of this application, a processing system includes any system having a processor such as, for example, a digital signal processor (DSP), a microcontroller, an application specific integrated circuit (ASIC), or a microprocessor.

[0210] Module code can be implemented with high-level modular language or object-oriented programming language to communicate with the processing system. When necessary, module code can also be implemented with assembly language or machine language. In fact, the mechanism described in this application is not limited to the scope of any specific programming language. In either case, the language can be a compiled language or an interpreted language.

[0211] In some cases, the disclosed embodiments can be implemented in hardware, firmware, software or any combination thereof. The disclosed embodiments can also be implemented as instructions carried or stored on one or more temporary or non-temporary machine-readable (e.g., computer-readable) storage media, which can be read and executed by one or more processors. For example, instructions can be distributed over a network or through other computer-readable media. Therefore, machine-readable media may include any mechanism for storing or transmitting information in a machine (e.g., computer) readable form, including but not limited to, floppy disks, optical disks, optical disks, magneto-optical disks, read-only memories (ROM), random access memories (RAM), erasable programmable read-only memories (EPROM), electrically erasable programmable read-only memories (EEPROM), magnetic or optical cards, flash memory, or tangible machine-readable memories for transmitting information (e.g., carrier waves, infrared signals, digital signals, etc.) using the Internet in electrical, optical, acoustic or other forms of propagation signals. Accordingly, machine-readable media includes any type of machine-readable media suitable for storing or transmitting electronic instructions or information in a form readable by a machine (eg, a computer).

[0212] References in the specification to "one embodiment" or "an embodiment" mean that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one exemplary implementation or technique disclosed according to the embodiment of the present application. The appearances of the phrase "in one embodiment" in various places in the specification do not necessarily all refer to the same embodiment.

[0213] The disclosure of the embodiments of the present application also relates to an operating device for executing the text. The device can be constructed specifically for the required purpose or it can include a general-purpose computer that is selectively activated or reconfigured by a computer program stored in the computer. Such a computer program can be stored in a computer-readable medium, such as, but not limited to, any type of disk, including a floppy disk, an optical disk, a CD-ROM, a magneto-optical disk, a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic or optical card, an application-specific integrated circuit (ASIC) or any type of medium suitable for storing electronic instructions, and each can be coupled to a computer system bus. In addition, the computer mentioned in the specification can include a single processor or can be an architecture involving multiple processors for increased computing power.

[0214] In addition, the language used in this specification has been primarily selected for readability and instructional purposes and may not be selected to describe or limit the disclosed subject matter. Therefore, the present disclosure of embodiments is intended to illustrate, not to limit, the scope of the concepts discussed herein.

Claims

1. A device control method, applied to a first electronic device, characterized in that: The method comprises: determining at least one second electronic device within the first target area, and a first device parameter value corresponding to the second electronic device; Acquiring environmental parameters of the first target area; detecting that a first parameter of the environmental parameters changes to a first parameter value, wherein the first parameter is used to represent the number of people in the first target area; adjusting the first device parameter value to a second device parameter value based on the first parameter value; The second electronic device is controlled based on the second device parameter value.

2. The method according to claim 1, characterized in that The detecting that a first parameter change in the environmental parameter is a first parameter value includes: It is determined at a first moment that the first parameter will change to a first parameter value at a second moment, wherein the first moment is earlier than the second moment.

3. The method according to claim 1, characterized in that The detecting that a first parameter change in the environmental parameter is a first parameter value includes: At a third moment, it is detected that the first parameter changes to a first parameter value.

4. The method according to claim 2 or 3, characterized in that The controlling the second electronic device based on the second device parameter value includes: corresponding to the first parameter value being greater than 0, controlling the first type of device in the second electronic device to be in a first state based on the second device parameter value; corresponding to the first parameter value being equal to 0, controlling the first type of device in the second electronic device to be in a second state based on the second device parameter value; The energy consumption value of the first type of equipment in the first state is greater than the energy consumption value of the first type of equipment in the second state.

5. The method according to claim 4, characterized in that The first type of equipment includes at least any one of lighting equipment, escalators and elevators.

6. The method according to claim 2 or 3, characterized in that The adjusting the first device parameter value to a second device parameter value based on the first parameter value includes: determining a heat production of the first target area based on the first parameter value; determining a cooling capacity of the first target area based on the first equipment parameter value; adjusting the first device parameter value to a second device parameter value based on the heat production and the cooling capacity, and controlling a second type of device in the second electronic device based on the second device parameter value; The second type of equipment is used to adjust the temperature of the first target area.

7. The method according to claim 6, characterized in that The determining the heat production of the first target area based on the first parameter value includes: determining the heat generation of the first target area based on the spatial data of the first target area, the first parameter value, and a third parameter value of the second parameter among the environmental parameters; The second parameter includes at least one or more of the following: the amount of light in the first target area, the cooling capacity of the electrical equipment in the first target area, and the heat transfer coefficient of the enclosure structure of the first target area.

8. The method according to claim 6, characterized in that The determining the cooling capacity of the first target area based on the first device parameter value includes: determining a cooling capacity corresponding to the first target area based on the spatial data of the first target area and the first equipment parameter value; The spatial data includes at least one or more of the following: ventilation volume of the first target area, heat transfer coefficient of the enclosure structure of the first target area, and space size of the first target area; The first device parameter value is a default parameter value preset for the second type of device.

9. The method according to claim 8, wherein adjusting the first device parameter value to a second device parameter value based on the heat production and the cooling capacity comprises: a first indicator value determined based on the heat production, the cooling capacity, and the first device parameter value; corresponding to the first indicator value satisfying the target indicator corresponding to the first target area, using the first device parameter value as the second device parameter value; Corresponding to the first indicator value not meeting the target indicator corresponding to the first target area, the first device parameter value is adjusted to a second device parameter value, wherein the second indicator value determined based on the heat production, the cooling capacity and the second device parameter value meets the target indicator.

10. The method according to claim 9, characterized in that The target indicators include: at least one or more of energy consumption indicators, comfort indicators and energy cost indicators; The first indicator value determined based on the heat production, the cooling capacity, and the first device parameter value includes: determining a first energy consumption value based on the second device parameter value and the power consumption parameter value of the second type of device; determining a first energy cost value based on the second device parameter value, the power consumption parameter value of the second type of device, and the energy price value; determining a first comfort value based on a first temperature value and a preset comfort index, wherein the first temperature value is determined based on the space data, the heat production, and the cooling capacity; The first index value is determined based on the first energy consumption value, the first comfort value, and the first energy cost value.

11. The method according to claim 8, characterized in that The method further comprises: inputting the first target area into a preset first model; determining the spatial data of the first target area based on the output of the first model, The training samples of the first model include: structural data of the building corresponding to the first target area; The construction data of the building includes: construction data of one or more typical floors of the building; The typical floors include at least any one of an above-ground floor, a ground floor, and an underground floor.

12. The method according to claim 10, characterized in that After controlling the second type of device based on the second device parameter value, the method further includes: Obtaining energy consumption values ​​corresponding to the second type of equipment; The energy consumption value is outside the first indicator value interval corresponding to the energy consumption indicator, and a fourth device parameter value is determined by an optimization algorithm based on the second device parameter value.

13. The method according to claim 2 or 3, characterized in that The method further comprises: Inputting the first target area and time into a preset second model; determining the number of people in the first target area based on the output of the second model; Wherein, the number of personnel includes the first parameter value; The training samples of the second model include: parameter values ​​of the first parameter of each area of ​​the building corresponding to the first target area at each time.

14. An electronic device, characterized in that: include: one or more processors; One or more memories; the one or more memories store one or more programs, and when the one or more programs are executed by the one or more processors, the electronic device executes the device control method according to any one of claims 1 to 13.

15. A computer-readable medium, characterized in that The readable medium stores instructions, which, when executed on a computer, cause the computer to execute the device control method according to any one of claims 1 to 13.

16. A computer program product, characterized in that The device comprises a computer program / instruction, which implements the device control method according to any one of claims 1 to 13 when executed by a processor.

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