Control method and electronic equipment for flexible load of building air conditioning

Abstract

The present application provides a control method and electronic device for a flexible load of an air conditioner in a building. The mass of an indoor building wall, the heat capacity of the wall, a second derivative model and a fourth derivative model are processed through a linearization algorithm to obtain a building wall temperature model at a target moment. The building wall temperature model at the target moment, the mass of indoor building air, the heat capacity of the air, a first derivative model, a second derivative model and a third derivative model are processed through a linearization algorithm to obtain an indoor air temperature model in the building at the target moment. Then, a temperature comfort index at the target moment is introduced, and a user temperature comfort constraint is constructed with the indoor air temperature model in the building at the target moment, so that under this constraint, a pre-constructed control resource consumption function associated with the rated power of the air conditioner can fully take into account the overall control resource consumption and the user experience, and can avoid the problem of being unable to guarantee the user experience due to the relatively single factors considered in the control.

Description

Technical Field

[0001] The present application relates to the technical field of power regulation and control, and particularly to a method for regulating and controlling a flexible load of a building air conditioner and an electronic device. Background Art

[0002] As a flexible load, the air-conditioning load is gradually becoming an important part of the controllable load in a virtual power plant with the substantial increase in users' demand for air conditioners.

[0003] However, in the related art, the factors considered for regulating and controlling the flexible load of a building air conditioner are relatively single, and the user experience cannot be guaranteed. Summary of the Invention

[0004] In view of this, the purpose of the present application is to propose a method for regulating and controlling a flexible load of a building air conditioner and an electronic device to solve the above technical problems.

[0005] Based on the above purpose, the first aspect of the present application provides a method for regulating and controlling a flexible load of a building air conditioner, including:

[0006] Obtain the quality of the air in the indoor building, the heat capacity of the air, the quality of the indoor building wall, and the heat capacity of the wall;

[0007] Determine the heat transferred from the surrounding environment to the indoor air at the target moment, and the first derivative model of the target moment;

[0008] Determine the heat exchange between the indoor building air and the wall at the target moment, and the second derivative model of the target moment;

[0009] Determine the cooling capacity of the air conditioner at the target moment, and the third derivative model of the target moment;

[0010] Determine the heat transferred from the surrounding environment to the wall at the target moment, and the fourth derivative model of the target moment;

[0011] Based on the quality of the indoor building wall, the heat capacity of the wall, the second derivative model, and the fourth derivative model, perform processing through a linearization algorithm to obtain the building wall temperature model at the target moment;

[0012] Based on the building wall temperature model at the target moment, the quality of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model, and the third derivative model, perform processing through a linearization algorithm to obtain the indoor air temperature model in the building at the target moment;

[0013] The indoor air temperature model in the building at the target moment is processed through a temperature comfort algorithm to obtain the temperature comfort index at the target moment, and a user temperature comfort constraint is constructed by using the temperature comfort index at the target moment and the indoor air temperature model in the building at the target moment.

[0014] Under the user temperature comfort constraint, the pre-constructed regulation resource consumption function associated with the rated power of the air conditioner is minimized to obtain the target rated power of the air conditioner, and the load of the building air conditioner is regulated according to the target rated power of the air conditioner.

[0015] Based on the same inventive concept, the second aspect of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable by the processor. When the processor executes the computer program, the method described in the first aspect above is implemented.

[0016] As can be seen from the above, the regulation method and electronic device for the flexible load of the building air conditioner provided by the present application are processed through a linearization algorithm based on the quality of the indoor building wall, the heat capacity of the wall, the second derivative model, and the fourth derivative model to obtain the building wall temperature model at the target moment, and are processed through a linearization algorithm based on the building wall temperature model at the target moment, the quality of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model, and the third derivative model to obtain the indoor air temperature model in the building at the target moment. Then, the temperature comfort index at the target moment is introduced, and a user temperature comfort constraint is constructed with the indoor air temperature model in the building at the target moment, so that the pre-constructed regulation resource consumption function associated with the rated power of the air conditioner can fully consider the overall regulation resource consumption and the user experience under this constraint, and can avoid the problem of being unable to guarantee the user experience caused by the relatively single factors considered in the regulation. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a flowchart of the regulation method for the flexible load of the building air conditioner according to the embodiment of the present application;

[0019] Figure 2 It is a schematic diagram of the composition of the virtual power plant regulation system according to the embodiment of the present application;

[0020] Figure 3Structural block diagram of the regulation device for the flexible load of the building air conditioner according to the embodiment of the present application;

[0021] Figure 4 Schematic diagram of the electronic device according to the embodiment of the present application. Detailed implementation manners

[0022] To make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to specific embodiments and the accompanying drawings.

[0023] It should be noted that unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should have the ordinary meanings understood by those with ordinary skills in the field to which the present application belongs. The "first", "second" and similar terms used in the embodiments of the present application do not denote any order, quantity or importance, but are only used to distinguish different components. Words such as "including" or "comprising" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. Words such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Upper", "lower", "left", "right", etc. are only used to represent relative position relationships, and when the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0024] It can be understood that before using the technical solutions of the various embodiments of the present application, the types, usage scopes, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0025] For example, when responding to receiving an active request from the user, a prompt message is sent to the user to clearly prompt the user that the operation requested by the user will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, an application program, a server or a storage medium that performs the operations of the technical solutions of the present application according to the prompt message.

[0026] As an optional but non-limiting implementation manner, the manner of sending a prompt message to the user in response to receiving an active request from the user may be, for example, in the form of a pop-up window, and the prompt message may be presented in text in the pop-up window. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0027] It can be understood that the above-mentioned notification and the process of obtaining user authorization are only illustrative and do not limit the implementation manner of this application. Other methods that comply with relevant laws and regulations can also be applied to the implementation manner of this application.

[0028] As a flexible load, with the substantial increase in users' demand for air conditioners, air-conditioning load is gradually becoming an important part of the controllable load in a virtual power plant. As a virtual power plant resource participating in power demand response to improve the operation efficiency and reliability of the system, air-conditioning load has a certain tolerance for reducing power to a certain extent, decreasing the startup time, or interrupting operation. By sacrificing a part of user comfort, some air conditioners can be reduced for use according to the dispatch requirements.

[0029] By analyzing and processing the collected air-conditioning load data, various parameters and indicators are obtained, such as the energy consumption, operation efficiency, and regulation range of air-conditioning equipment, to help evaluate the regulation potential of air-conditioning load. Through historical data and prediction models, the regulation potential of future air-conditioning load is predicted to help the virtual power plant formulate a reasonable power dispatch plan and optimize the operation strategy in advance.

[0030] However, due to the complex mechanism modeling calculation of air conditioners based on thermodynamic principles, the common relationship between air-conditioning power and temperature usually adopts a prediction algorithm, that is, a black-box model, and in-depth research on the energy optimization of building air conditioners has not been carried out.

[0031] This application incorporates air-conditioning load into the virtual power plant system, effectively improving the flexible regulation ability of the power system. By precisely establishing the thermoelectric coupling relationship of air conditioners, establishing a second-order equivalent thermal parameter model of air conditioners and performing linearization processing, the adjustable potential of air-conditioning load can be maximally explored. Then, by introducing the temperature comfort index at the target moment and constructing a user temperature comfort constraint with the indoor air temperature model in the building at the target moment, the overall regulation resource consumption and user experience are fully considered, so that the pre-constructed regulation resource consumption function associated with the rated power of air conditioners can fully consider the overall regulation resource consumption and user experience under this constraint.

[0032] An embodiment of the present application provides a method for regulating flexible loads of building air conditioners. Through linearization algorithms based on the mass of the indoor building wall, the heat capacity of the wall, the second derivative model, and the fourth derivative model, a building wall temperature model at the target time is obtained. Then, through linearization algorithms based on the building wall temperature model at the target time, the mass of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model, and the third derivative model, an indoor air temperature model within the building at the target time is obtained. Subsequently, the temperature comfort index at the target time is introduced, and a user temperature comfort constraint is constructed with the indoor air temperature model within the building at the target time, such that under this constraint, the pre-constructed regulation resource consumption function associated with the air conditioner rated power can fully consider both the overall regulation resource consumption and the user experience, and can avoid the problem of being unable to guarantee the user experience due to relatively single factors considered in the regulation.

[0033] As Figure 1 shown, the method of this embodiment includes:

[0034] Step 101, obtain the mass of the indoor building air, the heat capacity of the air, the mass of the indoor building wall, and the heat capacity of the wall.

[0035] In this step, in order to describe the relationship between the indoor temperature and the air conditioner power, the present application needs to construct an air conditioner second-order equivalent thermal parameter model. To construct the air conditioner second-order equivalent thermal parameter model, it is necessary to obtain the mass of the indoor building air, the heat capacity of the air, the mass of the indoor building wall, and the heat capacity of the wall.

[0036] Among them, the mass of the indoor building air, the heat capacity of the air, the mass of the indoor building wall, and the heat capacity of the wall can be obtained through the following several methods:

[0037] Mass of the indoor building air: Use an air quality detection instrument to directly measure the indoor air to judge the indoor air quality.

[0038] Heat capacity of the air: Use the adiabatic expansion method to measure the heat capacity of the air, that is, by observing the changes in state and its basic physical laws during the thermodynamic process, using the relationship of the universal gas constant, and measuring the specific heat ratio of the gas through the adiabatic expansion process. The specific operations include: Regarding the air as an ideal gas, through the adiabatic expansion process, measure the ratio of the specific heat at constant pressure to the specific heat at constant volume, that is, the specific heat ratio of the air. Under adiabatic conditions, through the inflation and deflation processes, observe and analyze the changes in the air state, and calculate the specific heat ratio using the gas state equation and the principle of energy conservation to obtain the heat capacity of the air.

[0039] Mass of the indoor building wall: The mass of the wall can be estimated by measuring the thickness and density of the wall.

[0040] Heat capacity of the wall: The heat capacity of the wall can be determined by the specific heat calculation method using a laser thermal conductivity meter, that is, by comparing and measuring with a reference standard sample with similar conditions to the sample to be measured and a known specific heat capacity value. Under ideal adiabatic conditions, by comparing the test curves of the sample and the reference standard sample, the specific heat capacity of the sample to be measured is calculated. This method requires the sample and the reference standard sample to be similar in terms of area, thickness, surface structure, thermal properties, etc. to ensure the accuracy of the measurement results.

[0041] Step 102: Determine the heat transferred from the surrounding environment to the indoor air at the target moment, and the first derivative model of the target moment.

[0042] In this step, the second-order equivalent thermal parameter model takes into account the solid temperature (building wall). The second-order equivalent thermal parameter model includes the first derivative model, and the first derivative model describes the rate of change of the heat gain transferred from the environment to the indoor air.

[0043] Step 103: Determine the heat exchange between the indoor building air and the wall at the target moment, and the second derivative model of the target moment.

[0044] In this step, the second-order equivalent thermal parameter model takes into account the solid temperature (building wall). The second-order equivalent thermal parameter model includes the second derivative model, and the second derivative model describes the rate of change of the heat gain between the indoor air and the wall.

[0045] Step 104: Determine the air-conditioning cooling capacity at the target moment, and the third derivative model of the target moment.

[0046] In this step, the second-order equivalent thermal parameter model takes into account the solid temperature (building wall). The second-order equivalent thermal parameter model includes the third derivative model, and the third derivative model describes the rate of change of the air-conditioning cooling energy.

[0047] Step 105: Determine the heat transferred from the surrounding environment to the wall at the target moment, and the fourth derivative model of the target moment.

[0048] In this step, the second-order equivalent thermal parameter model takes into account the solid temperature (building wall). The second-order equivalent thermal parameter model includes the fourth derivative model, and the fourth derivative model describes the rate of change of the heat acquisition transferred from the environment to the wall.

[0049] Step 106: Based on the mass of the indoor building wall, the heat capacity of the wall, the second derivative model, and the fourth derivative model, perform processing through a linearization algorithm to obtain the building wall temperature model at the target moment.

[0050] In this step, the building wall temperature model and the indoor air temperature model affect each other. For the convenience of iterative calculation, the time period t is divided into N time steps. If N is large enough, the ambient temperature, wall temperature, and indoor air temperature can be regarded as constant values within any time period.

[0051] Based on the building wall temperature model at the target moment, the mass of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model, and the third derivative model, processing is performed through a linearization algorithm to obtain the indoor air temperature model within the building at the target moment. This indoor air temperature model within the building at the target moment is the linearized model of the second-order equivalent thermal parameters of the air conditioner.

[0052] Step 107: Based on the building wall temperature model at the target moment, the mass of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model, and the third derivative model, processing is performed through a linearization algorithm to obtain the indoor air temperature model within the building at the target moment.

[0053] In this step, the building wall temperature model and the indoor air temperature model affect each other. For the convenience of iterative calculation, the time period t is divided into N time steps. If N is large enough, the ambient temperature, wall temperature, and indoor air temperature can be regarded as constant values within any time period.

[0054] Based on the building wall temperature model at the target moment, the mass of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model, and the third derivative model, processing is performed through a linearization algorithm to obtain the indoor air temperature model within the building at the target moment. This obtained indoor air temperature model within the building at the target moment is the linearized model of the second-order equivalent thermal parameters of the air conditioner.

[0055] Step 108: Based on the indoor air temperature model within the building at the target moment, processing is performed through a temperature comfort algorithm to obtain the temperature comfort index at the target moment, and a user temperature comfort constraint is constructed using the temperature comfort index at the target moment and the indoor air temperature model within the building at the target moment.

[0056] In this step, first, an air conditioner satisfaction index is constructed. The human perception of temperature forms human comfort. The temperature comfort index (TCI) is affected by main factors such as indoor temperature, human metabolic rate, and clothing insulation value. In addition, the building population density affects the feeling of human comfort, and the building population density is introduced to correct the TCI.

[0057] The expression of TCI (i.e., the temperature comfort model) is as follows:

[0058]

[0059] In the formula, T a (t) is the human skin temperature at the target time t (i.e., the user skin temperature at the target time t), σ 0 is the metabolic rate of the human body (i.e., the preset user metabolic rate), I cl is the clothing thermal resistance (i.e., the thermal resistance between the human skin and the indoor air). D(t) is the personnel density at the target time t (i.e., the user density at the target time t).

[0060] Establish a model of building personnel density based on the black box theory. Consider the building as a black box, and regard each entrance and exit as a connection channel connecting the black box to the outside world. By observing and counting the number of people flowing in and out of each entrance and exit in real time, the change of the number of people flowing in the building at different time periods can be obtained, and then the personnel density corresponding to the corresponding time period can be calculated according to the effective area of the building.

[0061]

[0062] In the formula, R t is the number of people flowing in the building at the target time t (i.e., the user flow in the building at the target time t), R t-1 is the number of people flowing in the building at the previous moment t - 1 of the target time t (i.e., the number of people flowing in the building at the previous moment t - 1 of the target time t), E tβ is the number of people entering at the β entrance of the building at time t (i.e., the number of users entering at the β entrance of the building at the target time t), G tβ is the number of people going out at the β entrance of the building at time t (i.e., the number of users going out at the β entrance of the building at the target time t), D(t) is the personnel density at the target time t (i.e., the target time t at the target time t), is the effective building area, A is the building area, and K is the conversion coefficient of the building effective area.

[0063] When the TCI value is within the range of [-0.5, 0.5], the temperature change is subtle and the human body cannot feel it. Therefore, the temperature range within [-1, 1] is regarded as the comfortable temperature range for the human body, as shown in Table 1 below:

[0064] Table 1

[0065]

[0066] The marginal temperatures (i.e., the temperature comfort index at the target time) θ 1 , θ -1 corresponding to TCI being 1 and -1 are used to construct the user temperature comfort constraint with the indoor air temperature model in the building at the target time, so that under this constraint, the pre - constructed regulation resource consumption function associated with the air - conditioner rated power can fully consider the overall regulation resource consumption and the user experience.

[0067] Step 109: Minimize the pre-constructed regulation resource consumption function associated with the rated power of the air conditioner under the user's temperature comfort constraint to obtain the target rated power of the air conditioner, and regulate the load of the building air conditioner according to the target rated power of the air conditioner.

[0068] In this step, the virtual power plant regulation system is composed as Figure 2 shown. The building air conditioner load belongs to an adjustable load. In this typical system, the consumption of wind power grid-connected resources is lower than that of external power grid resources. New energy should be consumed as much as possible.

[0069] However, considering the uncertainty of the power generation of the fan equipment, it is necessary to configure an electrical energy storage device to smooth the output. When the electrical energy storage device cannot meet the power balance demand, the user can obtain power resources from the external power grid. On the contrary, when the user demand is low, power resources can be provided to the external power grid.

[0070] Under the constraint of constructing the temperature comfort index at the target moment, minimizing the pre-constructed regulation resource consumption function associated with the rated power of the air conditioner can fully consider the overall regulation resource consumption and the user experience, and can avoid the problem of being unable to ensure the user experience caused by relatively single factors considered in the regulation.

[0071] In the above solution, based on the quality of the building wall, the heat capacity of the wall, the second derivative model and the fourth derivative model, through linearization algorithm processing, the building wall temperature model at the target moment is obtained. And based on the building wall temperature model at the target moment, the quality of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model and the third derivative model, through linearization algorithm processing, the indoor air temperature model in the building at the target moment is obtained. Then, the temperature comfort index at the target moment is introduced, and the user temperature comfort constraint is constructed with the indoor air temperature model in the building at the target moment, so that under this constraint, the pre-constructed regulation resource consumption function associated with the rated power of the air conditioner can fully consider the overall regulation resource consumption and the user experience, and can avoid the problem of being unable to ensure the user experience caused by relatively single factors considered in the regulation.

[0072] In some embodiments, step 102 includes:

[0073] Step A1: Obtain the environmental temperature T at the target moment t amb , the indoor air temperature T in the building r , and the equivalent thermal resistance R of the building shell corresponding to the environmental temperature and the outer wall temperature eq .

[0074] Step A2: Based on the environmental temperature T at the target moment t amb, the indoor air temperature T in the building r , and the equivalent thermal resistance R of the building envelope corresponding to the ambient temperature and the outer wall surface temperature eq , determine the first derivative model through the following formula

[0075]

[0076] In the above solution, comprehensively considering the ambient temperature T at the target time t amb , the ambient temperature T at the target time t amb , and the equivalent thermal resistance R of the building envelope eq , can improve the accuracy of the first derivative model .

[0077] In some embodiments, step 103 includes:

[0078] Step B1, obtain the building wall temperature T w , the indoor air temperature T in the building r , and the equivalent thermal resistance R corresponding to the inner wall surface temperature and the indoor air temperature wr .

[0079] Step B2, based on the building wall temperature T w , the indoor air temperature T in the building r , and the equivalent thermal resistance R corresponding to the inner wall surface temperature and the indoor air temperature wr , determine the second derivative through the following formula

[0080]

[0081] In the above solution, comprehensively considering the building wall temperature T w , the indoor air temperature T in the building r , and the equivalent thermal resistance R between the indoor air of the building and the inner wall surface wr , can improve the accuracy of the second derivative .

[0082] In some embodiments, step 104 includes:

[0083] Step C1, obtain the coefficient of performance COP of the air conditioner and the rated power P of the air conditioner ac .

[0084] Step C2, based on the coefficient of performance COP of the air conditioner and the rated power P of the air conditioner ac determine the third derivative model through the following formula

[0085]

[0086] In the above solution, by comprehensively considering the coefficient of performance COP of the air conditioner and the rated power of the air conditioner, the accuracy of the third derivative model can be improved.

[0087] In some embodiments, step 105 includes:

[0088] Step D1, obtaining the ambient temperature T at the target time t amb and the building wall temperature T w .

[0089] Step D2, based on the ambient temperature T at the target time t amb and the building wall temperature T w determine the fourth derivative model through the following formula

[0090]

[0091] In the above solution, by comprehensively considering the ambient temperature T at the target time t amb and the building wall temperature T w , the accuracy of the fourth derivative model can be improved.

[0092] In some embodiments, step 106 includes:

[0093] Step E1, based on the mass M of the indoor building wall w , the heat capacity C of the wall pw , the second derivative model and the fourth derivative model determine the derivative model of the building wall temperature at the target time t with respect to the building wall temperature at the target time t through the following formula

[0094]

[0095] Step E2, in response to the target time t being 1, based on the building wall temperature derivative model obtain the equivalent thermal resistance R between the environment and the outer surface of the building wall wa , the building wall temperature T at the initial time w_ini , the ambient temperature T at the initial time amb_ini , and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr .

[0096] Step E3, based on the mass M of the indoor building wall w , the heat capacity C of the wall​pw The equivalent thermal resistance R between the environment and the outer surface of the building wall wa The temperature T of the building wall at the initial time w_ini The environmental temperature T at the initial time amb_ini The temperature T of the building wall at the initial time w_ini The equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr The temperature model T of the building wall at the target time t is determined by the following formula w (t):

[0097] Or

[0098] Step E4, in response to the target time t being greater than 1, based on the derivative model of the building wall temperature Obtain the temperature model T of the building wall at the previous time t - 1 of the target time t w (t - 1), the equivalent thermal resistance R between the environment and the outer surface of the building wall wa The environmental temperature T at the previous time t - 1 of the target time t amb (t - 1), the indoor air temperature model T at the previous time t - 1 of the target time t r (t - 1), and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr .

[0099] Step E5, based on the mass M of the indoor building wall w The heat capacity C of the wall pw The temperature model T of the building wall at the previous time t - 1 of the target time t w (t - 1), the equivalent thermal resistance R between the environment and the outer surface of the building wall wa The environmental temperature T at the previous time t - 1 of the target time t amb (t - 1), the indoor air temperature model T at the previous time t - 1 of the target time t r (t - 1), and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr The temperature model T of the building wall at the target time t is determined by the following formula w (t):

[0100]

[0101] In the above solution, the derivative model of the building wall temperature at the target time t Involves the rate of change of the wall temperature

[0102] For the convenience of iterative calculation, the time period t is divided into N time steps. If N is large enough, the ambient temperature, wall temperature, and indoor air temperature can be regarded as constant values within any time period. The linearized model of the second-order equivalent thermal parameters of the air conditioner (i.e., the building wall temperature model T of the target time t w (t)) is expressed as follows:

[0103] When the target time t is equal to 1, the building wall temperature model T of the target time t w (t) is:

[0104] Or,

[0105] When the target time t, the building wall temperature model T of the target time t w (t) is:

[0106]

[0107] In some embodiments, step 107 includes:

[0108] Step F1, based on the mass M of the indoor building air a , the heat capacity C of the air pa , the first derivative model the second derivative model and the third derivative model to determine the derivative model of the indoor air temperature T r (t) of the indoor air temperature with respect to the target time t

[0109]

[0110] Step F2, in response to the target time t being 1, based on the derivative model of the indoor air temperature to obtain the equivalent thermal resistance R of the building shell eq , the indoor air temperature T at the initial time r_ini , the ambient temperature T at the initial time amb_ini , the building wall temperature T at the initial time w_ini , the cooling capacity Q of the air conditioner ac , the operating state S of the air conditioner at the initial time ac_ini , and the equivalent thermal resistance R between the indoor air and the inner surface of the wall wr .

[0111] Step F3, based on the mass M of the indoor building air a , the heat capacity C of the air pa , the equivalent thermal resistance R of the building shell eq, the indoor air temperature T at the initial time r_ini , the ambient temperature T at the initial time amb_ini , the building wall temperature T at the initial time w_ini , the air-conditioning cooling capacity Q ac , the operating state S of the air conditioner at the initial time ac_ini , and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , determine the indoor air temperature model T in the building at the target time t through the following formula r (t):

[0112] Or,

[0113] Step F4, in response to the target time t being greater than 1, obtain the equivalent thermal resistance R of the building shell eq , the indoor air temperature model T in the building at the previous time t - 1 of the target time t r (t - 1), the ambient temperature T at the initial time amb_ini , the building wall temperature model T at the previous time t - 1 of the target time t w (t - 1), the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , the air-conditioning cooling capacity Q at the previous time t - 1 of the target time t ac (t - 1) and the operating state S of the air conditioner at the target time t ac (t).

[0114] Step F5, based on the building wall temperature model T at the target time w (t) determine the building wall temperature model T at the previous time t - 1 of the target time t w (t - 1).

[0115] Step F6, based on the mass M of the indoor building air a , the heat capacity C of the air pa , the equivalent thermal resistance R of the building shell eq , the indoor air temperature model T in the building at the previous time t - 1 of the target time t r (t - 1), the ambient temperature T at the initial time amb_ini , the building wall temperature model T at the previous time t - 1 of the target time t w (t - 1), the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , the air-conditioning cooling capacity Q at the previous time t - 1 of the target time t ac (t - 1) and the operating state S of the air conditioner at the target time t ac (t), determine the indoor air temperature model T in the building at the target time t through the following formula r (t):

[0116]

[0117] In the above solution, the indoor air temperature derivative model at the target time t involves the change rate of indoor air temperature.

[0118] For the convenience of iterative calculation, the time period t is divided into N time steps. If N is large enough, the environmental temperature, wall temperature, and indoor air temperature can be regarded as constant values within any time period. The second-order equivalent thermal parameter linearization model of the air conditioner (i.e., the indoor air temperature model T r (t) in the building at the target time t) is expressed as follows:

[0119] When the target time t is equal to 1, the indoor air temperature model T r (t) in the building at the target time t is:

[0120] Or,

[0121] When the target time is, the indoor air temperature model T r (t) in the building at the target time t is:

[0122]

[0123] In some embodiments, in step 108, the indoor air temperature model in the building at the target time is processed through a temperature comfort algorithm to obtain the temperature comfort index at the target time, including:

[0124] Step G1, obtain the building area A of the building where the air conditioner is located.

[0125] Step G2, use the preset building effective area conversion coefficient K and the building area A of the building where the air conditioner is located to determine the effective building area through the following formula

[0126]

[0127] Step G3, obtain the number of people R in the building at the previous time t - 1 of the target time t t-1 、the number of users entering at the entrance and exit β of the building at the target time t E tβ 、the number of users leaving at the entrance and exit β of the building at the target time t G tβ .

[0128] Step G4, based on the number of people R in the building at the previous time t - 1 of the target time t t-1 、the number of users entering at the entrance and exit β of the building at the target time t E tβ, the number of users going out at the entrance of building β at the target time t is G tβ , determine the user flow rate R in the building at the target time t through the following formula t :

[0129]

[0130] Step G5, based on the user flow rate R in the building at the target time t t and the effective floor area determine the user density D(t) at the target time t through the following formula:

[0131]

[0132] Step G6, obtain the skin temperature T of the user at the target time t a (t).

[0133] Step G7, based on the indoor air temperature model T in the building at the target time r (t), the skin temperature T of the user at the target time t a (t), the preset user metabolic rate σ 0 , the clothing thermal resistance I cl , the preset constant parameter s and the user density D(t) at the target time t, determine the temperature comfort model TCI(t) at the target time t through the following formula:

[0134]

[0135] Step G8, determine the first marginal temperature θ corresponding to the temperature comfort model TCI(t) when the value of the temperature comfort model TCI(t) at the target time t is -1 -1 , and determine the second marginal temperature θ corresponding to the temperature comfort model TCI(t) when the value of the temperature comfort model TCI(t) at the target time t is 1 1 , and use the first marginal temperature θ -1 and the second marginal temperature θ 1 as the temperature comfort index at the target time.

[0136] In the above solution, first construct the air-conditioning satisfaction index. The human perception of temperature forms the human comfort level. The temperature comfort index (TCI) is affected by main factors such as indoor temperature, human metabolic rate, and clothing insulation value. In addition, the density of building occupants will affect the comfort level, and the density of building occupants is introduced to correct the TCI.

[0137] The expression of TCI (i.e., the temperature comfort model) is as follows:

[0138]

[0139] In the formula, T a (t) is the human skin temperature at the target time t (i.e., the user skin temperature at the target time t), σ 0 is the metabolic rate of the human body (i.e., the preset user metabolic rate), I cl is the clothing thermal resistance (i.e., the thermal resistance between the human skin and the indoor air). D(t) is the personnel density at the target time t (i.e., the user density at the target time t).

[0140] Establish a model of building personnel density based on the black box theory. Consider the building as a black box, and regard each entrance and exit as a connection channel connecting the black box to the outside world. By observing and counting the number of people flowing in and out of each entrance and exit in real time, the change of the number of people flowing in the building at different time periods can be obtained, and then the personnel density corresponding to the corresponding time period can be calculated according to the effective area of the building.

[0141]

[0142]

[0143] In the formula, R t is the number of people flowing in the building at the target time t (i.e., the user flow in the building at the target time t), R t-1 is the number of people flowing in the building at the previous time t - 1 of the target time t (i.e., the number of people flowing in the building at the previous time t - 1 of the target time t), E tβ is the number of people entering at the β entrance of the building at time t (i.e., the number of users entering at the β entrance of the building at the target time t), G tβ is the number of people going out at the β entrance of the building at time t (i.e., the number of users going out at the β entrance of the building at the target time t), D(t) is the personnel density at the target time t (i.e., the target time t at the target time t), is the effective building area, A is the building area, and K is the conversion coefficient of the building effective area.

[0144] When the TCI value is in the interval [-0.5, 0.5], the temperature change is subtle and the human body cannot feel it. Therefore, the interval [-1, 1] is regarded as the temperature interval comfortable for the human body, as shown in Table 1 below:

[0145] Table 1

[0146]

[0147] The marginal temperature (i.e., the temperature comfort index at the target time) θ corresponding to TCI being 1 and -1 1 (i.e., the second marginal temperature), θ -1 (i.e., the first marginal temperature), which is used to construct the user temperature comfort constraint with the indoor air temperature model in the building at the target time (i.e., θ-1 ≤T r (t) ≤ θ 1 )。

[0148] In some embodiments, the regulation resource consumption function is constructed and obtained through the following process:

[0149] Step H1, obtain the power quantity P gb (t) obtained from the external power grid at the power equipment node i at the target time t, the power resource acquisition consumption parameter C b (t) at the power equipment node i at the target time t, the power quantity P gs (t) supplied to the external power grid at the power equipment node i at the target time t, the power configuration consumption parameter C s (t), the rated power P of the air conditioner at the target time t ab (t), the power operation and maintenance resource consumption parameter C o (t) at the power equipment node i at the target time t.

[0150] Step H2, based on the power quantity P gb (t) obtained from the external power grid at the power equipment node i at the target time t, the power resource acquisition consumption parameter C b (t) at the power equipment node i at the target time t, the power quantity P gs (t) supplied to the external power grid at the power equipment node i at the target time t, the power configuration consumption parameter C s (t), the rated power P of the air conditioner at the target time t ab (t), the power operation and maintenance resource consumption parameter C o (t) at the power equipment node i at the target time t and the preset constant parameter time step τ, determine the regulation resource consumption function C through the following formula:

[0151]

[0152] where t represents the order of the target time, N represents the number of target times, i represents the order of the power equipment node, and N represents the number of power equipment nodes.

[0153] In the above solution, the virtual power plant regulation system is composed as Figure 2 shown. The building air-conditioning load belongs to an adjustable load. In this typical system, the consumption of wind power grid-connected resources is lower than that of external power grid resources, and new energy should be consumed as much as possible.

[0154] However, considering the uncertainty of power generation by wind turbine equipment, it is necessary to configure electrical energy storage equipment to smooth the output. When the electrical energy storage equipment cannot meet the power balance demand, users can obtain power resources from the external power grid. On the contrary, when the user demand is low, power resources can be provided to the external power grid.

[0155] Under the constraint of constructing the temperature comfort index at the target moment, a long-term optimal scheduling model for the day-ahead (i.e., the regulation resource consumption function) is constructed:

[0156] Schedule 24 hours in advance, and the scheduling time scale is selected as 1 hour. The scenario generation method is used to handle the uncertainty of wind power output and power acquisition resource consumption, and the minimum regulation resource consumption is taken as the objective function (i.e., minimizing the regulation resource consumption function).

[0157]

[0158] The constraint condition is the human body temperature comfort constraint (i.e., the user temperature comfort constraint):

[0159] θ -1 ≤T r (t)≤θ 1 .

[0160] Among them, the constraint conditions can also include power balance constraint, the electric power constraint of the virtual power plant (VPP) to obtain power resources, energy storage constraint, etc.

[0161] Minimizing this regulation resource consumption function can fully take into account the overall regulation resource consumption and the user experience, and can avoid the problem of being unable to guarantee the user experience caused by the relatively single factors considered in the regulation.

[0162] In addition, an intraday rolling optimal scheduling model can also be used. In the intraday stage, the objective function not only includes the relevant resource consumption in the previous scheduling, but also fully considers the prediction error of the day-ahead long-term scale, the error of the model itself, and the deviation problems caused by the change of intraday climate conditions. Therefore, an output deviation penalty is added in the intraday scheduling, and the sum of the total resource consumption of the virtual power plant and the output deviation penalty within the scheduling period is taken as the objective function. The rolling optimization step size is selected as 15 minutes, and the rolling optimization process is as follows:

[0163] In the first time step, parameters including power acquisition resource consumption, ambient temperature, and wind energy output are determined based on the ultra-short-term power prediction data. The mixed integer programming (MIP) model will calculate and generate a set of parameters according to the minimum resource consumption target (such as T r (t) and T w (t).

[0164] At the next time step, based on the updated input parameters (including the newly predicted ambient temperature, the updated future wind power output, the data T generated in the previous step, etc.), the particle swarm optimization algorithm is used to solve the objective function to generate a new set of parameters for the next moment.

[0165] At each time step, the control window is moved forward, and the above process is repeated until the last time step of the planned scope is completed.

[0166] It should be noted that the method of the embodiment of the present application can be executed by a single device, such as a computer or a server, etc. The method of this embodiment can also be applied to a distributed scenario and completed by the cooperation of multiple devices. In such a distributed scenario, one of the multiple devices can only execute one or more steps of the method of the embodiment of the present application, and these multiple devices will interact with each other to complete the described method.

[0167] It should be noted that some embodiments of the present application are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order from those in the above embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0168] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present application further provides a control device for the flexible load of a building air conditioner.

[0169] Referring to Figure 3 , the control device for the flexible load of the building air conditioner includes:

[0170] An acquisition module 301, configured to acquire the quality of the indoor building air, the heat capacity of the air, the quality of the indoor building wall, and the heat capacity of the wall;

[0171] A first derivative model determination module 302, configured to determine the heat transferred from the surrounding environment to the indoor air at the target moment, for the first derivative model of the target moment;

[0172] A second derivative model determination module 303, configured to determine the heat exchange between the indoor building air and the wall at the target moment, for the second derivative model of the target moment;

[0173] A third derivative model determination module 304, configured to determine the air-conditioning cooling capacity at the target moment, for the third derivative model of the target moment;

[0174] The fourth derivative model determination module 305 is configured to determine the heat transferred from the surrounding environment to the wall at the target moment, for the fourth derivative model at the target moment;

[0175] The building wall temperature model determination module 306 is configured to process based on the mass of the indoor building wall, the heat capacity of the wall, the second derivative model and the fourth derivative model through a linearization algorithm to obtain the building wall temperature model at the target moment;

[0176] The indoor air temperature model determination module 307 is configured to process based on the building wall temperature model at the target moment, the mass of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model and the third derivative model through a linearization algorithm to obtain the indoor air temperature model in the building at the target moment;

[0177] The temperature comfort constraint construction module 308 is configured to process through a temperature comfort algorithm based on the indoor air temperature model in the building at the target moment to obtain the temperature comfort index at the target moment, and construct the user temperature comfort constraint by using the temperature comfort index at the target moment and the indoor air temperature model in the building at the target moment;

[0178] The air-conditioning load regulation module 309 is configured to minimize the pre-constructed regulation resource consumption function associated with the air-conditioning rated power under the user temperature comfort constraint to obtain the target air-conditioning rated power, and regulate the load of the building air-conditioning according to the target air-conditioning rated power.

[0179] In some embodiments, the first derivative model determination module 302 is specifically configured to:

[0180] Obtain the ambient temperature T at the target moment t amb 、the indoor air temperature T in the building r ,and the equivalent thermal resistance R of the building envelope corresponding to the ambient temperature and the outer wall surface temperature eq ;

[0181] Based on the ambient temperature T at the target moment t amb 、the indoor air temperature T in the building r ,and the equivalent thermal resistance R of the building envelope corresponding to the ambient temperature and the outer wall surface temperature eq ,determine the first derivative model through the following formula

[0182]

[0183] In some embodiments, the second derivative model determination module 303 is specifically configured to:

[0184] Obtain the building wall temperature T w , the indoor air temperature T inside the building r , and the equivalent thermal resistance R corresponding to the inner surface temperature of the wall and the indoor air temperature wr ;

[0185] Based on the building wall temperature T w , the indoor air temperature T inside the building r , and the equivalent thermal resistance R corresponding to the inner surface temperature of the wall and the indoor air temperature wr , determine the second derivative through the following formula

[0186]

[0187] In some embodiments, the third derivative model determination module 304 is specifically configured to:

[0188] Obtain the coefficient of performance COP of the air conditioner and the rated power P of the air conditioner ac ;

[0189] Based on the coefficient of performance COP of the air conditioner and the rated power P of the air conditioner ac Determine the third derivative model through the following formula

[0190]

[0191] In some embodiments, the fourth derivative model determination module 305 is specifically configured to:

[0192] Obtain the ambient temperature T at the target time t amb and the building wall temperature T w ;

[0193] Based on the ambient temperature T at the target time t amb and the building wall temperature T w Determine the fourth derivative model through the following formula

[0194]

[0195] In some embodiments, the building wall temperature model determination module 306 is specifically configured to:

[0196] Based on the mass M of the indoor building wall w , the heat capacity C of the wall pw , the second derivative model and the fourth derivative model Determine the derivative model of the building wall temperature at the target time t with respect to the building wall temperature at the target time t through the following formula

[0197]

[0198] In response to the target time t being 1, based on the derivative model of the building wall temperature Obtain the equivalent thermal resistance R between the environment and the outer surface of the building wall wa , the building wall temperature T at the initial time w_ini , the environmental temperature T at the initial time amb_ini , and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr ;

[0199] Based on the mass M of the indoor building wall w , the heat capacity C of the wall pw , the equivalent thermal resistance R between the environment and the outer surface of the building wall wa , the building wall temperature T at the initial time w_ini , the environmental temperature T at the initial time amb_ini , the building wall temperature T at the initial time w_ini , the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , determine the building wall temperature model T at the target time t through the following formula w (t):

[0200] Or,

[0201] In response to the target time t being greater than 1, based on the derivative model of the building wall temperature Obtain the building wall temperature model T at the previous time t - 1 of the target time t w (t - 1), the equivalent thermal resistance R between the environment and the outer surface of the building wall wa , the environmental temperature T at the previous time t - 1 of the target time t amb (t - 1), the indoor air temperature model T at the previous time t - 1 of the target time t r (t - 1), and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr ;

[0202] Based on the mass M of the indoor building wall w , the heat capacity C of the wall pw , the building wall temperature model T at the previous time t - 1 of the target time t w (t - 1), the equivalent thermal resistance R between the environment and the outer surface of the building wall wa , the environmental temperature T at the previous time t - 1 of the target time tamb (t - 1), the indoor air temperature model T at the previous moment t - 1 of the target moment t r (t - 1), and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , the building wall temperature model T at the target moment t is determined by the following formula w (t):

[0203]

[0204] In some embodiments, the indoor air temperature model determination module 307 is specifically configured to

[0205] Based on the mass M of the indoor building air a 、the heat capacity C of the air pa 、the first derivative model the second derivative model and the third derivative model The indoor air temperature T in the building at the target moment t is determined by the following formula r (t) for the derivative model of the indoor air temperature at the target moment t

[0206]

[0207] In response to the target moment t being 1, based on the indoor air temperature derivative model Obtain the equivalent thermal resistance R of the building shell eq 、the indoor air temperature T at the initial time r_ini 、the environmental temperature T at the initial time amb_ini 、the building wall temperature T at the initial time w_ini 、the air - conditioning cooling capacity Q ac 、the operating state S of the air - conditioner at the initial time ac_ini ,and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr ;

[0208] Based on the mass M of the indoor building air a 、the heat capacity C of the air pa 、the equivalent thermal resistance R of the building shell eq 、the indoor air temperature T at the initial time r_ini 、the environmental temperature T at the initial time amb_ini 、the building wall temperature T at the initial time w_ini 、the air - conditioning cooling capacity Q ac 、the operating state S of the air - conditioner at the initial time ac_ini ,and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr, the indoor air temperature model T in the building at the target time t is determined by the following formula: r (t):

[0209] Or,

[0210] In response to the target time t being greater than 1, obtain the equivalent thermal resistance R of the building envelope; eq , the indoor air temperature model T in the building at the previous time t-1 of the target time t; r (t-1), the ambient temperature T at the initial time; amb_ini , the building wall temperature model T at the previous time t-1 of the target time t; w (t-1), the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall; wr , the air conditioning cooling capacity Q at the previous time t-1 of the target time t; ac (t-1) and the operating state S of the air conditioner at the target time t; ac (t);

[0211] Based on the building wall temperature model T at the target time; w (t) determines the building wall temperature model T at the previous time t-1 of the target time t; w (t-1);

[0212] Based on the mass M of the indoor building air; a , the heat capacity C of the air; pa , the equivalent thermal resistance R of the building envelope; eq , the indoor air temperature model T in the building at the previous time t-1 of the target time t; r (t-1), the ambient temperature T at the initial time; amb_ini , the building wall temperature model T at the previous time t-1 of the target time t; w (t-1), the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall; wr , the air conditioning cooling capacity Q at the previous time t-1 of the target time t; ac (t-1) and the operating state S of the air conditioner at the target time t, determine the indoor air temperature model T in the building at the target time t by the following formula: ac (t): r (t):

[0213]

[0214] In some embodiments, the temperature comfort constraint construction module 308 is specifically configured to:

[0215] Obtain the building floor area A where the air conditioner is located;

[0216] Determine the effective building area by using the preset conversion coefficient K of the effective building area and the building area A where the air conditioner is located through the following formula

[0217]

[0218] Obtain the number of people flow R in the building at the previous moment t - 1 of the target moment t t-1 and the number of users entering E at the entrance and exit β of the building at the target moment t tβ and the number of users leaving G at the entrance and exit β of the building at the target moment t tβ ;

[0219] Based on the number of people flow R in the building at the previous moment t - 1 of the target moment t t-1 and the number of users entering E at the entrance and exit β of the building at the target moment t tβ and the number of users leaving G at the entrance and exit β of the building at the target moment t tβ determine the user flow R in the building at the target moment t through the following formula t :

[0220]

[0221] Based on the user flow R in the building at the target moment t t and the effective building area determine the user density D(t) at the target moment t through the following formula:

[0222]

[0223] Obtain the skin temperature T of the user at the target moment t a (t);

[0224] Based on the indoor air temperature model T r (t) at the target moment in the building, the skin temperature T a (t) of the user at the target moment t, the preset user metabolic rate σ 0 , the clothing thermal resistance I cl , the preset constant parameter s and the user density D(t) at the target moment t, determine the temperature comfort model TCI(t) at the target moment t through the following formula:

[0225]

[0226] Determine the first marginal temperature θ corresponding to the temperature comfort model TCI(t) when the value of the temperature comfort model TCI(t) at the target moment t is -1 -1 , and determine the second marginal temperature θ corresponding to the temperature comfort model TCI(t) when the value of the temperature comfort model TCI(t) at the target moment t is 1 1, taking the first marginal temperature θ -1 and the second marginal temperature θ 1 as the temperature comfort index at the target moment.

[0227] In some embodiments, the control device for the flexible load of the building air conditioner further includes a control resource consumption function construction module, and the control resource consumption function construction module is specifically configured to:

[0228] Obtain the power consumption P gb (t) obtained from the external power grid at the power equipment node i at the target moment t, the power resource acquisition consumption parameter C b (t) at the power equipment node i at the target moment t, the power supplied to the external power grid at the power equipment node i at the target moment t is P gs (t), the power configuration consumption parameter C s (t) at the power equipment node i at the target moment t, the rated power P ab (t) of the air conditioner at the target moment t, and the power operation and maintenance resource consumption parameter C o (t) at the power equipment node i at the target moment t;

[0229] Based on the power consumption P gb (t) obtained from the external power grid at the power equipment node i at the target moment t, the power resource acquisition consumption parameter C b (t) at the power equipment node i at the target moment t, the power supplied to the external power grid at the power equipment node i at the target moment t is P gs (t), the power configuration consumption parameter C s (t) at the power equipment node i at the target moment t, the rated power P ab (t) of the air conditioner at the target moment t, the power operation and maintenance resource consumption parameter C o (t) at the power equipment node i at the target moment t and the preset constant parameter time step τ, determine the control resource consumption function C through the following formula:

[0230]

[0231] where t represents the order of the target moment, N represents the number of target moments, i represents the order of the power equipment nodes, and N represents the number of power equipment nodes.

[0232] For the convenience of description, when describing the above device, various modules are described separately according to their functions. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0233] The device of the above embodiment is used to implement the corresponding control method for the flexible load of building air conditioners in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0234] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present application also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the control method for the flexible load of building air conditioners described in any of the above embodiments.

[0235] Figure 4 FIG. shows a more specific schematic diagram of the hardware structure of the electronic device provided in this embodiment. The device may include: a processor 401, a memory 402, an input / output interface 403, a communication interface 404, and a bus 405. Among them, the processor 401, the memory 402, the input / output interface 403, and the communication interface 404 are communicatively connected to each other inside the device through the bus 405.

[0236] The processor 401 may be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0237] The memory 402 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 402 may store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 402 and are called and executed by the processor 401.

[0238] The input / output interface 403 is used to connect to an input / output module to implement information input and output. The input / output module may be configured as a component in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Among them, the input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0239] The communication interface 404 is used to connect to a communication module (not shown in the figure) to achieve communication and interaction between this device and other devices. The communication module can achieve communication through wired means (such as USB, network cable, etc.) or through wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0240] The bus 405 includes a path for transmitting information between various components of the device (such as the processor 401, the memory 402, the input / output interface 403, and the communication interface 404).

[0241] It should be noted that although the above device only shows the processor 401, the memory 402, the input / output interface 403, the communication interface 404, and the bus 405, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device may also only include the components necessary to implement the solution of the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0242] The electronic device of the above embodiment is used to implement the regulation method of the corresponding building air-conditioning flexible load in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0243] Based on the same inventive concept, corresponding to the method of any of the above embodiments, the present application also provides a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute the regulation method of the building air-conditioning flexible load as described in any of the foregoing embodiments.

[0244] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible by a computing device.

[0245] The computer instructions stored in the storage medium of the above embodiments are used to cause the computer to execute the method for regulating the flexible load of the building air conditioner as described in any one of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0246] Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of the present application is limited to these examples; under the concept of the present application, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of brevity.

[0247] In addition, for the sake of simplicity of description and discussion, and in order not to make the embodiments of the present application difficult to understand, the well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. In addition, the devices may be shown in block diagram form in order not to make the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present application will be implemented (i.e., these details should be completely within the understanding of those skilled in the art). In the case where specific details (such as circuits) are set forth to describe the exemplary embodiments of the present application, it will be apparent to those skilled in the art that the embodiments of the present application can be implemented without these specific details or with variations of these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0248] Although the present application has been described in connection with specific embodiments of the present application, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other memory architectures (such as dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0249] The embodiments of the present application are intended to cover all such alternatives, modifications, and variations that fall within the broad scope of the present application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application shall be included within the protection scope of the present application.

Claims

1. A method for controlling flexible load of building air conditioning, characterized in that: include: Obtain the mass of indoor building air, the heat capacity of the air, the mass of indoor building walls, and the heat capacity of the walls; determining the amount of heat transferred from the ambient environment to the indoor air at a target time, a first derivative model for said target time; determining heat exchange between indoor building air and a wall at a target time, a second derivative model for said target time; Determine the air conditioning cooling capacity at a target time, and a third derivative model for the target time; determining the amount of heat transferred from the surroundings to the wall at a target time, a fourth derivative model for said target time; Based on the mass of the indoor building wall, the heat capacity of the wall, the second derivative model and the fourth derivative model, a building wall temperature model at a target time is obtained by processing through a linearization algorithm; Based on the building wall temperature model at the target time, the mass of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model and the third derivative model, a linearization algorithm is used to process to obtain an indoor air temperature model in the building at the target time; The indoor air temperature model in the building at the target time is processed by a temperature comfort algorithm to obtain a temperature comfort index at the target time, and the temperature comfort index at the target time and the indoor air temperature model in the building at the target time are used to construct a user temperature comfort constraint; A pre-constructed control resource consumption function associated with the air conditioner rated power is minimized under the user temperature comfort constraint to obtain a target air conditioner rated power, and the load of the building air conditioner is regulated according to the target air conditioner rated power.

2. The method according to claim 1, characterized in that The step of determining the amount of heat transferred from the surrounding environment to the indoor air at the target time, and the first derivative model of the target time, comprises: Get the ambient temperature T at the target time t amb , Indoor air temperature in the building T r , and the equivalent thermal resistance R of the building shell corresponding to the ambient temperature and the wall surface temperature eq ; Based on the ambient temperature T at the target time t amb , the indoor air temperature T in the building r , and the equivalent thermal resistance R of the building shell corresponding to the ambient temperature and the wall surface temperature eq , the first derivative model is determined by the following formula 3. The method according to claim 1, characterized in that The determining of the heat exchange between the indoor building air and the wall at the target time, and the second derivative model for the target time, comprises: Get the building wall temperature T w , Indoor air temperature in the building T r , and the equivalent thermal resistance R corresponding to the inner surface temperature of the wall and the indoor air temperature wr ; Based on the building wall temperature T w , Indoor air temperature in the building T r , and the equivalent thermal resistance R corresponding to the inner surface temperature of the wall and the indoor air temperature wr The second derivative is determined by the following formula 4. The method according to claim 1, characterized in that: The step of determining the air conditioning cooling capacity at the target time and the third derivative model of the target time includes: Get the coefficient of performance COP of the air conditioner and the rated power P of the air conditioner ac ; Based on the coefficient of performance COP of the air conditioner and the rated power P of the air conditioner ac The third derivative model is determined by the following formula 5. The method according to claim 1, characterized in that The determining of the heat transferred from the surrounding environment to the wall at the target time, and the fourth derivative model at the target time, include: Get the ambient temperature T at the target time t amb and building wall temperature T w ; Based on the ambient temperature T at the target time t amb and the building wall temperature T w The fourth derivative model is determined by the following formula 6. The method according to claim 1, characterized in that The mass of the indoor building wall, the heat capacity of the wall, the second derivative model and the fourth derivative model are processed by a linearization algorithm to obtain a building wall temperature model at a target time, including: Based on the mass M of the interior building wall w , the heat capacity of the wall C pw The second derivative model and the fourth derivative model The derivative model of the building wall temperature at target time t to the building wall temperature at target time t is determined by the following formula: In response to the target time t being 1, based on the building wall temperature derivative model Get the equivalent thermal resistance R between the environment and the exterior surface of the building wall wa , the building wall temperature at the initial time T w_ini , initial ambient temperature T amb_ini , and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr ; Based on the mass M of the interior building wall w , the heat capacity of the wall C pw , the equivalent thermal resistance R between the environment and the outer surface of the building wall wa , the building wall temperature at the initial time T w_ini , initial ambient temperature T amb_ini , the building wall temperature at the initial time T w_ini , the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , the building wall temperature model T at the target time t is determined by the following formula w (t): or, In response to the target time t being greater than 1, based on the building wall temperature derivative model Get the building wall temperature model T at the previous time t-1 of the target time t w (t-1), the equivalent thermal resistance R between the environment and the outer surface of the building wall wa , the ambient temperature T at the previous moment t-1 before the target moment t amb (t-1), indoor air temperature model T at the previous moment t-1 of the target moment t r (t-1), and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr ; Based on the mass M of the interior building wall w , the heat capacity of the wall C pw , the building wall temperature model T at the previous time t-1 of the target time t w (t-1), the equivalent thermal resistance R between the environment and the outer surface of the building wall wa , the ambient temperature T at the previous moment t-1 before the target moment t amb (t-1), indoor air temperature model T at the previous moment t-1 of the target moment t r (t-1), and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , the building wall temperature model T at the target time t is determined by the following formula w (t):

7. The method according to claim 1, characterized in that The building wall temperature model at the target time, the mass of the indoor building air, the heat capacity of the air, the first derivative model, the second derivative model and the third derivative model are processed by a linearization algorithm to obtain the indoor air temperature model in the building at the target time, including: Based on the indoor building air quality M a , the heat capacity of the air C pa , the first derivative model The second derivative model and the third derivative model The indoor air temperature T in the building at the target time t is determined by the following formula r (t) Indoor air temperature derivative model for the target time t In response to the target time t being 1, based on the indoor air temperature derivative model Get the equivalent thermal resistance R of the building shell eq , the indoor air temperature at the initial time T r_ini , initial ambient temperature T amb_ini , the building wall temperature at the initial time T w_ini 、Air conditioning cooling capacity Q ac , the operating status of the air conditioner at the initial time S ac_ini , and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr ; Based on the indoor building air quality M a , the heat capacity of the air C pa , Building shell equivalent thermal resistance R eq , the indoor air temperature at the initial time T r_ini , initial ambient temperature T amb_ini , the building wall temperature at the initial time T w_ini 、Air conditioning cooling capacity Q ac , the operating status of the air conditioner at the initial time S ac_ini , and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , the indoor air temperature model T in the building at the target time t is determined by the following formula r (t): or, In response to the target time t being greater than 1, obtaining the equivalent thermal resistance R of the building shell eq , the indoor air temperature model T in the building at the previous time t-1 of the target time t r (t-1), initial ambient temperature T amb_ini , the building wall temperature model T at the previous time t-1 of the target time t w (t-1), the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr 、Air conditioning cooling capacity Q at the previous time t-1 before the target time t ac (t-1) and the operating state S of the air conditioner at the target time t ac (t); Based on the building wall temperature model T at the target time w (t) Determine the building wall temperature model T at the previous time t-1 of the target time t w (t-1); Based on the indoor building air quality M a , the heat capacity of the air C pa , Building shell equivalent thermal resistance R eq , the indoor air temperature model T in the building at the previous time t-1 of the target time t r (t-1), initial ambient temperature T amb_ini , the building wall temperature model T at the previous time t-1 of the target time t w (t-1), the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr 、Air conditioning cooling capacity Q at the previous time t-1 before the target time t ac (t-1) and the operating state S of the air conditioner at the target time t ac (t), the indoor air temperature model T in the building at the target time t is determined by the following formula r (t):

8. The method according to claim 1, characterized in that: The indoor air temperature model in the building at the target time is processed by a temperature comfort algorithm to obtain a temperature comfort index at the target time, including: Get the building area A of the building where the air conditioner is located; Use the preset building effective area conversion coefficient K and the building area A of the air conditioner to determine the effective building area through the following formula: Get the flow of people R in the building at the previous time t-1 before the target time t t-1 , the number of users entering the building β entrance and exit at the target time t E tβ , the number of users exiting the building β entrance at the target time t G tβ ; Based on the flow of people in the building at the previous time t-1 of the target time t, R t-1 , the number of users entering the building β entrance and exit at the target time t E tβ , the number of users exiting the building β entrance at the target time t G tβ , the user flow R in the building at the target time t is determined by the following formula t : Based on the user flow R in the building at the target time t t and effective building area The user density D(t) at the target time t is determined by the following formula: Get the user's skin temperature T at target time t a (t); Based on the indoor air temperature model T in the building at the target time r (t), user skin temperature T at target time t a (t), preset user metabolic rate σ0, clothing thermal resistance I cl , the preset constant parameter s and the user density D(t) at the target time t, the temperature comfort model TCI(t) at the target time t is determined by the following formula: Determine the first marginal temperature θ corresponding to the temperature comfort model TCI(t) when the value of the temperature comfort model TCI(t) at the target time t is -1 -1 , and determine the second marginal temperature θ1 corresponding to the temperature comfort model TCI(t) when the value of the temperature comfort model TCI(t) at the target time t is 1, and set the first marginal temperature θ -1 And the second marginal temperature θ1 is used as the temperature comfort index at the target moment.

9. The method according to claim 1, characterized in that: The resource consumption control function is constructed by the following process: Get the power P obtained from the external power grid at the power equipment node i at the target time t gb (t), the power resource acquisition consumption parameter C at the power equipment node i at the target time t b (t), the amount of electricity P supplied to the external power grid at the power equipment node i at the target time t gs (t), the power configuration consumption parameter C at the power equipment node i at the target time t s (t), the rated power of the air conditioner at the target time t P ab (t), the power operation and maintenance resource consumption parameter C at the power equipment node i at the target time t o (t); Based on the power P obtained from the external power grid at the power equipment node i at the target time t gb (t), the power resource acquisition consumption parameter C at the power equipment node i at the target time t b (t), the amount of electricity P supplied to the external power grid at the power equipment node i at the target time t gs (t), the power configuration consumption parameter C at the power equipment node i at the target time t s (t), the rated power of the air conditioner at the target time t P ab (t), the power operation and maintenance resource consumption parameter C at the power equipment node i at the target time t o (t) and the preset constant parameter time step τ, the resource consumption function C is determined by the following formula: Among them, t represents the order of the target time, N represents the number of the target time, i represents the order of the power equipment node, and N represents the number of the power equipment node.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 9 is implemented.

Images