Building air conditioner flexible load regulation and control method and electronic equipment

Abstract

The invention provides a building air conditioner flexible load regulation and control method and electronic equipment, and the method comprises the steps: carrying out the processing through a linearization algorithm based on the quality of an indoor building wall, the heat capacity of the wall, a second derivative model and a fourth derivative model, and obtaining a building wall temperature model at a target moment; based on the building wall temperature model at the target moment, the indoor building air quality, the air heat capacity, the first derivative model, the second derivative model and the third derivative model, processing is conducted through a linearization algorithm, an indoor air temperature model in the building at the target moment is obtained, and then a temperature comfort index at the target moment is introduced; a user temperature comfort constraint is constructed according to the indoor air temperature model in the building at the target moment, so that the overall regulation resource consumption and the user experience can be fully considered for the pre-constructed regulation resource consumption function associated with the rated power of the air conditioner under the constraint, and the situation that the regulation resource consumption and the user experience are influenced due to relatively single factors considered by regulation can be avoided. And the use experience of the user cannot be ensured.

Description

Technical Field

[0001] The present application relates to the technical field of power control, and in particular to a control method and electronic equipment for a building air-conditioning flexible load. Background Art

[0002] As a flexible load, air conditioning load is gradually becoming an important part of the controllable load in virtual power plants as users' demand for air conditioning increases significantly.

[0003] However, the factors considered in the related art for regulating the flexible load of building air conditioning are relatively simple and cannot guarantee the user experience. Summary of the invention

[0004] In view of this, the purpose of this application is to propose a control method and electronic equipment for building air-conditioning flexible load to solve the above technical problems.

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

[0006] 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;

[0007] 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;

[0008] determining heat exchange between indoor building air and a wall at a target time, a second derivative model for said target time;

[0009] Determine the air conditioning cooling capacity at a target time, and a third derivative model for the target time;

[0010] determining the amount of heat transferred from the surroundings to the wall at a target time, a fourth derivative model for said target time;

[0011] 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;

[0012] 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;

[0013] 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;

[0014] 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.

[0015] Based on the same inventive concept, the second aspect of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable by the processor, wherein the processor implements the method described in the first aspect above when executing the computer program.

[0016] From the above, it can be seen that the control method and electronic equipment for the flexible load of building air conditioning provided in the present application are 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 time, and 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 through a linearization algorithm to obtain the indoor air temperature model in the building at the target time, and then the temperature comfort index at the target time is introduced, and the user temperature comfort constraint is constructed with the indoor air temperature model in the building at the target time, so that under this constraint, the 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 user experience, and can avoid the problem of not being able to guarantee the user experience due to the relatively single factors considered in the control. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A flow chart of a method for controlling a building air conditioning flexible load according to an embodiment of the present application;

[0019] Figure 2 A schematic diagram of the composition of a virtual power plant control system according to an embodiment of the present application;

[0020] Figure 3This is a structural block diagram of a control device for a building air conditioning flexible load according to an embodiment of the present application;

[0021] Figure 4 A schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to 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 be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0024] It is understandable that before using the technical solutions of each embodiment of the present application, the type, scope of use, 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, in response to receiving an active request from a user, a prompt message is sent to the user to clearly remind the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to the electronic device, application, server, storage medium or other software or hardware that performs the operation of the technical solution of the present application according to the prompt message.

[0026] As an optional but non-limiting implementation, in response to receiving the user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. 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 is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation method of this application. Other methods that meet relevant laws and regulations may also be applied to the implementation method of this application.

[0028] As a flexible load, air conditioning load is gradually becoming an important part of the controllable load in the virtual power plant as the demand for air conditioning by users increases significantly. As a virtual radio resource participating in the power demand response and improving the operating efficiency and reliability of the system, the air conditioning load has a certain tolerance for reducing power, reducing the start-up time or interrupting operation to a certain extent. By giving up some user comfort, the use of some air conditioners can be reduced according to the dispatching needs.

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

[0030] However, due to the complex calculation of the mechanism modeling of air conditioning based on thermodynamic principles, the common relationship between air conditioning power and temperature is usually predicted by a prediction algorithm, that is, a black box model, which has failed to conduct in-depth research on the optimization of building air conditioning energy use.

[0031] This application incorporates air conditioning load into the virtual power plant system, effectively improving the flexible adjustment capability of the power system. The thermoelectric coupling relationship of the air conditioner is refined, and the second-order equivalent thermal parameter model of the air conditioner is established and linearized, which can maximize the adjustable potential of the air conditioning load, and then introduce the temperature comfort index at the target time, and construct the user temperature comfort constraint with the indoor air temperature model in the building at the target time, fully taking into account the overall control resource consumption and user experience, so that the pre-constructed control resource consumption function associated with the rated power of the air conditioner under this constraint can fully take into account the overall control resource consumption and user experience.

[0032] An embodiment of the present application provides a method for regulating the flexible load of a building air conditioner. 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 linearization algorithm is used to process to obtain a building wall temperature model at a target moment. 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, a linearization algorithm is used to process 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.

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

[0034] Step 101, obtaining 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.

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

[0036] Among them, obtaining the quality of indoor building air, the heat capacity of air, the quality of indoor building walls and the heat capacity of walls can be done in the following ways:

[0037] Indoor building air quality: Use air quality testing instruments to directly measure indoor air to determine indoor air quality.

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

[0039] Quality of interior building walls: The quality of walls can be estimated by measuring the thickness and density of the walls.

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

[0041] Step 102, determining the heat transferred from the ambient environment to the indoor air at a target time, and a first derivative model for the target time.

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

[0043] Step 103, determining the heat exchange between the indoor building air and the wall at the target time, and the second derivative model for the target time.

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

[0045] Step 104, determining the air conditioning cooling capacity at the target time, and the third derivative model of the target time.

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

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

[0048] In this step, the second-order equivalent thermal parameter model takes into account the solid temperature (building wall), and the second-order equivalent thermal parameter model includes a fourth derivative model, which describes the rate of change of heat gain 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, a linearization algorithm is used to process to obtain a building wall temperature model at a target time.

[0050] In this step, the building wall temperature model and the indoor air temperature model influence each other. In order to facilitate 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 ​​in any time period.

[0051] Based on the building wall temperature model at the target time, the mass of indoor building air, the heat capacity of air, the first derivative model, the second derivative model and the third derivative model, the indoor air temperature model in the building at the target time is obtained through linearization algorithm. The indoor air temperature model in the building at the target time is the second-order equivalent thermal parameter linearization model 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, a linearization algorithm is used to process and obtain the indoor air temperature model in the building at the target moment.

[0053] In this step, the building wall temperature model and the indoor air temperature model influence each other. In order to facilitate 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 ​​in any time period.

[0054] Based on the building wall temperature model at the target time, the mass of indoor building air, the heat capacity of air, the first derivative model, the second derivative model and the third derivative model, the indoor air temperature model in the building at the target time is obtained through linearization algorithm. The indoor air temperature model in the building at the target time is the second-order equivalent thermal parameter linearization model of the air conditioner.

[0055] Step 108, based on the indoor air temperature model in the building at the target moment, a temperature comfort algorithm is used to process the indoor air temperature model in the building to obtain a 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 in the building at the target moment.

[0056] In this step, the air conditioning satisfaction index is first constructed. The human body's perception of temperature forms the human body's comfort. The temperature comfort index (TCI) is affected by the main factors such as indoor temperature, human metabolic rate and clothing insulation value. The density of building personnel will affect people's comfort. The density of building personnel is introduced to correct TCI.

[0057] The expression of TCI (temperature comfort model) is as follows:

[0058]

[0059] Where, T a (t) is the human skin temperature at the target time t (i.e., the user skin temperature at the target time t), σ0 is the human metabolic rate (i.e., the preset user metabolic rate), I cl is the thermal resistance of clothing (i.e. the thermal resistance between human skin and indoor air). D(t) is the population density at target time t (i.e. the user density at target time t).

[0060] A model of building occupancy density is established based on the black box theory. The building is regarded as a black box, and each entrance and exit is regarded as a connection channel between the black box and the outside world. The flow of people at each entrance and exit is observed and counted in real time, and the changes in the flow of people in the building at different time periods can be obtained. Then, the occupancy density of the corresponding time period is calculated according to the effective area of ​​the building.

[0061]

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

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

[0064] Table 1

[0065]

[0066] When TCI is 1, -1, the corresponding marginal temperature (i.e., the temperature comfort index at the target time) θ1, θ -1 , which is 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-built control resource consumption function associated with the rated power of the air conditioner can fully take into account the overall control resource consumption and user experience.

[0067] Step 109, minimizing a pre-built control resource consumption function associated with the air conditioner rated power under the user temperature comfort constraint to obtain a target air conditioner rated power, and regulating the load of the building air conditioner according to the target air conditioner rated power.

[0068] In this step, the virtual power plant control system consists of Figure 2 As shown, the building air-conditioning load is an adjustable load. In this typical system, the consumption of wind power resources is lower than that of external power grid resources, and as much new energy as possible should be absorbed.

[0069] However, considering the uncertainty of wind turbine power generation, it is necessary to configure energy storage equipment to smooth the output. When the energy storage equipment cannot meet the power balance demand, users can obtain power resources from the external power grid. Conversely, when the user demand is low, power resources can be provided to the external power grid.

[0070] Under the constraint of introducing the temperature comfort index at the target moment, minimizing the 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 user experience, and avoid the problem of being unable to guarantee user experience due to the relatively single factors considered in the control.

[0071] Through the above scheme, 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 the building wall temperature model at the target moment, and the indoor air temperature model in the building at the target moment is obtained by a linearization algorithm 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. 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 control resource consumption function associated with the rated power of the air conditioner can fully take into account the overall control resource consumption and user experience, and can avoid the problem of failure to guarantee user experience due to the relatively single factors considered in the control.

[0072] In some embodiments, step 102 includes:

[0073] Step A1: Obtain 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 .

[0074] Step A2: 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

[0075]

[0076] In the above scheme, the ambient temperature T at the target time t is comprehensively considered. amb , the ambient temperature T at the target time t amb , Building shell equivalent thermal resistance R eq , which can improve the first derivative model The accuracy rate.

[0077] In some embodiments, step 103 includes:

[0078] Step B1, obtain 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 .

[0079] Step B2, 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

[0080]

[0081] In the above scheme, the building wall temperature T is taken into consideration w , Indoor air temperature in the building T r , and the equivalent thermal resistance R between the indoor air of the building and the inner surface of the wall wr , which can improve the second derivative The accuracy rate.

[0082] In some embodiments, step 104 includes:

[0083] Step C1, obtaining 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 The third derivative model is determined by the following formula

[0085]

[0086] In the above scheme, the coefficient of performance COP of the air conditioner and the rated power of the air conditioner are comprehensively considered to improve the third derivative model The accuracy rate.

[0087] In some embodiments, step 105 includes:

[0088] Step D1, obtaining the ambient temperature T at the target time t amb and 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 The fourth derivative model is determined by the following formula

[0090]

[0091] In the above scheme, the ambient temperature T at the target time t is comprehensively considered. amb The building wall temperature T w , which can improve the fourth derivative model The accuracy rate.

[0092] In some embodiments, step 106 includes:

[0093] Step E1, based on the mass M of the indoor 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:

[0094]

[0095] Step E2, 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 .

[0096] Step E3, based on the mass M of the indoor building wall w , the heat capacity of the wall Cpw , 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):

[0097] or,

[0098] Step E4, 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 .

[0099] Step E5, based on the mass M of the indoor 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):

[0100]

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

[0102] In order to facilitate 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 ​​in any time period. The second-order equivalent thermal parameter linearization model of the air conditioner (i.e., the building wall temperature model T at 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 at the target time t w (t) is:

[0104] or,

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

[0106]

[0107] In some embodiments, step 107 includes:

[0108] Step F1, based on the quality M of the indoor building air 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

[0109]

[0110] Step F2, 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 .

[0111] Step F3, based on the quality M of the indoor building air 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):

[0112] or,

[0113] Step F4, 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), 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 、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).

[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 quality M of the indoor building air 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), 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 、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):

[0116]

[0117] In the above scheme, the indoor air temperature derivative model at the target time t is Related to the rate of change of indoor air temperature.

[0118] In order to facilitate 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 ​​in any time period. The second-order equivalent thermal parameter linearization model of the air conditioner (i.e., the indoor air temperature model T in the building at the target time t) r (t)) is expressed as follows:

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

[0120] or,

[0121] When the target moment At the target time t, the indoor air temperature model T r (t) is:

[0122]

[0123] In some embodiments, in step 108, 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:

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

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

[0126]

[0127] Step G3, obtain the flow of people in the building R 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 .

[0128] Step G4: based on the flow of people in the building at the previous time t-1 before 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 :

[0129]

[0130] Step G5: 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:

[0131]

[0132] Step G6, obtaining the user's skin temperature T 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), 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:

[0134]

[0135] Step G8, determining 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.

[0136] In the above scheme, the air conditioning satisfaction index is first constructed. The human body's perception of temperature forms the human body's comfort. The temperature comfort index (TCI) is affected by the main factors such as indoor temperature, human metabolic rate and clothing insulation value. The density of building personnel will affect people's comfort. The density of building personnel is introduced to correct TCI.

[0137] The expression of TCI (temperature comfort model) is as follows:

[0138]

[0139] Where, T a (t) is the human skin temperature at the target time t (i.e., the user skin temperature at the target time t), σ0 is the human metabolic rate (i.e., the preset user metabolic rate), I cl is the thermal resistance of clothing (i.e. the thermal resistance between human skin and indoor air). D(t) is the population density at target time t (i.e. the user density at target time t).

[0140] A model of building occupancy density is established based on the black box theory. The building is regarded as a black box, and each entrance and exit is regarded as a connection channel between the black box and the outside world. The flow of people at each entrance and exit is observed and counted in real time, and the changes in the flow of people in the building at different time periods can be obtained. Then, the occupancy density of the corresponding time period is calculated according to the effective area of ​​the building.

[0141]

[0142]

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

[0144] When the TCI value is in the range of [-0.5, 0.5], the temperature change is subtle and the human body cannot feel it. Therefore, the range of [-1, 1] is considered to be a comfortable temperature range for the human body, as shown in Table 1 below:

[0145] Table 1

[0146]

[0147] When TCI is 1, -1, the corresponding marginal temperature (i.e., the temperature comfort index at the target time) is θ1 (i.e., the second marginal temperature), θ -1 (i.e., the first marginal temperature) is used to construct the user temperature comfort constraint (i.e., θ -1 ≤T r (t)≤θ1).

[0148] In some embodiments, the resource consumption control function is constructed by the following process:

[0149] Step H1, obtaining 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).

[0150] Step H2: 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:

[0151]

[0152] 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.

[0153] In the above scheme, the virtual power plant control system consists of Figure 2 As shown, the building air-conditioning load is an adjustable load. In this typical system, the consumption of wind power resources is lower than that of external power grid resources, and as much new energy as possible should be absorbed.

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

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

[0156] The dispatch is carried out 24 hours in advance, and the dispatch time scale is selected as 1 hour. The scenario generation method is used to deal with the uncertainty of wind power output and power acquisition resource consumption, and the minimum regulation resource consumption is taken as the objective function (that is, the regulation resource consumption function is minimized).

[0157]

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

[0159] θ -1 ≤T r (t)≤θ1.

[0160] Among them, the constraints may also include power balance constraints, power constraints for obtaining power resources by a virtual power plant (Virtual Power Plant, VPP), energy storage constraints, etc.

[0161] The minimization process of the 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 due to the relatively single factor considered in the regulation.

[0162] In addition, the intraday rolling optimization 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 deviation caused by the long-term prediction error of the day before, the error of the model itself, and the change of climate conditions within the day. Therefore, the output error penalty is added to the intraday scheduling, and the sum of the total resource consumption of the virtual power plant and the output deviation penalty within the scheduling cycle is minimized as the objective function. The rolling optimization step length is selected as 15 minutes, and the rolling optimization process is as follows:

[0163] In the first time step, the parameters including power acquisition resource consumption, ambient temperature and wind energy output are determined based on the ultra-short-term power forecast data. The Mixed Integer Programming (MIP) model calculates and generates a set of parameters (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 energy output, the data T generated in the previous step, etc.), the particle swarm optimization algorithm is used to solve the objective function and 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 planning horizon is completed.

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

[0167] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0168] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a control device for building air-conditioning flexible load.

[0169] refer to Figure 3 The control device for the building air conditioning flexible load comprises:

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

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

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

[0173] The third derivative model determination module 304 is configured to determine the air conditioning cooling capacity at the target moment, and the third derivative model at the target moment;

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

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

[0176] The indoor air temperature model determination module 307 is configured to obtain the indoor air temperature model in the building at the target time 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;

[0177] The temperature comfort constraint building module 308 is configured to process the indoor air temperature model in the building at the target time through a temperature comfort algorithm to obtain a temperature comfort index at the target time, and to build a user temperature comfort constraint using the temperature comfort index at the target time and the indoor air temperature model in the building at the target time;

[0178] The air conditioning load control module 309 is configured to minimize the pre-built control resource consumption function associated with the air conditioning rated power under the user temperature comfort constraint, obtain the target air conditioning rated power, and control 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] 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 ;

[0181] 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

[0182]

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

[0184] 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 ;

[0185] 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

[0186]

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

[0188] Get 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 The third derivative model is determined by the following formula

[0190]

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

[0192] Get the ambient temperature T at the target time t amb and 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 The fourth derivative model is determined by 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 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:

[0197]

[0198] 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 ;

[0199] 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):

[0200] or,

[0201] 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 ;

[0202] 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):

[0203]

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

[0205] 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

[0206]

[0207] 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 ;

[0208] 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):

[0209] or,

[0210] 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), 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 、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);

[0211] 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);

[0212] 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), 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 、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):

[0213]

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

[0215] Get the building area A of the building where the air conditioner is located;

[0216] 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:

[0217]

[0218] 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 ;

[0219] 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 :

[0220]

[0221] 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:

[0222]

[0223] Get the user's skin temperature T at target time t a (t);

[0224] 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:

[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 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.

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

[0228] 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);

[0229] 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:

[0230]

[0231] 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.

[0232] For the convenience of description, the above device is described in terms of functions divided into various modules. 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 building air-conditioning flexible load control method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0234] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for controlling the flexible load of the building air conditioner as described in any of the above embodiments is implemented.

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

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

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

[0238] The input / output interface 403 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. 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 a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0240] The bus 405 comprises a pathway for transmitting information between the various components of the device (eg, 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, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present 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 corresponding building air-conditioning flexible load control method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0243] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method for controlling the flexible load of building air conditioning as described in any of the above 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. Information can be computer-readable instructions, data structures, modules of programs, 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 technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0245] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method for controlling the flexible load of building air conditioning as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0246] A person skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0247] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making 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 to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0248] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0249] The embodiments of the present application are intended to cover all such substitutions, 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 should be included in 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 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.

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