Control strategy determination method and device of air conditioning system, electronic equipment and storage medium

Abstract

The invention discloses a control strategy determination method and device of an air conditioning system, electronic equipment and a storage medium. Comprising the steps that a building and air-conditioning system partition model is created, and building and air-conditioning system partitions comprise an inner area and an outer area; for any load type of the building, air conditioner working modes corresponding to the inner area and the outer area are set, and setting models corresponding to the air conditioner working modes are obtained; undetermined parameters in the air conditioner working modes corresponding to the inner area and the outer area are sampled, and a plurality of sample parameter sets are obtained; based on the multiple sample parameter sets, air conditioner operation simulation is conducted on the building and air conditioner system partition model, and simulation operation indexes corresponding to the multiple sample parameter sets are obtained; and determining an air conditioning system control strategy of the building for the load type based on the simulation operation index. According to the scheme, the corresponding air conditioning system control strategy is determined according to any load type of the building, partition control over the air conditioning system is achieved, and the accuracy and adaptability of air conditioning system control are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of system control, and particularly to a method, device, electronic device and storage medium for determining a control strategy of an air conditioning system. Background Art

[0002] A variable air volume air conditioning system is an energy-saving all-air central air conditioning system, which is widely used in commercial and office buildings. Reasonably setting its supply air temperature is an effective means to improve the energy efficiency of the air conditioning system.

[0003] Traditional control uses a fixed supply air temperature, sets corresponding fixed values according to different services, and adjusts the indoor temperature by variable air volume at the end. The fixed temperature supply air method ignores the law of indoor heat load change caused by the change of load with outdoor meteorological conditions, and sometimes leads to the occurrence of simultaneous refrigeration and heating phenomena, as well as excessive supply air volume, resulting in waste of energy. Improved methods include linearly resetting the supply air temperature according to the average temperature of the partition and the outdoor temperature, which improves the simultaneous refrigeration and heating phenomena to a certain extent, but has poor flexibility. It also corrects the supply air temperature by considering the outdoor temperature and introducing the fan speed on the basis of linear change, and adjusts the supply air temperature as the fan speed increases / decreases. However, there is still a problem of being unable to determine the optimal supply air temperature, and the existing methods also fail to consider the influence of load factors such as refrigeration in the transition season or regional cooling and heating loads, and fail to independently adjust the supply air temperature for the internal and external partitions and the regional cooling and heating load conditions, resulting in poor adaptability and inaccuracy of the air conditioning system control. Summary of the Invention

[0004] The present invention provides a method, device, electronic device and storage medium for determining a control strategy of an air conditioning system, so as to solve the problems of poor accuracy and adaptability of the air conditioning system control and inability to adaptively control the internal and external partitions and the regional heat load conditions.

[0005] According to an aspect of the present invention, there is provided a method for determining a control strategy of an air conditioning system, including:

[0006] Create a building and air conditioning system partition model, where the building and air conditioning system partition includes an inner zone and an outer zone;

[0007] For any load type of the building, set the air conditioning working modes corresponding to the inner zone and the outer zone respectively, obtain the setting model corresponding to the air conditioning working mode, and the setting model includes undetermined parameters;

[0008] Sample the undetermined parameters in the air conditioning working modes corresponding to the inner zone and the outer zone respectively to obtain a plurality of sample parameter groups;

[0009] Based on multiple sets of sample parameters, perform air-conditioning operation simulations on the building and air-conditioning system zoning model respectively to obtain the simulated operation indicators corresponding to each set of sample parameters; determine the air-conditioning system control strategy for the building according to the load type based on the simulated operation indicators corresponding to multiple sets of sample parameters.

[0010] Optionally, the setting model corresponding to any air-conditioning working mode includes a supply air temperature setting sub-model and a chilled water temperature setting sub-model; perform air-conditioning operation simulations on the building and air-conditioning system zoning model respectively based on multiple sets of sample parameters to obtain the simulated operation indicators corresponding to each set of sample parameters, including: for any set of sample parameters, determine the supply air temperature and chilled water temperature in the inner zone during the simulation process based on the set of sample parameters and the setting model corresponding to the air-conditioning working mode in the inner zone; and determine the supply air temperature and chilled water temperature in the outer zone during the simulation process based on the set of sample parameters and the setting model corresponding to the air-conditioning working mode in the outer zone; perform air-conditioning operation simulations on the building and air-conditioning system zoning model based on the supply air temperature and chilled water temperature in the inner zone during the simulation process, and the supply air temperature and chilled water temperature in the outer zone to obtain the simulated operation indicators corresponding to each set of sample parameters.

[0011] Optionally, the air-conditioning working modes include a cooling mode and a heating mode; the air-conditioning working modes corresponding to the inner zone and the outer zone are the same or different; the supply air temperature setting sub-model and the chilled water temperature setting sub-model corresponding to the cooling mode are determined based on the first undetermined parameter and the indoor temperature of the building respectively; the supply air temperature setting sub-model corresponding to the heating mode is determined based on the second undetermined parameter and the indoor temperature of the building; the chilled water temperature setting sub-model corresponding to the heating mode is determined based on the third undetermined parameter and the outdoor temperature of the building.

[0012] Optionally, determining the air-conditioning system control strategy for the building according to the load type based on the simulated operation indicators corresponding to multiple sets of sample parameters includes: training a prediction model based on the simulated operation indicators corresponding to multiple sets of sample parameters, and the prediction model is used to determine the simulated operation indicators corresponding to the input parameter set; performing iterative optimization processing on the parameter values of the undetermined parameters based on the target optimization algorithm: in any iterative optimization process, determine the candidate parameter set obtained in the current iteration, and determine the simulated operation indicators corresponding to the candidate parameter set based on the prediction model, and use the simulated operation indicators as the fitness data in the iterative optimization process until the target parameter set is obtained, and determine the air-conditioning system control strategy for the building according to the load type based on the target parameter set.

[0013] Optionally, the method further includes: during the control process of the air-conditioning system based on the air-conditioning system control strategy, obtain the actual operation indicators corresponding to the target parameter set in the air-conditioning system control strategy, update the prediction model based on the target parameter set and the actual operation indicators, and update the target parameter set based on the updated prediction model, and update the air-conditioning system control strategy for the building according to the load type.

[0014] Optionally, the air conditioning system control strategy corresponding to any load type includes a first air conditioning system control strategy for the inner zone and a second air conditioning system control strategy for the outer zone.

[0015] Optionally, the method further includes: determining the target load type of the building based on the external building environment information, and invoking the air conditioning system control strategy corresponding to the target load type, where the air conditioning system control strategy corresponding to the target load type includes a first air conditioning system control strategy for the inner zone and a second air conditioning system control strategy for the outer zone; and executing the first air conditioning system control strategy for the inner zone and the second air conditioning system control strategy for the outer zone to control the air conditioning system of the building.

[0016] According to another aspect of the present invention, there is provided a device for determining an air conditioning system control strategy, including:

[0017] A building and air conditioning system partition model creation module for creating a building and air conditioning system partition model, where the building and air conditioning system partition includes an inner zone and an outer zone;

[0018] A setting model determination module for setting the air conditioning operating modes corresponding to the inner zone and the outer zone respectively for any load type of the building, obtaining the setting model corresponding to the air conditioning operating mode, and the setting model includes undetermined parameters;

[0019] A sample parameter group determination module for sampling the undetermined parameters in the air conditioning operating modes corresponding to the inner zone and the outer zone respectively to obtain a plurality of sample parameter groups;

[0020] An air conditioning system control strategy determination module for performing air conditioning operation simulation on the building and air conditioning system partition model respectively based on a plurality of sample parameter groups to obtain simulation operation indexes corresponding to the plurality of sample parameter groups respectively; and determining the air conditioning system control strategy of the building for the load type based on the simulation operation indexes corresponding to the plurality of sample parameter groups respectively.

[0021] According to another aspect of the present invention, there is provided an electronic device, the electronic device includes:

[0022] At least one processor; and

[0023] A memory communicatively connected to the at least one processor; wherein,

[0024] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining the air conditioning system control strategy according to any embodiment of the present invention.

[0025] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the control strategy determination method of the air-conditioning system according to any embodiment of the present invention when executed.

[0026] The technical solution of the embodiment of the present invention is as follows: By creating a building and air-conditioning system partition model, the building and air-conditioning system partition includes an inner zone and an outer zone; for any load type of the building, set the air-conditioning working modes corresponding to the inner zone and the outer zone respectively, obtain the setting model corresponding to the air-conditioning working mode, and the setting model includes undetermined parameters; sample the undetermined parameters in the air-conditioning working modes corresponding to the inner zone and the outer zone respectively to obtain multiple sample parameter groups; based on the multiple sample parameter groups, perform air-conditioning operation simulation on the building and air-conditioning system partition model respectively to obtain the simulation operation indexes corresponding to the multiple sample parameter groups respectively; determine the air-conditioning system control strategy of the building for the load type based on the simulation operation indexes corresponding to the multiple sample parameter groups respectively. In this solution, for any load type, the building and air-conditioning system partition model of the corresponding inner zone and outer zone, as well as multiple samples corresponding to each model, are determined. Based on the multiple samples, the corresponding models are simulated to obtain the simulation operation indexes corresponding to each sample parameter group, so as to obtain the sample parameter group corresponding to the optimal operation index, so as to obtain the air-conditioning system strategy for the load type. It realizes the simulation of the building and air-conditioning system model under the corresponding load type through multiple sample parameter groups to obtain the building and air-conditioning system partition model with the optimal operation index, and obtains the air-conditioning system control strategy of the building for the load type, solving the problems of poor accuracy and adaptability of the air-conditioning system control, and being unable to adaptively control the internal and external partitions and the regional heat load situation, and improving the operation performance of the entire air-conditioning system.

[0027] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0029] Figure 1 It is a flowchart of a method for determining a control strategy of an air-conditioning system provided in Embodiment 1 of the present invention;

[0030] Figure 2It is a flowchart of a method for determining a control strategy of an air conditioning system provided in Embodiment 2 of the present invention;

[0031] Figure 3 It is a schematic structural diagram of a device for determining a control strategy of an air conditioning system provided in Embodiment 3 of the present invention;

[0032] Figure 4 It is a schematic structural diagram of an electronic device for implementing the method for determining a control strategy of the air conditioning system according to the embodiment of the present invention. Detailed implementation manners

[0033] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0035] Embodiment 1

[0036] Figure 1 It is a flowchart of a method for determining a control strategy of an air conditioning system provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of determining the control strategy of an air conditioning system. This method can be executed by a device for determining the control strategy of an air conditioning system, and the device for determining the control strategy of an air conditioning system can be implemented in the form of hardware and / or software. The device for determining the control strategy of an air conditioning system can be configured in an electronic device such as a control device and a server of an air conditioning system. As Figure 1 shown, the method includes:

[0037] S110. Create a building and air conditioning system partition model, where the building and air conditioning system partition includes an inner zone and an outer zone.

[0038] Among them, the building and air-conditioning system zoning model can be specifically understood as a three-dimensional mathematical model representing the physical space area of the building and the air-conditioning system, which is used to replace the actual building and air-conditioning system and simulate its energy consumption behavior. The physical space within a preset distance inward from the boundary of the three-dimensional mathematical model of the entire building is set as the outer zone, and the physical space outside the outer zone within the entire building is set as the inner zone. Then, the corresponding building and air-conditioning system can be zoned according to the physical zoning within the building, that is, the inner zone and the corresponding air-conditioning system are set as the inner zone model of the building and air-conditioning system, and the outer zone and the corresponding air-conditioning system are set as the outer zone model of the building and air-conditioning system, thereby obtaining the building and air-conditioning system zoning model.

[0039] Specifically, a corresponding building and air-conditioning zoning model can be created according to the overall space design of the building to zone the physical space of the entire building and the corresponding air-conditioning system. In this embodiment, the physical space of the entire building and the corresponding air-conditioning system can be divided into an outer zone and an inner zone, thereby obtaining the building and air-conditioning system zoning model. Exemplarily, the physical space within a preset distance inward from the boundary of the three-dimensional mathematical model of the entire building is set as the outer zone, and the preset distance can be set according to the range affected by the outdoor environmental conditions on the inner side of the outer wall of the building. For example, it can be set to 2m. The outer zone and the corresponding air-conditioning system are constructed as the outer zone model of the building and air-conditioning system, the physical space outside the outer zone within the entire building is set as the inner zone, and the inner zone and the corresponding air-conditioning system are constructed as the inner zone model of the building and air-conditioning system.

[0040] In this embodiment, by creating the building and air-conditioning system zoning model to simulate the overall temperature control of the actual building and air-conditioning system, it helps to achieve zoning processing of the building and air-conditioning system, reasonably consider the environmental changes in the inner and outer zones to determine the corresponding air-conditioning control strategy, so as to improve the accuracy of the air-conditioning system control of the entire building.

[0041] S120. For any load type of the building, set the air-conditioning working modes corresponding to the inner zone and the outer zone respectively, obtain the setting model corresponding to the air-conditioning working mode, and the setting model includes undetermined parameters.

[0042] It is understandable that the meteorological conditions outside the building are different, and the loads of the corresponding air conditioning systems of the building also vary. Different load types can be set according to the different meteorological conditions outside the building. The meteorological conditions outside the building include, but are not limited to, temperature conditions, humidity conditions, and solar radiation intensity. Exemplarily, the greater the temperature difference between the inside and outside of the building, the stronger the load. Corresponding load types can be set according to the strength of the load. Exemplarily, the strength of the load can be classified by level, and then the corresponding load types can be set according to the classification results. The representation of the load type can be represented by numbers or strings, which is not limited here. The air conditioning working modes of the inner zone and the outer zone corresponding to different load types are different. Exemplarily, if the temperature outside the building is too low, the air conditioning system needs to enter the heating mode, and the load type can be set to the strong heating load type, and the corresponding air conditioning working modes of the outer zone and the inner zone are both set to the heating mode. If the temperature outside the building is too high, the air conditioning system needs to enter the cooling mode, and the load type can be set to the forced cooling load type, and the corresponding air conditioning working modes of the outer zone and the inner zone are both set to the cooling mode. If the temperature outside the building is lower than the preset temperature and the temperature difference is within the preset temperature difference threshold, the load type can be set to the normal load type, the air conditioning working mode of the outer zone is set to the heating mode, and the air conditioning working mode of the inner zone can be set to the heating mode or the cooling mode to ensure that the temperature inside the building meets the temperature comfort requirements. It should be noted that the load type can be set according to the temperature outside each building and the requirements for temperature comfort, and the corresponding air conditioning working modes of the inner zone and the outer zone corresponding to each load type are set, which is not limited here. The various load types, the air conditioning working models of the inner zone corresponding to the load types, the air conditioning working modes of the outer zone, and the setting models corresponding to the air conditioning working modes can be stored in the preset storage space in advance and can be flexibly retrieved during the operation of the air conditioning system.

[0043] Among them, the setting model can be specifically understood as the adjustment model corresponding to the air conditioning working mode. The adjustment model is a mathematical model that describes the relationship between the control temperature and the undetermined parameters corresponding to different air conditioning working modes. It can be a relational expression constructed by undetermined parameters and control temperature. Exemplarily, the setting model includes, but is not limited to, the supply air temperature setting sub-model and the water outlet temperature setting sub-model. The supply air temperature setting sub-model is used to determine the supply air temperature, and the water outlet temperature setting sub-model is used to determine the water outlet temperature. The undetermined parameters include, but are not limited to, the parameters corresponding to the water supply temperature setting sub-model and the parameters corresponding to the water outlet temperature setting sub-model.

[0044] Specifically, the corresponding load type can be determined according to the external temperature of the building. When the load type corresponding to the building is determined, the air-conditioning working modes corresponding to the inner zone and the outer zone are respectively matched from a preset storage space, and then the corresponding setting models are matched according to the air-conditioning working modes, so as to obtain the setting models corresponding to the outer zone and the inner zone respectively, where the setting model includes undetermined parameters.

[0045] In this embodiment, for any load type of the building, the setting models corresponding to the inner zone and the outer zone of the load type are determined, which is used to determine the control strategies of the air-conditioning systems corresponding to each zone, helps to accurately determine the setting models of each zone according to the temperature control requirements of each zone, and helps to improve the accuracy and adaptability of the control strategies of the air-conditioning control system.

[0046] S130. Sample the undetermined parameters in the air-conditioning working modes corresponding to the inner zone and the outer zone respectively to obtain a plurality of sample parameter groups.

[0047] Specifically, obtain the undetermined parameters in the air-conditioning working modes corresponding to the inner zone and the outer zone respectively from the historical operation data of the air-conditioning system, and sample in the historical data through a preset big data sampling processing method to obtain a plurality of sample parameter groups. Each sample parameter group includes a plurality of parameter data. Exemplarily, a sample parameter group can be set as (a 1 , a 2 , a 3 , T b1 . T b2 ). Among them, the preset big data sampling processing method includes but is not limited to Latin hypercube sampling, Monte Carlo sampling, and orthogonal data sampling.

[0048] In this embodiment, sampling processing is performed through a big data sampling method to obtain a plurality of sample parameter groups, which are used for subsequent air-conditioning operation simulation of the building and the air-conditioning system partition model, so as to ensure the sufficiency of the number of sample parameter groups in the model simulation process, and helps to improve the accuracy of determining the optimal air-conditioning system control strategy.

[0049] S140. Based on the plurality of sample parameter groups, perform air-conditioning operation simulation on the building and the air-conditioning system partition model respectively to obtain the simulated operation indexes corresponding to the plurality of sample parameter groups respectively; determine the air-conditioning system control strategy of the building for the load type based on the simulated operation indexes corresponding to the plurality of sample parameter groups respectively.

[0050] Among them, the simulation operation index can be specifically understood as the key index to be concerned during the simulation process of the building and air-conditioning system partition model, which is used to evaluate the simulation results obtained by the building and air-conditioning system partition model according to each sample parameter group. The simulation operation index includes but is not limited to the energy consumption index and the temperature comfort index. In this embodiment, the simulation software can be used to perform air-conditioning operation simulation on the building and air-conditioning system partition model according to multiple sample parameter groups respectively, so as to obtain the corresponding simulation operation index. The air-conditioning system control strategy can be understood as the control algorithm adopted to enable the air-conditioning system to meet the requirements such as energy consumption and temperature comfort during operation. In this embodiment, the air-conditioning system control strategy specifically refers to the parameter group corresponding to the optimal simulation operation index. According to the parameter group, the corresponding setting model can also be determined. Therefore, the air-conditioning system control strategy can also be understood as the setting model of each air-conditioning working mode corresponding to the load type.

[0051] Specifically, the simulation software is used to perform air-conditioning operation simulation on the building and air-conditioning system partition model according to multiple sample parameter groups respectively, and obtain the simulation operation indexes corresponding to the multiple sample parameter groups respectively. Then, the optimal simulation operation index is selected from each simulation operation index, and the sample parameter group corresponding to the optimal simulation operation index is set as the air-conditioning system control strategy corresponding to the corresponding load type. Or, the setting model adjusted according to the sample parameter group corresponding to the optimal simulation operation index for the setting model of the corresponding air-conditioning working mode can also be used as the air-conditioning system control strategy. Optionally, the air-conditioning system control strategy corresponding to any load type includes the first air-conditioning system control strategy for the inner zone and the second air-conditioning system control strategy for the outer zone. Among them, the first air-conditioning system control strategy and the second air-conditioning system control strategy are specifically used to distinguish the air-conditioning control strategies for the inner and outer zones. The first air-conditioning system control strategy specifically represents the control strategy for the inner zone, and the second air-conditioning system control strategy specifically represents the air-conditioning control strategy for the outer zone.

[0052] Optionally, the setting model corresponding to any air-conditioning working mode includes a supply air temperature setting sub-model and a chilled water temperature setting sub-model; based on multiple sample parameter groups, perform air-conditioning operation simulation on the building and air-conditioning system partition model respectively, and obtain the simulation operation indexes corresponding to the multiple sample parameter groups respectively, including: for any sample parameter group, determine the supply air temperature and chilled water temperature in the inner zone during the simulation process based on the sample parameter group and the setting model corresponding to the air-conditioning working mode in the inner zone; and determine the supply air temperature and chilled water temperature in the outer zone during the simulation process based on the sample parameter group and the setting model corresponding to the air-conditioning working mode in the outer zone; perform air-conditioning operation simulation on the building and air-conditioning system partition model based on the supply air temperature and chilled water temperature in the inner zone during the simulation process, and the supply air temperature and chilled water temperature in the outer zone, and obtain the simulation operation indexes corresponding to the sample parameter groups respectively.

[0053] In this embodiment, the air conditioner operating modes include a heating mode and a cooling mode. The setting model corresponding to each air conditioner operating mode includes a supply air temperature setting sub-model and a water outlet temperature setting sub-model. Among them, when the air conditioner operating mode is the heating mode, the supply air temperature setting sub-model can be expressed as: T s-heating = 22 + a 1 (T b1 - T in ), where T s-heating represents the heating supply air temperature, a 1 and T b1 are parameters corresponding to the heating supply air temperature in the supply air temperature setting sub-model, and T in represents the indoor temperature; the water outlet temperature setting sub-model can be expressed as: T Hot Water = 71.5 + a 3 *(T b1 - T out ), where T Hot Water represents the heating water outlet temperature, a 3 and T b1 are parameters corresponding to the heating water outlet temperature in the water outlet temperature setting sub-model, and T out represents the outdoor temperature. When the air conditioner operating mode is the cooling mode, the supply air temperature setting sub-model can be expressed as: T s-cooling = 13 + a 2 (T in - T b2 ), where T s-cooling represents the cooling supply air temperature, a 2 and T b2 are parameters corresponding to the cooling supply air temperature in the supply air temperature setting sub-model, and T in represents the indoor temperature; the water outlet temperature setting sub-model can be expressed as: T Chilled = T s-cooling - 5, where T Chilled represents the cooling water outlet temperature.

[0054] For any set of sample parameters, adjust the setting model corresponding to the air-conditioning operation mode in the inner zone according to the set of sample parameters. The indoor temperature data and outdoor temperature data corresponding to the set of sample parameters are used as known data. Through the adjusted setting model, calculate the supply air temperature and water outlet temperature in the inner zone during the simulation process. Also, adjust the setting model corresponding to the air-conditioning operation mode in the outer zone according to the set of sample parameters. The indoor temperature data and outdoor temperature data corresponding to the set of sample parameters are used as known data, and fill them into the setting model after parameter adjustment to calculate the supply air temperature and water outlet temperature in the outer zone during the simulation process. Use the obtained supply air temperature and water outlet temperature in the inner zone to perform air-conditioning operation simulation on the building and air-conditioning system zoning model through simulation software to obtain the simulation operation indexes corresponding to each set of sample parameters. Also, use the obtained supply air temperature and water outlet temperature in the outer zone to perform air-conditioning operation simulation on the building and air-conditioning system zoning model through simulation software to obtain the simulation operation indexes corresponding to the set of sample parameters. It should be noted that if the output data of the simulation software is the data corresponding to the simulation operation indexes, the output result of the simulation software can be used as the simulation operation index data. If the output data of the simulation software is the simulated temperature data, then the simulated temperature data obtained through simulation operation can be compared with the preset control temperature, and the corresponding temperature comfort level can be determined according to the temperature difference, so as to obtain the corresponding temperature comfort index data. If the output data of the simulation software is the simulated energy consumption data, then compare the energy consumption data with the preset energy consumption threshold to determine the energy consumption index data. It is also possible to determine the temperature comfort index and energy consumption index corresponding to each set of sample parameters simultaneously according to the above method, that is, use the temperature comfort index and energy consumption index as the simulation operation indexes simultaneously.

[0055] In this embodiment, multiple sets of sample parameters obtained by the big data sampling method and the setting models of each air-conditioning operation mode are used to determine the supply air temperature and water outlet temperature in the inner zone and outer zone corresponding to each set of sample parameters. Then, based on the supply air temperature and water outlet temperature, perform air-conditioning operation simulation on the building and air-conditioning system zoning model to obtain the simulation operation indexes corresponding to multiple sets of sample parameters, so as to determine the set of sample parameters with the optimal simulation operation indexes, in order to obtain the accurate supply air temperature and water outlet temperature corresponding to the air-conditioning systems in the inner zone and outer zone respectively, realizing the continuous optimization of the air-conditioning control system according to the measured data and simulation data, which helps to improve the accuracy of the air-conditioning control strategy.

[0056] Optionally, the air-conditioning operation modes include a cooling mode and a heating mode; the air-conditioning operation modes corresponding to the inner zone and the outer zone are the same or different; the supply air temperature setting sub-model and the water outlet temperature setting sub-model corresponding to the cooling mode are respectively determined based on the first undetermined parameter and the indoor temperature of the building; the supply air temperature setting sub-model corresponding to the heating mode is determined based on the second undetermined parameter and the indoor temperature of the building; the water outlet temperature setting sub-model corresponding to the heating mode is determined based on the third undetermined parameter and the outdoor temperature of the building.

[0057] Among them, the first undetermined parameter specifically represents the undetermined parameter corresponding to the cooling mode, and the second undetermined parameter specifically represents the undetermined parameter corresponding to the heating mode. The first undetermined parameter and the second undetermined parameter respectively include the parameter items in the sample parameter group. Exemplarily, for the supply air temperature setting sub-model corresponding to the cooling mode, the first undetermined parameter includes a 1 and T b1 .

[0058] Specifically, in order to make the temperature comfort of the inner zone and the outer zone meet the user's needs, the air-conditioning working modes of the inner zone and the outer zone can be set according to the actual temperature control requirements. The air-conditioning working modes of the inner zone and the outer zone can be set to be the same or different. Exemplarily, for the air-conditioning working mode of the inner zone, it can be set to the cooling mode and the cooling mode, or it can be set to the cooling mode and the heating mode. The settings of the air-conditioning working modes of the inner zone and the outer zone are set according to the actual heating and cooling requirements. The first undetermined parameter includes a 2 and T b2 , the indoor temperature of the building is T in , and the supply air temperature setting sub-model corresponding to the cooling mode can be expressed as T s-cooling =13 + a 2 (T in -T b2 ). The outlet water temperature setting sub-model corresponding to the cooling mode can be expressed as: T Chilled =T s-cooling -5. The second undetermined parameter includes a 1 and T b1 , the indoor temperature of the building is T in , and the supply air temperature setting sub-model corresponding to the heating mode can be expressed as T s-heating =22 + a 1 (T b1 -T in ); The third undetermined parameter includes a 3 and T b1 , the outdoor temperature of the building is T out , and the outlet water temperature setting sub-model corresponding to the heating mode can be expressed as T Hot Water =71.5 + a 3 *(T b1 -T out ). Therefore, in the case of obtaining the optimal sample parameter group, the optimal sample parameter group can be assigned to the setting models corresponding to the air-conditioning working modes of each zone to obtain the setting models that conform to the current air-conditioning working modes of each zone, which are used to adjust and control the temperature according to the setting models of each zone.

[0059] Based on the above embodiments, the method further includes: determining the target load type of the building based on the building external environment information, and invoking the air conditioning system control strategy corresponding to the target load type, where the air conditioning system control strategy corresponding to the target load type includes the first air conditioning system control strategy for the inner zone and the second air conditioning system control strategy for the outer zone; executing the first air conditioning system control strategy for the inner zone and the second air conditioning system control strategy for the outer zone to control the air conditioning system of the building.

[0060] Among them, the building external environment information can be specifically understood as representing the meteorological conditions outside the building, including but not limited to outdoor temperature information, humidity information, and solar radiation intensity information. The building external environment information can be the average data of the environmental data within a historical time period, or the mean square deviation data of the environmental data within a historical time period, or the data obtained by weighted processing of the environmental data within a historical time period. Among them, the historical time period can be one week, half a month, or one month, which is specifically set according to actual needs, so as to consider the environmental information changes in the transition season or the rapid changes in environmental information within a period of time, which helps to improve the accuracy of the air conditioning system control strategy.

[0061] Specifically, by detecting the building external environment information, determining the detection result, invoking the mapping relationship between the environmental information and the load type, matching according to the detection result and the mapping relationship, determining the target load type corresponding to the detection result, matching and invoking the corresponding air conditioning system control strategy according to the target load type, where the air conditioning system control strategy corresponding to the target load type includes the first air conditioning system control strategy for the inner zone and the second air conditioning system control strategy for the outer zone, and then controlling the air conditioning system to execute the first air conditioning system control strategy for the inner zone and the second air conditioning system control strategy for the outer zone to complete the control of the air conditioning system of the building.

[0062] In this embodiment, determining the corresponding target load type based on the building external environment information and determining the corresponding air conditioning system control strategy according to the target load type, which includes both the first air conditioning system control strategy for the inner zone and the second air conditioning system control strategy for the outer zone, realizes determining the corresponding air conditioning system control strategies for the inner zone and the outer zone of the building according to the building external environment information, so as to realize the control of the air conditioning systems of the inner zone and the outer zone of the building, and thus complete the control of the air conditioning system of the building.

[0063] The technical solution of this embodiment is to create a building and air-conditioning system partition model. The building and air-conditioning system partition includes an inner zone and an outer zone. For any load type of the building, set the air-conditioning working modes corresponding to the inner zone and the outer zone respectively, obtain the setting model corresponding to the air-conditioning working mode, and the setting model includes undetermined parameters. Sample the undetermined parameters in the air-conditioning working modes corresponding to the inner zone and the outer zone respectively to obtain multiple sample parameter groups. Based on the multiple sample parameter groups, perform air-conditioning operation simulation on the building and air-conditioning system partition model respectively to obtain the simulated operation indexes corresponding to the multiple sample parameter groups. Determine the air-conditioning system control strategy of the building for the load type based on the simulated operation indexes corresponding to the multiple sample parameter groups. For any load type, this solution determines the building and air-conditioning system partition model of the corresponding inner zone and outer zone, as well as multiple samples corresponding to each model. Based on the multiple sample parameters, simulate the corresponding model to obtain the simulated operation indexes corresponding to each sample parameter group, so as to obtain the sample parameter group corresponding to the optimal operation index, so as to obtain the air-conditioning system strategy for the load type, realizing the simulation of the building and air-conditioning system model under the corresponding load type through multiple sample parameter groups to obtain the building and air-conditioning system partition model with the optimal operation index, and obtaining the air-conditioning system control strategy of the building for the load type, solving the problems of poor accuracy and adaptability of air-conditioning system control, and being unable to adaptively control the internal and external partitions and the regional heat load situation, and improving the operation performance of the entire air-conditioning system.

[0064] Embodiment 2

[0065] Figure 2 It is a flowchart of a method for determining the control strategy of an air-conditioning system provided by Embodiment 2 of the present invention. The method of this embodiment is a further optimization of the method of the above embodiment. Optionally, a prediction model is trained based on the simulated operation indexes corresponding to the multiple sample parameter groups. The prediction model is used to determine the simulated operation index corresponding to the input parameter group. Perform iterative optimization processing on the parameter values of the undetermined parameters based on the target optimization algorithm: In any iterative optimization process, determine the candidate parameter group obtained in the current iteration, and based on the prediction model, determine the simulated operation index corresponding to the candidate parameter group, and use the simulated operation index as the fitness data in the iterative optimization process until the target parameter group is obtained, and determine the air-conditioning system control strategy of the building for the load type based on the target parameter group. As Figure 2 shown, the method includes:

[0066] S210. Create a building and air-conditioning system partition model. The building and air-conditioning system partition includes an inner zone and an outer zone.

[0067] S220. For any load type of the building, set the air-conditioning working modes corresponding to the inner zone and the outer zone respectively, obtain the setting model corresponding to the air-conditioning working mode, and the setting model includes undetermined parameters.

[0068] S230. Sample the undetermined parameters in the air-conditioning working modes corresponding to the inner zone and the outer zone respectively to obtain multiple sets of sample parameters.

[0069] S240. Based on multiple sets of sample parameters, perform air-conditioning operation simulation on the building and air-conditioning system zoning model respectively to obtain the simulated operation indexes corresponding to multiple sets of sample parameters.

[0070] S250. Train a prediction model based on the simulated operation indexes corresponding to multiple sets of sample parameters respectively. The prediction model is used to determine the simulated operation index corresponding to the input parameter set.

[0071] Among them, the prediction model can be specifically understood as a model for predicting the corresponding simulated operation index according to known data. The preset model includes but is not limited to neural network models, decision tree models, and locally weighted linear regression models. In this embodiment, the known data is the input parameter set. The prediction model specifically refers to a model for determining the simulated operation index corresponding to the input parameter set. The input parameter set can be a set of sample parameters obtained by sampling from big data or a set of sample parameters obtained by processing according to an optimization algorithm. The optimization algorithm includes but is not limited to multi-objective particle swarm optimization algorithm, non-dominated sorting genetic algorithm, and MOEA algorithm based on adaptive geometric estimation, which is not limited here.

[0072] Specifically, train the prediction model according to the simulated operation data corresponding to multiple sets of sample parameters respectively to obtain a prediction model for determining the simulated operation index corresponding to the input parameter set. Specifically, use multiple sets of sample parameters as the input data of the prediction model, and use the simulated operation indexes corresponding to each set of sample parameters as the corresponding label data for model training to obtain a training model that meets the preset model training end condition, so that the trained prediction model can predict the corresponding simulated operation index according to the input parameter set.

[0073] In this embodiment, a prediction model is trained through the simulated operation indexes corresponding to multiple sets of sample parameters respectively, which can predict according to the input parameter set to obtain the corresponding simulated index data, used to evaluate the suitability of the set of sample parameters, and helps to quickly determine the optimal air-conditioning control strategy.

[0074] S260. Perform iterative optimization processing on the parameter values of the undetermined parameters based on the target optimization algorithm: In any iterative optimization process, determine the candidate parameter set obtained in the current iteration, and based on the prediction model, determine the simulated operation index corresponding to the candidate parameter set. Use the simulated operation index as the fitness data in the iterative optimization process until the target parameter set is obtained, and determine the air-conditioning system control strategy of the building for the load type based on the target parameter set.

[0075] In this embodiment, the parameter values ​​of the parameters to be determined are iteratively optimized by the target optimization algorithm to obtain the target parameter group, which is the optimal parameter group in the iterative process. The target optimization algorithm includes but is not limited to the multi-objective particle swarm optimization algorithm, the non-dominated sorting genetic algorithm and the MOEA algorithm of adaptive geometric estimation. In the process of iterative optimization by the target optimization algorithm, in any iterative optimization process, a candidate parameter group that meets the preset candidate conditions is selected from the parameter group generated in the current iterative processing process, and the candidate parameter group is used as the input data of the prediction model for prediction to obtain the simulation operation index corresponding to the candidate parameter group, and the simulation operation index is used as the fitness data in the current iterative optimization process, until the fitness data no longer changes or the fitness data meets the preset fitness threshold, the target parameter group is output, and the target parameter group is added to the setting model of the air conditioning working mode of the building for the load type to obtain the corresponding air conditioning system control strategy.

[0076] Based on the above embodiments, the method also includes: in the process of controlling the air-conditioning system based on the air-conditioning system control strategy, obtaining the actual operating indicators corresponding to the target parameter group in the air-conditioning system control strategy, updating the prediction model based on the target parameter group and the actual operating indicators, and updating the target parameter group based on the updated prediction model, as well as updating the air-conditioning system control strategy for the building according to the load type.

[0077] It should be noted that after a period of operation, the air-conditioning system will inevitably experience a decrease in system performance, so the prediction model of the air-conditioning system needs to be updated. In this embodiment, in the process of controlling the air-conditioning system according to the air-conditioning system control strategy, the actual operation index corresponding to the target parameter group in the current air-conditioning system control strategy is obtained from the operation data of the air-conditioning system, the target parameter group is used as the input data of the prediction model, and the actual operation index is used as the label data of the model. The prediction model is trained to adjust the prediction model to obtain an updated prediction model, and the updated prediction model is predicted according to the input parameter group through the updated prediction model to obtain the simulated operation index corresponding to the input parameter group, and then the corresponding input parameter group is adjusted to obtain the updated target parameter group, and the corresponding setting model is adjusted according to the updated target parameter group to update the air-conditioning system control strategy for the building load type.

[0078] The technical solution of this embodiment is to create a building and air-conditioning system zoning model. The building and air-conditioning system zoning includes an inner zone and an outer zone. For any load type of the building, set the corresponding air-conditioning working modes for the inner zone and the outer zone, obtain the setting model corresponding to the air-conditioning working mode, and the setting model includes undetermined parameters. Sample the undetermined parameters in the air-conditioning working modes corresponding to the inner zone and the outer zone respectively to obtain multiple sample parameter groups. Based on the multiple sample parameter groups, perform air-conditioning operation simulation on the building and air-conditioning system zoning model respectively to obtain the simulated operation indexes corresponding to the multiple sample parameter groups. Train a prediction model based on the simulated operation indexes corresponding to the multiple sample parameter groups respectively. The prediction model is used to determine the simulated operation index corresponding to the input parameter group. Perform iterative optimization processing on the parameter values of the undetermined parameters based on the target optimization algorithm: In any iterative optimization process, determine the candidate parameter group obtained in the current iteration, and based on the prediction model, determine the simulated operation index corresponding to the candidate parameter group. Use the simulated operation index as the fitness data in the iterative optimization process until the target parameter group is obtained. Based on the target parameter group, determine the air-conditioning system control strategy of the building for the load type. This solution determines the corresponding building and air-conditioning system zoning models for the inner zone and the outer zone for any load type, as well as multiple sample parameters corresponding to each model. Perform simulation on the corresponding models based on the multiple sample parameters to obtain the simulated operation indexes corresponding to each sample parameter group, so as to obtain the sample parameter group corresponding to the optimal operation index. Train a prediction model according to the simulated operation indexes corresponding to the sample parameter group, so that the simulated operation index of the input parameter group can be quickly predicted through the prediction model to obtain the air-conditioning system strategy for the load type. It realizes the simulation of the building and air-conditioning system model under the corresponding load type through multiple sample parameter groups to obtain the building and air-conditioning system zoning model with the optimal operation index, and obtains the air-conditioning system control strategy of the building for the load type, solves the problems of poor accuracy and adaptability of the air-conditioning system control, and inability to adaptively control the internal and external zoning and regional heat load conditions, and improves the operation performance of the entire air-conditioning system.

[0079] Embodiment III

[0080] Figure 3 It is a schematic structural diagram of a device for determining an air-conditioning system control strategy provided by Embodiment III of the present invention. As Figure 3 shown, the device includes:

[0081] A building and air-conditioning system zoning model creation module 310, configured to create a building and air-conditioning system zoning model, where the building and air-conditioning system zoning includes an inner zone and an outer zone;

[0082] A setting model determination module 320 is configured to set, for any load type of a building, the air-conditioning operation modes corresponding to the inner zone and the outer zone respectively, obtain the setting model corresponding to the air-conditioning operation mode, and the setting model includes undetermined parameters;

[0083] A sample parameter group determination module 330 is configured to sample the undetermined parameters in the air-conditioning operation modes corresponding to the inner zone and the outer zone respectively to obtain a plurality of sample parameter groups;

[0084] An air-conditioning system control strategy determination module 340 is configured to perform air-conditioning operation simulation on the building and the air-conditioning system partition model respectively based on a plurality of sample parameter groups to obtain the simulated operation indexes corresponding to the plurality of sample parameter groups respectively; determine the air-conditioning system control strategy of the building for the load type based on the simulated operation indexes corresponding to the plurality of sample parameter groups respectively.

[0085] In the technical solution of this embodiment, a building and air-conditioning system partition model creation module creates a building and air-conditioning system partition model, and the building and air-conditioning system partition includes an inner zone and an outer zone; the setting model determination module sets, for any load type of the building, the air-conditioning operation modes corresponding to the inner zone and the outer zone respectively, obtains the setting model corresponding to the air-conditioning operation mode, and the setting model includes undetermined parameters; the sample parameter group determination module samples the undetermined parameters in the air-conditioning operation modes corresponding to the inner zone and the outer zone respectively to obtain a plurality of sample parameter groups; the air-conditioning system control strategy determination module performs air-conditioning operation simulation on the building and the air-conditioning system partition model respectively based on a plurality of sample parameter groups to obtain the simulated operation indexes corresponding to the plurality of sample parameter groups respectively; determines the air-conditioning system control strategy of the building for the load type based on the simulated operation indexes corresponding to the plurality of sample parameter groups respectively. In this solution, for any load type, the building and air-conditioning system partition models of the corresponding inner zone and outer zone are determined, as well as a plurality of sample parameters corresponding to each model. The corresponding models are simulated based on the plurality of sample parameters to obtain the simulated operation indexes corresponding to each sample parameter group, so as to obtain the sample parameter group corresponding to the optimal operation index, so as to obtain the air-conditioning system strategy for the load type, realizing the simulation of the building and air-conditioning system models under the corresponding load type through a plurality of sample parameter groups to obtain the building and air-conditioning system partition model with the optimal operation index, and obtaining the air-conditioning system control strategy of the building for the load type, solving the problems of poor accuracy and poor adaptability of the air-conditioning system control, and being unable to adaptively control the internal and external partitions and the regional heat load conditions, and improving the operation performance of the entire air-conditioning system.

[0086] Based on the above embodiments, optionally, the setting model corresponding to any air-conditioning operating mode includes a supply air temperature setting sub-model and a water outlet temperature setting sub-model; the air-conditioning system control strategy determination module 340 includes a simulation result determination unit and a first simulated operation index determination unit. The simulation result determination unit is configured to, for any sample parameter set, determine the supply air temperature and water outlet temperature in the inner zone during the simulation based on the sample parameter set and the setting model corresponding to the air-conditioning operating mode in the inner zone; and determine the supply air temperature and water outlet temperature in the outer zone during the simulation based on the sample parameter set and the setting model corresponding to the air-conditioning operating mode in the outer zone. The first simulated operation index determination unit is configured to perform air-conditioning operation simulation on the building and air-conditioning system zoning model based on the supply air temperature and water outlet temperature in the inner zone during the simulation, and the supply air temperature and water outlet temperature in the outer zone, to obtain the simulated operation indexes corresponding to the sample parameter sets respectively. Optionally, the air-conditioning operating mode includes a cooling mode and a heating mode; the air-conditioning operating modes corresponding to the inner zone and the outer zone are the same or different; the supply air temperature setting sub-model and the water outlet temperature setting sub-model corresponding to the cooling mode are respectively determined based on the first undetermined parameter and the indoor temperature of the building; the supply air temperature setting sub-model corresponding to the heating mode is determined based on the second undetermined parameter and the indoor temperature of the building; the water outlet temperature setting sub-model corresponding to the heating mode is determined based on the third undetermined parameter and the outdoor temperature of the building. Optionally, the air-conditioning system control strategy corresponding to any load type includes a first air-conditioning system control strategy for the inner zone and a second air-conditioning system control strategy for the outer zone.

[0087] Optionally, the air-conditioning system control strategy determination module 340 further includes a second simulated operation index determination unit and an air-conditioning system control strategy determination unit. The second simulated operation index determination unit is configured to train a prediction model based on the simulated operation indexes corresponding to multiple sample parameter sets respectively, and the prediction model is used to determine the simulated operation index corresponding to the input parameter set. The air-conditioning system control strategy determination unit is configured to perform iterative optimization processing on the parameter values of the undetermined parameters based on the target optimization algorithm: in any iterative optimization process, determine the candidate parameter set obtained in the current iteration, and determine the simulated operation index corresponding to the candidate parameter set based on the prediction model, and use the simulated operation index as the fitness data in the iterative optimization process until the target parameter set is obtained, and determine the air-conditioning system control strategy of the building for the load type based on the target parameter set.

[0088] Optionally, the air-conditioning system control strategy determination module 340 is further specifically configured to, during the control process of the air-conditioning system based on the air-conditioning system control strategy, obtain the actual operation index corresponding to the target parameter set in the air-conditioning system control strategy, update the prediction model based on the target parameter set and the actual operation index, and update the target parameter set based on the updated prediction model, and update the air-conditioning system control strategy of the building for the load type.

[0089] Optionally, the device is further configured to determine a target load type of the building based on the external building environment information, and call an air conditioning system control strategy corresponding to the target load type. The air conditioning system control strategy corresponding to the target load type includes a first air conditioning system control strategy for the inner zone and a second air conditioning system control strategy for the outer zone; execute the first air conditioning system control strategy for the inner zone and the second air conditioning system control strategy for the outer zone to control the air conditioning system of the building.

[0090] The control strategy determination device of the air conditioning system provided by the embodiments of the present invention can execute the control strategy determination method of the air conditioning system provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0091] Embodiment 4

[0092] Figure 4 FIG. 10 is a schematic structural diagram of an electronic device provided in Embodiment 4 of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device (such as a helmet, glasses, a watch, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0093] As Figure 4 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor. The processor 11 may execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0094] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0095] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the control strategy determination method of the air-conditioning system.

[0096] In some embodiments, the control strategy determination method of the air-conditioning system can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the control strategy determination method of the air-conditioning system described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the control strategy determination method of the air-conditioning system by any other suitable means (e.g., by means of firmware).

[0097] The various embodiments of the systems and technologies described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0098] A computer program for implementing the control strategy determination method of the air conditioning system of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the computer programs are executed by the processor, the functions / operations specified in the flowchart and / or block diagram are implemented. The computer programs can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0099] Embodiment Five

[0100] Embodiment Five of the present invention also provides a computer-readable storage medium. The computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a processor to execute a method for determining a control strategy of an air conditioning system. The method includes:

[0101] Create a building and air conditioning system partition model, and the building and air conditioning system partition includes an inner zone and an outer zone;

[0102] For any load type of the building, set the air conditioning operating modes corresponding to the inner zone and the outer zone respectively, obtain the setting model corresponding to the air conditioning operating mode, and the setting model includes undetermined parameters;

[0103] Sample the undetermined parameters in the air conditioning operating modes corresponding to the inner zone and the outer zone respectively to obtain multiple sample parameter groups;

[0104] Based on multiple sample parameter groups, perform air conditioning operation simulation on the building and air conditioning system partition model respectively to obtain the simulated operation indexes corresponding to the multiple sample parameter groups respectively; determine the air conditioning system control strategy of the building for the load type based on the simulated operation indexes corresponding to the multiple sample parameter groups respectively.

[0105] In the context of the present invention, the computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0106] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball), by which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0107] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0108] A computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0109] It should be understood that various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is imposed herein.

[0110] The above specific embodiments do not constitute a limitation to the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining a control strategy for an air conditioning system, characterized in that: include: Creating a building and air conditioning system zoning model, wherein the building and air conditioning system zoning includes an inner zone and an outer zone; For any load type of the building, set the air conditioning working modes corresponding to the inner zone and the outer zone respectively, and obtain the setting model corresponding to the air conditioning working mode, wherein the setting model includes undetermined parameters; Sampling the undetermined parameters in the air-conditioning working modes corresponding to the inner zone and the outer zone respectively to obtain a plurality of sample parameter groups; Based on the multiple sample parameter groups, air conditioning operation simulation is performed on the building and the air-conditioning system partition model to obtain simulation operation indicators corresponding to the multiple sample parameter groups; based on the simulation operation indicators corresponding to the multiple sample parameter groups, the air-conditioning system control strategy of the building for the load type is determined.

2. The method according to claim 1, characterized in that The setting model corresponding to any of the air-conditioning working modes includes a supply air temperature setting sub-model and a water outlet temperature setting sub-model; The air conditioning operation simulation is performed on the building and the air conditioning system partition model based on the multiple sample parameter groups to obtain the simulation operation indicators corresponding to the multiple sample parameter groups, including: For any of the sample parameter groups, the supply air temperature and the outlet water temperature of the inner zone during the simulation are determined based on the sample parameter group and the setting model corresponding to the air conditioning working mode of the inner zone; and the supply air temperature and the outlet water temperature of the outer zone during the simulation are determined based on the sample parameter group and the setting model corresponding to the air conditioning working mode of the outer zone; Based on the supply air temperature and the outlet water temperature of the inner zone and the supply air temperature and the outlet water temperature of the outer zone during the simulation process, the air conditioning operation simulation is performed on the building and air conditioning system partition model to obtain the simulation operation indicators corresponding to the sample parameter groups respectively.

3. The method according to claim 2, characterized in that The air-conditioning working mode includes a cooling mode and a heating mode; the air-conditioning working modes corresponding to the inner zone and the outer zone are the same or different; The air supply temperature setting sub-model and the water outlet temperature setting sub-model corresponding to the cooling mode are determined based on the first undetermined parameter and the indoor temperature of the building respectively; The air supply temperature setting sub-model corresponding to the heating mode is determined based on a second parameter to be determined and the indoor temperature of the building; The outlet water temperature setting sub-model corresponding to the heating mode is determined based on a third undetermined parameter and an outdoor temperature of the building.

4. The method according to claim 1, characterized in that: The determining of the air conditioning system control strategy of the building for the load type based on the simulated operation indicators respectively corresponding to the multiple sample parameter groups includes: A prediction model is obtained based on the simulation operation indicators corresponding to the multiple sample parameter groups, and the prediction model is used to determine the simulation operation indicator corresponding to the input parameter group; Iterative optimization processing is performed on the parameter values ​​of the undetermined parameters based on the target optimization algorithm: in any iterative optimization process, the candidate parameter group obtained in the current iteration is determined, and the simulation operation index corresponding to the candidate parameter group is determined based on the prediction model, and the simulation operation index is used as the fitness data in the iterative optimization process until the target parameter group is obtained, and the air-conditioning system control strategy of the building for the load type is determined based on the target parameter group.

5. The method according to claim 4, characterized in that The method further comprises: During the control of the air-conditioning system based on the air-conditioning system control strategy, the actual operating indicators corresponding to the target parameter group in the air-conditioning system control strategy are obtained, the prediction model is updated based on the target parameter group and the actual operating indicators, and the target parameter group is updated based on the updated prediction model, and the air-conditioning system control strategy of the building for the load type is updated.

6. The method according to claim 1, characterized in that The air conditioning system control strategy corresponding to any of the load types includes a first air conditioning system control strategy for the inner zone and a second air conditioning system control strategy for the outer zone.

7. The method according to claim 1, characterized in that The method further comprises: Based on the external environment information of the building, determine the target load type of the building, and call the air-conditioning system control strategy corresponding to the target load type, wherein the air-conditioning system control strategy corresponding to the target load type includes a first air-conditioning system control strategy for the inner zone and a second air-conditioning system control strategy for the outer zone; The first air conditioning system control strategy for the inner zone and the second air conditioning system control strategy for the outer zone are executed to control the air conditioning system of the building.

8. A control strategy determination device for an air conditioning system, characterized in that: include: A building and air conditioning system partition model creation module, used to create a building and air conditioning system partition model, wherein the building and air conditioning system partitions include an inner zone and an outer zone; A setting model determination module, for setting the air conditioning working modes corresponding to the inner zone and the outer zone respectively for any load type of the building, and obtaining a setting model corresponding to the air conditioning working mode, wherein the setting model includes undetermined parameters; A sample parameter group determination module, used for sampling the undetermined parameters in the air-conditioning working modes corresponding to the inner zone and the outer zone respectively, to obtain a plurality of sample parameter groups; The air conditioning system control strategy determination module is used to perform air conditioning operation simulation on the building and the air conditioning system partition model based on the multiple sample parameter groups, and obtain the simulation operation indicators corresponding to the multiple sample parameter groups; based on the simulation operation indicators corresponding to the multiple sample parameter groups, determine the air conditioning system control strategy of the building for the load type.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the control strategy determination method for the air-conditioning system according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the control strategy determination method for the air-conditioning system according to any one of claims 1 to 7 when executed.

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