Intelligent station building air conditioner load optimization control method and platform

Abstract

The embodiment of the invention provides an intelligent station building air conditioner load optimization control method and platform, and the method comprises the steps: determining the usable area of a current time period according to the number of users in the current time period, and dividing a room into a plurality of regions according to the installation position of a fan coil if the usable area of the current time period is smaller than an energy-saving area threshold value, selecting at least one area from the plurality of areas as a target area according to the illumination intensity and the use area of the current time period, taking the set temperature of the room and the average value of the indoor temperature as the target temperature of other areas, and obtaining the required cooling capacity of the target area according to the set temperature of the room, obtaining the required cooling capacity of other areas according to the target temperatures of the other areas, calculating the sum of the required cooling capacity of all the areas in the room to obtain the required cooling capacity of the room, calculating the sum of the required cooling capacity of all the rooms, and adjusting the output cooling capacity of the central air conditioner host according to the sum of the required cooling capacity of all the rooms. The temperature adjusting requirement is met, and energy waste is reduced.

Description

Technical Field

[0001] The present application relates to the field of intelligent building and energy management systems, and in particular to a method and platform for optimizing the control of air conditioning loads in smart station buildings. Background Art

[0002] With the development of science and technology, air conditioning systems have been widely used in people's lives, and the operation and control of air conditioning systems has gradually attracted attention.

[0003] The traditional station air conditioning system includes a central air conditioning host and multiple fan coil units, and multiple fan coil units are arranged in each room. In the operation and control of the station air conditioning system, the temperature of the control room is usually controlled as a whole. The overall control strategy often leads to energy waste and increases the operating cost of the station air conditioning system. Summary of the invention

[0004] The embodiments of the present application provide a smart station air conditioning load optimization control method and platform, which performs fine-grained control of different areas in the room based on the number of users in each time period, thereby reducing energy waste and lowering the operating cost of the station air conditioning system.

[0005] The present application provides a method for optimizing the control of air conditioning load in a smart station. The air conditioning system of the smart station works in a cooling mode and is used to adjust the temperature of multiple rooms. Multiple fan coil units are arranged in each room. The method includes: Obtain the number of users in the room during the current period, the light intensity during the current period, the indoor temperature during the current period, building data, and the set temperature; determine the usage area of ​​the current period based on the number of users during the current period, If the usage area of ​​the current period is less than the energy-saving area threshold, the room is divided into multiple areas according to the installation location of the fan coil unit, so that one area corresponds to one fan coil unit; Selecting at least one area from a plurality of areas as a target area according to the light intensity of the current period and the usage area of ​​the current period; The average of the set temperature of the room and the indoor temperature is used as the target temperature of other areas; the set temperature of the room is lower than the indoor temperature of the room, and other areas are areas in the room other than the target area; The required cooling capacity of the target area is calculated based on the set temperature of the room, and the required cooling capacity of other areas is calculated based on the target temperature of other areas; the sum of the required cooling capacity of all areas in the room is calculated to obtain the required cooling capacity of the room; Calculate the total cooling demand of all rooms, and adjust the cooling output of the central air-conditioning unit according to the total cooling demand of all rooms.

[0006] In the above technical solution, the area occupied by the users is calculated according to the number of users in the room. If the area occupied by the users is less than the energy-saving area threshold, the energy-saving mode is entered. If the area occupied by the users is greater than or equal to the energy-saving area threshold, the overall adjustment mode is entered. In the energy-saving mode, the room is divided into multiple areas. One part of the area is the target area, and the adjustment target is the set temperature. The other part of the area is other areas, and the adjustment target is the target temperature. The cooling capacity of different types of areas is calculated according to different temperatures, and then the required cooling capacity output of the central air-conditioning host is controlled according to the total cooling capacity of the room. When the number of users is relatively small, the temperature of the target area is set to the set temperature, and the temperature of other areas is the target temperature. Compared with controlling the room temperature to the set temperature as a whole, it can reduce energy waste while meeting the user's demand for temperature adjustment, thereby reducing the operating cost of the station air-conditioning system.

[0007] In a possible implementation, the method further includes: If the area used by the user is greater than or equal to the energy-saving area threshold, the required cooling capacity of the room is calculated based on the set temperature of the room; Determine whether the room's required cooling capacity is greater than the maximum cooling capacity supplied. If so, use the maximum cooling capacity supplied as the room's required cooling capacity.

[0008] In the above technical solution, when the overall temperature is adjusted, the room's required cooling capacity will be greater. At this time, it is necessary to consider whether it will exceed the maximum cooling capacity supplied by the central air-conditioning host. After exceeding the maximum cooling capacity supplied by the central air-conditioning host, the maximum cooling capacity supplied is used as the room's required cooling capacity. This avoids overload operation of the central air-conditioning host and ensures the safety of the central air-conditioning host.

[0009] In a possible implementation, at least one area is selected from multiple areas as a target area according to the light intensity of the current period and the usage area of ​​the current period. Obtain the number of users in the next time period, and determine the usage area in the next time period according to the number of users in the next time period; determine whether the difference between the usage area in the next time period and the usage area in the current time period is greater than or equal to the area of ​​the minimum area; If so, the difference between the area of ​​the target area and the area used in the next time period is made smaller than a preset threshold; if not, the difference between the area of ​​the target area and the area used in the current time period is made smaller than a preset threshold.

[0010] In the above technical solution, if the usage area between the next time period and the current time period is smaller than the area of ​​the minimum area, it means that the target area of ​​the current time period and the next time period are the same, and when selecting the target area, the usage area of ​​the current time period is referred to. If the usage area between the next time period and the current time period is larger than the area of ​​the minimum area, it means that an area will be added in the next time period, and when selecting the target area, the usage area of ​​the next time period is referred to, so as to adapt to the usage area demand of the next time period and meet the temperature adjustment demand of the surging number of users.

[0011] In a possible implementation, the method further includes: If the usage area in the current period is less than the energy-saving area threshold, prompt information is generated according to the location of the target area and displayed on a display screen set in the room; the prompt information is used to prompt the user to move within the target area.

[0012] In the above technical solution, prompt information is generated to guide users to move in the target area, thereby meeting the temperature adjustment needs of users and reducing the cooling demand, thereby reducing the operating cost of the station air conditioning system.

[0013] In a possible implementation, the required cooling capacity of the target area is calculated according to the set temperature of the room, and the required cooling capacity of other areas is calculated according to the target temperature of other areas, which specifically includes: The required cooling capacity of the target area is calculated based on the number of users in the target area during the current period, the power of the electrical equipment during the current period, the indoor temperature during the current period, the building data and the set temperature; The required cooling capacity of other areas is calculated based on the power of electrical equipment in other areas during the current period, the light intensity in the current period, the indoor temperature in the current period, the building data and the target temperature.

[0014] In the above technical solution, when calculating the required cooling capacity of the target area, the influence of the users and electrical equipment in the target area on the temperature is taken into account, and the required cooling capacity of the target area is calculated according to the indoor temperature after the temperature rise and the set temperature, so as to accurately control the temperature of the target area. When calculating the required cooling capacity of other areas, since most of the users are in the target area, only the influence of the electrical equipment and light on the temperature in other areas is taken into account, and the required cooling capacity of other areas is calculated according to the indoor temperature after the temperature rise and the set temperature, so as to accurately control the temperature of other areas.

[0015] In a possible implementation, the required cooling capacity of the target area is calculated according to the number of users in the current time period, the power of the electrical equipment in the current time period, the indoor temperature in the current time period, the building data and the set temperature in the target area, specifically including: According to the number of users in the target area during the current period, the power consumption of the electrical equipment, and the unit duration, the heat generated in the target area is obtained; Calculate the temperature rise corresponding to the heat generated in the target area according to the first conversion function and the building data of the target area, and take the sum of the indoor temperature of the target area and the temperature rise as the indoor temperature after the temperature rise; The temperature difference between the indoor temperature after the temperature rise of the target area and the set temperature is calculated, and the required cooling capacity corresponding to the temperature difference is calculated according to the second conversion function and the building data of the target area, and the required cooling capacity corresponding to the temperature difference is used as the required cooling capacity of the target area.

[0016] In the above technical solution, the heat generated in the target area is first calculated based on the number of users and the power of electrical equipment, and the heat is converted into temperature rise. Then, the temperature difference is calculated based on the indoor temperature after temperature rise and the set temperature. The required cooling capacity corresponding to the temperature difference is calculated according to the conversion relationship to realize the conversion of heat and cooling capacity.

[0017] In a possible implementation, the heat generated in the target area is obtained according to the number of users in the current time period of the target area, the power consumption of the electrical equipment, and the unit time, specifically including: The heat generated by the crowd is calculated based on the number of users in the target area, the heat generated by each person per unit time, and the unit duration; The heat generated by the electrical equipment is calculated based on the power of the electrical equipment in the target area, the preset heat conversion efficiency coefficient and the unit time; The sum of the heat generated by the crowd and the heat generated by electrical equipment is calculated as the heat generated in the target area.

[0018] In the above technical solution, the heat generated by the crowd and the heat generated by the electrical equipment are calculated separately, and the sum of the heat generated by the crowd and the heat generated by the electrical equipment is taken as the heat generated in the target area, so as to take into account the impact of users and electrical equipment on the cooling demand.

[0019] The embodiment of the present application provides a smart station air conditioning load optimization control platform, including: The acquisition module is used to obtain the number of users in the room during the current period, the light intensity during the current period, the indoor temperature during the current period, the building data and the set temperature; and determine the usage area of ​​the current period according to the number of users during the current period. A processing module, for dividing the room into a plurality of areas according to the installation positions of the fan coil units when the usage area in the current time period is less than the energy-saving area threshold, so that one area corresponds to one fan coil unit; The processing module is further used to select at least one area from the multiple areas as the target area according to the light intensity of the current time period and the usage area of ​​the current time period; The processing module is further used to use the average of the set temperature of the room and the indoor temperature as the target temperature of other areas; the set temperature of the room is lower than the indoor temperature of the room, and the other areas are areas in the room other than the target area; The processing module is further used to calculate the required cooling capacity of the target area according to the set temperature of the room, and calculate the required cooling capacity of the other areas according to the target temperature of the other areas; calculate the sum of the required cooling capacity of all areas in the room to obtain the required cooling capacity of the room; The processing module is also used to calculate the total cooling demand of all rooms, and adjust the cooling output of the central air-conditioning host according to the total cooling demand of all rooms.

[0020] Optionally, the processing module is further specifically used for: If the area used by the user is greater than or equal to the energy-saving area threshold, the required cooling capacity of the room is calculated based on the set temperature of the room; Determine whether the room's required cooling capacity is greater than the maximum cooling capacity supplied. If so, use the maximum cooling capacity supplied as the room's required cooling capacity.

[0021] Optionally, the acquisition module is further specifically used for: Obtain the number of users in the next time period, and determine the usage area in the next time period according to the number of users in the next time period; determine whether the difference between the usage area in the next time period and the usage area in the current time period is greater than or equal to the area of ​​the minimum area; Optionally, the processing module is further specifically used for: If so, the difference between the area of ​​the target area and the area used in the next time period is made smaller than a preset threshold; if not, the difference between the area of ​​the target area and the area used in the current time period is made smaller than a preset threshold.

[0022] Optionally, the processing module is further specifically used for: If the usage area in the current period is less than the energy-saving area threshold, prompt information is generated according to the location of the target area and displayed on a display screen arranged in the room; the prompt information is used to prompt the user to move within the target area.

[0023] Optionally, the processing module is further specifically used for: Calculate the required cooling capacity of the target area according to the number of users in the target area in the current period, the power of the electrical equipment in the current period, the indoor temperature in the current period, the building data and the set temperature; The required cooling capacity of the other areas is obtained by calculation according to the power of electrical equipment in the other areas in the current period, the light intensity in the current period, the indoor temperature in the current period, the building data and the target temperature.

[0024] Optionally, the processing module is further specifically used for: Obtaining the amount of heat generated in the target area according to the number of users in the target area during the current period, the power consumption of electrical equipment, and the unit duration; Calculate the temperature rise corresponding to the heat generated in the target area according to the first conversion function and the building data of the target area, and use the sum of the indoor temperature of the target area and the temperature rise as the indoor temperature after the temperature rise; The temperature difference between the indoor temperature after the temperature rise of the target area and the set temperature is calculated, and the required cooling capacity corresponding to the temperature difference is calculated according to the second conversion function and the building data of the target area, and the required cooling capacity corresponding to the temperature difference is used as the required cooling capacity of the target area.

[0025] Optionally, the processing module is further specifically used for: The heat generated by the crowd is calculated based on the number of users in the target area, the heat generated by each person per unit time and the unit time length; Calculate the heat generated by the electrical equipment according to the power of the electrical equipment in the target area, the preset heat conversion efficiency coefficient and the unit time; The sum of the heat generated by the crowd and the heat generated by the electrical equipment is calculated as the heat generated in the target area.

[0026] The embodiment of the present application provides a smart station air conditioning load optimization control platform, including: a memory, a processor; Memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes various possible implementations as described above.

[0027] An embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the various possible implementation methods described above.

[0028] An embodiment of the present application provides a computer program product, including a computer program, which implements the above various possible implementation methods when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0030] Figure 1 Schematic diagram of the station air conditioning system provided for this application; Figure 2A flow chart of the intelligent station air conditioning load optimization control method provided for this application; Figure 3 A schematic diagram of the room partitions provided for this application; Figure 4 Schematic diagram of the structure of the smart station air conditioning load optimization control platform provided for this application.

[0031] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0032] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0033] Figure 1 The schematic diagram of the station air conditioning system provided for this application is as follows: Figure 1 As shown in the figure, the station air conditioning system includes a central air conditioning main unit and multiple fan coil units. Multiple fan coil units are arranged in each room. The central air conditioning main unit provides chilled water to each fan coil unit through a water diffuser, and the fan coil unit provides cold air to the room. The chilled water return flows into the central air conditioning main unit through a water collector, and the central air conditioning main unit cools the chilled water return water. The central air conditioning main unit also provides cooling water to the cooling tower, and the cooling water flows into the central air conditioning main unit after being cooled by the cooling tower.

[0034] In the operation and control of the station building air-conditioning system, the temperature of the control room is usually controlled as a whole. The overall control strategy often leads to energy waste and increases the operation cost of the station building air-conditioning system.

[0035] In view of this, the embodiments of the present application provide a smart station air conditioning load optimization control method and platform, which performs fine-grained control of different areas in the room based on the number of users in each time period, thereby reducing energy waste and lowering the operating cost of the station air conditioning system.

[0036] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0037] Figure 2 The flowchart of the intelligent station air conditioning load optimization control method provided for this application is as follows: Figure 2 As shown, the smart station air conditioning system works in cooling mode to adjust the temperature of multiple rooms, and multiple fan coil units are arranged in each room. The method specifically includes the following steps: S101, obtaining the number of users in the room during the current period, the light intensity during the current period, the indoor temperature during the current period, building data and the set temperature, and determining the usage area during the current period according to the number of users during the current period.

[0038] Among them, taking any one of the multiple rooms as an example, by setting a flow detector at the entrance of the room, the number of users in the room at each time period is counted. By installing light detectors on each window of the room, the light intensity at each time period is detected. By setting a temperature sensor in the room, the temperature sensor detects the temperature in the room. In order to more accurately measure the indoor temperature of the room, sensors can be set in various areas of the room, and the average temperature collected by multiple sensors is calculated as the indoor temperature of the room. Obtain the set temperature of the room entered by the room administrator. Obtain the three-dimensional model data of the building, and extract the architectural data of the room from the three-dimensional model data.

[0039] Extract the layout of tables and chairs in the room and the number of users each table and chair can accommodate from the architectural data of the room. Calculate the number of tables and chairs required based on the user data of the current period and the number of users each table and chair can accommodate. Calculate the usage area of ​​the current period based on the layout of tables and chairs in the room and the number of tables and chairs required.

[0040] S102, when judging whether the usage area of ​​the current time period is less than the energy-saving area threshold, if so, the room is divided into multiple areas according to the installation positions of the fan coil units, so that one area corresponds to one fan coil unit, if not, enter S106.

[0041] Among them, taking any one of the multiple rooms as an example, the energy-saving area threshold is determined according to the total area of ​​the room, and can be a value greater than half of the total area of ​​the room. It is judged whether the usage area of ​​the current period is less than the energy-saving area threshold. If so, the energy-saving mode is entered. If not, the overall adjustment mode is entered.

[0042] In energy-saving mode, for any two adjacent fan coil units, the middle position between the two adjacent fan coil units is determined according to the installation positions of the two adjacent fan coil units, and the area regulated by the two fan coil units is divided using a line passing through the middle position.

[0043] S103: Select at least one area from multiple areas as a target area according to the light intensity in the current period and the usage area in the current period.

[0044] In which, taking any one of the multiple rooms as an example, an area with a smaller light intensity is selected as a target area, so that the cooling demand can be reduced. The number of selected areas is determined according to the area used by the user, and it is ensured that the difference between the area of ​​at least one target area and the area used by the user is less than a preset threshold. The preset threshold can be designed based on user needs.

[0045] S104: The average of the set temperature of the room and the indoor temperature is used as the target temperature of other areas. The set temperature of the room is lower than the indoor temperature of the room, and the other areas are areas in the room other than the target area.

[0046] Here, any one of the multiple rooms is taken as an example for explanation. Figure 3 A schematic diagram of a room partition is shown in FIG. Figure 3 As shown in the figure, the room is divided into 6 areas. If area 1 and area 2 are selected as the target areas, then area 3, area 4, area 5 and area 6 are other areas. The temperature in the room is collected by sensors arranged in the room, and the average value of the temperature in the room collected by the sensors is calculated, and the average value is used as the indoor temperature of the room. The set temperature of the room and the average value of the indoor temperature of the room are calculated, and the calculated average value is used as the set temperature of area 3, area 4, area 5 and area 6.

[0047] S105, calculating the required cooling capacity of the target area according to the set temperature of the room, calculating the required cooling capacity of other areas according to the target temperatures of other areas, and calculating the sum of the required cooling capacity of all areas in the room to obtain the required cooling capacity of the room.

[0048] The required cooling capacity of the target area is calculated by adjusting the temperature of the target area to the set temperature, and the required cooling capacity of other areas is calculated by adjusting the temperature of other areas to the target temperature. The set temperature of the room is lower than the indoor temperature of the room, so the set temperature is lower than the target temperature of other areas. After obtaining the required cooling capacity of the target area and the required cooling capacity of other areas, the sum of the required cooling capacity of all areas in the room is calculated to obtain the required cooling capacity of the room.

[0049] S106: If the area used by the user is greater than or equal to the energy-saving area threshold, the required cooling capacity of the room is calculated according to the set temperature of the room.

[0050] If the area used by the user is greater than or equal to the energy-saving area threshold, the overall adjustment mode is entered. That is, when the number of users is large, the area used is larger, and the entire room is used as the adjustment object.

[0051] The required cooling capacity of the room is obtained according to the set temperature of the room, specifically including: calculating the required cooling capacity of the room according to the number of users in the room in the current period, the light intensity in the current period, the power of the electrical equipment in the current period, the indoor temperature in the current period, the building data of the room and the set temperature of the room.

[0052] More specifically, the heat generated in the room is calculated based on the number of users in the room during the current period, the light intensity during the current period, and the power of electrical equipment during the current period. The heat generated in the room is converted into temperature rise to obtain the indoor temperature after the temperature rise. The required cooling capacity of the room is calculated based on the difference between the indoor temperature after the temperature rise and the set temperature and the conversion relationship between cooling capacity and temperature difference.

[0053] When the entire room is used as the adjustment object, more cooling capacity will be required. It is necessary to determine whether the room's required cooling capacity is greater than the maximum cooling capacity supplied. If so, the maximum cooling capacity supplied will be used as the room's required cooling capacity.

[0054] S107, determine whether the room's required cooling capacity is greater than the maximum cooling capacity supplied. If so, take the maximum cooling capacity supplied as the room's required cooling capacity and proceed to S108. If not, directly proceed to S108.

[0055] Among them, the maximum supply cooling capacity is determined according to the maximum output cooling capacity of the central air-conditioning host. When the overall temperature is adjusted, the room's required cooling capacity will be greater. At this time, it is necessary to consider whether it will exceed the maximum supply cooling capacity of the central air-conditioning host. After exceeding the maximum supply cooling capacity of the central air-conditioning host, the maximum supply cooling capacity is used as the room's required cooling capacity. This avoids overload operation of the central air-conditioning host and ensures the safety of the central air-conditioning host.

[0056] Specifically, in the further implementation of the intelligent station air conditioning load optimization control method, when the user's usage area is greater than or equal to the energy-saving area threshold, the system will directly calculate the required cooling capacity of the entire room based on the set temperature of the room. This strategy ensures that when there are a large number of users in the room and the usage area is large, the air conditioning system can respond quickly and meet the overall temperature regulation needs. However, in this scenario, the room's required cooling capacity may increase significantly. Therefore, the system also introduces an important safety protection measure, which is to determine whether the room's required cooling capacity exceeds the maximum supply cooling capacity of the central air-conditioning host.

[0057] When the room's required cooling capacity exceeds the maximum supply cooling capacity of the central air conditioner, the system will adjust the room's required cooling capacity to the maximum supply cooling capacity. This adjustment mechanism is crucial because it effectively avoids the failure or damage of the central air conditioner due to overload operation. By limiting the output cooling capacity to the maximum range that the host can withstand, the system ensures long-term stable operation, extends the service life of the equipment, and reduces the repair and replacement costs caused by equipment failure.

[0058] In the overall temperature control mode, although the system outputs cooling capacity with the maximum supply cooling capacity as the upper limit, this does not mean unnecessary waste of energy. On the contrary, the system uses intelligent adjustment strategies to ensure that the indoor temperature reaches the set requirements while minimizing unnecessary cooling losses. For example, the system can dynamically adjust the wind speed and cooling output of the fan coil according to factors such as the indoor and outdoor temperature difference and the room insulation performance to achieve optimal energy utilization.

[0059] For users, this implementation ensures the flexibility and responsiveness of the air conditioning system in different usage scenarios. Whether it is the energy-saving mode when the number of users is small, or the overall temperature adjustment mode when the number of users is large, the system can quickly adapt to and meet the temperature needs of users. This intelligent adjustment method not only improves the user's comfort experience, but also enhances the overall flexibility and adaptability of the system.

[0060] In summary, in the above scheme, by introducing the intelligent judgment and restriction mechanism of the room's required cooling capacity, the intelligent station air conditioning load optimization control method not only avoids the overload operation of the central air conditioning host, ensures the safety and stability of the system, but also optimizes energy utilization through intelligent adjustment strategies and improves user experience. This technical effect has significant comprehensive benefits and promotion value in practical applications, and provides strong technical support for the management and operation of the intelligent station air conditioning system.

[0061] S108. Calculate the total cooling demand of all rooms, and adjust the cooling output of the central air-conditioning host according to the total cooling demand of all rooms.

[0062] The total cooling demand of all rooms is calculated, and the cooling output of the central air-conditioning host is adjusted according to the total cooling demand of all rooms, so that the central air-conditioning host can meet the cooling demand of each room.

[0063] In the above technical solution, the area occupied by the users is calculated according to the number of users in the room. If the area occupied by the users is less than the energy-saving area threshold, the energy-saving mode is entered. If the area occupied by the users is greater than or equal to the energy-saving area threshold, the overall adjustment mode is entered. In the energy-saving mode, the room is divided into multiple areas. One part of the area is the target area, and the adjustment target is the set temperature. The other part of the area is other areas, and the adjustment target is the target temperature. The cooling capacity of different types of areas is calculated according to different temperatures, and then the required cooling capacity output of the central air-conditioning host is controlled according to the total cooling capacity of the room. When the number of users is relatively small, the temperature of the target area is set to the set temperature, and the temperature of other areas is the target temperature. Compared with controlling the room temperature to the set temperature as a whole, it can reduce energy waste while meeting the user's demand for temperature adjustment, thereby reducing the operating cost of the station air-conditioning system.

[0064] Specifically, in traditional station air conditioning systems, an overall control strategy is often adopted, that is, a uniform temperature adjustment is performed on the entire room. However, this method will lead to energy waste when the number of users is small. The above solution introduces an energy-saving mode and determines the usage area based on the number of users in the current period. If the usage area is less than the energy-saving area threshold, the room is divided into multiple areas according to the installation position of the fan coil. This strategy enables the air conditioning system to be flexibly adjusted according to actual usage, avoiding unnecessary energy consumption.

[0065] In energy-saving mode, the above scheme further selects at least one area from multiple areas as the target area based on the light intensity and usage area of ​​the current period. The temperature of the target area is set to the set temperature of the room, while the temperature of other areas is set to the average indoor temperature, which is usually higher than the set temperature. This regional temperature setting strategy enables the air-conditioning system to meet the temperature needs of users more accurately, while reducing the supply of cooling to other non-critical areas, thereby achieving energy-saving effects.

[0066] The above solution calculates the required cooling capacity of the target area and other areas separately, and sums them up to get the total required cooling capacity of the room. This calculation process takes into account multiple factors, including the number of users, light intensity, indoor temperature, building data, and set temperature, to ensure the accuracy of the cooling demand. Subsequently, the output cooling capacity of the central air-conditioning host is adjusted according to the total cooling capacity required by all rooms. This cooling capacity allocation strategy based on actual demand avoids excess or insufficient cooling capacity and further improves energy efficiency.

[0067] The above scheme also has the ability to adapt dynamically. When the usage area in the next period changes, the method can adjust the selection of the target area and the cooling capacity calculation method accordingly to adapt to the change in the number of users. In addition, the intelligent control system monitors and adjusts the operating status of the air-conditioning system in real time, ensuring that the user's temperature requirements are met while achieving the optimal use of energy.

[0068] In summary, the above scheme achieves efficient and accurate control of the load of the station air conditioning system through the introduction of energy-saving mode, regional division, target area selection, accurate calculation and allocation of cooling demand, dynamic adaptation and intelligent control. The above scheme can significantly reduce energy waste and reduce the operating cost of the station air conditioning system when the number of users is small, while improving the user's comfort. In addition, this method also has the advantages of easy implementation and low maintenance cost, and has a high value for promotion and application.

[0069] In a possible implementation, S104, calculating the required cooling capacity of the target area according to the set temperature of the room, and calculating the required cooling capacity of other areas according to the target temperature of other areas, specifically includes: S201. Calculate the required cooling capacity of the target area according to the number of users in the current period, the power of electrical equipment in the current period, the indoor temperature in the current period, building data and the set temperature in the target area.

[0070] Among them, when users are active in the target area, heat is generated. When the electrical equipment in the target area is working, it will also convert electrical energy into thermal energy, thereby generating heat. Since the light intensity in the target area is relatively low, there is no need to consider the heat generated by light. Based on the above data, the heat generated in the target area can be determined. Then, the impact of the generated heat on the indoor temperature can be determined. The temperature difference can be calculated based on the indoor temperature after the temperature rise and the set temperature of the target area, and the required cooling capacity can be calculated based on the temperature difference and the space volume.

[0071] S202. Calculate the required cooling capacity of other areas according to the indoor temperature of other areas in the current period, the light intensity of the current period, the power of electrical equipment in the current period, the target temperature and the building data.

[0072] Among them, light can also provide heat to other areas. When the electrical equipment in other areas is working, it will also convert electrical energy into thermal energy, thereby generating heat. Since there are relatively few users in other areas, there is no need to consider the heat generated by users in other areas. Based on the above data, the heat generated in other areas can be determined. Then the impact of the generated heat on the indoor temperature can be determined. The temperature difference can be calculated based on the indoor temperature after the temperature rise and the target temperature of other areas, and the required cooling capacity can be calculated based on the temperature difference and the space volume.

[0073] In the above technical solution, when calculating the required cooling capacity of the target area, the influence of the users and electrical equipment in the target area on the temperature is taken into account, and the required cooling capacity of the target area is calculated according to the indoor temperature after the temperature rise and the set temperature, so as to accurately control the temperature of the target area. When calculating the required cooling capacity of other areas, since most of the users are in the target area, only the influence of the electrical equipment and light on the temperature in other areas is taken into account, and the required cooling capacity of other areas is calculated according to the indoor temperature after the temperature rise and the set temperature, so as to accurately control the temperature of other areas.

[0074] Specifically, in the calculation of the cooling demand of the target area, multiple factors such as the number of users in the current period, the power of electrical equipment, indoor temperature, building data, and set temperature are comprehensively considered. By analyzing the impact of these factors on the temperature, the above scheme can accurately calculate the required cooling capacity required by the target area. Compared with other areas, the target area usually gathers more users and electrical equipment, so its cooling demand is more significant. In other areas, due to the small number of users, the heat generated by electrical equipment is relatively low. Therefore, when calculating the required cooling capacity in other areas, the above scheme takes into account factors such as the power of electrical equipment, light intensity, indoor temperature, and building data, and appropriately reduces the impact of the number of users on the cooling demand. This differentiated calculation method enables the air-conditioning system to allocate cooling resources more reasonably and reduce unnecessary energy waste.

[0075] By calculating the required cooling capacity of the target area and other areas, the above solution enables the air conditioning system to output cooling capacity according to actual demand, avoiding energy waste under the traditional overall control strategy. This refined control method significantly improves energy utilization efficiency and reduces the operating cost of the station air conditioning system. At the same time, since the temperature of the target area is quickly and accurately controlled, user satisfaction with the air conditioning system has also been improved.

[0076] The above solution not only focuses on energy efficiency and operating cost reduction, but also fully considers the needs of user experience. By accurately controlling the temperature of the target area and other areas, the above solution ensures that the comfort of users in the activity area is fully guaranteed. At the same time, since the calculation of cooling demand is based on real-time data, the air conditioning system can be flexibly adjusted according to actual conditions, further enhancing the flexibility and adaptability of the system.

[0077] To summarize, in one possible implementation, the above solution achieves precise control of the air-conditioning system load by accurately calculating the required cooling capacity of the target area and other areas, which not only improves energy utilization efficiency and reduces operating costs, but also enhances user experience and system flexibility.

[0078] In a possible implementation, S201, according to the number of users in the target area in the current period, the power of the electrical equipment in the current period, the indoor temperature in the current period, the building data and the set temperature, the required cooling capacity of the target area is calculated, specifically including: S301, obtaining the heat generated in the target area according to the number of users in the target area during the current period, the power consumption of the electrical equipment, and the unit time.

[0079] The heat generated by users is related to the number of users. The larger the number of users, the more heat is generated. The heat generated by electrical equipment is related to the power of the electrical equipment. The larger the power of the electrical equipment, the more heat is generated. Heat is the result of time accumulation, so the heat generated by the target area is calculated based on the unit time. A day is divided into multiple time periods based on the unit time. For example, the unit time is 30 minutes.

[0080] S302: Calculate the temperature rise corresponding to the heat generated in the target area according to the first conversion function and the building data of the target area, and take the sum of the indoor temperature of the target area and the temperature rise as the indoor temperature after the temperature rise.

[0081] After the room is divided into multiple areas according to each fan coil unit, the building data of the target area is extracted from the building data of the room according to the segmentation result, and the spatial volume of the target area is extracted from the building data of the target area.

[0082] The first conversion function is the conversion relationship between heat, spatial volume and temperature difference. The spatial volume of the target area and the heat generated in the target area are input into the first conversion function to obtain the temperature rise, and the sum of the indoor temperature of the target area and the temperature rise is used as the indoor data after the temperature rise.

[0083] It is worth noting that the first transfer function mentioned above can be based on the first law of thermodynamics (law of conservation of energy) and the heat capacity of materials. When heat is added to a system (such as a room), this heat will cause the temperature of the system to rise unless the heat is removed by conduction, convection or radiation. The magnitude of the temperature rise depends on the amount of heat added, the heat capacity of the system, and the mass or volume of the system.

[0084] S303, calculating the temperature difference between the indoor temperature after the temperature rise of the target area and the set temperature, calculating the required cooling capacity corresponding to the temperature difference according to the second conversion function and the building data of the target area, and taking the required cooling capacity corresponding to the temperature difference as the required cooling capacity of the target area.

[0085] The second conversion function is a conversion relationship between cooling capacity, spatial volume and temperature. The spatial volume and temperature difference of the target area are input into the second conversion function to obtain the required cooling capacity of the target area.

[0086] It is worth noting that temperature difference is the driving force of heat transfer. When there is a temperature difference between two areas, heat will flow from the area with higher temperature to the area with lower temperature until thermal equilibrium is reached. Refrigeration systems (such as air conditioners) can transfer heat from the indoor environment to the outdoor environment, thereby reducing the indoor temperature. The performance of refrigeration systems is usually measured by refrigeration efficiency (Coefficient of Performance, COP) or cooling capacity (usually expressed in heat units, such as joules or watts). During the refrigeration process, the input electrical energy (or other forms of energy) is converted into cooling capacity, which is used to reduce the indoor temperature. This process follows the law of conservation of energy, that is, the input energy is equal to the output cooling capacity plus the energy lost by the system. The second conversion function can be based on the relationship between temperature difference and heat transfer and the performance of the refrigeration system. By considering factors such as the temperature difference, volume and COP of the target area, we can calculate the required cooling capacity. However, in actual applications, the specific calculation formulas and parameters may vary depending on the type of refrigeration system, the specific conditions of the target area, and the required calculation accuracy.

[0087] In the above technical solution, the heat generated in the target area is first calculated based on the number of users and the power of electrical equipment, and the heat is converted into temperature rise. Then, the temperature difference is calculated based on the indoor temperature after temperature rise and the set temperature. The required cooling capacity corresponding to the temperature difference is calculated according to the conversion relationship to realize the conversion of heat and cooling capacity.

[0088] Specifically, first determine the total heat generated in the target area based on the number of users in the current period and the power consumption of electrical equipment in the target area, combined with the unit duration. This step fully considers the joint impact of people and electrical equipment on indoor temperature, ensuring the accuracy of heat calculation. Through the above solution, the system can more accurately grasp the heat changes in the target area, providing a solid foundation for the subsequent calculation of cooling demand.

[0089] After obtaining the heat generated in the target area, the above scheme uses the first conversion function and the building data of the target area to convert this heat into the corresponding temperature rise. This step enables the system to more intuitively understand the temperature change trend of the target area by converting the abstract concept of heat into a specific temperature change value. At the same time, the original indoor temperature of the target area and the calculated temperature rise are added to obtain the indoor temperature after the temperature rise, which provides accurate data support for the subsequent temperature difference calculation.

[0090] After obtaining the indoor temperature after the temperature rise, the above scheme further calculates the temperature difference between this temperature and the set temperature. This temperature difference directly reflects the gap between the current temperature of the target area and the expected temperature, and is the key basis for determining the required cooling capacity. By accurately calculating the temperature difference, the system can more accurately determine how much cooling capacity is needed to achieve the set temperature target.

[0091] Finally, the above scheme uses the second conversion function and the building data of the target area to convert the calculated temperature difference into the corresponding required cooling capacity. The temperature difference is converted into a specific cooling capacity demand value, realizing the accurate conversion between heat and cooling capacity. The required cooling capacity determined by the above scheme is more in line with the actual needs of the target area, which helps the system achieve more accurate temperature control.

[0092] In summary, the above scheme realizes accurate prediction and control of the cooling demand in the target area by determining the heat generated in the target area, converting the heat into temperature rise, accurately calculating the temperature difference, and calculating the required cooling capacity based on the temperature difference. It not only improves the energy utilization efficiency and reduces the operating cost of the station air-conditioning system, but also improves the user's comfort experience.

[0093] In a possible implementation, S301, according to the number of users in the room during the current period, the power consumption of the electrical equipment in the room, the light intensity of the target area during the current period, and the unit duration, the heat generated in the target area is calculated, specifically including: S401. Calculate the heat generated by the crowd according to the number of users in the room, the heat generated by each person per unit time and the unit duration.

[0094] The heat generated by each person per unit time is obtained based on statistical data, and the product of the number of users in the room, the heat generated by each person per unit time and the unit time is calculated, and the product is used as the heat generated by the crowd.

[0095] S402: Calculate the heat generated by the electrical equipment according to the power of the electrical equipment in the target area, a preset heat conversion efficiency coefficient and a unit time.

[0096] The heat generated by the electrical equipment per unit time is obtained by calculating the product of the power of the electrical equipment in the target area and the preset heat conversion efficiency coefficient. The heat generated by the electrical equipment per unit time is obtained by calculating the product of the heat generated by the electrical equipment per unit time and the unit time length.

[0097] S403: Calculate the heat generated by the crowd and the heat generated by the electrical equipment to be the heat generated in the target area.

[0098] In the above technical solution, the heat generated by the crowd and the heat generated by the electrical equipment are calculated separately, and the sum of the heat generated by the crowd and the heat generated by the electrical equipment is taken as the heat generated in the target area, so as to take into account the impact of users and electrical equipment on the cooling demand.

[0099] Specifically, the above technical solution calculates the heat generated by the crowd based on the number of users in the target area, the heat generated by each person per unit time, and the unit duration. This step fully considers the heat released during human metabolism and the impact of crowd density on the indoor thermal environment. By introducing the parameter of the heat generated by each person per unit time and combining it with the real-time number of users, it can dynamically reflect the contribution of crowd activities to indoor heat at different time periods, thereby improving the accuracy of heat calculation.

[0100] Secondly, the above technical solution also takes into account the impact of electrical equipment on indoor heat. The heat generated by the electrical equipment is calculated based on the power of the electrical equipment in the target area, the preset heat conversion efficiency coefficient and the unit time. Electrical equipment consumes electrical energy and converts it into heat energy during operation. This part of heat is also an important component of indoor heat. By introducing the preset heat conversion efficiency coefficient, the electrical energy consumption of the electrical equipment can be accurately converted into heat output, further improving the comprehensiveness of the heat calculation.

[0101] Finally, the above technical solution adds the heat generated by the crowd and the heat generated by the electrical equipment to obtain the total heat generated in the target area. This step realizes the comprehensive consideration of the two main heat sources and ensures the integrity and accuracy of the heat calculation. By calculating and summing the heat generated by the crowd and the electrical equipment separately, the actual heat conditions in the target area can be more accurately reflected, providing strong data support for subsequent air conditioning load prediction and optimization control.

[0102] In summary, the above technical solution achieves comprehensive consideration of the factors affecting the cooling demand by separately calculating the heat generated by the crowd and the heat generated by electrical equipment and taking the sum of them as the heat generated in the target area.

[0103] In a possible implementation, S202, according to the indoor temperature of the current period of other areas, the light intensity of the current period, the power of the electric equipment in the current period, the target temperature and the building data, the required cooling capacity of other areas is calculated, specifically including: S501. Obtain the heat generated in other areas according to the light intensity of other areas during the current period, the power consumption of electrical equipment, and the unit time.

[0104] The heat generated by the electrical equipment is calculated based on the power of the electrical equipment in the target area, the preset heat conversion efficiency coefficient and the unit duration. The heat generated by light is calculated based on the glass size of the target area, the light intensity of the target area and the unit duration. The sum of the heat generated by light and the heat generated by the electrical equipment is calculated as the heat generated in other areas.

[0105] More specifically, the product of the glass size of the target area and the light intensity of the target area is calculated to obtain the light intensity per unit time. The product of the light intensity per unit time and the unit duration is calculated to obtain the total light intensity. The product of the total light intensity and the heat conversion coefficient is calculated as the heat generated by light.

[0106] S502: Calculate the temperature rise corresponding to the heat generated in other areas according to the first conversion function and the building data of other areas, and take the sum of the indoor temperature of other areas and the temperature rise as the indoor temperature after the temperature rise.

[0107] S503, calculating the temperature difference between the indoor temperature after the temperature rise of other areas and the set temperature, calculating the required cooling capacity corresponding to the temperature difference according to the second conversion function and the building data of other areas, and taking the required cooling capacity corresponding to the temperature difference as the required cooling capacity of other areas.

[0108] In the above technical solution, the heat generated in other areas is first calculated based on the power of electrical equipment and light intensity, and the heat is converted into temperature rise. Then, the temperature difference is calculated based on the indoor temperature after temperature rise and the target temperature. The required cooling capacity corresponding to the temperature difference is calculated according to the conversion relationship to realize the conversion of heat and cooling capacity.

[0109] In some embodiments, S102, selecting at least one area from multiple areas as a target area according to the light intensity of the current time period and the usage area of ​​the current time period, specifically includes: S601. Obtain the number of users in the next time period, and determine the usage area in the next time period according to the number of users in the next time period.

[0110] The number of users in the next period is predicted based on the historical period user data of the room by counting the historical period user data of the room. The method of calculating the user's usage area based on the number of users has been described in detail in the above embodiment and will not be repeated here.

[0111] S602: Determine whether the difference between the usage area of ​​the next time period and the usage area of ​​the current time period is greater than or equal to the area of ​​the smallest area. If yes, proceed to S603; if not, proceed to S604.

[0112] The minimum area refers to the area with the smallest area among the multiple areas divided by the room, so as to determine whether a new target area needs to be added in the next period to accommodate more users.

[0113] S603: The difference between the area of ​​the target area and the usage area of ​​the next time period is less than a preset threshold.

[0114] Among them, an area with the smallest light intensity is selected from multiple areas as the central area, and an area is selected from the areas adjacent to the central area, and it is determined whether the total area of ​​the selected area and the central area is greater than or equal to the usage area of ​​the next time period. If so, the selected area and the central area are output as target areas.

[0115] If the total area of ​​the selected area and the central area is smaller than the usage area of ​​the next time period, two areas are selected from the areas adjacent to the target area, and it is determined whether the total area of ​​the two selected areas and the central area is larger than the usage area of ​​the next time period. If so, the selected area and the central area are output as the target area.

[0116] Among them, the area with the lowest light intensity receives the least light, generates the least heat, and requires the least cooling. When working in energy-saving mode, select the area with the lowest light intensity as the central area. For example: the light in areas 1 and 6 is the smallest, so you can choose any one of areas 1 and 6. If area 1 is selected as the central area, select area 2 adjacent to area 1, calculate the total area of ​​area 1 and area 2, and determine whether the total area of ​​area 1 and area 2 is greater than the usage area of ​​the next period. If so, output area 1 and area 2 as the target area. Adjust area 1 and area 2 according to the set temperature, and adjust area 3 to area 6 according to the target temperature.

[0117] If the total area of ​​area 1 and area 2 is smaller than the usage area of ​​the next period, take area 1 as the center area, select area 2 and area 3, and calculate the total area of ​​area 1, area 2 and area 3. Determine whether the total area of ​​area 1 to area 3 is larger than the usage area of ​​the next period. If so, output area 1 to area 3 as the target area. Adjust area 1 to area 3 according to the set temperature, and adjust area 4 to area 6 according to the target temperature.

[0118] The area with the least light is taken as the central area, and further selection is made near the central area to ensure that the target area is a continuous area with relatively low light intensity. Continuous target areas can reduce the heat exchange rate between areas, generate less heat, and require less cooling, thereby reducing the cooling demand while meeting the user's temperature requirements.

[0119] In the above scheme, in the further refinement of the intelligent station air conditioning load optimization control method, the above scheme further proposed an innovative strategy for accurately selecting the target area to minimize energy consumption while meeting the user's temperature requirements. This strategy achieves further optimization control of the air conditioning system load by comprehensively considering the changes in light intensity, area, and use area.

[0120] In practical applications, light intensity is one of the important factors affecting room temperature. Areas with greater light intensity tend to generate more heat due to the influence of solar radiation, thereby increasing the cooling demand of the air-conditioning system. The above scheme is guided by light intensity and selects the area with the lowest light intensity from multiple areas as the central area. This selection strategy ensures that the target area has a lower heat generation potential in the initial state, which helps to reduce the cooling demand of the air-conditioning system.

[0121] After determining the central area, the above scheme further selects one or more areas from the areas adjacent to the central area to form a continuous target area. This continuous area selection strategy helps to reduce the heat exchange rate between areas, thereby reducing the additional heat generated by heat exchange. In the target area, due to the low light intensity and continuous area, heat generation and transfer are effectively controlled, further reducing the cooling demand of the air conditioning system.

[0122] The above scheme also takes into account the change in the usage area in the next period. When the usage area in the next period is larger than that in the current period, the method dynamically adjusts the area of ​​the target area according to the increase in the usage area. By ensuring that the difference between the area of ​​the target area and the usage area in the next period is less than the preset threshold, the method can accurately match the user activity area and the air conditioning system adjustment area to avoid unnecessary waste of cooling. At the same time, when the usage area in the next period changes little, the method keeps the area of ​​the target area unchanged to maintain the current adjustment effect.

[0123] Through the implementation of the above strategies, the above scheme effectively reduces the cooling demand of the station air conditioning system. Since the selection of the target area fully considers factors such as light intensity, regional continuity and changes in the use area, the air conditioning system can reduce unnecessary cooling output while meeting the user's temperature requirements. This not only helps to improve energy efficiency and reduce operating costs, but also helps to reduce carbon emissions and promote sustainable development.

[0124] It is worth noting that the above solution does not sacrifice the user's temperature experience and comfort while reducing the cooling demand. By accurately selecting the target area and dynamically adjusting the output cooling capacity, the air conditioning system can ensure that the temperature in the user's activity area is always kept within a comfortable range. This refined control method not only improves user satisfaction, but also helps to enhance the overall environmental quality of the station building.

[0125] In summary, the above scheme effectively reduces the cooling demand of the station air-conditioning system, improves energy efficiency, and provides users with a more comfortable and environmentally friendly user experience through strategies such as precise selection of target areas based on light intensity, continuous area selection to reduce heat exchange rate, and dynamic adjustment of the target area to adapt to changes in the use area.

[0126] S604: The difference between the area of ​​the target area and the usage area of ​​the current time period is less than a preset threshold.

[0127] Among them, if the difference between the usage area of ​​the next time period and the usage area of ​​the current time period is less than the area of ​​the minimum area, the area with the smallest light intensity is selected from multiple areas as the central area, and an area is selected from the areas adjacent to the central area to determine whether the total area of ​​the selected area and the central area is larger than the usage area of ​​the current time period. If so, the selected area and the central area are output as the target area.

[0128] If the difference between the usage area of ​​the current period and the usage area of ​​the current period is less than the area of ​​the minimum area, the target area is selected according to the usage area at the current moment. If area 1 is selected as the central area, area 2 adjacent to area 1 is selected, the total area of ​​area 1 and area 2 is calculated, and it is determined whether the total area of ​​area 1 and area 2 is greater than the usage area of ​​the current period. If so, area 1 and area 2 are output as target areas. Areas 1 and 2 are adjusted according to the set temperature, and areas 3 to 6 are adjusted according to the target temperature.

[0129] In the above technical solution, if the use area between the next time period and the current time period is smaller than the area of ​​the minimum area, it means that the target area of ​​the current time period and the target area of ​​the next time period are the same, and when selecting the target area, the use area of ​​the current time period is referred to. If the use area between the next time period and the current time period is larger than the area of ​​the minimum area, it means that an area will be added in the next time period, and when selecting the target area, the use area of ​​the next time period is referred to, and the use area requirement of the next time period can be met.

[0130] Specifically, in the further exploration of the intelligent station air conditioning load optimization control method, the above scheme further proposed an innovative strategy to dynamically adjust the selection of the target area according to the change of the usage area between the current period and the next period, so as to more accurately meet the temperature adjustment needs of users in different time periods. This strategy realizes the refined control of the air conditioning system load by comprehensively considering the light intensity, usage area and time factors, and significantly improves the energy efficiency and user experience.

[0131] In practical applications, the number of users and the area used often change over time. The above scheme obtains the number of users in the next period and determines the area used in the next period accordingly, providing data support for dynamically adjusting the target area. When the area used in the next period changes significantly compared to the current period, the method can automatically determine whether the target area needs to be adjusted to adapt to the new area requirements.

[0132] If the usage area of ​​the next period increases compared to the current period, and the increase is greater than or equal to the area of ​​the minimum area, the above scheme will adjust the area of ​​the target area so that the difference between it and the usage area of ​​the next period is less than the preset threshold. This adjustment strategy ensures that the target area can accurately cover the main areas of user activities, thereby meeting the user's temperature adjustment needs while reducing the supply of cooling to other non-critical areas and avoiding unnecessary energy waste.

[0133] When the number of users increases sharply, traditional air conditioning systems often have difficulty responding quickly and meeting new temperature adjustment requirements. The above solution significantly improves the system's response speed by predicting the change in the usage area in the next period of time and adjusting the selection of the target area accordingly. This enables the air conditioning system to quickly adjust the output cooling capacity when the number of users increases, ensuring that the indoor temperature always remains within a comfortable range, improving user satisfaction and comfort.

[0134] The above solution also enhances the flexibility of the air conditioning system by dynamically adjusting the selection of the target area. In different time periods, the system can automatically adjust the target area and output cooling capacity according to the actual usage area and number of users, thereby achieving refined control of the air conditioning system load. This flexibility not only helps to improve the overall energy efficiency of the system, but also reduces operating costs and maintenance difficulties.

[0135] It is worth noting that the above scheme also takes into account multiple factors such as light intensity, usage area and time factors when selecting the target area. This comprehensive consideration enables the system to more accurately judge the user's temperature adjustment needs in different time periods and formulate a more scientific and reasonable control strategy based on this. This intelligent control method not only improves the control accuracy and response speed of the system, but also provides users with a more comfortable and convenient user experience.

[0136] In summary, the above solution significantly improves the energy efficiency and user experience of the air-conditioning system by dynamically adapting to changes in the usage area, accurately matching the target area with the usage area, improving the system response speed, enhancing the system flexibility, and comprehensively considering multiple factors to achieve intelligent control.

[0137] Some embodiments of the present application provide a method for optimizing the load of air conditioning in a smart station, the method specifically comprising the following steps: S701, obtaining the number of users in the room during the current period, the light intensity during the current period, the indoor temperature during the current period, building data, and the set temperature, and determining the usage area during the current period according to the number of users during the current period.

[0138] S702, determine whether the usage area of ​​the current period is less than the energy-saving area threshold. If so, divide the room into multiple areas according to the installation positions of the fan coil units so that one area corresponds to one fan coil unit; otherwise, enter S708.

[0139] For example, a building with 5 rooms has a usable area smaller than the energy-saving area threshold, that is, rooms 1, 2, 3, and 4 enter the energy-saving mode. The usable area of ​​1 room is greater than or equal to the energy-saving area threshold, and room 5 enters the overall adjustment mode.

[0140] S703: Obtain the number of users in the next time period, and determine the usage area in the next time period according to the number of users in the next time period.

[0141] S704: If the difference between the usage area of ​​the next time period and the usage area of ​​the current time period is greater than or equal to the area of ​​the minimum area, the difference between the area of ​​the target area and the usage area of ​​the next time period is less than a preset threshold. If the difference between the usage area of ​​the next time period and the usage area of ​​the current time period is less than the area of ​​the minimum area, the difference between the area of ​​the target area and the usage area of ​​the current time period is less than a preset threshold.

[0142] Among them, the difference in the usage area of ​​Room 1 and Room 2 is greater than or equal to the area of ​​the smallest area. When Room 1 and Room 2 select the target area, it is ensured that the difference between the area of ​​the target area and the usage area of ​​the next time period is less than a preset threshold.

[0143] The difference between the usage areas of Room 3 and Room 4 is smaller than the area of ​​the smallest area. When selecting the target area, Room 3 and Room 4 ensure that the difference between the area of ​​the target area and the usage area of ​​the current time period is smaller than a preset threshold.

[0144] S705: The average of the set temperature of the room and the indoor temperature is used as the target temperature of other areas. The set temperature is lower than the indoor temperature. The other areas are areas in the room other than the target area.

[0145] S706. Calculate the required cooling capacity of the target area according to the set temperature of the room, and calculate the required cooling capacity of other areas according to the target temperatures of other areas.

[0146] S707: If the difference between the usage area of ​​the next time period and the usage area of ​​the current time period is greater than the area of ​​the smallest area, the required cooling range of the room is calculated based on the required cooling of all areas in the room. If the difference between the usage area of ​​the next time period and the usage area of ​​the current time period is less than or equal to the area of ​​the smallest area, the required cooling range of the room is calculated based on the required cooling of all areas in the room.

[0147] The upper limit of the room's required cooling range is the sum of the required cooling of all areas in the room, and the width of the room's required cooling range is the required cooling of any target area minus the required cooling of any other area.

[0148] For room 1, obtain the required cooling capacity of each target area in room 1, and obtain the required cooling capacity of each other area in room 1. Calculate the sum of the required cooling capacity of each target area and the required cooling capacity of each other area in room 1 to obtain the upper limit value of the required cooling capacity range of room 1. If room 1 is divided into 6 areas, area 1 and area 2 are target areas, and area 3 to area 6 are other areas, calculate the difference between the required cooling capacity of area 1 and the required cooling capacity of area 5 as the width value of the required cooling capacity range of room 1. Subtract the width value of the required cooling capacity range of room 1 from the upper limit value of the required cooling capacity range of room 1 to obtain the lower limit value of the required cooling capacity range of room 1. The required cooling capacity range of room 1 is marked as [Q1d, Q1u].

[0149] The calculation method of the required cooling capacity range of room 2 is similar to that of room 1, and will not be repeated here. The required cooling capacity range of room 1 is marked as [Q2d, Q2u].

[0150] For room 3, the required cooling capacity of each target area in room 3 is obtained, and the required cooling capacity of each other area in room 3 is obtained. The sum of the required cooling capacity of each target area in room 3 and the required cooling capacity of each other area is calculated as the required cooling capacity of room 3. The required cooling capacity range of room 3 is marked as Q3.

[0151] The calculation method of the required cooling capacity range of room 4 is similar to that of room 3, and will not be repeated here. The required cooling capacity range of room 4 is marked as Q4.

[0152] S708: If the area used by the user is greater than or equal to the energy-saving area threshold, the required cooling capacity of the room is calculated according to the set temperature of the room.

[0153] Room 5 needs to calculate the required cooling capacity of room 5 according to the overall adjustment method. The calculation method has been described in detail in the above embodiment and will not be repeated here. The required cooling capacity range of room 5 is marked as Q5.

[0154] S709. For the required cooling capacity range of all rooms, the sum of the upper limit values ​​of the required cooling capacity range of all rooms is calculated to obtain the sum of the upper limit values; and the sum of the lower limit values ​​of the required cooling capacity range of all rooms is calculated to obtain the sum of the lower limit values.

[0155] The sum of the upper limit values ​​QTu of the required cooling capacity range of room 1 and the upper limit values ​​of the required cooling capacity range of room 2 is calculated according to formula (1) to obtain the sum of the upper limit values ​​QTu.

[0156] QTu=Q1u+Q2u (1) According to formula (2), the sum of the lower limit value of the required cooling capacity range of room 1 and the lower limit value of the required cooling capacity range of room 2 is calculated to obtain the lower limit value sum QTd.

[0157] QTd=Q1d+Q2d(2) S709. For the cooling demand of all rooms, the sum of the cooling demand of all rooms is obtained to obtain the total cooling demand; the sum of the upper limit values ​​and the cooling demand is calculated to obtain the upper limit of the cooling supply of the central air-conditioning host; the sum of the lower limit values ​​and the cooling demand is calculated to obtain the lower limit of the cooling supply of the central air-conditioning host.

[0158] The total cooling demand Qm is obtained by calculating the total cooling demand of room 3, room 4 and room 5 according to formula (3).

[0159] Qm=Q3+Q4+Q5(3) According to formula (4), the sum of the upper limit values ​​and the sum of the required cooling capacity are calculated to obtain the upper limit value Qcu of the cooling capacity supplied by the central air-conditioning host.

[0160] Qcu=QTu+Qm(4) According to formula (5), the sum of the lower limit values ​​and the total required cooling capacity is calculated to obtain the lower limit value Qcd of the cooling capacity supplied by the central air-conditioning host.

[0161] Qcd = QTd + Qm (5) S710, controlling the central air-conditioning host to increase the cooling capacity from the lower limit of the cooling capacity supply to the upper limit of the cooling capacity supply according to the proportional-integral control strategy within a unit time.

[0162] After obtaining the upper and lower limits of the cooling capacity supplied by the central air-conditioning host, the output cooling capacity of the central air-conditioning host is controlled to output cooling capacity at the lower limit of the cooling capacity supplied. The central air-conditioning host is controlled to output cooling capacity from the lower limit of the cooling capacity supplied to the upper limit of the cooling capacity supplied according to the proportional integral control strategy.

[0163] In some embodiments, the output cooling capacity of the central air-conditioning host is controlled to output cooling capacity at the lower limit of the supply cooling capacity in the first time period, and the output cooling capacity of the central air-conditioning host is controlled to increase from the lower limit of the supply cooling capacity to the upper limit of the supply cooling capacity in the second time period according to the proportional integral control strategy. The first time period is greater than the second time period, and the sum of the first time period and the second time period is the unit time period. If the number of users in the current period is relatively small, cooling is provided according to the lower limit of the supply cooling capacity. As time goes by, the cooling capacity is gradually increased to adapt to the gradually increasing number of users. On the one hand, it adapts to the temperature adjustment needs of the surging users, and on the other hand, it operates in a more energy-saving manner.

[0164] S711: If the usage area in the current period is less than the energy-saving area threshold, a prompt message is generated according to the location of the target area, and the prompt message is displayed on a display screen set in the room. The prompt message is used to prompt the user to move within the target area.

[0165] Among them, by generating prompt information, users are guided to move within the target area, meeting the user's temperature adjustment needs while reducing the cooling demand.

[0166] Specifically, intelligent prompt information is used to guide users to move within a specific area, thereby effectively reducing the cooling demand of the air-conditioning system while meeting the user's temperature control needs, thereby reducing energy consumption and operating costs.

[0167] In the smart station air conditioning system, when the usage area of ​​the current period is less than the energy-saving area threshold, the system will accurately calculate the target area based on multiple factors such as the layout of the room, light intensity, number of users, etc. The target area is the area where the system believes that the temperature demand needs to be met first. By centrally supplying cooling capacity, the comfort level of this area can be maintained more effectively.

[0168] Once the target area is determined, the system will immediately generate corresponding prompt information based on the location of the target area. These prompt information are clearly displayed to users through the display screens set up in the room, aiming to guide users to move within the target area. The generation of prompt information is based on in-depth analysis and understanding of user behavior patterns to ensure the accuracy and effectiveness of the information.

[0169] Guided by intelligent prompts, users are more inclined to move in the target area, which directly leads to a significant reduction in the cooling demand in the non-target area. Since temperature regulation in the non-target area is no longer the main focus, the system can reduce the cooling supply to these areas accordingly, thereby achieving efficient use of energy.

[0170] Although the ultimate goal of the prompt information is to reduce the demand for cooling, this process is achieved without sacrificing user comfort. On the contrary, through precise target area positioning and intelligent prompt information guidance, the system can more effectively meet the user's temperature adjustment needs. When users are active in the target area, they can feel a more comfortable ambient temperature, thereby enhancing their satisfaction with the entire station air conditioning system.

[0171] In summary, by intelligently generating prompt information to guide users to move within the target area, the cooling demand of the air-conditioning system is effectively reduced, energy efficiency is improved, operating costs are reduced, and user experience and satisfaction are enhanced.

[0172] In the above technical solution, if the number of users in the next period is larger than the number of users in the current period, and an additional area is needed to accommodate more users, the target area is selected in the current period according to the usage area of ​​the next period, and the fluctuation of cooling capacity after the target area becomes larger is considered when calculating the cooling capacity, and the central air-conditioning host is controlled in the current period. The proportional integral control strategy is from outputting cooling capacity at the lower limit of the supply cooling capacity to outputting cooling capacity at the upper limit of the supply cooling capacity. If the number of users in the current period is relatively small, the cooling capacity is supplied according to the lower limit of the supply cooling capacity. Over time, the cooling capacity is gradually increased to adapt to the gradually increasing number of users. On the one hand, it adapts to the temperature adjustment needs of the surging users, and on the other hand, it operates in a more energy-saving way. In this way, through intelligent technical means, efficient and accurate control of the load of the station air-conditioning system is achieved to achieve multiple goals of energy saving and emission reduction, improving environmental comfort and extending the service life of equipment. Dynamic optimization management of air-conditioning load is achieved to ensure that energy efficiency is maximized while meeting environmental comfort requirements.

[0173] Specifically, in the in-depth exploration of the intelligent station air conditioning load optimization control method, the above scheme further proposed an innovative cooling capacity calculation and adjustment strategy, which aims to achieve efficient and accurate management of the station air conditioning system load by finely controlling the output cooling capacity of the air conditioning system. This strategy comprehensively considers the changes in the number of users in the next period, the fluctuations in the room cooling demand, and the output capacity of the central air conditioning host. Through intelligent technical means, it achieves multiple goals of energy saving and emission reduction, improving environmental comfort, and extending the service life of equipment.

[0174] In actual applications, changes in the number of users and the area used often lead to fluctuations in the room's required cooling capacity. The above solution dynamically calculates the room's required cooling capacity range by judging whether the difference between the area used in the next period and the current period is greater than the area of ​​the minimum area. When the difference is greater than the minimum area, it means that an additional area is needed to accommodate more users. At this time, the calculated required cooling capacity range can cover possible cooling capacity fluctuations and ensure the responsiveness of the air conditioning system. If the difference is less than or equal to the minimum area, the required cooling capacity is directly calculated, which simplifies the calculation process.

[0175] After calculating the required cooling capacity range of all rooms, the above scheme further calculates the sum of the upper and lower limits of the required cooling capacity range of all rooms, as well as the sum of the required cooling capacity of all rooms. Based on these calculation results, the above scheme determines the upper and lower limits of the cooling capacity supplied by the central air-conditioning host. By controlling the central air-conditioning host to output cooling capacity from the lower limit of the cooling capacity supplied to the upper limit of the cooling capacity supplied in a unit time according to the proportional integral control strategy, refined control of the air-conditioning system output is achieved. This control method can not only adapt to the surging temperature adjustment needs of users, but also operate in a more energy-saving manner when the number of users is small, significantly improving energy efficiency.

[0176] By dynamically adjusting the target area and finely controlling the cooling output of the air conditioning system, the above solution ensures the stability and comfort of the room temperature in different time periods. Especially when the number of users increases sharply, by predicting and adjusting the target area and cooling output in advance, the discomfort caused by temperature fluctuations is avoided, and the user satisfaction and comfort are improved.

[0177] Fine-grained control of the cooling output of the air-conditioning system not only helps save energy and reduce emissions, but also reduces the operating load and wear of the equipment, thereby extending the service life of the equipment. In addition, by reducing unnecessary waste of cooling and frequent start-up and shutdown of equipment, this method also helps reduce the maintenance cost and repair frequency of the equipment, providing a strong guarantee for the long-term stable operation of the station air-conditioning system.

[0178] In summary, the above solution achieves efficient and accurate management of the station air conditioning system load through strategies such as dynamically calculating the room's required cooling capacity range, finely controlling the central air conditioning host output, and comprehensively considering multiple factors to achieve intelligent control. It not only improves energy efficiency and environmental comfort, but also extends the service life of the equipment and reduces maintenance costs.

[0179] Figure 4 This is a schematic diagram of the structure of the intelligent station air conditioning load optimization control platform provided for this application. Figure 4 As shown, the smart station air conditioning load optimization control platform 200 provided by the present application includes: The acquisition module 210 is used to obtain the number of users in the room during the current period, the light intensity during the current period, the indoor temperature during the current period, the building data and the set temperature; determine the usage area of ​​the current period according to the number of users during the current period, The processing module 220 is used to divide the room into a plurality of areas according to the installation positions of the fan coil units when the usage area in the current time period is less than the energy-saving area threshold, so that one area corresponds to one fan coil unit; The processing module 220 is further configured to select at least one area from the plurality of areas as a target area according to the light intensity of the current period and the usage area of ​​the current period; The processing module 220 is further used to use the average of the set temperature of the room and the indoor temperature as the target temperature of other areas; the set temperature of the room is lower than the indoor temperature of the room, and the other areas are areas in the room other than the target area; The processing module 220 is further configured to calculate the required cooling capacity of the target area according to the set temperature of the room, calculate the required cooling capacity of the other areas according to the target temperature of the other areas; calculate the sum of the required cooling capacity of all areas in the room to obtain the required cooling capacity of the room; The processing module 220 is further used to calculate the total cooling demand of all rooms, and adjust the cooling output of the central air-conditioning host according to the total cooling demand of all rooms.

[0180] The electronic device provided in this embodiment includes: at least one processor and a memory. Optionally, the device also includes a communication component. The processor, the memory and the communication component are connected via a bus.

[0181] In a specific implementation process, at least one processor executes computer-executable instructions stored in a memory, so that at least one processor executes the above method.

[0182] The specific implementation process of the processor can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0183] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the invention can be directly implemented as a hardware processor, or can be implemented by a combination of hardware and software modules in the processor.

[0184] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0185] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0186] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0187] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0188] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special-purpose computer.

[0189] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0190] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0191] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0192] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0193] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0194] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0195] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary technical means in the art not disclosed by the present invention, are not limited to the precise structure described above and shown in the drawings, and may be modified and changed in various ways without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for optimizing the air conditioning load of a smart station building, characterized in that: The smart station air conditioning system works in cooling mode and is used to adjust the temperature of multiple rooms. Multiple fan coil units are arranged in each room. The method includes: Obtain the number of users in the room during the current period, the light intensity during the current period, the indoor temperature during the current period, building data, and the set temperature; determine the usage area of ​​the current period according to the number of users during the current period, If the usage area in the current time period is less than the energy-saving area threshold, the room is divided into a plurality of areas according to the installation position of the fan coil unit, so that one area corresponds to one fan coil unit; Selecting at least one area from the plurality of areas as a target area according to the light intensity of the current period and the usage area of ​​the current period; The average of the set temperature of the room and the indoor temperature is used as the target temperature of other areas; the set temperature of the room is lower than the indoor temperature of the room, and the other areas are areas in the room other than the target area; The required cooling capacity of the target area is calculated according to the set temperature of the room, and the required cooling capacity of the other areas is calculated according to the target temperature of the other areas; the sum of the required cooling capacity of all areas in the room is calculated to obtain the required cooling capacity of the room; Calculate the total cooling demand of all rooms, and adjust the cooling output of the central air-conditioning unit according to the total cooling demand of all rooms.

2. The intelligent station air conditioning load optimization control method according to claim 1 is characterized in that: The method further comprises: If the area used by the user is greater than or equal to the energy-saving area threshold, the required cooling capacity of the room is calculated based on the set temperature of the room; Determine whether the room's required cooling capacity is greater than the maximum cooling capacity supplied. If so, use the maximum cooling capacity supplied as the room's required cooling capacity.

3. The intelligent station air conditioning load optimization control method according to claim 1 is characterized in that: According to the light intensity of the current period and the usage area of ​​the current period, at least one area is selected from multiple areas as the target area. Obtain the number of users in the next time period, and determine the usage area of ​​the next time period according to the number of users in the next time period; determine whether the difference between the usage area of ​​the next time period and the usage area of ​​the current time period is greater than or equal to the area of ​​the minimum area; If so, the difference between the area of ​​the target area and the area used in the next time period is made smaller than a preset threshold; if not, the difference between the area of ​​the target area and the area used in the current time period is made smaller than a preset threshold.

4. The intelligent station air conditioning load optimization control method according to any one of claims 1 to 3, characterized in that: The method further comprises: If the usage area in the current period is less than the energy-saving area threshold, prompt information is generated according to the location of the target area and displayed on a display screen arranged in the room; the prompt information is used to prompt the user to move within the target area.

5. The intelligent station air conditioning load optimization control method according to any one of claims 1 to 3, characterized in that: Calculating the required cooling capacity of the target area according to the set temperature of the room, and calculating the required cooling capacity of the other areas according to the target temperature of the other areas, specifically includes: Calculate the required cooling capacity of the target area according to the number of users in the target area in the current period, the power of the electrical equipment in the current period, the indoor temperature in the current period, the building data and the set temperature; The required cooling capacity of the other areas is obtained by calculation according to the power of electrical equipment in the other areas in the current period, the light intensity in the current period, the indoor temperature in the current period, the building data and the target temperature.

6. The intelligent station air conditioning load optimization control method according to claim 5 is characterized in that: The required cooling capacity of the target area is calculated based on the number of users in the target area in the current period, the power of the electrical equipment in the current period, the indoor temperature in the current period, the building data and the set temperature, specifically including: Obtaining the amount of heat generated in the target area according to the number of users in the target area during the current period, the power consumption of electrical equipment, and the unit duration; Calculate the temperature rise corresponding to the heat generated in the target area according to the first conversion function and the building data of the target area, and use the sum of the indoor temperature of the target area and the temperature rise as the indoor temperature after the temperature rise; The temperature difference between the indoor temperature after the temperature rise of the target area and the set temperature is calculated, and the required cooling capacity corresponding to the temperature difference is calculated according to the second conversion function and the building data of the target area, and the required cooling capacity corresponding to the temperature difference is used as the required cooling capacity of the target area.

7. The intelligent station air conditioning load optimization control method according to claim 6 is characterized in that: According to the number of users in the target area in the current time period, the power consumption of the electrical equipment and the unit time length, the heat generated in the target area is obtained, specifically including: The heat generated by the crowd is calculated based on the number of users in the target area, the heat generated by each person per unit time and the unit time length; Calculate the heat generated by the electrical equipment according to the power of the electrical equipment in the target area, the preset heat conversion efficiency coefficient and the unit time; The sum of the heat generated by the crowd and the heat generated by the electrical equipment is calculated as the heat generated in the target area.

8. A smart station air conditioning load optimization control platform, characterized in that: include: An acquisition module is used to obtain the number of users in the room during the current period, the light intensity during the current period, the indoor temperature during the current period, building data, and the set temperature; Determine the usage area of ​​the current period according to the number of users in the current period, A processing module, for dividing the room into a plurality of areas according to the installation positions of the fan coil units when the usage area in the current time period is less than the energy-saving area threshold, so that one area corresponds to one fan coil unit; The processing module is further used to select at least one area from the multiple areas as the target area according to the light intensity of the current time period and the usage area of ​​the current time period; The processing module is further used to use the average of the set temperature of the room and the indoor temperature as the target temperature of other areas; the set temperature of the room is lower than the indoor temperature of the room, and the other areas are areas in the room other than the target area; The processing module is further used to calculate the required cooling capacity of the target area according to the set temperature of the room, and calculate the required cooling capacity of the other areas according to the target temperature of the other areas; calculate the sum of the required cooling capacity of all areas in the room to obtain the required cooling capacity of the room; The processing module is also used to calculate the total cooling demand of all rooms, and adjust the cooling output of the central air-conditioning host according to the total cooling demand of all rooms.

9. An electronic device, characterized in that: include: processor; as well as, A memory, configured to store executable instructions of the processor; The processor is configured to perform the method of any one of claims 1 to 7 by executing the executable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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