技术领域Technical Field
本发明涉及中央空调控制技术领域，更具体地说，本发明涉及一种智慧楼宇中央空调供能智能调控系统。The present invention relates to the technical field of central air-conditioning control, and more specifically, to an intelligent control system for central air-conditioning energy supply in a smart building.
背景技术Background technique
申请公开号CN113503622A的一篇专利文件公开一种中央空调智能控制调控系统，将办公楼内区域划分成各子区域，分别检测办公楼内各子区域中各检测位置处温度，控制办公楼内中央空调开启，同时监测办公楼内各子区域中人员数量，分析办公楼内各子区域中人员分布密度，进行中央空调温度调控。本发明基于室内温差对房间管理区域进行划分，通过各独立近邻子区域和远邻子区域的实时温度和时刻电流量、当天峰谷电价综合分析，提高用户群体的体验，减少企业的运行成本。A patent document with application publication number CN113503622A discloses a central air-conditioning intelligent control and regulation system, which divides the area in the office building into sub-areas, detects the temperature at each detection position in each sub-area in the office building, controls the opening of the central air-conditioning in the office building, monitors the number of people in each sub-area in the office building, analyzes the distribution density of people in each sub-area in the office building, and performs temperature regulation of the central air-conditioning. The present invention divides the room management area based on the indoor temperature difference, and comprehensively analyzes the real-time temperature and current flow of each independent neighboring sub-area and distant sub-area, as well as the peak and valley electricity price of the day, to improve the experience of the user group and reduce the operating cost of the enterprise.
在中国的空调市场中，中央空调能耗高是一个普遍的问题，而中央空调的使用场景也逐渐从商场、办公楼向小区发展，市场份额越来越大，所以中央空调能耗高、电费贵的问题也迫切需要解决，这对于能源节约和生活成本控制都有着一定的意义。In China's air-conditioning market, high energy consumption of central air conditioners is a common problem. The usage scenarios of central air conditioners have gradually developed from shopping malls and office buildings to residential areas, and the market share is getting larger and larger. Therefore, the problems of high energy consumption and expensive electricity bills of central air conditioners also need to be solved urgently, which is of certain significance for energy conservation and living cost control.
目前，现有的中央空调智能调控通过人工的控制在一定时间内对室内区域进行降温或升温处理，可以满足用户群体的基本需求，相比于传统挂式空调和立式空调，它的功率更大，制冷或制热效果更强劲，对一些大范围的活动区域和场地可以起到快速调温的作用。At present, the existing central air-conditioning intelligent control can cool down or heat up the indoor area within a certain period of time through manual control, which can meet the basic needs of the user group. Compared with traditional wall-mounted air conditioners and floor-standing air conditioners, it has greater power and stronger cooling or heating effects, and can quickly adjust the temperature in some large activity areas and venues.
但是现有的中央空调无法根据智慧楼宇内外温度差进行智能控制，也不能结合中央空调主机的工作状态和室内环境对室内温度进行分阶段智能调控，从而使得中央空调控制系统缺乏智能性，降低用户群体对中央空调的体验感；并且当部分区域人员较少时，室内温度给人的体感处于舒服度较高的范围时，中央空调风口仍然以正常额度功率进行工作，会造成电能资源的浪费，增加用户群体的支出和企业的运行成本。However, the existing central air conditioners cannot be intelligently controlled according to the temperature difference between the inside and outside of the smart building, nor can they intelligently adjust the indoor temperature in stages based on the working status of the central air conditioner host and the indoor environment, which makes the central air conditioner control system lack intelligence and reduces the user group's experience of central air conditioning; and when there are fewer people in some areas and the indoor temperature gives people a more comfortable feeling, the central air conditioner vents still work at normal rated power, which will cause a waste of electric energy resources and increase the expenditure of the user group and the operating costs of the enterprise.
鉴于此，本发明提出一种智慧楼宇中央空调供能智能调控系统以解决上述问题。In view of this, the present invention proposes an intelligent building central air-conditioning energy supply intelligent control system to solve the above problems.
发明内容Summary of the invention
为了克服现有技术的上述缺陷，为实现上述目的，本发明提供如下技术方案：一种智慧楼宇中央空调供能智能调控系统，包括：智慧信息采集模块，用于采集智慧楼宇的室内温度、湿度原始数据；预构建目标区域的三维立体模型；In order to overcome the above-mentioned defects of the prior art and to achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent control system for central air-conditioning energy supply of a smart building, comprising: an intelligent information collection module for collecting raw data of indoor temperature and humidity of the smart building; a pre-constructed three-dimensional model of the target area;
智慧楼宇区域划分模块，基于房间管理区域的温差划分近邻子区域和远邻子区域；Smart building area division module, which divides the near-neighbor sub-areas and far-neighbor sub-areas based on the temperature difference of the room management area;
云计算数据库管理模块，预设子区域温度阈值指数和能源优化阈值区间；A cloud computing database management module, which presets sub-region temperature threshold index and energy optimization threshold interval;
智慧楼宇室内温度调控模块，将近邻子区域和远邻子区域二次温度调控次数数据代入预设的室内温度调控模型，得到智慧楼宇室内温度调控系数；The smart building indoor temperature control module substitutes the secondary temperature control times of the near-neighbor sub-region and the far-neighbor sub-region into the preset indoor temperature control model to obtain the indoor temperature control coefficient of the smart building;
智慧楼宇能源优化模块，判断能源评估系数是否处于预设的能源优化阈值区间内；根据判断结果确定空调主机的运行模式，实现智慧楼宇室内温度的精准调控。The smart building energy optimization module determines whether the energy assessment coefficient is within the preset energy optimization threshold range; based on the judgment result, the operating mode of the air-conditioning host is determined to achieve precise control of the indoor temperature of the smart building.
进一步地，所述用于采集智慧楼宇的室内温度、湿度原始数据；预构建目标区域的三维立体模型包括：Furthermore, the method for collecting the raw data of indoor temperature and humidity of the smart building and pre-building a three-dimensional model of the target area includes:
通过智慧楼宇室内的温度监测传感器和湿度检测传感器采集室内原始数据，根据录像测量仪对室内三维立体空间的长、宽、高进行全方位扫描，预构建目标区域的三维立体模型，根据三维立体模型获取目标区域内的基本数据信息；The temperature monitoring sensors and humidity detection sensors in the smart building are used to collect the raw data of the room. The length, width and height of the indoor three-dimensional space are scanned in all directions using the video measuring instrument. A three-dimensional model of the target area is pre-built, and basic data information in the target area is obtained based on the three-dimensional model.
所述获取目标区域内的基本数据信息，包括：The basic data information in the target area is obtained, including:
室内温度、湿度数据，三维立体空间的长、宽、高数据，中央空调风口的三维坐标数据，中央空调风口流量数据，中央空调主机运行功率。Indoor temperature and humidity data, length, width and height data of three-dimensional space, three-dimensional coordinate data of central air-conditioning vents, central air-conditioning vent flow data, and central air-conditioning host operating power.
进一步地，所述基于房间管理区域的温差划分近邻子区域和远邻子区域，包括：Furthermore, the dividing of the near-neighbor sub-areas and the far-neighbor sub-areas based on the temperature difference of the room management area includes:
将三维立体模型的目标区域标记房间管理区域，基于房间管理区域的温差划分近邻子区域和远邻子区域；在每个近邻子区域和远邻子区域里安装温度监测传感器；The target area of the three-dimensional model is marked as a room management area, and the room management area is divided into near-neighbor sub-areas and far-neighbor sub-areas based on the temperature difference; a temperature monitoring sensor is installed in each near-neighbor sub-area and far-neighbor sub-area;
对房屋管理区域内各近邻子区域和远邻子区域进行编号，记为1、2、3…n，将各近邻子区域和远邻子区域里的温度数据记为a1、a2、a3…an,各近邻子区域和远邻子区域里的湿度数据记为b1、b2、b3…bn。Each neighboring sub-area and distant sub-area in the housing management area is numbered as 1, 2, 3...n, the temperature data in each neighboring sub-area and distant sub-area is recorded as a1, a2, a3...an, and the humidity data in each neighboring sub-area and distant sub-area is recorded as b1, b2, b3...bn.
进一步地，所述预设的子区域温度阈值指数，包括：Furthermore, the preset sub-region temperature threshold index includes:
通过对智慧楼宇区域划分模块实时传输的近邻子区域和远邻子区域温度和湿度数据进行分析，将房间管理区域内的每一个中央空调风口进行身份编号，采集近邻子区域和远邻子区域各自对应的温度数据；By analyzing the temperature and humidity data of the neighboring sub-areas and distant sub-areas transmitted in real time by the smart building area division module, each central air-conditioning outlet in the room management area is numbered, and the temperature data corresponding to the neighboring sub-areas and distant sub-areas are collected;
将近邻子区域和远邻子区域各自对应的温度数据与预设子区域温度阈值指数相比对；得到对比结果；根据对比结果对近邻子区域和远邻子区域进行升温或降温处理；Compare the temperature data corresponding to the adjacent sub-region and the distant sub-region with the preset sub-region temperature threshold index; obtain a comparison result; and perform temperature increase or decrease processing on the adjacent sub-region and the distant sub-region according to the comparison result;
所述身份编号包括：The identification number includes:
三维立体模型中中央空调风口的三维坐标数据、风口的流量面积以及中央空调风口的能效比；The three-dimensional coordinate data of the central air-conditioning vents in the three-dimensional model, the flow area of the vents, and the energy efficiency ratio of the central air-conditioning vents;
所述预设的子区域温度阈值指数，对室内温度状态进行升温或降温的方式包括：The preset sub-area temperature threshold index, the way of raising or lowering the indoor temperature state includes:
将室内温度数据和湿度数据代入预设的温度舒适度指数模型中，得到子区域温度阈值指数THI；Substitute the indoor temperature data and humidity data into the preset temperature comfort index model to obtain the sub-area temperature threshold index THI;
所述温度舒适度指数模型的公式为：THI＝0.8T+(RH/100)(T14.4)+46.4,其中，T代表室内温度，RH代表室内湿度，当子区域温度高于或低于温度阈值指数THI时，中央空调主机开始工作，进行升温或降温处理。The formula of the temperature comfort index model is: THI=0.8T+(RH/100)(T14.4)+46.4, where T represents the indoor temperature and RH represents the indoor humidity. When the temperature of the sub-area is higher or lower than the temperature threshold index THI, the central air-conditioning host starts working to heat up or cool down.
进一步地，所述将近邻子区域和远邻子区域二次温度调控次数数据代入预设的室内温度调控模型，得到智慧楼宇室内温度调控系数，包括：Furthermore, the data of the secondary temperature control times of the near-neighbor sub-region and the far-neighbor sub-region is substituted into a preset indoor temperature control model to obtain the indoor temperature control coefficient of the smart building, including:
提取近邻子区域和远邻子区域中温度监测传感器产生的实时数据，通过预设的子区域温度阈值指数，判断房间管理区域的温度是否合格，当室内温度数据高于或低于THI数值时，中央空调主机自主进行工作，对房屋管理区域进行温度升温或降温处理；Extract the real-time data generated by the temperature monitoring sensors in the neighboring sub-areas and distant sub-areas, and judge whether the temperature of the room management area is qualified through the preset sub-area temperature threshold index. When the indoor temperature data is higher or lower than the THI value, the central air-conditioning host works autonomously to raise or lower the temperature of the house management area;
近邻子区域需要满足的温度条件对应第一阶梯温度阈值规则，远邻子区域需要满足的温度条件对应第二阶梯温度阈值规则；当中央空调主机停止工作后，通过各近邻子区域和远邻子区域内的温度监测传感器第二次采集区域实时温度数据；基于采集到的实时温度数据，代入预设的第一阶梯温度阈值规则和第二阶梯温度阈值规则，判断中央空调主机是否需要自主启动，基于云计算数据库管理模块中室内中央空调风口的三维立体坐标位置数据，启动距离最近的中央空调风口对温度不合格的近邻子区域和远邻子区域进行温度升温或降温处理；The temperature condition that needs to be met by the neighboring sub-area corresponds to the first-step temperature threshold rule, and the temperature condition that needs to be met by the distant sub-area corresponds to the second-step temperature threshold rule; when the central air-conditioning host stops working, the real-time temperature data of the area is collected for the second time through the temperature monitoring sensors in each neighboring sub-area and distant sub-area; based on the collected real-time temperature data, the preset first-step temperature threshold rule and the second-step temperature threshold rule are substituted to determine whether the central air-conditioning host needs to be started autonomously, and based on the three-dimensional coordinate position data of the indoor central air-conditioning outlet in the cloud computing database management module, the nearest central air-conditioning outlet is started to heat up or cool down the neighboring sub-areas and distant sub-areas with unqualified temperatures;
将各近邻子区域和远邻子区域温度调控的次数和时间数据，代入预设的智慧楼宇室内温度调控模型中，得到智慧楼宇室内温度调控系数η；Substitute the frequency and time data of temperature control of each neighboring sub-area and distant sub-area into the preset smart building indoor temperature control model to obtain the smart building indoor temperature control coefficient η;
所述智慧楼宇室内温度调控模型的公式为：其中，k为二次温度调控次数，Δt为房间管理区域中中央空调主机运行的总时间，/>为各近邻子区域和远邻子区域温度的方差值，VS为扫描出的房间管理区域体积，λ为房间管理区域体积的影响因子，/>为房间管理区域的平均湿度水平。The formula of the indoor temperature control model of the smart building is: Where k is the number of secondary temperature control times, Δt is the total operation time of the central air-conditioning host in the room management area, /> is the variance of the temperature of each neighboring sub-region and distant sub-region, VS is the volume of the scanned room management area, λ is the influencing factor of the volume of the room management area, /> Manages the average humidity level in the room area.
进一步地，所述第一阶梯温度阈值规则为THI1＝0.8Tn+(RHn/100)(Tn14.4)+45.4,其中，Tn代表近邻子区域内温度，RHn代表近邻子区域内湿度，得到第一阶梯温度阈值指数THI1,当近邻子区域的温度数据小于等于THI1时，近邻子区域内温度合格；Furthermore, the first step temperature threshold rule is THI1=0.8Tn+(RHn/100)(Tn14.4)+45.4, where Tn represents the temperature in the neighboring sub-region, and RHn represents the humidity in the neighboring sub-region, and the first step temperature threshold index THI1 is obtained. When the temperature data of the neighboring sub-region is less than or equal to THI1, the temperature in the neighboring sub-region is qualified;
所述第二阶梯温度阈值规则为THI2＝0.8Tn+(RHn/100)(Tn14.4)+47.4，其中，Tn代表远邻子区域内温度，RHn代表远邻子区域内湿度，得到第二阶梯温度阈值指数THI2,当远邻子区域的温度数据小于等于THI2时，远邻子区域内温度合格。The second step temperature threshold rule is THI2=0.8Tn+(RHn/100)(Tn14.4)+47.4, where Tn represents the temperature in the distant sub-area, and RHn represents the humidity in the distant sub-area. The second step temperature threshold index THI2 is obtained. When the temperature data of the distant sub-area is less than or equal to THI2, the temperature in the distant sub-area is qualified.
进一步地，所述判断能源评估系数是否处于预设的能源优化阈值区间内；根据判断结果确定空调主机的运行模式的方式，包括：Furthermore, the method of determining whether the energy evaluation coefficient is within a preset energy optimization threshold range and determining the operation mode of the air conditioner host according to the determination result includes:
根据云计算数据库管理模块实时传输的温度数据对需要温度调控的近邻子区域和远邻子区域进行判断；According to the temperature data transmitted in real time by the cloud computing database management module, the neighboring sub-areas and distant sub-areas that need temperature control are judged;
所述对需要温度调控的近邻子区域和远邻子区域进行判断的方式包括：The method of judging the neighboring sub-regions and distant sub-regions that need temperature control includes:
将智慧楼宇室内温度调控模块中温度调控系数代入预设的能源评估系数模型中，得到能源评估系数QS；Substitute the temperature control coefficient in the indoor temperature control module of the smart building into the preset energy assessment coefficient model to obtain the energy assessment coefficient QS ;
所述能源评估系数模型的公式为：QS＝η·MK·E·ξ1,其中，η为智慧楼宇室内温度调控系数，MK为时刻电价，E为时刻用电量，ξ1为时刻用电量的影响因子，判断能源评估系数QS是否处于预设的能源优化阈值区间中，得到判断结果，根据判断结果确定空调主机是否分阶段对房间管理区域进行升温或降温处理；The formula of the energy evaluation coefficient model is: QS =η·MK ·E·ξ1 , where η is the indoor temperature control coefficient of the smart building, MK is the electricity price at the time, E is the electricity consumption at the time, and ξ1 is the influencing factor of the electricity consumption at the time. It is judged whether the energy evaluation coefficient QS is in the preset energy optimization threshold range, and a judgment result is obtained. According to the judgment result, it is determined whether the air-conditioning host performs temperature increase or temperature reduction processing on the room management area in stages;
所述根据判断结果确定空调主机是否分阶段对房间管理区域进行升温或降温处理的方式包括：The method of determining whether the air conditioner host performs temperature increase or temperature decrease processing on the room management area in stages according to the judgment result includes:
基于在时刻用电量过大、电费峰值时间段和中央空调主机运行过热时，当能源评估系数在能源优化阈值区间内时，中央空调主机不进行分阶段降温或升温处理，当能源评估系数不在能源优化阈值区间中时，中央空调主机进行分阶段降温或升温处理。Based on the conditions of excessive power consumption, peak electricity price period and overheating of the central air-conditioning host, when the energy evaluation coefficient is within the energy optimization threshold range, the central air-conditioning host does not perform staged cooling or heating processing. When the energy evaluation coefficient is not within the energy optimization threshold range, the central air-conditioning host performs staged cooling or heating processing.
进一步地，所述智慧楼宇室内温度调控系数QS＝η·MK·E·ξ1,其中，E为时刻用电量，ξ1为时刻用电量的影响因子；Furthermore, the indoor temperature control coefficient of the smart building is QS =η·MK ·E·ξ1 , where E is the power consumption at the moment, and ξ1 is the influencing factor of the power consumption at the moment;
所述时刻用电量公式为：E＝ξ1∑(Pi+Δti×CFi)，其中，Pi为房间管理区域内第i个用电设备的功率，Δti为i个用电设备使用的总时间，CFi为第i个用电设备的功率数。The power consumption formula at the moment is: E=ξ1 ∑(Pi +Δti ×CFi ), wherePi is the power of the i-th power device in the room management area, Δti is the total time the i-th power device is used, and CFi is the power of the i-th power device.
进一步地，所述预设的能源优化阈值区间为[ω1，,ω2]；Furthermore, the preset energy optimization threshold interval is [ω1, ω2];
所述ω1＝Uτ·η·∑(Pi+Δti×CFi)，其中∑(Pi+Δti×CFi)为时刻用电量，η为智慧楼宇室内温度调控系数，Uτ为当天的峰谷电价；The ω1=Uτ·η·∑(Pi +Δti ×CFi ), where ∑(Pi +Δti ×CFi ) is the power consumption at the moment, η is the indoor temperature control coefficient of the smart building, and Uτ is the peak and valley electricity price of the day;
ω2＝6/5Uτ·η·Σ(Pi+Δti×CFi)，其中Σ(Pi+Δti×CFi)为时刻用电量，η为智慧楼宇室内温度调控系数，Uτ为当天的峰谷电价。ω2＝6/5Uτ·η·Σ(Pi +Δti ×CFi ), where Σ(Pi +Δti ×CFi ) is the electricity consumption at each moment, η is the indoor temperature control coefficient of the smart building, and Uτ is the peak and valley electricity price of the day.
进一步地，所述当能源评估系数不在能源优化阈值区间中时，中央空调主机进行分阶段降温或升温处理，其中，分阶段降温或升温处理基于能源评估系数QS是否处于预设的能源优化阈值区间中，当能源评估系数处于预设的能源优化阈值区间内时，中央空调主机直接工作，将房间管理区域内的温度升温或降温至预设的子区域温度阈值指数值，当能源评估系数不处于预设的能源优化阈值区间内时，中央空调主机将房间管理区域的温度升温至16摄氏度或降温至30摄氏度时停止工作，当监测到能源评估系数处于预设的能源优化阈值区间内时，再将房间管理区域内的温度升温或降温至预设的子区域温度阈值指数值。Furthermore, when the energy evaluation coefficient is not within the energy optimization threshold interval, the central air-conditioning host performs a staged cooling or heating process, wherein the staged cooling or heating process is based on whether the energy evaluation coefficientQS is within the preset energy optimization threshold interval. When the energy evaluation coefficient is within the preset energy optimization threshold interval, the central air-conditioning host works directly to raise or lower the temperature in the room management area to a preset sub-area temperature threshold index value. When the energy evaluation coefficient is not within the preset energy optimization threshold interval, the central air-conditioning host raises the temperature of the room management area to 16 degrees Celsius or lowers it to 30 degrees Celsius and stops working. When it is monitored that the energy evaluation coefficient is within the preset energy optimization threshold interval, the temperature in the room management area is raised or lowered to the preset sub-area temperature threshold index value.
本发明一种智慧楼宇中央空调供能智能调控系统的技术效果和优点：The technical effects and advantages of the intelligent control system for central air conditioning energy supply in a smart building of the present invention are as follows:
本发明实现对不同房间区域模型的特征化表达；基于房间管理区域的温差划分近邻子区域和远邻子区域，对房间温度精细化调控，增强用户群体的体验感；从而使中央空调控制系统智能性，高效性，提供给用户最舒服的室内体感温度，当房间管理区域人数较少时，中央空调风口以低额度功率进行工作，节约电能资源的浪费，减少用户群体的支出和企业的运行成本。The present invention realizes the characterization expression of different room area models; divides the room management area into near-neighbor sub-areas and far-neighbor sub-areas based on the temperature difference, finely controls the room temperature, and enhances the user experience; thereby making the central air-conditioning control system intelligent and efficient, and providing users with the most comfortable indoor temperature. When there are fewer people in the room management area, the central air-conditioning vents work at a low power rating, saving waste of electric energy resources and reducing the expenditure of the user group and the operating costs of the enterprise.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1为本发明的一种智慧楼宇中央空调供能智能调控系统示意图；FIG1 is a schematic diagram of an intelligent control system for central air conditioning energy supply in a smart building according to the present invention;
图2为本发明的一种智慧楼宇中央空调供能智能调控方法示意图；FIG2 is a schematic diagram of a method for intelligently controlling energy supply of central air conditioning in a smart building according to the present invention;
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
实施例1Example 1
请参阅图1所示，本实施例所述一种智慧楼宇中央空调供能智能调控系统，包括：Please refer to FIG1 , a smart building central air conditioning energy supply intelligent control system described in this embodiment includes:
智慧信息采集模块，用于采集智慧楼宇的室内温度、湿度原始数据；预构建目标区域的三维立体模型；Smart information collection module, used to collect raw data of indoor temperature and humidity of smart buildings; pre-build a three-dimensional model of the target area;
智慧楼宇区域划分模块，基于房间管理区域的温差划分近邻子区域和远邻子区域；Smart building area division module, which divides the near-neighbor sub-areas and far-neighbor sub-areas based on the temperature difference of the room management area;
云计算数据库管理模块，预设子区域温度阈值指数和能源优化阈值区间；A cloud computing database management module, which presets sub-region temperature threshold index and energy optimization threshold interval;
智慧楼宇室内温度调控模块，将近邻子区域和远邻子区域二次温度调控次数数据代入预设的室内温度调控模型，得到智慧楼宇室内温度调控系数；The smart building indoor temperature control module substitutes the secondary temperature control times of the near-neighbor sub-region and the far-neighbor sub-region into the preset indoor temperature control model to obtain the indoor temperature control coefficient of the smart building;
智慧楼宇能源优化模块，判断能源评估系数是否处于预设的能源优化阈值区间内；根据判断结果确定空调主机的运行模式，实现智慧楼宇室内温度的精准调控；The smart building energy optimization module determines whether the energy evaluation coefficient is within the preset energy optimization threshold range; determines the operation mode of the air-conditioning host based on the judgment result, and realizes precise control of the indoor temperature of the smart building;
进一步的，所述用于采集智慧楼宇的室内温度、湿度原始数据；预构建目标区域的三维立体模型包括：Furthermore, the method for collecting raw data of indoor temperature and humidity of smart buildings and pre-building a three-dimensional model of the target area includes:
通过智慧楼宇室内的温度监测传感器和湿度检测传感器采集室内原始数据，根据录像测量仪对室内三维立体空间的长、宽、高进行全方位扫描，预构建目标区域的三维立体模型，根据三维立体模型获取目标区域内的基本数据信息；The temperature monitoring sensors and humidity detection sensors in the smart building are used to collect the raw data of the room. The length, width and height of the indoor three-dimensional space are scanned in all directions using the video measuring instrument. A three-dimensional model of the target area is pre-built, and basic data information in the target area is obtained based on the three-dimensional model.
所述获取目标区域内的基本数据信息包括：The basic data information obtained in the target area includes:
室内温度、湿度数据，三维立体空间的长、宽、高数据，中央空调风口的三维坐标数据，中央空调风口流量数据，中央空调主机运行功率；并将所采集的原始温度、湿度数据和房间三维立体空间的长、宽、高数据传输至智慧楼宇区域划分模块。Indoor temperature and humidity data, length, width and height data of three-dimensional space, three-dimensional coordinate data of central air-conditioning vents, central air-conditioning vent flow data, and central air-conditioning host operating power; and transmit the collected original temperature and humidity data and the length, width and height data of the three-dimensional space of the room to the smart building area division module.
进一步的，所述基于房间管理区域的温差划分近邻子区域和远邻子区域包括：Furthermore, the dividing of the near-neighbor sub-areas and the far-neighbor sub-areas based on the temperature difference of the room management area includes:
将三维立体模型的目标区域标记房间管理区域，基于房间管理区域的温差划分近邻子区域和远邻子区域；在每个近邻子区域和远邻子区域里安装温度监测传感器；The target area of the three-dimensional model is marked as a room management area, and the room management area is divided into near-neighbor sub-areas and far-neighbor sub-areas based on the temperature difference; a temperature monitoring sensor is installed in each near-neighbor sub-area and far-neighbor sub-area;
所述基于房间管理区域的温差划分近邻子区域和远邻子区域：The temperature difference based room management area is divided into near neighbor sub-areas and far neighbor sub-areas:
其中近邻子区域为靠近中央空调风口的区域，远邻子区域为与中央空调风口不靠近的区域；The near neighbor sub-area is the area close to the central air-conditioning outlet, and the far neighbor sub-area is the area not close to the central air-conditioning outlet.
对房屋管理区域内各近邻子区域和远邻子区域进行编号，记为1、2、3…n，将各近邻子区域和远邻子区域里的温度数据记为a1、a2、a3…an,各近邻子区域和远邻子区域里的湿度数据记为b1、b2、b3…bn。Each neighboring sub-area and distant sub-area in the housing management area is numbered as 1, 2, 3...n, the temperature data in each neighboring sub-area and distant sub-area is recorded as a1, a2, a3...an, and the humidity data in each neighboring sub-area and distant sub-area is recorded as b1, b2, b3...bn.
进一步的，所述预设的子区域温度阈值指数，包括：Furthermore, the preset sub-region temperature threshold index includes:
通过对智慧楼宇区域划分模块实时传输的近邻子区域和远邻子区域温度和湿度数据进行分析，将房间管理区域内的每一个中央空调风口进行身份编号，采集近邻子区域和远邻子区域各自对应的温度数据；By analyzing the temperature and humidity data of the neighboring sub-areas and distant sub-areas transmitted in real time by the smart building area division module, each central air-conditioning outlet in the room management area is numbered, and the temperature data corresponding to the neighboring sub-areas and distant sub-areas are collected;
将近邻子区域和远邻子区域各自对应的温度数据与预设子区域温度阈值指数相比对；得到对比结果；根据对比结果对近邻子区域和远邻子区域进行升温或降温处理；Compare the temperature data corresponding to the adjacent sub-region and the distant sub-region with the preset sub-region temperature threshold index; obtain a comparison result; and perform temperature increase or decrease processing on the adjacent sub-region and the distant sub-region according to the comparison result;
所述身份编号包括：The identification number includes:
三维立体模型中中央空调风口的三维坐标数据、风口的流量面积以及中央空调风口的能效比；The three-dimensional coordinate data of the central air-conditioning vents in the three-dimensional model, the flow area of the vents, and the energy efficiency ratio of the central air-conditioning vents;
所述预设子区域温度阈值指数，对室内温度状态进行升温或降温包括：The preset sub-area temperature threshold index for raising or lowering the indoor temperature state includes:
将室内温度数据和湿度数据代入预设的温度舒适度指数模型中，得到子区域温度阈值指数THI；Substitute the indoor temperature data and humidity data into the preset temperature comfort index model to obtain the sub-area temperature threshold index THI;
所述温度舒适度指数模型的公式为：THI＝0.8T+(RH/100)(T14.4)+46.4,其中，T代表室内温度，RH代表室内湿度，当子区域温度高于或低于温度阈值指数THI时，中央空调主机开始工作，进行升温或降温处理，实现对室内温度状态的精准调控。The formula of the temperature comfort index model is: THI=0.8T+(RH/100)(T14.4)+46.4, where T represents the indoor temperature and RH represents the indoor humidity. When the temperature of the sub-area is higher or lower than the temperature threshold index THI, the central air-conditioning host starts to work and performs heating or cooling processing to achieve precise control of the indoor temperature state.
进一步的，所述将近邻子区域和远邻子区域二次温度调控次数数据代入预设的室内温度调控模型，得到智慧楼宇室内温度调控系数，包括：Furthermore, the data of the secondary temperature control times of the near-neighbor sub-region and the far-neighbor sub-region is substituted into a preset indoor temperature control model to obtain the indoor temperature control coefficient of the smart building, including:
提取近邻子区域和远邻子区域中温度监测传感器产生的实时数据，通过预设的子区域温度阈值指数，判断房间管理区域的温度是否合格，当室内温度数据高于或低于THI数值时，中央空调主机自主进行工作，对房屋管理区域进行温度升温或降温处理；Extract the real-time data generated by the temperature monitoring sensors in the neighboring sub-areas and distant sub-areas, and judge whether the temperature of the room management area is qualified through the preset sub-area temperature threshold index. When the indoor temperature data is higher or lower than the THI value, the central air-conditioning host works autonomously to raise or lower the temperature of the house management area;
近邻子区域需要满足的温度条件对应第一阶梯温度阈值规则，远邻子区域需要满足的温度条件对应第二阶梯温度阈值规则；当中央空调主机停止工作后，通过各近邻子区域和远邻子区域内的温度监测传感器第二次采集区域温度数据；基于采集到的实时温度数据，代入预设的第一阶梯温度阈值规则和第二阶梯温度阈值规则，判断中央空调主机是否需要自主启动，当近邻子区域和远邻子区域的温度数据小于或等于预设的第一阶梯温度阈值规则和第二阶梯温度阈值规则时，判断房间管理区域温度合格，当近邻子区域和远邻子区域的温度数据大于预设的第一阶梯温度阈值规则和第二阶梯温度阈值规则时，判断房间管理区域温度不合格，基于云计算数据库管理模块中室内中央空调风口的三维立体坐标位置数据，启动距离最近的中央空调风口对温度不合格的近邻子区域和远邻子区域进行温度升温或降温处理，以达到人体感最舒服的温度，提高用户群体的体验感；The temperature condition that needs to be met by the neighboring sub-area corresponds to the first-step temperature threshold rule, and the temperature condition that needs to be met by the distant sub-area corresponds to the second-step temperature threshold rule; when the central air-conditioning host stops working, the regional temperature data is collected for the second time through the temperature monitoring sensors in each neighboring sub-area and distant sub-area; based on the collected real-time temperature data, the preset first-step temperature threshold rule and the second-step temperature threshold rule are substituted to determine whether the central air-conditioning host needs to be started automatically; when the temperature data of the neighboring sub-area and the distant sub-area is less than or equal to the preset first-step temperature threshold rule and the second-step temperature threshold rule, the room management area temperature is determined to be qualified; when the temperature data of the neighboring sub-area and the distant sub-area is greater than the preset first-step temperature threshold rule and the second-step temperature threshold rule, the room management area temperature is determined to be unqualified; based on the three-dimensional coordinate position data of the indoor central air-conditioning outlet in the cloud computing database management module, the nearest central air-conditioning outlet is started to heat up or cool down the neighboring sub-area and the distant sub-area whose temperature is unqualified, so as to achieve the most comfortable temperature for human body and improve the user experience;
将各近邻子区域和远邻子区域温度调控的次数和时间数据，代入预设的智慧楼宇室内温度调控模型中，得到智慧楼宇室内温度调控系数η；Substitute the frequency and time data of temperature control of each neighboring sub-area and distant sub-area into the preset smart building indoor temperature control model to obtain the smart building indoor temperature control coefficient η;
所述智慧楼宇室内温度调控模型的公式为：其中，k为二次温度调控次数，Δt为房间管理区域中中央空调主机运行的总时间，/>为各近邻子区域和远邻子区域温度的方差值，VS为扫描出的房间管理区域体积，λ为房间管理区域体积的影响因子，/>为房间管理区域的平均湿度水平。The formula of the indoor temperature control model of the smart building is: Where k is the number of secondary temperature control times, Δt is the total operation time of the central air-conditioning host in the room management area, /> is the variance of the temperature of each neighboring sub-region and distant sub-region, VS is the volume of the scanned room management area, λ is the influencing factor of the volume of the room management area, /> Manages the average humidity level in the room area.
进一步的，所述近邻子区域需要满足的温度条件对应第一阶梯温度阈值规则，远邻子区域需要满足的温度条件对应第二阶梯温度阈值规则包括：Furthermore, the temperature condition that the neighboring sub-region needs to meet corresponds to the first step temperature threshold rule, and the temperature condition that the distant sub-region needs to meet corresponds to the second step temperature threshold rule, including:
在近邻子区域需要满足的温度条件对应第一阶梯温度阈值规则，第一阶梯温度阈值规则为THI1＝0.8Tn+(RHn/100)(Tn14.4)+45.4,其中，Tn代表近邻子区域内温度，单位摄氏度，RHn代表近邻子区域内湿度，得到第一阶梯温度阈值指数THI1,当近邻子区域的温度数据小于等于THI1时，近邻子区域内温度合格；远邻子区域需要满足的温度条件对应第二阶梯温度阈值规则，第二阶梯温度阈值规则为THI2＝0.8Tn+(RHn/100)(Tn14.4)+47.4，其中，Tn代表远邻子区域内温度，单位摄氏度，RHn代表远邻子区域内湿度，得到第二阶梯温度阈值指数THI2,当远邻子区域的温度数据小于等于THI2时，远邻子区域内温度合格。The temperature condition that needs to be met in the neighboring sub-area corresponds to the first-step temperature threshold rule, and the first-step temperature threshold rule is THI1=0.8Tn+(RHn/100)(Tn14.4)+45.4, where Tn represents the temperature in the neighboring sub-area, in degrees Celsius, and RHn represents the humidity in the neighboring sub-area, and the first-step temperature threshold index THI1 is obtained. When the temperature data of the neighboring sub-area is less than or equal to THI1, the temperature in the neighboring sub-area is qualified; the temperature condition that needs to be met in the distant sub-area corresponds to the second-step temperature threshold rule, and the second-step temperature threshold rule is THI2=0.8Tn+(RHn/100)(Tn14.4)+47.4, where Tn represents the temperature in the distant sub-area, in degrees Celsius, and RHn represents the humidity in the distant sub-area, and the second-step temperature threshold index THI2 is obtained. When the temperature data of the distant sub-area is less than or equal to THI2, the temperature in the distant sub-area is qualified.
进一步的，所述判断能源评估系数是否处于预设的能源优化阈值区间内；根据判断结果确定空调主机的运行模式的方式，包括：Furthermore, the method of determining whether the energy evaluation coefficient is within a preset energy optimization threshold range and determining the operation mode of the air conditioner host according to the determination result includes:
根据云计算数据库管理模块实时传输的温度数据对需要温度调控的近邻子区域和远邻子区域进行判断；According to the temperature data transmitted in real time by the cloud computing database management module, the neighboring sub-areas and distant sub-areas that need temperature control are judged;
所述对需要温度调控的近邻子区域和远邻子区域进行判断的方式包括：The method of judging the neighboring sub-regions and distant sub-regions that need temperature control includes:
将智慧楼宇室内温度调控模块中温度调控系数代入预设的能源评估系数模型中，得到能源评估系数QS；Substitute the temperature control coefficient in the indoor temperature control module of the smart building into the preset energy assessment coefficient model to obtain the energy assessment coefficient QS ;
所述能源评估系数模型的公式为：QS＝η·MK·E·ξ1,其中，η为智慧楼宇室内温度调控系数，MK为时刻电价，E为时刻用电量，ξ1为时刻用电量的影响因子，判断能源评估系数QS是否处于预设的能源优化阈值区间中，当能源评估系数QS处于预设的能源优化阈值区间中时，智慧楼宇的温度调控处于能源优化范围，当能源评估系数QS不处于预设的能源优化阈值区间中时，智慧楼宇的温度调控处于能源过度消耗范围，得到判断结果，根据判断结果确定空调主机是否分阶段对房间管理区域进行升温或降温处理，实现对智慧楼宇室内温度的精准调控；The formula of the energy evaluation coefficient model is: QS =η·MK ·E·ξ1 , wherein η is the indoor temperature control coefficient of the smart building, MK is the electricity price at the time, E is the electricity consumption at the time, and ξ1 is the influencing factor of the electricity consumption at the time. It is judged whether the energy evaluation coefficient QS is in the preset energy optimization threshold interval. When the energy evaluation coefficient QS is in the preset energy optimization threshold interval, the temperature control of the smart building is in the energy optimization range. When the energy evaluation coefficient QS is not in the preset energy optimization threshold interval, the temperature control of the smart building is in the energy over-consumption range. A judgment result is obtained, and according to the judgment result, it is determined whether the air-conditioning host performs temperature increase or temperature reduction processing on the room management area in stages, so as to realize precise control of the indoor temperature of the smart building;
所述对需要温度调控的近邻子区域和远邻子区域进行判断，是否需要进行分阶段升温或降温处理；The neighboring sub-regions and distant sub-regions that need temperature control are judged to determine whether they need to be heated up or cooled down in stages;
基于在时刻用电量过大、电费峰值时间段和中央空调主机运行过热时，当能源评估系数在能源优化阈值区间内时，中央空调主机不进行分阶段降温或升温处理，当能源评估系数不在能源优化阈值区间中时，中央空调主机进行分阶段降温或升温处理。Based on the conditions of excessive power consumption, peak electricity price period and overheating of the central air-conditioning host, when the energy evaluation coefficient is within the energy optimization threshold range, the central air-conditioning host does not perform staged cooling or heating processing. When the energy evaluation coefficient is not within the energy optimization threshold range, the central air-conditioning host performs staged cooling or heating processing.
所述智慧楼宇室内温度调控系数QS＝η·MK·E·ξ1,其中，E为时刻用电量，ξ1为时刻用电量的影响因子；The indoor temperature control coefficient of the smart building is QS =η·MK ·E·ξ1 , where E is the power consumption at any given moment and ξ1 is the influencing factor of the power consumption at any given moment;
所述时刻用电量公式为：E＝ξ1∑(Pi+Δti×CFi)，其中，Pi为房间管理区域内第i个用电设备的功率，Δti为i个用电设备使用的总时间，CFi为第i个用电设备的功率数。The power consumption formula at the moment is: E=ξ1 ∑(Pi +Δti ×CFi ), wherePi is the power of the i-th power device in the room management area, Δti is the total time the i-th power device is used, and CFi is the power of the i-th power device.
所述预设的能源优化阈值区间为[ω1，,ω2]；The preset energy optimization threshold interval is [ω1, ω2];
所述ω1＝Uτ·η·∑(Pi+Δti×CFi)，其中∑(Pi+Δti×CFi)为时刻用电量，η为智慧楼宇室内温度调控系数，Uτ为当天的峰谷电价；The ω1=Uτ·η·∑(Pi +Δti ×CFi ), where ∑(Pi +Δti ×CFi ) is the power consumption at the moment, η is the indoor temperature control coefficient of the smart building, and Uτ is the peak and valley electricity price of the day;
ω2＝6/5Uτ·η·∑(Pi+Δti×CFi)，其中∑(Pi+Δti×CFi)为时刻用电量，η为智慧楼宇室内温度调控系数，Uτ为当天的峰谷电价。ω2＝6/5Uτ·η·∑(Pi +Δti ×CFi ), where ∑(Pi +Δti ×CFi ) is the electricity consumption at each moment, η is the indoor temperature control coefficient of the smart building, and Uτ is the peak and valley electricity price of the day.
进一步的，所述当能源评估系数不在能源优化阈值区间中时，中央空调主机进行分阶段降温或升温处理，其中，分阶段降温或升温处理基于能源评估系数QS是否处于预设的能源优化阈值区间中，当能源评估系数处于预设的能源优化阈值区间内时，中央空调主机直接工作，将房间管理区域内的温度升温或降温至预设的子区域温度阈值指数值，当能源评估系数不处于预设的能源优化阈值区间内时，中央空调主机将房间管理区域的温度升温至16摄氏度或降温至30摄氏度时停止工作，当监测到能源评估系数处于预设的能源优化阈值区间内时，再将房间管理区域内的温度升温或降温至预设的子区域温度阈值指数值。Furthermore, when the energy evaluation coefficient is not within the energy optimization threshold interval, the central air-conditioning host performs a staged cooling or heating process, wherein the staged cooling or heating process is based on whether the energy evaluation coefficientQS is within the preset energy optimization threshold interval. When the energy evaluation coefficient is within the preset energy optimization threshold interval, the central air-conditioning host works directly to raise or lower the temperature in the room management area to a preset sub-area temperature threshold index value. When the energy evaluation coefficient is not within the preset energy optimization threshold interval, the central air-conditioning host raises or lowers the temperature in the room management area to 16 degrees Celsius or lowers it to 30 degrees Celsius and stops working. When it is monitored that the energy evaluation coefficient is within the preset energy optimization threshold interval, the temperature in the room management area is raised or lowered to the preset sub-area temperature threshold index value.
本实施例，实现对不同房间区域模型的特征化表达；基于房间管理区域的温差划分近邻子区域和远邻子区域，对房间温度精细化调控，增强用户群体的体验感；从而使中央空调控制系统智能性，高效性，提供给用户最舒服的室内体感温度，当房间管理区域人数较少时，中央空调风口以低额度功率进行工作，节约电能资源的浪费，减少用户群体的支出和企业的运行成本。This embodiment realizes the characterization expression of different room area models; divides the room management area into near-neighbor sub-areas and far-neighbor sub-areas based on the temperature difference, and finely controls the room temperature to enhance the user experience; thereby making the central air-conditioning control system intelligent and efficient, and providing users with the most comfortable indoor temperature. When there are fewer people in the room management area, the central air-conditioning vents work at a low power rating, saving waste of electric energy resources and reducing the expenditure of the user group and the operating costs of the enterprise.
实施例2Example 2
请参阅图2所示，本实施例未详细叙述部分见实施例1描述内容，提供一种智慧楼宇中央空调供能智能调控方法，包括：Please refer to FIG. 2 . For the parts not described in detail in this embodiment, please refer to the description of Embodiment 1. A method for intelligently controlling energy supply of central air conditioning in a smart building is provided, including:
S1、采集智慧楼宇的室内温度、湿度原始数据；预构建完成目标区域的三维立体模型，根据三维立体模型获取目标区域内的基本数据信息；S1. Collect the original data of indoor temperature and humidity of the smart building; pre-build a three-dimensional model of the target area, and obtain basic data information in the target area based on the three-dimensional model;
S2、将三维立体模型标记房间管理区域，基于房间管理区域的温差划分近邻子区域和远邻子区域，对近邻子区域和远邻子区域进行编号，记为1、2、3…N；S2, marking the room management area with the three-dimensional model, dividing the room management area into near neighbor sub-areas and far neighbor sub-areas based on the temperature difference, and numbering the near neighbor sub-areas and far neighbor sub-areas as 1, 2, 3...N;
S3、将房间管理区域内每一个中央空调风口进行身份编号，采集近邻子区域和远邻子区域各自对应的温度数据；并预设子区域温度阈值指数；S3. Number each central air-conditioning outlet in the room management area, collect temperature data corresponding to the adjacent sub-areas and distant sub-areas, and preset the sub-area temperature threshold index;
S4、基于近邻子区域和远邻子区域各自对应的温度数据，通过预设子区域温度阈值指数，判断房间管理区域温度是否合格；并提取近邻子区域和远邻子区域二次温度调控次数，S4. Based on the temperature data corresponding to the neighboring sub-areas and the distant sub-areas, determine whether the temperature of the room management area is qualified by presetting the sub-area temperature threshold index; and extract the number of secondary temperature control times of the neighboring sub-areas and the distant sub-areas.
将近邻子区域和远邻子区域二次温度调控次数代入预设的室内温度调控模型，得到智慧楼宇室内温度调控系数；Substitute the secondary temperature control times of the near-neighbor sub-region and the far-neighbor sub-region into the preset indoor temperature control model to obtain the indoor temperature control coefficient of the smart building;
S5、将智慧楼宇室内温度调控系数代入预设的能源评估模型中，得到能源评估系数，判断能源评估系数是否处于预设的能源优化阈值区间内，得到判断结果；根据判断结果确定空调主机的运行模式，实现智慧楼宇室内温度的精准调控。S5. Substitute the indoor temperature control coefficient of the smart building into the preset energy assessment model to obtain the energy assessment coefficient, determine whether the energy assessment coefficient is within the preset energy optimization threshold range, and obtain a judgment result; determine the operation mode of the air-conditioning host according to the judgment result to achieve precise control of the indoor temperature of the smart building.
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.
上述公式均是去量纲取其数值计算，公式是由采集大量数据进行软件模拟得到最近真实情况的一个公式，公式中的预设参数以及阈值选取由本领域的技术人员根据实际情况进行设置。The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and thresholds in the formula are set by technicians in this field according to actual conditions.
最后以上所述仅为本发明的优选实施例而已，并不用于限制本发明，凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
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| CN118548564A (en)* | 2024-05-28 | 2024-08-27 | 广州广视物业管理服务有限公司 | Air conditioning equipment energy-saving management system based on Internet of things |
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| TWI896372B (en) | 2024-10-14 | 2025-09-01 | 城市學校財團法人臺北城市科技大學 | Air conditioner capacity estimator |
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| CN118548564A (en)* | 2024-05-28 | 2024-08-27 | 广州广视物业管理服务有限公司 | Air conditioning equipment energy-saving management system based on Internet of things |
| CN118623464A (en)* | 2024-08-15 | 2024-09-10 | 江苏众兴永达制冷机械制造有限公司 | A thermal management system for industrial air conditioning |
| CN119105584A (en)* | 2024-10-09 | 2024-12-10 | 深圳市祥兴电热连接线科技有限公司 | An intelligent control method for temperature intelligent control system |
| CN119105584B (en)* | 2024-10-09 | 2025-07-08 | 深圳市祥兴电热连接线科技有限公司 | An intelligent control method for temperature intelligent control system |
| TWI896372B (en) | 2024-10-14 | 2025-09-01 | 城市學校財團法人臺北城市科技大學 | Air conditioner capacity estimator |
| CN119647992A (en)* | 2024-11-18 | 2025-03-18 | 湖南国科精控科技有限公司 | Evaluation method of power consumption of refrigeration equipment based on BIM simulation system |
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