CN113344287A - Indoor temperature distribution prediction system - Google Patents

Indoor temperature distribution prediction system Download PDF

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CN113344287A
CN113344287A CN202110717385.3A CN202110717385A CN113344287A CN 113344287 A CN113344287 A CN 113344287A CN 202110717385 A CN202110717385 A CN 202110717385A CN 113344287 A CN113344287 A CN 113344287A
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张伟荣
臧紫晗
赵雅楠
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Beijing University of Technology
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Abstract

The application provides an indoor temperature distribution prediction system. The system comprises: the temperature acquisition device is used for sequentially acquiring temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction; the calculating device is used for calculating a temperature change value at a temperature prediction target point in the space to be predicted according to the temperature data acquired by the temperature acquiring device and through a linear temperature distribution prediction model; and the output device is used for outputting the temperature change value at the temperature prediction target point in the space to be predicted, which is calculated by the calculation device. Therefore, temperature collection at any temperature collection point can be carried out, the limitation of the fixed sensors in the aspects of installation quantity, installation positions and the like is overcome, the cost is saved, the temperature change value at the temperature prediction target point can be rapidly calculated, and the limitation of long indoor temperature distribution calculation time, high calculation load and the like in computational fluid mechanics is avoided.

Description

Indoor temperature distribution prediction system
Technical Field
The application relates to the technical field of green building technology research, in particular to an indoor temperature distribution prediction system.
Background
The indoor thermal environment of a building is affected by a plurality of heat sources, and the indoor thermal environment has non-uniformity due to different heat transfer characteristics of the heat sources and the influence of air supply flow. With the increasing demands for satisfying personalized thermal comfort, improving building energy consumption, etc., obtaining the temperature distribution of the working area of the indoor thermal environment is very important for satisfying personalized thermal comfort and improving building energy efficiency. Currently, obtaining indoor temperature distribution is mainly achieved by predicting temperature through Computational Fluid Dynamics (CFD) according to indoor temperature data collected by a sensor fixed indoors.
In the process of realizing the prior art, the inventor finds that:
the fixed sensors have limitations in the number of installations, installation locations, etc., such as too many installations not being aesthetically pleasing and convenient for maintenance, installation locations being fixed and far from the target control area. This leaves room temperature distribution prediction accuracy to be improved. Moreover, each fixed sensor can only acquire temperature in a certain area, and if temperature data of different positions need to be acquired, a large number of fixed sensors need to be installed. This will increase the equipment cost.
In addition, CFD has limitations such as long calculation time and high calculation load, and particularly, when the boundary conditions are changed, the changed boundary conditions are difficult to acquire and the related data need to be recalculated. In this way, the temperature distribution prediction accuracy of thermal environment simulations, which are usually under varying boundary conditions, or long-term building energy consumption simulations, which take into account the temperature distribution, will be directly influenced.
Therefore, it is necessary to provide an indoor temperature distribution prediction system to solve the technical problem of low indoor temperature distribution prediction accuracy.
Disclosure of Invention
The embodiment of the application provides a technical scheme for predicting the temperature distribution of a working area in a thermal environment, which is used for solving the technical problem of low prediction precision of indoor temperature distribution.
Specifically, an indoor temperature distribution prediction system includes:
the temperature acquisition device is used for sequentially acquiring temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction;
the calculating device is used for calculating a temperature change value at a temperature prediction target point in the space to be predicted according to the temperature data acquired by the temperature acquiring device and through a linear temperature distribution prediction model;
and the output device is used for outputting the temperature change value at the temperature prediction target point in the space to be predicted, which is calculated by the calculation device.
Further, the temperature acquisition device is used for sequentially acquiring temperature data of each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction, and is also used for:
determining the coordinates of each temperature acquisition point according to the heat source distribution condition in the space to be predicted;
planning a temperature data acquisition path according to the coordinates of each temperature acquisition point;
wherein, the distribution of the heat source in the space to be predicted at least comprises:
coordinates of heat sources and the number of the heat sources in the space to be predicted.
Further, the temperature acquisition device is used for sequentially acquiring temperature data of each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction, and is specifically used for:
receiving a temperature acquisition path planning instruction;
determining coordinates of each temperature acquisition point in the space to be predicted according to the acquisition path planning instruction;
sequentially moving to each temperature acquisition coordinate point; collecting temperature data at each temperature collection coordinate point;
and sending the acquired temperature data at each temperature acquisition coordinate point to a computing device.
Further, the temperature acquisition device is configured to send the acquired temperature data at the temperature acquisition coordinate point to the computing device, and is further configured to:
and sending the position information of each temperature acquisition coordinate point corresponding to the acquired temperature data to the computing device.
Further, the calculating device is configured to calculate a temperature change value at a temperature prediction target point in the space to be predicted according to the temperature data acquired by the temperature acquiring device and through a linear temperature distribution prediction model, and is further configured to:
according to the distribution condition of the heat source in the space to be predicted, CFD simulation is carried out on the space to be predicted to obtain a sub-temperature field of the heat source in the space to be predicted;
calculating an indoor environment formation contribution rate CRI value of the heat source at each temperature acquisition point on the basis of the sub-temperature field of the heat source and through a CRI calculation model;
calculating an indoor environment formation Contribution Rate (CRI) value of the heat source at a temperature prediction target point based on the sub-temperature field of the heat source and through a CRI calculation model;
wherein, the distribution of the heat source in the space to be predicted at least comprises:
coordinates of heat sources and the number of the heat sources in the space to be predicted.
Further, the computing device is configured to perform CFD simulation on the space to be predicted according to the distribution of the heat source in the space to be predicted, to obtain a sub-temperature field of the heat source in the space to be predicted, and specifically is configured to:
performing CFD simulation on the space to be predicted according to the heat source distribution condition in the space to be predicted to obtain a total flow field of the space to be predicted;
performing CFD simulation based on the total flow field of the space to be predicted and according to the forming conditions of the heat source sub-temperature field to obtain the sub-temperature field of the heat source in the space to be predicted;
wherein, the distribution of the heat source in the space to be predicted at least comprises:
coordinates of heat sources and the number of the heat sources in the space to be predicted;
and the forming condition of the heat source sub-temperature field is that the number of heat sources participating in heat exchange in the space to be predicted is 1.
Further, the calculating device is configured to calculate, according to the temperature data acquired by the temperature acquiring device and through a linear temperature distribution prediction model, a temperature change value at a temperature prediction target point in the space to be predicted, and specifically is configured to:
according to the temperature data collected by the temperature collecting device, calculating the difference value between the temperature at the temperature collecting coordinate point in the space to be predicted and the neutral temperature, wherein the difference value is expressed as follows:
ΔθSi＝θSi-θn
in the formula, thetaSiCollecting coordinate point x for temperature collection device in space to be predictediOn the collected temperature data, thetanIs the neutral temperature of the space to be predicted;
according to the difference value between the temperature at each temperature collection coordinate point in the space to be predicted and the neutral temperature, and through a linear temperature distribution prediction model, calculating the temperature change value at the temperature prediction target point in the space to be predicted, and expressing as follows:
Figure BDA0003135408020000041
in the formula, CanPredicting target point x for temperature of heat source n in space to be predicteda(ii) a contribution ratio CRI value, C of indoor environment formationinCollecting coordinate points x for the temperature of a heat source n in a space to be predictediThe indoor environment of (a) forms a contribution ratio CRI value.
Further, the calculating device is configured to calculate a temperature change value at a temperature prediction target point in the space to be predicted according to the temperature data acquired by the temperature acquiring device and through a linear temperature distribution prediction model, and is further configured to:
when the number of the temperature acquisition coordinate points is larger than that of the heat sources in the space to be predicted, screening the temperature acquisition coordinate points through a data processing model to obtain the temperature acquisition coordinate points consistent with the number of the heat sources in the space to be predicted;
and extracting the CRI value of the indoor environment formation contribution rate of the heat source at the corresponding temperature acquisition point according to the position information of the temperature acquisition coordinate point obtained by screening.
Further, the calculating device is configured to calculate a temperature change value at a temperature prediction target point in the space to be predicted according to the temperature data acquired by the temperature acquiring device and through a linear temperature distribution prediction model, and is further configured to:
according to the temperature change value at the temperature prediction target point in the space to be predicted, calculating the prediction temperature at the temperature prediction target point in the space to be predicted as follows:
θa＝Δθa+θn
in the formula, thetanFor neutral temperature of the space to be predicted, Δ θaAnd predicting the temperature change value at the target point for the temperature in the space to be predicted.
Further, the output device is configured to output the temperature change value at the temperature prediction target point in the space to be predicted, which is calculated by the calculation device, and is further configured to:
and outputting the predicted temperature at the temperature prediction target point in the space to be predicted, which is obtained through calculation.
The technical scheme provided by the embodiment of the application at least has the following beneficial effects:
the indoor temperature distribution prediction system carries out the mobile acquisition of temperature data through the temperature acquisition device, can carry out the temperature acquisition of arbitrary temperature acquisition point department, has overcome the restriction that fixed sensor exists in the aspect of installation quantity and mounted position etc. to equipment cost has been practiced thrift. In addition, the indoor temperature distribution prediction system can quickly calculate the temperature change value at the temperature prediction target point through the linear temperature distribution prediction model, and avoids the limitations of long indoor temperature distribution calculation time, high calculation load and the like in computational fluid dynamics.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic structural diagram of an indoor temperature distribution prediction system according to an embodiment of the present application.
100 indoor temperature distribution prediction system
11 temperature acquisition device
12 computing device
13 output device
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, a system 100 for predicting indoor temperature distribution provided by an embodiment of the present application includes:
the temperature acquisition device 11 is used for sequentially acquiring temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction;
the calculating device 12 is used for calculating a temperature change value at a temperature prediction target point in the space to be predicted according to the temperature data acquired by the temperature acquiring device 11 and through a linear temperature distribution prediction model;
and the output device 13 is used for outputting the temperature change value at the temperature prediction target point in the space to be predicted, which is calculated by the calculation device 12.
And the temperature acquisition device 11 is used for sequentially acquiring temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction. The temperature acquisition device 11 is a movable temperature acquisition device 11 which is provided with a temperature sensor and can controllably move relative to the ground. The movement of the temperature acquisition device 11 relative to the ground is mainly controlled and realized through a temperature acquisition path planning instruction. The temperature acquisition path planning instruction is the movement path planning information of the temperature acquisition device 11 in the space to be predicted, and at least comprises the position coordinate information of each temperature acquisition point in the space to be predicted. And the space to be predicted is a three-dimensional space in a building room. The temperature acquisition device 11 sequentially moves to each temperature acquisition point to acquire the temperature according to the position coordinate information of each temperature acquisition point. In this way, the temperature acquisition device 11 can acquire the temperature at any temperature acquisition point, and overcomes the limitations of the fixed sensors in terms of installation quantity, installation positions and the like, such as inconvenience in maintenance due to too much installation quantity, fixed installation positions far away from a target control area, unattractive appearance and the like. For example, if a fixed sensor is used to collect the indoor temperature, it needs to be installed near the working area to ensure the reliability of the collected temperature data. Wherein the working area is an area near indoor personnel. If the fixed sensor is far away from the indoor working area, the reliability of the acquired temperature data is low; if the distance from the indoor working area is short, the indoor appearance is deteriorated and the movement of the person is hindered to some extent. In addition, a large number of fixed sensors are required to be installed for acquiring the temperatures of different areas of the indoor working area, so that later-stage equipment maintenance is not convenient, and the equipment cost is high. Therefore, the temperature acquisition is carried out by utilizing the fixed sensor, and the installation position and the installation quantity of the fixed sensor are greatly limited. However, one mobile temperature sensor can acquire the temperatures of different areas of the indoor working area and different areas of the non-working area according to actual requirements, and the limitation of the temperature acquisition position does not exist. This not only reduces costs, but also enables higher reliability of the temperature data collected.
And the calculating device 12 is used for calculating the temperature change value of the temperature prediction target point in the space to be predicted through a linear temperature distribution prediction model according to the temperature data acquired by the temperature acquiring device 11. It is understood that the thermal environment in the building room is affected by many heat sources, and the thermal environment in the building room has non-uniformity due to the different heat transfer characteristics of the heat sources and the influence of the air flow. However, the indoor flow field of a general building is mainly dominated by forced convection of air flow and the like of an air conditioning system, and at the moment, the influence of buoyancy change near a heat source on the indoor flow field can be ignored, so that the indoor flow field can be assumed to be a fixed flow field. Within a fixed flow field, the heat transfer can be considered linear, i.e. the total temperature field is linearly composed of a plurality of sub-temperature fields controlled by a single heat source. According to the temperature data collected by the temperature collecting device 11, the temperature change value at the temperature prediction target point can be rapidly calculated in real time through the linear temperature distribution prediction model. Wherein the temperature prediction target point includes at least one temperature prediction position coordinate point. Therefore, even if the boundary condition of the flow field is changed, the calculation is not required to be carried out again, and the limitations that the indoor temperature distribution calculation time is long and the calculation load is high in Computational Fluid Dynamics (CFD for short) are overcome.
And the output device 13 is used for outputting the temperature change value at the temperature prediction target point in the space to be predicted, which is calculated by the calculation device 12. When the temperature change value at the temperature prediction target point in the space to be predicted is calculated by the calculation device 12, the output device 13 can output the calculated temperature change value at the temperature prediction target point. Wherein the temperature prediction target point includes at least one temperature prediction position coordinate point. When the temperature prediction target points include at least two temperature prediction position coordinate points, the output device 13 outputs a temperature change value at each temperature prediction target point. The output device 13 may directly mark the temperature change value at each temperature prediction target point, or may combine the predicted temperature at each temperature prediction target point and the coordinates of each temperature prediction target point into a data set and output it. Therefore, the indoor temperature change value obtained through calculation can be in one-to-one correspondence with the position of the predicted point, the accuracy of predicted temperature data is improved, and the problem that the predicted temperature data is not matched with the temperature predicted point is avoided. It should be understood that the specific expression of the output device 13 for outputting the indoor temperature variation value is obviously not limited to the protection scope of the present application.
Further, in a preferred embodiment provided in the present application, the temperature acquisition device 11 is configured to sequentially acquire temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction, and is further configured to:
determining the coordinates of each temperature acquisition point according to the heat source distribution condition in the space to be predicted; planning a temperature data acquisition path according to the coordinates of each temperature acquisition point; wherein, the distribution of the heat source in the space to be predicted at least comprises: coordinates of heat sources and the number of the heat sources in the space to be predicted.
It will be appreciated that the indoor heat source distribution is closely related to the distribution of the indoor thermal environment. Therefore, before the temperature acquisition device 11 acquires the temperature, the coordinates of each temperature acquisition point need to be determined according to the heat source distribution in the space to be predicted. The distribution condition of the heat source in the space to be predicted at least comprises the coordinates of the heat source in the space to be predicted and the number of the heat sources. The heat source may be an indoor heat source unit, or may be a heat source unit group formed by grouping all indoor heat source units according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source unit. The heat source unit can be a single human body, a single computer, a single lamp body, a single air supply outlet and the like which participate in indoor heat exchange according to actual conditions. It will be understood that the specific form of the heat source unit described herein is not intended to limit the scope of the present application. Correspondingly, the number of the heat sources may be the actual number of the indoor heat source units, or may be the grouping number after all the indoor heat source units are grouped according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source units. The coordinates of the heat source may be coordinates of indoor heat source units, or may be coordinates of heat source unit groups obtained by grouping all indoor heat source units according to factors such as types, actual distribution positions, or heat exchange amounts of the indoor heat source units. Thus, according to the distribution condition of the heat source, the temperature acquisition device 11 can determine the position coordinates of the temperature acquisition points with more accurate acquisition temperature, so that the reliability of the acquired temperature data is improved. It should be noted that the coordinates of the temperature collection points are determined based on the fact that the temperature collection points can be uniformly distributed in the room. Preferably, the temperature collection points are evenly distributed around the perimeter of the indoor heat source. Therefore, the reliability of the temperature data at each temperature acquisition point acquired by the temperature acquisition device 11 under the combined action of the heat source can be improved, and the problem of large deviation of the acquired temperature data caused by uneven distribution of the acquisition points is solved. Then, the moving path of the temperature acquisition device 11 can be determined according to the position coordinates of each temperature acquisition point. Therefore, the temperature acquisition device 11 can acquire the temperature of each temperature acquisition point on the optimal moving path, so that the total moving distance of the temperature acquisition device 11 is reduced, and the total time of temperature acquisition is shortened.
Further, in a preferred embodiment provided in the present application, the temperature acquisition device 11 is configured to sequentially acquire temperature data at each temperature acquisition coordinate point in the space to be predicted according to a temperature acquisition path planning instruction, and specifically configured to: receiving a temperature acquisition path planning instruction; determining coordinates of each temperature acquisition point in the space to be predicted according to the acquisition path planning instruction; sequentially moving to each temperature acquisition coordinate point; collecting temperature data at each temperature collection coordinate point; and sending the acquired temperature data at each temperature acquisition coordinate point to the computing device 12.
It can be understood that the temperature acquisition device 11 sequentially acquires the temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction, and firstly needs to acquire the temperature acquisition path planning instruction. Namely, receiving a temperature acquisition path planning instruction. The temperature acquisition path planning instruction is the indoor moving path planning information of the temperature acquisition device 11 and at least comprises the position coordinate information of each indoor temperature acquisition point. Here, the position coordinates of the temperature collection points and the moving route of the temperature collection device 11 between the indoor temperature collection points may be determined in a manner set by a person. Or the position coordinates of the temperature acquisition points and the moving route of the temperature acquisition device 11 between the indoor temperature acquisition points can be planned in a planning mode automatically set by the system. In this way, according to the received temperature collection path planning instruction, the temperature collection device 11 can determine the position coordinate information of each temperature collection point therein. After the temperature acquisition device 11 determines the position of each temperature acquisition point, the temperature acquisition device can move to each temperature acquisition point in sequence according to the temperature acquisition path planning instruction, and acquire temperature data at each acquisition point. Here, the temperature acquisition means 11 acquires at least one temperature data at each temperature acquisition point. The temperature acquisition device 11 may send the acquired temperature data to the computing device 12. Specifically, the temperature acquisition device 11 sends the acquired temperature data to the computing device 12, and after the temperature data at each temperature acquisition point is acquired, the temperature acquisition device 11 immediately sends the currently acquired temperature data to the computing device 12; or the temperature data at each temperature acquisition point is acquired completely, the temperature acquisition device 11 temporarily stores the currently acquired temperature data, and after the temperature data at all the temperature acquisition points are acquired completely, all the acquired temperature data are simultaneously sent to the computing device 12; or, after the temperature data at each temperature collection point is collected, the temperature collection device 11 temporarily stores the currently collected temperature data, and when the number of temperature collection points at which the temperature collection work is completed reaches a set threshold, sends all the currently collected and stored temperature data to the calculation device 12.
For example, the temperature acquisition path planning instruction includes position information L of 3 temperature acquisition coordinate points1(x1，y1，z1)、L2(x2，y2，z2)、L3(x3，y3，z3) The moving route of the temperature acquisition device 11 is L2-L1-L3. After the temperature acquisition device 11 receives the temperature acquisition path planning instruction, the position information of the temperature acquisition coordinate point can be determined. Then, the temperature acquisition means 11 acquires the route (L) according to the temperature2-L1-L3) The movement is started. When the temperature acquisition device 11 moves to the temperature acquisition coordinate point L2(x2，y2，z2) While, the temperature at that location is collected as T2And (4) showing. Then, the temperature acquisition device 11 is started from the temperature acquisition point L2Moving to a temperature acquisition coordinate point L1(x1，y1，z1) And collecting the temperature at the location, as T1And (4) showing. Then, the temperature acquisition device 11 is started from the temperature acquisition point L1Moving to a temperature acquisition coordinate point L3(x3，y3，z3) And collecting the temperature at the location, as T3And (4) showing. When temperature is highData T2、T1、T3After all the data are collected, the temperature collection device 11 can send the data to the computing device 12. Or, when the temperature acquisition device 11 acquires the coordinate point L at the temperature2(x2，y2，z2) Collecting temperature data T2And then immediately sends it to the computing device 12. Then carrying out temperature data T1Is collected, transmitted, and temperature data T3Collecting and sending. Or, when the threshold value of the number of temperature collection points for which the temperature collection operation is completed is set to 2, the temperature collection device 11 completes the temperature data T2、T1After collection, T is first2、T1Sent to the computing device 12 and then moved to the temperature acquisition coordinate point L3(x3，y3，z3) Is subjected to temperature data T3And (4) collecting. Because 3 collection points are in total, when the last temperature data collection is finished but the data sending condition of the set threshold is not met, the temperature data T also needs to be collected3Is sent.
Further, in a preferred embodiment provided herein, the temperature acquisition device 11 is configured to send the acquired temperature data at the temperature acquisition coordinate point to the computing device 12, and further configured to:
and sending the position information of each temperature acquisition coordinate point corresponding to the acquired temperature data to the computing device 12.
It is understood that the temperature acquisition device 11 transmits the acquired temperature data to the calculation device 12 after acquiring the temperature data at each temperature acquisition point. Furthermore, the temperature acquisition device 11 can acquire at least one temperature data at each temperature acquisition point. This results in a confused match of the temperature data sent by the temperature acquisition device 11 with the temperature acquisition point location information. Therefore, the temperature acquisition device 11 needs to transmit the position information of each temperature acquisition coordinate point corresponding to the acquired temperature data to the calculation device 12 while transmitting the acquired temperature data. In this way, the temperature data and the temperature acquisition point position information are in one-to-one correspondence, so that the accuracy of the calculation result of the calculation device 12 is increased.
Specifically, the temperature acquisition device 11 may send the acquired temperature data to the computing device 12, and after the temperature data at each temperature acquisition point is acquired, the temperature acquisition device 11 immediately sends the currently acquired temperature data to the computing device 12. At this time, the temperature acquisition device 11 transmits the position information of each temperature acquisition point to the calculation device 12 together with the temperature data. For example, the temperature acquisition path planning instruction includes position information L of 3 temperature acquisition coordinate points1(x1，y1，z1)、L2(x2，y2，z2)、L3(x3，y3，z3) The moving route of the temperature acquisition device 11 is L2-L1-L3. When the temperature acquisition device 11 acquires the coordinate point L at the temperature2(x2，y2，z2) Collecting temperature data T2Then, the temperature data T is immediately transmitted2With the current temperature collection point L2Position information (x) of2，y2，z2) Together to the computing device 12. Then collecting temperature data T1Sending temperature data T1With temperature collection point L1Position information (x) of1，y1，z1) To the computing means 12, and a temperature collection point L3Temperature data collection and related data transmission. Similarly, when the temperature acquisition device 11 finishes acquiring the temperature data of all the temperature acquisition points and simultaneously transmits all the acquired temperature data to the calculation device 12, the transmitted data includes both the temperature data of each temperature acquisition point and the position information corresponding to each temperature data. Or when the number of the temperature collection points which have finished the temperature collection work reaches the set threshold value, the temperature collection device 11 sends all the currently collected and stored temperature data to the computing device 12, and the sent data contains the temperature data of each temperature collection point and the position information corresponding to each temperature data. In this way, the calculation device 12 can specify the position information corresponding to the received temperature data, and can predict the indoor temperature distribution more accurately.
Further, in a preferred embodiment provided in the present application, the calculating device 12 is configured to calculate, according to the temperature data acquired by the temperature acquiring device 11 and through a linear temperature distribution prediction model, a temperature change value at a temperature prediction target point in the space to be predicted, and is further configured to:
according to the distribution condition of the heat source in the space to be predicted, CFD simulation is carried out on the space to be predicted to obtain a sub-temperature field of the heat source in the space to be predicted;
calculating an indoor environment formation contribution rate CRI value of the heat source at each temperature acquisition point on the basis of the sub-temperature field of the heat source and through a CRI calculation model;
calculating an indoor environment formation Contribution Rate (CRI) value of the heat source at a temperature prediction target point based on the sub-temperature field of the heat source and through a CRI calculation model;
wherein, the distribution of the heat source in the space to be predicted at least comprises:
coordinates of heat sources and the number of the heat sources in the space to be predicted.
It can be understood that the indoor flow field of a general building is mainly dominated by forced convection such as air flow of an air conditioning system, the influence of buoyancy change near a heat source on the indoor flow field can be ignored, and the indoor flow field can be assumed to be a fixed flow field. Within a fixed flow field, the heat transfer can be considered linear, i.e. the total temperature field is linearly composed of a plurality of sub-temperature fields controlled by a single heat source. The Contribution rate of Indoor environment formation (CRI) can quantitatively evaluate the influence and range of any heat source on the Indoor temperature distribution. The CRI is a parameter extracted based on the CFD calculation result, and is defined as a ratio of an increase (or decrease) in temperature of any heat source to a point in the room to an absolute value of the increase (or decrease) in temperature of the point when the heat source dissipates (or absorbs) heat under a completely uniform mixing condition. In a fixed representative flow field, the buoyancy generated by the temperature change due to the change in the calorific value of the heat source is negligible compared to the air supplied by the air conditioning system, and thus the CRI may be regarded as a certain value. Therefore, the CRI value of the indoor environment formation contribution rate in the indoor flow field is determined, and the calculating device 12 can calculate the temperature change value at the temperature prediction target point in real time and quickly according to the temperature data acquired by the temperature acquiring device 11. Even if the boundary condition of the flow field is changed, the calculation is not required to be carried out again, so that the limitations of long indoor temperature distribution calculation time, high calculation load and the like in Computational Fluid Dynamics (CFD) are overcome.
Determining an indoor environment formation contribution rate CRI value in an indoor flow field, firstly, performing computational fluid dynamics CFD simulation on a space to be predicted according to the heat source distribution condition in the space to be predicted to obtain a sub-temperature field of a heat source in the space to be predicted, thereby facilitating the analysis of the sub-temperature field corresponding to each heat source. And then, calculating the CRI value of the indoor environment forming contribution rate. And the distribution condition of the heat source in the space to be predicted at least comprises the coordinates of the heat source in the space to be predicted and the number of the heat sources. The heat source may be an indoor heat source unit, or may be a heat source unit group formed by grouping all indoor heat source units according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source unit. Correspondingly, the number of the heat sources may be the actual number of the indoor heat source units, or may be the grouping number after all the indoor heat source units are grouped according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source units. The coordinates of the heat source may be coordinates of indoor heat source units, or may be coordinates of heat source unit groups obtained by grouping all indoor heat source units according to factors such as types, actual distribution positions, or heat exchange amounts of the indoor heat source units.
Specifically, the indoor flow field is a forced convection main flow field, and the CRI calculation model of the indoor environment formation contribution rate is expressed as follows:
Figure BDA0003135408020000121
wherein each parameter represents:
CRIm(xi): heat source m is in xiIndoor ring of pointAmbient formation contribution values;
xi: spatial coordinates;
θn: neutral temperature, i.e. indoor initial temperature, in units;
θm，o: heat source m heat radiation (or heat absorption) QmIndoor temperature in unit for uniform diffusion;
Δθm，o＝θm，o-θn: the temperature difference between the uniform diffusion temperature and the neutral temperature is unit ℃;
θm(xi): heat source m heat dissipation (or heat absorption) Q obtained through CFD calculationmRear xiPoint temperature, in units;
Δθm(xi)＝θm(xi)-θn: heat source m heat radiation (or heat absorption) QmRear xiThe temperature difference between the point temperature and the neutral temperature is unit ℃;
Figure BDA0003135408020000131
the convection heat transfer capacity of a heat source m is kW;
Cp: indoor air specific heat capacity, unit kJ/(kg. DEG C);
ρ: air Density in kg/m3；
F: air delivery in m3/s。
It is worth noting that the CRI values of the heat source at different points in the room are different under the combined action of different sub-temperature fields. The spatial positions of the indoor temperature collection point and the temperature prediction point are different, which requires the calculating device 12 to calculate the CRI value CRI of the indoor environment formation contribution rate of the heat source at each temperature collection point respectivelym(xi) And the CRI value of the indoor environment formation contribution rate of the heat source at the temperature prediction target pointm(xa). It is understood that the specific representation form of the CRI value of the indoor environment formation contribution rate of the heat source at each temperature collection point and each temperature prediction target point obviously does not limit the protection scope of the present application.
Further, in a preferred embodiment provided by the present application, the computing device 12 is configured to perform CFD simulation on the space to be predicted according to the distribution of the heat source in the space to be predicted, so as to obtain a sub-temperature field of the heat source in the space to be predicted, and specifically configured to:
performing CFD simulation on the space to be predicted according to the heat source distribution condition in the space to be predicted to obtain a total flow field of the space to be predicted;
performing CFD simulation based on the total flow field of the space to be predicted and according to the forming conditions of the heat source sub-temperature field to obtain the sub-temperature field of the heat source in the space to be predicted;
wherein, the distribution of the heat source in the space to be predicted at least comprises: coordinates of heat sources and the number of the heat sources in the space to be predicted; the forming conditions of the heat source sub-temperature field are as follows: the number of heat sources participating in heat exchange in the space to be predicted is 1.
It can be understood that, by performing computational fluid dynamics CFD simulation on the space to be predicted according to the heat source distribution in the space to be predicted, a total flow field, that is, an indoor total flow field, of the space to be predicted can be obtained. It should be noted that, in the indoor CFD simulation, the target room needs to be modeled first, and then the operations of grid division, boundary condition setting, and the like are performed. Therefore, the flow field in the space to be predicted can be simulated more accurately according to the indoor heat source distribution condition. And the distribution condition of the heat source in the space to be predicted at least comprises the coordinates of the heat source in the space to be predicted and the number of the heat sources. The heat source may be an indoor heat source unit, or may be a heat source unit group formed by grouping all indoor heat source units according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source unit. Correspondingly, the number of the heat sources may be the actual number of the indoor heat source units, or may be the grouping number after all the indoor heat source units are grouped according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source units. The coordinates of the heat source may be coordinates of indoor heat source units, or may be coordinates of heat source unit groups obtained by grouping all indoor heat source units according to factors such as types, actual distribution positions, or heat exchange amounts of the indoor heat source units. Whereas within a fixed flow field the heat transport is considered linear, i.e. the total temperature field is linearly composed of a plurality of sub-temperature fields controlled by a single heat source. Therefore, after the indoor total flow field is obtained, the number of the heat sources participating in heat exchange is controlled to be 1, and the sub-temperature field controlled by a single heat source can be obtained. Therefore, the indoor representative flow field can be obtained after the indoor total flow field is obtained and the representative flow field is selected and fixed. And at the moment, continuously performing CFD simulation according to the forming conditions of the heat source sub-temperature field to obtain the sub-temperature field of the heat source in the space to be predicted. The forming condition of the heat source sub-temperature field is that the number of heat sources participating in heat exchange in the space to be predicted is 1, and other heat sources are not set to exchange heat with indoor air. When each heat source works independently, the temperature field obtained through CFD simulation is the sub-temperature field corresponding to each heat source in the room.
Further, in a preferred embodiment provided in the present application, the calculating device 12 is configured to calculate, according to the temperature data acquired by the temperature acquiring device 11 and through a linear temperature distribution prediction model, a temperature change value at a temperature prediction target point in the space to be predicted, and specifically, is configured to:
according to the temperature data collected by the temperature collecting device 11, the difference value between the temperature at the temperature collecting coordinate point in the space to be predicted and the neutral temperature is calculated, which is expressed as follows:
ΔθSi＝θSi-θn
in the formula, thetaSiCollecting coordinate point x for temperature of temperature collecting device 11 in space to be predictediOn the collected temperature data, thetanIs the neutral temperature of the space to be predicted;
according to the difference value between the temperature at each temperature collection coordinate point in the space to be predicted and the neutral temperature, and through a linear temperature distribution prediction model, calculating the temperature change value at the temperature prediction target point in the space to be predicted, and expressing as follows:
Figure BDA0003135408020000151
in the formula, CanPredicting target point x for temperature of heat source n in space to be predicteda(ii) a contribution ratio CRI value, C of indoor environment formationinCollecting coordinate points x for the temperature of a heat source n in a space to be predictediThe indoor environment of (a) forms a contribution ratio CRI value.
It can be understood that, by predicting the indoor temperature distribution through the linear temperature prediction model, after the position of the indoor temperature collection point is determined, the temperature collection device 11 can sequentially collect the temperature data at the temperature collection point according to the temperature collection path planning instruction. According to the temperature data collected by the temperature collecting device 11 and the indoor neutral temperature, the temperature change value of each temperature collecting point under the action of the indoor heat source can be calculated. The neutral temperature is an indoor initial temperature, namely an indoor temperature when the heat source does not participate in heat exchange. The calculation formula of the temperature change value at each temperature collection point under the action of the indoor heat source is represented as follows:
ΔθSi＝θSi-θn
in the formula, thetaSiCollecting coordinate point x for temperature of temperature collecting device 11 in space to be predictediOn the collected temperature data, thetanIs the neutral temperature of the space to be predicted.
In a fixed flow field, when the position of an indoor temperature acquisition point is determined, the temperature data theta at the temperature acquisition pointSiAnd then fixed. Due to the neutral temperature theta in the roomnFor constant value, corresponding to the temperature variation value delta theta at each temperature collection point under the action of indoor heat sourceSiIs a constant value. And the position of an indoor temperature acquisition point in the fixed flow field is determined, and a heat source n acquires a coordinate point x at the temperature in the space to be predictediIndoor environment formation contribution rate CRI value CinAnd then determined. At this time, the indoor temperature distribution is predicted, and the delta theta can be calculatedSiAnd CinThe values are considered constant. When the coordinates of the temperature prediction point are changed, the temperature prediction target point x of the heat source n in the space to be predictedaIndoor environment formation contribution rate CRI value CanWith consequent changes. At this time, CanCan be regarded as independent variable in the linear temperature prediction model. To pairAccordingly, the dependent variable in the linear temperature prediction model is a temperature change value at the indoor temperature prediction target point. Therefore, the independent variable in the linear temperature prediction model is the temperature prediction target point x of the heat source n in the space to be predictedaIndoor environment formation contribution rate CRI value CanThe dependent variable is a temperature change value at the indoor temperature prediction target point. The linear temperature prediction model calculation formula is expressed as follows:
Figure BDA0003135408020000161
in the formula,. DELTA.theta.aPredicting a temperature variation value, C, at a target point for an indoor temperatureanPredicting target point x for temperature of heat source n in space to be predicteda(ii) a contribution ratio CRI value, C of indoor environment formationinCollecting coordinate points x for the temperature of a heat source n in a space to be predictedi(ii) a contribution ratio CRI value of indoor environment formation, Delta thetaSnThe temperature change value of each temperature collection point under the action of the indoor heat source. In a fixed flow field, the coordinates of the temperature acquisition points are known, then Cin、ΔθSnIs a fixed value. Therefore, the temperature change value at the indoor temperature prediction target point can be obtained by determining the indoor environment forming contribution rate of the heat source at the temperature prediction point according to the coordinates of the temperature prediction point. When there is only one temperature prediction point in the room, the calculation result of the calculation device 12 is only the temperature variation value corresponding to the prediction point. When there are not less than two temperature prediction points indoors, the calculating device 12 can obtain the temperature change value at each temperature prediction point through the linear temperature prediction model, so as to obtain the indoor temperature distribution prediction result.
For ease of understanding, the linear temperature prediction model calculation formula may be expressed as:
Δθa＝(Ca1 Ca2 … Can)*k1*k2
wherein the content of the first and second substances,
Figure BDA0003135408020000162
in a fixed flow field, the coordinates of the temperature acquisition points are known, then Cin、ΔθSnIs a fixed value. I.e., in the formula k1、k2All values of (A) are constant values, k can be expressed1And k is2The product of (d) is considered to be a constant. Determining the indoor environment formation contribution rate CRI value C of the heat source at the temperature prediction point according to the coordinates of the temperature prediction pointanTo obtain Delta thetaaThe calculation result of (2). Notably, k is performed1The value calculation involves the inverse operation of the matrix, and k is guaranteed1The value of i is equal to the value of n in the calculation. Namely, the number i of the temperature collection points corresponding to the CRI value of the indoor environment formation contribution rate participating in the calculation is ensured to be consistent with the number n of the heat sources. At this time, the temperature data Δ θ corresponding to the temperature acquisition coordinate point participating in the calculationSnThe number is consistent with the number of heat sources. However, it is not required that the number of temperature collection point sets is consistent with the number of heat sources, and the number of temperature collection point sets is not less than the number of heat sources. The heat source may be an indoor heat source unit, or may be a heat source unit group formed by grouping all indoor heat source units according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source unit. Correspondingly, the number of the heat sources may be the actual number of the indoor heat source units, or may be the grouping number after all the indoor heat source units are grouped according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source units. It will be appreciated that the specific grouping of the indoor heat source units described herein is clearly not intended to limit the scope of the present application.
Further, in a preferred embodiment provided herein, the calculating device 12 is configured to calculate an indoor environment formation contribution ratio CRI value of the heat source at the temperature collecting point based on the sub-temperature field of the heat source and through a CRI calculation model, and further configured to:
when the number of the temperature acquisition coordinate points is larger than that of the heat sources in the space to be predicted, screening the temperature acquisition coordinate points through a data processing model to obtain the temperature acquisition coordinate points consistent with the number of the heat sources in the space to be predicted;
and extracting the CRI value of the indoor environment formation contribution rate of the heat source at the corresponding temperature acquisition point according to the position information of the temperature acquisition coordinate point obtained by screening.
It can be understood that, when the indoor temperature distribution is predicted by the linear temperature prediction model, the number of the temperature collection points corresponding to the CRI value of the indoor environment formation contribution rate participating in the calculation needs to be kept consistent with the number of the heat sources, but the setting number of the temperature collection points is not required to be strictly kept consistent with the number of the heat sources, and only the number of the temperature collection points needs to be set to be not less than the number of the heat sources. The heat source may be an indoor heat source unit, or may be a heat source unit group formed by grouping all indoor heat source units according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source unit. Correspondingly, the number of the heat sources may be the actual number of the indoor heat source units, or may be the grouping number after all the indoor heat source units are grouped according to factors such as the type, the actual distribution position, or the heat exchange amount of the indoor heat source units. It will be appreciated that the specific grouping of the indoor heat source units described herein is clearly not intended to limit the scope of the present application. When the number of temperature collection points is consistent with the number of heat sources, the calculation device 12 can directly predict the temperature at the temperature prediction target point according to the collected data. When the number of the temperature collection points is larger than that of the heat sources, if the indoor environment formation contribution rate C of all the temperature collection points is larger than that of the heat sourcesinAll participate in the computation, and since the temperature prediction model involves a matrix inversion operation, the computing device 12 will not be able to perform temperature prediction at the temperature prediction target point. At this time, the set temperature collection points need to be screened through a data processing model, so that the number of the temperature collection points corresponding to the CRI value of the indoor environment formation contribution rate finally participating in the calculation is consistent with the number of the heat sources. It is worth noting that the data processing model is used for screening the temperature collection points, and the principle that the temperature collection points can be uniformly distributed indoors and the number of the temperature collection points is consistent with the number of the heat sources is mainly used. For example, when the number of indoor heat sources is 10 and the number of temperature collection points is 20, temperature collection is requiredThe temperature data collected by the device 11 is subjected to screening processing, that is, temperature collection points are screened, so that the number of the temperature data participating in calculation is consistent with the number of heat sources. Specifically, when the number of the temperature collection points is larger than that of the heat sources, the temperature collection points are screened, and averaging processing can be performed on the temperature collection points which are relatively close to each other. For example, temperature acquisition Point A (x) is knownA，yA，zA) With temperature collection point B (x)B，yB，zB) Is 2m away from the temperature collection point C (x)C，yC，zC) When the distance from the temperature sensor (A) to the temperature sensor (x) is 2.5m, the temperature sensor (A) is detectedA，yA，zA) At a close distance, is temperature acquisition point B (x)B，yB，zB). At this time, the coordinate (x) of the midpoint M between the temperature acquisition point A and the temperature acquisition point B can be calculated according to the coordinates of the temperature acquisition points A and BM，yM，zM). Temperature T at the midpoint MMThe corresponding collection temperature T at the temperature collection point A and the temperature collection point BA、TBIs measured. And then, calculating the CRI value of the indoor environment formation contribution rate at the midpoint M. Correspondingly, the calculation result of the CRI value of the indoor environment formation contribution rate at the midpoint M is finally involved in the prediction of the indoor temperature distribution. Or, screening the temperature collection points, and discarding the temperature collection points far away from the temperature prediction target point according to the coordinates of all the temperature collection points and the coordinates of the temperature prediction target point until the number of the temperature collection points is consistent with that of the heat sources. Therefore, the temperature data corresponding to the temperature acquisition points and the reliability of the CRI value of each heat source at the corresponding temperature acquisition point can be improved by screening the temperature acquisition points, and the accuracy of indoor temperature distribution prediction is improved. And then, extracting the temperature data of the corresponding temperature acquisition points and the CRI value of the indoor environment formation contribution rate according to the coordinate information of the temperature acquisition points obtained by screening. Therefore, the quantity of the temperature data of the temperature collection points and the quantity of the temperature collection points which finally participate in indoor temperature distribution prediction can be consistent with the quantity of the indoor heat sources, and indoor temperature distribution prediction is facilitated.
Further, in a preferred embodiment provided in the present application, the calculating device 12 is configured to calculate, according to the temperature data acquired by the temperature acquiring device 11 and through a linear temperature distribution prediction model, a temperature change value at a temperature prediction target point in the space to be predicted, and is further configured to:
according to the temperature change value at the temperature prediction target point in the space to be predicted, calculating the prediction temperature at the temperature prediction target point in the space to be predicted as follows:
θa＝Δθa+θn
in the formula, thetanFor neutral temperature of the space to be predicted, Δ θaAnd predicting the temperature change value at the target point for the temperature in the space to be predicted.
It is understood that the calculating device 12 can obtain the temperature variation value at each temperature prediction point in the room through a linear temperature prediction model according to the temperature data collected by the temperature collecting device 11. However, in order to make it easier for the user to more intuitively observe the indoor temperature under the action of the heat source, the calculation device 12 is also configured to calculate the predicted temperature at each temperature prediction target point from the temperature change value at each temperature prediction target point in the room, and the calculation formula is as follows:
θa＝Δθa+θn
in the formula, thetaaPredicting the predicted temperature, theta, at the target point for the temperature in the space to be predictednFor neutral temperature of the space to be predicted, Δ θaAnd predicting the temperature change value at the target point for the temperature in the space to be predicted. When there is only one temperature prediction point in the room, the calculation result of the calculation means 12 is only the temperature corresponding to the prediction point. When there are not less than two temperature prediction points in the room, the calculation device 12 calculates the result as the temperature at each temperature prediction point.
Further, in a preferred embodiment provided by the present application, the output device 13 is configured to output the temperature change value at the temperature prediction target point in the space to be predicted, which is calculated by the calculation device 12, and is further configured to:
and outputting the predicted temperature at the temperature prediction target point in the space to be predicted, which is obtained through calculation.
It is understood that, when the calculating device 12 calculates the temperature change value at each temperature prediction point in the room according to the temperature data collected by the temperature collecting device 11 and through the linear temperature prediction model, the output device 13 outputs the temperature change value at each temperature prediction point. Accordingly, when the calculation means 12 calculates the predicted temperature at each temperature prediction target point from the temperature change value at each temperature prediction target point in the room, the output means 13 outputs the predicted temperature at each temperature prediction target point. The output device 13 may directly mark the predicted temperature at each temperature prediction target point, or may output the predicted temperature at each temperature prediction target point and the coordinates of each temperature prediction target point in the form of a data set. Therefore, the indoor predicted temperature obtained through calculation can be in one-to-one correspondence with the position of the predicted point, the accuracy of predicted temperature data is improved, and the problem that the predicted temperature data is not matched with the temperature predicted point is avoided.
It is to be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the statement that there is an element defined as "comprising" … … does not exclude the presence of other like elements in the process, method, article, or apparatus that comprises the element.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (10)

1. An indoor temperature distribution prediction system, comprising:
the temperature acquisition device is used for sequentially acquiring temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction;
the calculating device is used for calculating a temperature change value at a temperature prediction target point in the space to be predicted according to the temperature data acquired by the temperature acquiring device and through a linear temperature distribution prediction model;
and the output device is used for outputting the temperature change value at the temperature prediction target point in the space to be predicted, which is calculated by the calculation device.
2. The indoor temperature distribution prediction system according to claim 1, wherein the temperature acquisition device is configured to sequentially acquire temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction, and is further configured to:
determining the coordinates of each temperature acquisition point according to the heat source distribution condition in the space to be predicted;
planning a temperature data acquisition path according to the coordinates of each temperature acquisition point;
wherein, the distribution of the heat source in the space to be predicted at least comprises:
coordinates of heat sources and the number of the heat sources in the space to be predicted.
3. The indoor temperature distribution prediction system according to claim 1, wherein the temperature acquisition device is configured to sequentially acquire temperature data at each temperature acquisition coordinate point in the space to be predicted according to the temperature acquisition path planning instruction, and is specifically configured to:
receiving a temperature acquisition path planning instruction;
determining coordinates of each temperature acquisition point in the space to be predicted according to the acquisition path planning instruction;
sequentially moving to each temperature acquisition coordinate point; collecting temperature data at each temperature collection coordinate point;
and sending the acquired temperature data at each temperature acquisition coordinate point to a computing device.
4. The indoor temperature distribution prediction system according to claim 3, wherein the temperature acquisition device is configured to transmit the acquired temperature data at the temperature acquisition coordinate points to a calculation device, and is further configured to:
and sending the position information of each temperature acquisition coordinate point corresponding to the acquired temperature data to the computing device.
5. The indoor temperature distribution prediction system according to claim 1, wherein the calculation means is configured to calculate, from the temperature data collected by the temperature collection means, a temperature change value at a temperature prediction target point in the space to be predicted through a linear temperature distribution prediction model, and is further configured to:
according to the distribution condition of the heat source in the space to be predicted, CFD simulation is carried out on the space to be predicted to obtain a sub-temperature field of the heat source in the space to be predicted;
calculating an indoor environment formation contribution rate CRI value of the heat source at each temperature acquisition point on the basis of the sub-temperature field of the heat source and through a CRI calculation model;
calculating an indoor environment formation Contribution Rate (CRI) value of the heat source at a temperature prediction target point based on the sub-temperature field of the heat source and through a CRI calculation model;
wherein, the distribution of the heat source in the space to be predicted at least comprises:
coordinates of heat sources and the number of the heat sources in the space to be predicted.
6. The indoor temperature distribution prediction system according to claim 5, wherein the computing device is configured to perform CFD simulation on the space to be predicted according to the heat source distribution in the space to be predicted, so as to obtain the sub-temperature field of the heat source in the space to be predicted, and is specifically configured to:
performing CFD simulation on the space to be predicted according to the heat source distribution condition in the space to be predicted to obtain a total flow field of the space to be predicted;
performing CFD simulation based on the total flow field of the space to be predicted and according to the forming conditions of the heat source sub-temperature field to obtain the sub-temperature field of the heat source in the space to be predicted;
wherein, the distribution of the heat source in the space to be predicted at least comprises:
coordinates of heat sources and the number of the heat sources in the space to be predicted;
and the forming condition of the heat source sub-temperature field is that the number of heat sources participating in heat exchange in the space to be predicted is 1.
7. The indoor temperature distribution prediction system according to claim 1, wherein the calculation device is configured to calculate, according to the temperature data collected by the temperature collection device and through a linear temperature distribution prediction model, a temperature change value at a temperature prediction target point in the space to be predicted, and specifically configured to:
according to the temperature data collected by the temperature collecting device, calculating the difference value between the temperature at the temperature collecting coordinate point in the space to be predicted and the neutral temperature, wherein the difference value is expressed as follows:
ΔθSi＝θSi-θn
in the formula, thetaSiCollecting coordinate point x for temperature collection device in space to be predictediOn the collected temperature data, thetanIs the neutral temperature of the space to be predicted;
according to the difference value between the temperature at each temperature collection coordinate point in the space to be predicted and the neutral temperature, and through a linear temperature distribution prediction model, calculating the temperature change value at the temperature prediction target point in the space to be predicted, and expressing as follows:
Figure FDA0003135408010000031
in the formula, CanPredicting target point x for temperature of heat source n in space to be predicteda(ii) a contribution ratio CRI value, C of indoor environment formationinCollecting coordinate points x for the temperature of a heat source n in a space to be predictediIndoor environment ofForming a contribution ratio CRI value.
8. The indoor temperature distribution prediction system according to claim 7, wherein the calculation means is configured to calculate, from the temperature data collected by the temperature collection means, a temperature change value at a temperature prediction target point in the space to be predicted through a linear temperature distribution prediction model, and is further configured to:
when the number of the temperature acquisition coordinate points is larger than that of the heat sources in the space to be predicted, screening the temperature acquisition coordinate points through a data processing model to obtain the temperature acquisition coordinate points consistent with the number of the heat sources in the space to be predicted;
and extracting the CRI value of the indoor environment formation contribution rate of the heat source at the corresponding temperature acquisition point according to the position information of the temperature acquisition coordinate point obtained by screening.
9. The indoor temperature distribution prediction system according to claim 7, wherein the calculation means is configured to calculate, from the temperature data collected by the temperature collection means, a temperature change value at a temperature prediction target point in the space to be predicted through a linear temperature distribution prediction model, and is further configured to:
according to the temperature change value at the temperature prediction target point in the space to be predicted, calculating the prediction temperature at the temperature prediction target point in the space to be predicted as follows:
θa＝Δθa+θn
in the formula, thetanFor neutral temperature of the space to be predicted, Δ θaAnd predicting the temperature change value at the target point for the temperature in the space to be predicted.
10. The indoor temperature distribution prediction system according to claim 9, wherein the output means is configured to output the temperature change value at the temperature prediction target point in the space to be predicted calculated by the calculation means, and is further configured to:
and outputting the predicted temperature at the temperature prediction target point in the space to be predicted, which is obtained through calculation.
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Application publication date: 20210903