Energy-saving Modeling Method, Model and Control System for Dynamic Energy Consumption Control of Educational Buildings

Abstract

The present invention discloses an energy-saving modeling method, model and control system for dynamic energy consumption control of educational buildings. The energy-saving modeling method includes obtaining and calculating the heating load and cooling load, obtaining and calculating the dynamic energy loss, and correlatively analyzing the heating load, cooling load and dynamic energy loss to obtain the optimal combination of multi-variable influencing factors; a mathematical theoretical model is obtained by using this method; a control system using this method and model, the control system includes: a first data acquisition module, a second data acquisition module, a third data acquisition module, a cloud data processing module, a branch processing module, and a visualization control module. This application constructs a mathematical theoretical model between multi-variables through sensor data collection, data correlation analysis, data association rule mining, data association analysis and visualization operations, and proposes the optimal strategies for energy-saving design and control of educational buildings based on this model, and presents them in a visualized form.

Description

Technical Field

[0001] The present invention relates to the technical field of building energy conservation, in particular to an energy-saving modeling method, model and control system for dynamic energy consumption control of educational buildings. Background Art

[0002] Buildings, as major energy consumers, play an important role in the process of achieving the "dual carbon" goal. Among all building types, public buildings consume the most energy. The energy consumption of public buildings is 2.4 times and 3 times that of urban and rural residential buildings respectively. Among them, the stock area of educational buildings accounts for 50% of the stock area of ordinary public buildings in China. The population density in educational buildings is much higher than that of other types of public buildings. The users are mainly children and teenagers, who are energetic. The way of people flow is continuous, which will lead to frequent opening and closing of classroom doors and continuous exchange of indoor and outdoor air. In primary and secondary school educational buildings, children and teenagers have a large amount of activities and many collective behaviors, such as collective reading and activities, which will cause an increase in indoor heat gain and temperature rise. Without changing heating or cooling, doors and windows will be frequently opened and closed, which will cause changes in the indoor and outdoor microenvironment and bring changes in energy consumption. The microenvironment monitoring variables mainly include indoor and outdoor air temperatures, air flow direction and speed, the wind speed entering the room through exterior doors and windows, and the change of indoor heat gain. For classrooms equipped with air purification devices and fresh air systems, the change of indoor and outdoor air quality needs to be monitored simultaneously. The main monitoring variables include air pollutants such as carbon dioxide (CO2) and inhalable particulate matter (PMs). Therefore, the energy transfer in educational buildings is more complex. The frequent opening and closing of classroom doors and exterior windows will cause a significant increase in energy consumption. In recent years, the stock area of educational buildings has increased extremely fast. Along with the improvement of the requirements for the indoor environmental quality of educational buildings and the installation of air conditioners and heaters, the energy consumption level of educational buildings shows a gradually increasing trend. Therefore, it is necessary to provide an energy-saving design and control system that conforms to the characteristics of educational buildings, which is extremely important for the sustainable development of our country. Summary of the Invention

[0003] In view of the above-mentioned defects existing in the prior art, the present invention proposes an energy-saving modeling method, model and control system for dynamic energy consumption control of educational buildings, avoiding the problems of heat loss and increased energy consumption caused by frequent opening and closing of doors and windows.

[0004] To solve the above technical problems, the technical solution adopted by the present invention is an energy-saving modeling method for dynamic energy consumption control of educational buildings, which obtains and calculates the heating load and cooling load of educational buildings, obtains and calculates the dynamic energy loss in educational buildings, and correlates and analyzes the heating load, cooling load and dynamic energy loss of educational buildings to obtain the optimal combination of multi-variable influencing factors, including the following steps:

[0005] (1) Obtain the heat load of the educational building, where the heat load of the educational building includes the heat consumption brought by indoor and outdoor microenvironment variables, and the heat consumption Q of the building envelope j , additional heat consumption Q f ;

[0006] (2) Obtain indoor and outdoor microenvironment variables, where the indoor and outdoor microenvironment variables include the energy consumption change Q brought by the air exchange between the indoor and outdoor corridors S , the energy consumption change Q caused by air entering the indoor through the outer doors and windows W ;

[0007] (3) Calculate the heat consumption Q of the building envelope j = aKf(T i - T o ), where Q j is the temperature difference heat transfer through a certain building envelope surface of the heating room, K is the heat transfer coefficient of this building envelope surface, f is the heat dissipation area of this building envelope surface, T i is the calculated indoor air temperature, T o is the calculated outdoor heating temperature, a is the temperature difference correction coefficient, and the values for exterior walls, roofs, floors, and floors communicating with the outdoors are 1;

[0008] (4) Calculate the additional heat consumption Q f = Q j (1 + βch + βf + βli + βm)(1 + βf·g)(1 + βj), where βch is the orientation correction, βf is the wind force correction, βli is the correction for two exterior walls, βm is the correction for an excessive window-wall area ratio, βf.g is the correction for additional building height, and βj is the correction for intermittent operation;

[0009] (5) Obtain the heat load Q of the educational building from (1)-(4) H = Q j + Q s + Q w + Q f ;

[0010] (6) Obtain the cooling load of the educational building, where the cooling load Q c of the educational building includes the cooling load Q formed by human body heat dissipation O , the cooling load Q formed through the exterior walls and roof wr , the cooling load of the outer doors and windows, the cooling load Q of indoor lighting L , the cooling load Q of equipment e ;

[0011] (7) Calculate the cooling load Q formed by human body heat dissipation O = qnn′, where q is the heat dissipation of adult men at different indoor temperatures and labor natures, n is the total number of people indoors, and n' is the clustering coefficient;

[0012] (8) Calculate the cooling load Q formed by the external wall and the roof wr , Q wr = KFΔT τ-ε , where K is the heat transfer coefficient of the building envelope, F is the area of the wall or roof, τ is the calculation time, ε is the time delay of the temperature wave reaching the inner surface when the building envelope surface is subjected to a harmonic temperature wave with a period of 24 hours, τ - ε is the action time of the temperature wave, that is, the time when the temperature wave acts on the inner surface of the building envelope, and ΔTτ - ε is the temperature difference for calculating the cooling load of the building envelope at the action moment;

[0013] (9) The cooling load of the external door and window includes the cooling load Q formed by the transient heat transfer gain through the external door and window d , the cooling load Q formed by the solar heat gain of the external door and window r , and the cooling load Q formed by the hot air intrusion of the external door i ;

[0014] (10) Calculate the indoor lighting cooling load Q L , Q L = 1000n1n2N, where N is the required power of the lighting fixture, in kW; n1 is the power consumption coefficient of the ballast, and n2 is the heat insulation coefficient of the lampshade;

[0015] (11) Calculate the equipment cooling load Qe, Q e = 1000n1n2n3N, where Q is the heat dissipation of the electronic equipment, in W; N is the installed power of the electronic equipment, in kW, n1 is the installation coefficient, n2 is the load power, and n3 is the simultaneous use coefficient;

[0016] (12) Calculate the cooling load of the educational building. The cooling load Q of the educational building c = Q o + Q wr + Q d + Q r + Q i + Q L + Q e .

[0017] (13) Obtain and calculate the dynamic energy loss, where the dynamic energy loss includes the dynamic energy loss caused by the opening of the external doors and windows and the dynamic energy loss generated by the change in the heat released by the indoor personnel Q do ;

[0018] (14) Combine the Apriori algorithm and the FP-Growth algorithm to perform data correlation analysis on the heating load, cooling load and dynamic energy loss of the educational building, and obtain a mathematical theoretical model.

[0019] Further, in step (2), calculate the energy consumption change Q brought about by the air exchange between the indoor and outdoor corridors s = 0.28C ps V s ρ s (T i -T o ), where V = ∑(lLm), Cps is the air density at the outdoor temperature, ρs is the air density at the outdoor temperature, Vs is the volume flow rate of the infiltrating air, Tn is the calculated indoor air temperature, Tw is the calculated outdoor heating temperature, l is the length of the door and window gaps in a certain orientation, L is the reference infiltration air volume per meter of door and window gaps, and m is the comprehensive correction coefficient of the infiltration air volume of the door and window gaps; calculate the energy consumption change Q caused by the air entering the indoor through the outer doors and windows w = NQ d·j·m = NaK d f d (T i -T o ), where N is the additional rate of the outer door; Q d﹒j﹒m is the basic heat consumption of the outer door; K d is the heat transfer coefficient of the outer door; f is the heat dissipation area of the outer door; T i is the calculated indoor air temperature; To is the calculated outdoor heating temperature.

[0020] Further, in step (9), calculate the cooling load Q formed by the transient heat transfer gain of the outer doors and windows d , Q d = KFΔT τ , where K is the heat transfer coefficient of the outer window, in units of W / m 2 ·K, F is the area of the outer window, in units of m 2 , ΔTτ is the load temperature difference at the calculation moment, in units of °C, calculate the cooling load Q formed by the solar radiation heat gain of the outer doors and windows r , Q r = xg×xd×Cs×Cn×Jj τ , where xg is the effective area coefficient of the outer window, xd is the location correction coefficient, Jjτ is the cooling load formed by the total solar radiation heat passing through the unit window area at the calculation moment, in units of W / m 2 , Cs is the shading coefficient of the window glass, Cn is the shading coefficient of the internal shading facility of the window; calculate the cooling load Q formed by the hot air intrusion of the outer door i , Q i = G·0.24(T w -T n ), where G is the amount of air intruding through the opening of the outer door, in units of kg / h, and the calculation formula is G = nV m γ w , where V mThe air infiltration volume for one opening of the outer door, including one entry and one exit, is in the unit of m 2 / person - time·h, n is the number of people per hour, in the unit of person / h; Y w is the specific gravity of outdoor air, in the unit of kg / m 2 .

[0021] Furthermore, in step (13):

[0022] (1) Obtain the dynamic energy loss caused by the opening of the outer doors and windows, and calculate as follows: The opening amplitude of the outer door, that is, the air exchange volume V d =S d v d τ d where S d is the door opening area, in the unit of m 2 ; v d is the speed of air flowing through the outer door, in the unit of m / s, τ d is the opening duration of the outer door, in the unit of s. The opening amplitude of the outer window is calculated for the air exchange volume V w =S w v w τ w , where S w is the window opening area, in the unit of m 2 , v w is the speed of air flowing through the outer window, in the unit of m / s, τ w is the opening duration of the outer window, in the unit of s. The dynamic energy loss Q dd =C p ρS d v d ΔT. The dynamic energy loss Q dw =C p ρS w ν w ΔT. Among them, C p is the specific heat capacity of air, in the unit of kJ / (kg·K), ρ is the air density at outdoor temperature, in the unit of Kg / m 3 , ΔT is the real - time temperature difference between indoors and outdoors, in the unit of °C. The energy loss within a certain period of time is

[0023] ∑Q dd =Q(dd1)+Q(dd2)+……+Q(ddn)

[0024] ∑Q dw =Q(dw1)+Q(dw2)+……+Q(dwn);

[0025] (2) Obtain the dynamic energy loss Q do generated by the change in heat released by indoor personnel, Q do =Wout ×N, where W out is the real-time heat dissipation of the human body in different states, with the unit of W, N is the real-time number of people indoors, and the energy loss within a certain period of time is ∑Q do = Q(do1) + Q(do2) + …… + Q(don);

[0026] (3) The dynamic energy loss Q d , Q d = Q dd + Q dw + Q do .

[0027] Furthermore, using the above energy-saving modeling method for dynamic energy consumption control in educational buildings, a mathematical theoretical relationship model is obtained. The model includes correlation analysis 1, correlation analysis 2, correlation analysis 3, correlation analysis 4, correlation analysis 5. The correlation analysis 1, that is, the relationship between the door opening duration (τ d ) and the dynamic energy loss (Q dd ),

[0028]

[0029] The correlation analysis 2, that is, the relationship between the door opening amplitude (S d ) and the dynamic energy loss (Q dd ),

[0030]

[0031] The correlation analysis 3, that is, the relationship between the window opening duration (τ w ) and the dynamic energy loss (Q dw ),

[0032]

[0033] The correlation analysis 4, that is, the relationship between the window opening amplitude (S w ) and the relationship of the dynamic energy loss (Q dw ),

[0034]

[0035] The correlation analysis 5, the relationship between the indoor human body heat dissipation (W out ) and the dynamic energy loss (Q do ),

[0036] In the above analysis, r = 1 or -1, and the two indicators are completely positively or negatively correlated; when r > 0, the two indicators are positively correlated and have the same trend; when r < 0, the two indicators are negatively correlated and have opposite trends; when r = 0, the two indicators are not correlated. From this, the relationship between the cooling and heating load and the heat loss is obtained as follows:

[0037] Q dd +Q dw >Q do When, the building cooling and heating load (Q H +Q c ) increases, and at the same time, adjust the opening of the doors and windows to reduce the opening of the doors and windows;

[0038] Q dd +Q dw <Q do When, the building cooling and heating load (Q H +Q c ) decreases, and at the same time, adjust the opening of the doors and windows and appropriately increase the opening of the doors and windows;

[0039] Q dd +Q dw =Q do When, the building cooling and heating load does not need to be adjusted.

[0040] Furthermore, the control system for the dynamic energy consumption control of the above-mentioned educational building includes:

[0041] The first data acquisition module, which is arranged in the classroom and is used to acquire various data of the internal environment of the classroom;

[0042] The second data acquisition module, which is arranged in the corridor outside the classroom and is used to acquire various data in the corridor;

[0043] The third data acquisition module, which is arranged outdoors and is used to acquire various data of the outdoor environment;

[0044] The cloud data processing module, which receives the data of the first data acquisition module, the second data acquisition module, and the third data acquisition module in real time, processes the above data using the mathematical theory relationship model, obtains the optimal combination of multiple variables, and then converts it into code using the Python programming language;

[0045] The sub-processing module is used to control the opening and closing of the doors and windows in the classroom and the corridor, and the heating and cooling equipment in the classroom;

[0046] The visualization control module is used to receive the data processed by the cloud data processing module, display it on the screen in real time, and control the sub-processing module through the screen to control the opening and closing of the doors and windows, thereby controlling the dynamic energy loss.

[0047] Furthermore, the first data acquisition module includes:

[0048] A temperature sensor, installed in the classroom, is used to detect the temperature in the classroom;

[0049] A magnetic attraction and angle sensor, installed at the classroom doorframe, is used to detect the opening angle of the classroom door;

[0050] A wind speed and wind direction sensor, installed at the classroom doorframe, is used to detect the wind speed and wind direction when the classroom door is opened, and installed at the outer window frame, is used to detect the wind speed and wind direction inside and outside the room;

[0051] An air circulation sensor, installed on the desk, is used to detect the air flow when people move;

[0052] A thermal imager sensor, installed in the classroom, is used to detect the distribution of human infrared radiation energy;

[0053] A face and behavior sensor, installed in the classroom, is used to detect the number of people and human behaviors in the classroom;

[0054] A magnetic attraction and scale sensor, installed at the outer window frame of the classroom, is used to detect the opening angle of the outer window;

[0055] An air quality sensor, installed in the classroom, is used to detect the air quality in the classroom;

[0056] A device usage timing sensor, installed in the classroom, is used to detect the operating time of heating and cooling equipment.

[0057] Furthermore, the second data acquisition module includes:

[0058] A temperature and air quality sensor, installed in the corridor, is used to detect the temperature and air quality in the corridor;

[0059] An air circulation sensor, installed in the corridor, is used to detect the air flow in the corridor;

[0060] A magnetic attraction and scale sensor, installed at the outer window frame of the corridor, is used to detect the opening angle of the outer window;

[0061] Furthermore, the third data acquisition module includes:

[0062] A temperature and air quality sensor, installed outdoors, is used to detect the temperature and air quality outdoors;

[0063] A wind speed sensor, installed at the corridor doorframe, is used to detect the wind speed between the outdoors and the corridor;

[0064] A magnetic attraction and angle sensor, installed at the corridor doorframe, is used to detect the opening angle of the corridor door;

[0065] A wind speed and wind direction sensor, installed near the building entrance, is used to detect the wind speed and wind direction around the building.

[0066] The beneficial effects of the energy-saving modeling method, model and control system for dynamic energy consumption control of educational buildings in the present invention are as follows: multiple sensors are used to realize real-time big data collection, a mathematical theoretical model of multivariables and dynamic energy loss is constructed, and based on this mathematical model as the calculation basis, the changes of each variable and the changes of building energy consumption are displayed on the screen in real time, which is convenient for architects and operation and maintenance engineers to find the changes of building energy consumption, and is convenient for targeted adjustment of the opening and closing of doors and windows to reduce building energy consumption; it realizes real-time viewing and intelligent control of the energy changes in educational buildings, and provides a comfortable learning and working environment for students and teachers. Through sensor data collection, data correlation analysis, data association rule mining, data association analysis and visualization operations, the internal influence mechanism between dynamic energy loss and multivariables is sorted out, and a mathematical theoretical model between building energy-saving design and multivariables is constructed. Based on this model, the optimal strategies for building energy-saving design and control under specific environmental conditions are proposed and presented in a visual form. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 It is a schematic diagram of the technical route of the present invention;

[0068] Figure 2 It is a schematic diagram of the idea for determining the research content of the present invention;

[0069] Figure 3 It is a schematic diagram of the thinking of reverse multivariable optimal combination of the present invention;

[0070] Figure 4 It is a schematic diagram of the thinking of forward multivariable optimal combination of the present invention;

[0071] Figure 5 It is a schematic diagram of the structure of the present invention;

[0072] Figure 6 It is a display diagram of the visualization control module of the present invention.

[0073] In the figure, 1 is the classroom outer window; 2 is the outdoors; 3 is the classroom door; 4 is the desk; 5 is the corridor; 6 is the corridor outer window; 7 is the corridor door; 8 is the face and behavior sensor; 9 is the thermal imager sensor. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0074] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0075] As Figures 1-6 shown, first, the influencing factors of the energy consumption of educational buildings need to be determined. The outer doors of educational buildings include the classroom door 3 and the corridor door 7, and the outer windows include the classroom outer window 1 and the corridor outer window 6. The qualitative analysis method is as follows:

[0076] (1) Literature review method: Conduct keyword searches through databases such as CNKI, ScienceDirect, Scopus, PubMed, and Web of science to collect research materials related to building dynamic energy loss, user behavior, and microenvironment. Use Review Manager and Stata Mp16 software to conduct META analysis on the collected materials, and use Cite Space software to conduct visual analysis on the collected materials to deeply analyze the structure, rules, and distribution of existing literature.

[0077] (2) Observation and recording method: Use smoke experiments to conduct air flow monitoring experiments on the surrounding environment near the entrances and exits of educational buildings and the doors and windows of rooms, and at the same time use videos to record the smoke flow. The air flow experiment can enable researchers to clearly understand the air flow situation in and around the building.

[0078] (3) Questionnaire and interview method: Conduct interviews with campus managers, architects, engineers, building users, etc. The interview results will be analyzed using qualitative analysis software NVivo to extract the behavioral preference factors that affect building dynamic energy loss.

[0079] The energy-saving modeling method for controlling the dynamic energy consumption of educational buildings, obtaining and calculating the heating load and cooling load of educational buildings, obtaining and calculating the dynamic energy loss in educational buildings, and correlating and analyzing the heating load, cooling load, and dynamic energy loss of educational buildings to obtain the optimal combination of multi-variable influencing factors, including the following steps:

[0080] (1) Obtain the heating load of the educational building, where the heating load of the educational building includes the heat consumption brought by indoor and outdoor microenvironment variables, and the heat consumption Q j of the building envelope, and the additional heat consumption Q f ;

[0081] (2) Obtain indoor and outdoor microenvironment variables, where the indoor and outdoor microenvironment variables include the energy consumption change Q S brought by the air exchange between the indoor and outdoor corridors, and the energy consumption change Q W caused by the air entering the indoor through the outer doors and windows;

[0082] (3) Calculate the heat consumption Q j of the building envelope = aKf(T i - T o ), where Q j is the temperature difference heat transfer through a certain side of the building envelope of the heated room, K is the heat transfer coefficient of this side of the building envelope, f is the heat dissipation area of this side of the building envelope, T i is the indoor air calculated temperature, and T ois the outdoor heating calculation temperature, a is the temperature difference correction coefficient, and the values for exterior walls, roofs, floors, and floors communicating with the outdoors are 1;

[0083] (4) Calculate the additional heat loss Q f = Q j (1 + βch + βf + βli + βm)(1 + βf·g)(1 + βj), where βch is the orientation correction, βf is the wind force correction, βli is the correction for two exterior walls, βm is the correction for an excessive window-wall area ratio, βf.g is the correction for building height addition, and βj is the intermittent addition correction;

[0084] (5) Obtain the heating load Q of educational buildings from (1)-(4) H = Q j + Q s + Q w + Q f ;

[0085] (6) Obtain the cooling load of educational buildings. The cooling load Q of the educational building c includes the cooling load Q formed by human body heat dissipation O , the cooling load Q formed through the exterior walls and roof wr , the cooling load of exterior doors and windows, the indoor lighting cooling load Q L , the equipment cooling load Q e ;

[0086] (7) Calculate the cooling load Q formed by human body heat dissipation O = qnn′, where q is the heat dissipation of adult men at different room temperatures and labor natures, n is the total number of people indoors, and n' is the clustering coefficient;

[0087] (8) Calculate the cooling load Q formed through the exterior walls and roof wr , Q wr = KFΔT τ-s , where K is the heat transfer coefficient of the enclosure structure, F is the area of the wall or roof, τ is the calculation time, ε is the time delay for the temperature wave to reach the inner surface when the enclosure structure surface is subjected to a harmonic temperature wave with a period of 24 hours, τ - ε is the action time of the temperature wave, that is, the time when the temperature wave acts on the inner surface of the enclosure structure, and ΔTτ - ε is the cooling load calculation temperature difference of the enclosure structure at the action moment;

[0088] (9) The cooling load of exterior doors and windows includes the cooling load Q formed by the transient heat transfer gain through exterior doors and windows d , the cooling load Q formed by the solar radiation gain of exterior doors and windows r , the cooling load Q formed by the hot air intrusion of exterior doors i ;

[0089] (10) Calculate the indoor lighting cooling load Q L , QL = 1000n1n2 N , where N is the power required for the lighting fixture, in kW; n1 is the power consumption coefficient of the ballast, and n2 is the heat insulation coefficient of the lampshade;

[0090] (11) Calculate the cooling load Qe of the equipment, Q e = 1000n1n2n3N, where Q is the heat dissipation of the electronic equipment, in W; N is the installed power of the electronic equipment, in kW, n1 is the installation coefficient, n2 is the load power, and n3 is the simultaneous use coefficient;

[0091] (12) Calculate the cooling load of the educational building. The cooling load of the educational building Q c = Q o + Q wr + Q d + Q r + Q i + Q L + Q e .

[0092] (13) Obtain and calculate the dynamic energy loss, where the dynamic energy loss includes the dynamic energy loss caused by the opening of external doors and windows, and the dynamic energy loss generated by the change in heat released by indoor personnel Q do ;

[0093] (14) Combine the Apriori algorithm and the FP-Growth algorithm to perform data correlation analysis on the heating load, cooling load, and dynamic energy loss of the educational building, and obtain a mathematical theoretical model.

[0094] In step (2), calculate the energy consumption change Q brought about by the air exchange between the indoor and outdoor corridors s = 0.28C ps V s ρ s (T i - T o ), where V = ∑(lLm), Cps is the air density at the outdoor temperature, ρs is the air density at the outdoor temperature, Vs is the volume flow rate of the infiltrating air, Tn is the calculated indoor air temperature, Tw is the calculated outdoor heating temperature, l is the length of the door and window gap in a certain orientation, L is the reference infiltration air volume per meter of the door and window gap, and m is the comprehensive correction coefficient of the infiltration air volume of the door and window gap; calculate the energy consumption change Q caused by the air entering the indoor through the external doors and windows w = NQ d·j·m = NaK d f d (T i - T o ), where N is the additional rate of the external door; Q d﹒j﹒m is the basic heat consumption of the external door; Kd is the heat transfer coefficient of the exterior door; f is the heat dissipation area of the exterior door; T i is the calculated indoor air temperature; To is the calculated outdoor heating temperature.

[0095] In step (9), calculate the cooling load Q formed by the transient heat gain of the exterior door and exterior window d , Q d = KFΔT τ , where K is the heat transfer coefficient of the exterior window, in units of W / m 2 ·K, F is the area of the exterior window, in units of m 2 , ΔTτ is the load temperature difference at the calculation time, in units of °C. Calculate the cooling load Q formed by the solar heat gain of the exterior door and exterior window r , Q r = xg×xd×Cs×Cn×Ji τ , where xg is the effective area coefficient of the exterior window, xd is the location correction coefficient, Jjτ is the cooling load formed by the total solar radiation heat passing through the unit window area at the calculation time, in units of W / m 2 , Cs is the shading coefficient of the window glass, Cn is the shading coefficient of the interior window shading facility; calculate the cooling load Q formed by the hot air intrusion of the exterior door i , Q i = G·0.24(T w - T n ), where G is the amount of air intruding through the opening of the exterior door, in units of kg / h, and the calculation formula is G = nV m γ w , where V m is the air infiltration volume for one opening of the exterior door, including one entry and one exit, in units of m 2 / person·h, n is the number of people per hour, in units of person / h; Y w is the specific gravity of outdoor air, in units of kg / m 2 .

[0096] In step (13):

[0097] (a) Obtain the dynamic energy loss caused by the opening of the exterior doors and windows, and calculate as follows: the opening amplitude of the exterior door, that is, the air exchange volume V d = S d v d τ d where S d is the door opening area, in units of m 2 ; v d is the speed of air flowing through the exterior door, in units of m / s, τ d is the exterior door opening duration, in units of s. The opening amplitude of the exterior window is the air exchange volume calculation V w = S w v w τw , where S w is the window opening area, in m 2 , v w is the velocity of air flowing through the outer window, in m / s, τ w is the duration of the outer window opening, in s, and the dynamic energy loss Q caused by the opening of the outer door dd = C p ρS d v d ΔT, and the dynamic energy loss Q caused by the opening of the outer window dw = C p ρS w v w ΔT, where C p is the specific heat capacity of air, in kJ / (kg·K), ρ is the air density at the outdoor temperature, in Kg / m 3 , and ΔT is the real-time temperature difference between indoors and outdoors, in °C. The energy loss within a certain period of time is

[0098] ΣQ dd = Q(dd1) + Q(dd2) + …… + Q(ddn)

[0099] ΣQ dw = Q(dw1) + Q(dw2) + …… + Q(dwn);

[0100] (b) Obtain the dynamic energy loss Q generated by the change in heat released by indoor occupants do , Q do = W out × N, where W out is the real-time heat dissipation of the human body in different states, in W, and N is the real-time number of people indoors. The energy loss within a certain period of time is ΣQ do = Q(do1) + Q(do2) + …… + Q(don);

[0101] (c) The dynamic energy loss Q d , Q d = Q dd + Q dw + Q do .

[0102] Using the above energy-saving modeling method for dynamic energy consumption control in educational buildings, through forward thinking and reverse thinking, a mathematical theoretical relationship model can be obtained. Reverse thinking is the collection and analysis of multi-variable data based on the current situation of educational buildings, exploring the mathematical theoretical logical relationship and design strategies between multi-variables and building energy conservation in the already built environment. Forward thinking is based on the general applicable value of the research results of this study, and at the same time fitting the characteristic variables of newly built buildings, giving the optimal design strategies to assist architects. The characteristic variables of newly built buildings here include building attribute variables other than microenvironment and user behavior information, that is, building volume size (shape coefficient), orientation, location, occupancy density, number and location of entrances and exits (including single door lobbies and multi-layer door lobbies), etc.

[0103] Stata MP software can also be used to conduct correlation analysis on the data collected by sensors, extract key influencing factors, and establish a mathematical theoretical model. Analysis of variance method and correlation analysis method are respectively used to interpret the mutual influence between various types of data and the relationship with dynamic energy loss.

[0104] Then, data association rule mining algorithm and data association analysis algorithm are used to explore the optimal combination of multi-variable influencing factors. Currently, Apriori and FP-Growth are classic association analysis algorithms. Among them, Apriori, as an algorithm for mining frequent item sets of association rules, is widely used in various scientific research fields due to its stability and has relatively rich reference cases. When the data volume is too large and the running efficiency of the Apriori algorithm decreases, the FP-Growth algorithm is used instead. The FP-Growth algorithm can map the data set to the FP-Tree to find frequent item sets, and this process has high running efficiency and short time. Using these two algorithms can improve the efficiency of solving the optimal combination of multi-variables, and the operation results of the two algorithms can be cross-validated. This working mode helps to comprehensively explore the influencing variables of dynamic energy loss and helps to establish a theoretical model more systematically.

[0105] It can be concluded from this that the model includes Correlation Analysis 1, Correlation Analysis 2, Correlation Analysis 3, Correlation Analysis 4, Correlation Analysis 5;

[0106] Correlation Analysis 1, that is, the relationship between the door opening duration (τ d ) and the dynamic energy loss (Q dd ),

[0107]

[0108] Correlation Analysis 2, that is, the relationship between the door opening amplitude (S d ) and the dynamic energy loss (Q dd ),

[0109]

[0110] Correlation analysis 3, that is, the relationship between the window opening duration (τ w ) and the dynamic energy loss (Q dw ).

[0111]

[0112] Correlation analysis 4, that is, the relationship between the window opening amplitude (S w ) and the dynamic energy loss (Q dw ).

[0113]

[0114] Correlation analysis 5, the relationship between the heat dissipation of the indoor human body (W out ) and the dynamic energy loss (Q do ). In the above analysis, r = 1 or -1, and the two indicators are completely positively or negatively correlated; r > 0, the two indicators are positively correlated and have the same trend; r < 0, the two indicators are negatively correlated and have opposite trends; r = 0, the two indicators are not correlated. From this, the relationship between the cooling and heating load and the heat loss is obtained as follows:

[0115] Q dd +Q dw >Q do When, the building cooling and heating load (Q H +Q c ) increases, and at the same time, the opening of the doors and windows is adjusted to reduce the opening of the doors and windows;

[0116] Q dd +Q dw <Q do When, the building cooling and heating load (Q H +Q c ) decreases, and at the same time, the opening of the doors and windows is adjusted to appropriately increase the opening of the doors and windows;

[0117] Q dd +Q dw =Q do When, the building cooling and heating load does not need to be adjusted.

[0118] The control system for the dynamic energy consumption control of the above educational building includes:

[0119] The first data acquisition module is arranged in the classroom and is used to acquire various data of the internal environment of the classroom;

[0120] The second data acquisition module is arranged in the corridor outside the classroom and is used to acquire various data in the corridor;

[0121] The third data acquisition module, which is installed outdoors and is used to collect various data of the outdoor environment;

[0122] The cloud data processing module, which receives the data of the first data acquisition module, the second data acquisition module, and the third data acquisition module in real time, processes the above data using the mathematical theory relationship model, obtains the optimal combination of multiple variables, and then converts it into code using the Python programming language;

[0123] The branch processing module is used to control the opening and closing of the doors and windows in the classroom and the corridor, as well as the heating and cooling equipment in the classroom;

[0124] The visualization control module is used to receive the data processed by the cloud data processing module, display it on the screen in real time, and control the branch processing module through the screen to control the opening and closing of the doors and windows, thereby controlling the dynamic energy loss.

[0125] The first data acquisition module includes:

[0126] A temperature sensor, which is installed in the classroom and is used to detect the temperature in the classroom;

[0127] A magnetic attraction and angle sensor, which is installed at the classroom door frame and is used to detect the opening angle of the classroom door;

[0128] A wind speed and wind direction sensor, which is installed at the classroom door frame and is used to detect the wind speed and wind direction when the classroom door is opened, and is installed at the outer window frame and is used to detect the wind speed and wind direction inside and outside the room;

[0129] An air circulation sensor, which is installed on the desk 4 and is used to detect the air flow when people move;

[0130] A thermal imager sensor 9, which is installed in the classroom and is used to detect the distribution of human infrared radiation energy;

[0131] A face and behavior sensor 8, which is installed in the classroom and is used to detect the number of people in the classroom and human behavior;

[0132] A magnetic attraction and scale sensor, which is installed at the outer window frame of the classroom and is used to detect the opening angle of the outer window;

[0133] An air quality sensor, which is installed in the classroom and is used to detect the air quality in the classroom;

[0134] An equipment usage timing sensor, which is installed in the classroom and is used to detect the running time of the heating and cooling equipment.

[0135] The second data acquisition module includes:

[0136] A temperature and air quality sensor, which is installed in the corridor and is used to detect the temperature and air quality in the corridor;

[0137] An air circulation sensor is installed in the corridor and is used to detect the air flow condition in the corridor;

[0138] A magnetic attraction and scale sensor is installed at the window frame of the outer window in the corridor and is used to detect the opening angle of the outer window;

[0139] The third data acquisition module includes:

[0140] A temperature and air quality sensor is installed outdoors and is used to detect the outdoor temperature and air quality;

[0141] An air velocity sensor is installed at the door frame of corridor door 7 and is used to detect the air velocity between the outdoors and the corridor;

[0142] A magnetic attraction and angle sensor is installed at the door frame of corridor door 7 and is used to detect the opening angle of corridor door 7;

[0143] An air velocity and wind direction sensor is installed near the building entrance and is used to detect the air velocity and wind direction around the building.

[0144] The above indoor and outdoor microenvironment variables and sensor types can be listed in the following corresponding data formats,

[0145]

[0146]

[0147] The visualization control module can build a computer web - end visualization operating system using WebGL and Three.js. WebGL is the current mainstream computer 3D scene display technology, which is highly convenient and is conducive to real - time data update and display. Three.js is the preferred visualization rendering engine for WebGL, with good scalability and customizability. WebGL can implement the production of web - end interactive 3D scenes through the HTML script itself. Combining with the Python language program and the Threejs rendering engine to present the data visualization effect, only by inputting the Http protocol website address into the browser can various real - time online data and data relationship processing results be obtained.

[0148] To make the visualization control module run smoothly on the computer port, it is necessary to perform lightweight processing on the building model. Currently, mainstream modeling software, such as Revit and 3DMax, can export the building model as OBJ and MTL files, and generate a 3D scene by parsing these files in HT. The completed model has a higher degree of lightweight.

[0149] Workflow: The first data acquisition module transmits data such as the detected indoor temperature, the opening angle of the classroom door, the wind speed and direction when the classroom door is opened, the wind speed and direction inside and outside the room, the air flow situation when people move, the distribution of human infrared radiation energy, the number of people in the classroom and human behavior, the opening angle of the exterior window, the indoor air quality, the operating time of heating and cooling equipment, etc. to the cloud data processing module; at the same time, the data such as the detected corridor temperature and air quality, the air flow situation in the corridor, the window opening angle, etc. detected by the second data acquisition module are transmitted to the cloud data processing module; at the same time, the third data acquisition module transmits data such as the detected outdoor temperature and air quality, the wind speed between the outside and the corridor, the opening angle of corridor door 7, the wind speed and direction around the building, etc. to the cloud data processing module; the three data acquisition modules synchronously and real-time detect the microenvironment changes inside and outside the classroom, transmit the data to the cloud data processing module, the cloud processing module uses a combination of the Apriori algorithm and the FP-Growth algorithm to process the above data, obtains the optimal combination of multiple variables, and then converts it into code using the Python programming language; then sends these data to the visualization control module, the visualization control module displays these data on the computer screen in real time, and then sends a signal to the branch processing module through the visualization control module to control the opening and closing of the doors and windows in the classroom and the corridor, and the heating and cooling equipment in the classroom, so that the indoor temperature and air quality reach comfortable indicators.

[0150] In summary, this application combs the internal influence mechanism between dynamic energy loss and multiple variables and constructs a mathematical theoretical model between building energy-saving design and multiple variables through sensor data collection, data correlation analysis, data association rule mining, data association analysis and visualization operations, and proposes the optimal strategy for building energy-saving design and control under specific environmental conditions based on this model, and presents it in a visual form.

[0151] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by those of ordinary skill in the art within the scope of the essence of the present invention shall also fall within the protection scope of the present invention.

Claims

1. Energy-saving modeling method for dynamic energy consumption control of educational buildings, characterized in that: Obtain and calculate the heating load and cooling load of educational buildings, obtain and calculate the dynamic energy loss in educational buildings, and analyze the correlation of the heating load, cooling load and dynamic energy loss of educational buildings to obtain the optimal combination of multi-variable influencing factors, including the following steps: (1) Obtain the heating load of the educational building, where the heating load of the educational building includes the heat consumption caused by indoor and outdoor microenvironment variables and the heat consumption Q of the building envelope j , additional heat consumption Q f ; (2) Obtain indoor and outdoor microenvironment variables, where the indoor and outdoor microenvironment variables include the energy consumption change Q brought about by the air exchange between the indoor and the corridor S , and the energy consumption change Q caused by the air entering the indoor through the outer doors and outer windows W ; (3) Calculate the heat consumption Q of the building envelope j = aKf(T i - T o ), where Q j is the temperature difference heat transfer through a certain side of the building envelope of the heated room, K is the heat transfer coefficient of this side of the building envelope, f is the heat dissipation area of this side of the building envelope, T i is the calculated indoor air temperature, T o is the calculated outdoor heating temperature, and a is the temperature difference correction coefficient. The values for exterior walls, roofs, floors, and floors communicating with the outside are 1; (4) Calculate the additional heat consumption Q f = Q j (1 + βch + βf + βli + βm)(1 + βf·g)(1 + βj), where βch is the orientation correction, βf is the wind force correction, βli is the correction for two external walls, βm is the correction for excessive window-wall area ratio, βf.g is the correction for additional height of the building, and βj is the correction for intermittent use; (5) It can be obtained from (1)-(4) that the heating load Q of educational buildings H = Q j + Q s + Q w + Q f ; (6) Obtain the cooling load of educational buildings, where the cooling load Q of educational buildings c includes the cooling load Q formed by the heat dissipation of the human body O , the cooling load Q formed through the exterior walls and roof wr , the cooling load of exterior doors and windows, the indoor lighting cooling load Q L , the equipment cooling load Q e ; (7) Calculate the cooling load Q formed by the heat dissipation of the human body O = qnn′, where q is the heat dissipation of adult men at different room temperatures and labor natures, n is the total number of people in the room, and n′ is the crowding coefficient; (8) Calculate the cooling load Q formed by the external wall and the roof wr , Q wr = KFΔT τ-s , where K is the heat transfer coefficient of the building envelope, F is the area of the wall or roof, τ is the calculation time, ε is the time delay when the temperature wave with a period of 24 hours acts on the surface of the building envelope and the temperature wave reaches the inner surface, τ - ε is the action time of the temperature wave, that is, the time when the temperature wave acts on the inner surface of the building envelope, and ΔTτ - ε is the temperature difference for calculating the cooling load of the building envelope at the action moment; (9) The cooling load of the exterior doors and windows includes the cooling load Q d formed by the transient heat transfer gain through the exterior doors and windows, the cooling load Q r formed by the solar heat gain of the exterior doors and windows, and the cooling load Q i formed by the hot air infiltration of the exterior doors; (10) Calculate the cooling load Q of indoor lighting L , Q L = 1000n1n2N, where N is the power required for lighting fixtures, in kW; n1 is the power consumption coefficient of the ballast, and n2 is the heat insulation coefficient of the lampshade; (11) Calculate the cold load Qe of the computing device, Q e = 1000n1n2n3N, where Qe is the heat dissipation of the electronic device, in W; N is the installed power of the electronic device, in kW, n1 is the installation coefficient, n2 is the load power, and n3 is the simultaneous use coefficient; (12) Calculate the cooling load of educational buildings. The cooling load of educational buildings is Q c = Q o + Q wr + Q d + Q r + Q i + Q L + Q e ; (13)Obtain and calculate the dynamic energy loss, where the dynamic energy loss includes the dynamic energy loss caused by the opening of external doors and windows, and the dynamic energy loss Q generated by the change in heat released by indoor occupants do ; (14) Combine the Apriori algorithm and the FP-Growth algorithm to perform data correlation analysis on the heating load, cooling load and dynamic energy loss of educational buildings, and obtain a mathematical theoretical model; In step (13): 1) Obtain the dynamic energy loss caused by the opening of exterior doors and windows, calculated as follows: the opening amplitude of the exterior door, i.e., the air exchange volume V d = S d v d τ d where S d is the door opening area, in m 2 ; v d is the velocity of air flowing through the exterior door, in m / s, and τ d is the exterior door opening duration, in s. The opening amplitude of the exterior window is calculated for the air exchange volume V w = S w v w τ w where S w is the window opening area, in m 2 ; v w is the velocity of air flowing through the exterior window, in m / s, and τ w is the exterior window opening duration, in s. The dynamic energy loss Q caused by the opening of the exterior door dd = C p ρS d v d ΔT. The dynamic energy loss Q caused by the opening of the exterior window dw = C p ρS w v w ΔT. Where C p is the specific heat capacity of air, in kJ / (kg·K), ρ is the air density at outdoor temperature, in Kg / m 3 , and ΔT is the real-time temperature difference between indoors and outdoors, in °C. The energy loss within a certain period is ∑Q dd = Q dd1 + Q dd2 + …… + Q ddn ∑Q dw = Q dw1 + Q dw2 + …… + Q dwn ; 2) Obtain the dynamic energy loss Q generated by the change in heat released by indoor personnel do , Q do = W out × N, where W out is the real-time heat dissipation of the human body in different states, with the unit of W, N is the real-time number of people indoors, and the energy loss within a certain period of time is ∑Q do = Q do1 + Q do2 + …… + Q don ; 3) The dynamic energy loss Q d , Q d = Q dd + Q dw + Q do ; In step (14), the mathematical theory model includes correlation analysis 1, correlation analysis 2, correlation analysis 3, correlation analysis 4, and correlation analysis 5. The correlation analysis 1 is the relationship between the door opening duration (τ d ) and the dynamic energy loss (Q dd ). The correlation analysis 2, i.e., the relationship between the door opening amplitude (S d ) and the dynamic energy loss (Q dd ). The correlation analysis 3, i.e., the relationship between the window opening duration (τ w ) and the dynamic energy loss (Q dw ). The correlation analysis 4, i.e., the relationship between the window opening amplitude (S w ) and the dynamic energy loss (Q dw ). The correlation analysis 5, the heat dissipation of the human body indoors (W out ) and the relationship with the dynamic energy loss (Q do ), In the above analysis, r = 1 or -1, and the two indicators are completely positively or negatively correlated; when r > 0, the two indicators are positively correlated and have the same trend; when r < 0, the two indicators are negatively correlated and have opposite trends; when r = 0, the two indicators are not correlated. From this, the relationship between the cooling and heating loads and the heat loss is obtained as follows: Q dd +Q dw >Q do When the building heating and cooling load (Q H +Q c ) increases, adjust the opening degree of doors and windows at the same time to reduce the opening of doors and windows; Q dd +Q dw <Q do When, the building cooling and heating load (Q H +Q c ) decreases, and at the same time, adjust the opening degree of doors and windows, and appropriately increase the opening of doors and windows; Q dd +Q dw =Q do When this occurs, the heating and cooling loads of the building do not need to be adjusted.

2. The energy-saving modeling method for dynamic energy consumption control of educational buildings according to claim 1, characterized in that: In step (2), calculate the energy consumption change Q brought about by the air exchange between the indoor and corridor areas s = 0.28C ps V s ρ s (T i - T o ), where V s = ∑(lLm), Cps is the specific heat capacity of air at the outdoor temperature, ρs is the air density at the outdoor temperature, Vs is the volume flow rate of the infiltrating air, Ti is the calculated indoor air temperature, To is the calculated outdoor heating temperature, l is the length of the door and window gaps in a certain orientation, L is the reference air infiltration rate per meter of door and window gaps, and m is the comprehensive correction factor for the air infiltration rate of the door and window gaps; Calculate the energy consumption change Q caused by air entering the room through the outer doors and windows w = NQ d·j·m = NaK d f d (T i - T o ), where N is the additional rate of the outer door; Q d﹒j﹒m is the basic heat consumption of the outer door; K d is the heat transfer coefficient of the outer door; f d is the heat dissipation area of the outer door; T i is the calculated indoor air temperature; To is the calculated outdoor heating temperature.

3. The energy-saving modeling method for dynamic energy consumption control of educational buildings according to claim 2, characterized in that: Calculate the cooling load Q formed by the transient heat transfer gain of the exterior doors and windows in step (9). d , Q d = KFΔT τ , where K is the heat transfer coefficient of the exterior window, in units of W / m 2 ·K, F is the area of the exterior window, in units of m 2 , ΔTτ is the load temperature difference at the calculation time, in units of °C. Calculate the cooling load Q formed by the solar heat gain of the exterior doors and windows r , Q r = xg×xd×Cs×Cn×Jj τ , where xg is the effective area coefficient of the exterior window, xd is the location correction coefficient, Jjτ is the cooling load formed by the total solar radiation heat passing through the unit window area at the calculation time, in units of W / m 2 , Cs is the shading coefficient of the window glass, Cn is the shading coefficient of the interior window shading device; Calculate the cooling load Q formed by the hot air intrusion of the exterior door i , Q i = G·0.24(T w - T n ), where G is the amount of air intruding through the opening of the exterior door, in units of kg / h, and the calculation formula is G = nV m γ w , where V m is the air infiltration amount for one opening of the exterior door, including one entry and one exit each, in units of m 2 / person·h, n is the number of people per hour, in units of person / h; Y w is the specific gravity of outdoor air, in units of kg / m 2 .

4. An educational building dynamic energy consumption control system for implementing the energy-saving modeling method for dynamic energy consumption control of an educational building according to any one of claims 1-3, characterized in that, Include: The first data acquisition module, which is installed in the classroom and is used to collect various data of the internal environment of the classroom; The second data acquisition module, which is installed in the teaching corridor and is used to collect various data in the corridor; The third data acquisition module, which is installed outdoors and is used to collect various data of the outdoor environment; The cloud data processing module, which receives the data of the first data acquisition module, the second data acquisition module and the third data acquisition module in real time, processes the above data using the mathematical theoretical model, obtains the optimal combination of multi-variables, and then converts it into code using the Python programming language; The sub-processing module is used to control the opening and closing of the doors and windows in the classroom and the corridor, and the heating and cooling equipment in the classroom; The visualization control module is used to receive the data processed by the cloud data processing module, display it on the screen in real time, and control the sub-processing module through the screen to control the opening and closing of the doors and windows, so as to control the dynamic energy loss.

5. The dynamic energy consumption control system for educational buildings according to claim 4, wherein The first data acquisition module includes: A temperature sensor, which is installed in the classroom and is used to detect the temperature in the classroom; A magnetic attraction and angle sensor, which is installed at the classroom door frame and is used to detect the opening angle of the classroom door; A wind speed and wind direction sensor, which is installed at the classroom door frame and is used to detect the wind speed and wind direction when the classroom door is opened, and is installed at the outer window frame and is used to detect the wind speed and wind direction inside and outside the room; An air circulation sensor, which is installed on the desk and is used to detect the air flow when people move; A thermal imager sensor, which is installed in the classroom and is used to detect the distribution of human infrared radiation energy; A face and behavior sensor, which is installed in the classroom and is used to detect the number of people in the classroom and human behavior; A magnetic attraction and scale sensor, which is installed at the outer window frame of the classroom and is used to detect the opening angle of the outer window; An air quality sensor, which is installed in the classroom and is used to detect the air quality in the classroom; An equipment usage timing sensor, which is installed in the classroom and is used to detect the running time of the heating and cooling equipment.

6. The dynamic energy consumption control system for educational buildings according to claim 5, wherein The second data acquisition module includes: A temperature and air quality sensor, which is installed in the corridor and is used to detect the corridor temperature and air quality; An air circulation sensor, which is installed in the corridor and is used to detect the air flow in the corridor; A magnetic attraction and scale sensor, which is installed at the outer window frame of the corridor and is used to detect the opening angle of the outer window.

7. The dynamic energy consumption control system for educational buildings according to claim 6, characterized in that The third data acquisition module includes: A temperature and air quality sensor, which is installed outdoors and is used to detect the outdoor temperature and air quality; A wind speed sensor, which is installed at the corridor door frame and is used to detect the wind speed between the outside and the corridor; A magnetic attraction and angle sensor, which is installed at the corridor door frame and is used to detect the opening angle of the corridor door; A wind speed and wind direction sensor, which is installed near the building entrance and is used to detect the wind speed and wind direction around the building.

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