System, method, computer program, and computer-readable recording medium for HVAC control of building

Abstract

Disclosed is a method for the heating, ventilating, and air conditioning (HVAC) control of a building. The method comprises the steps of: acquiring indoor environment data, outdoor environment data, and wall data; generating modeling data corresponding to the building on the basis of the acquired data; and controlling the HVAC of the building on the basis of the generated modeling data, wherein the step of generating modeling data comprises a step of estimating a wall temperature gradient for each section of the building by inputting the acquired data into a first model.

Description

HVAC control system, method, computer program and computer-readable recording medium for a building

[0001] The present invention relates to a technology for controlling HVAC (heating, ventilating, and air conditioning) of a building.

[0002] An Energy Management System (EMS) is a system that collects various energy usage information in a building, factory, or home using sensors and meters, and optimizes and controls energy usage through real-time monitoring and analysis.

[0003] Energy management systems can be divided into BEMS (Building Energy Management System) for buildings, FEMS (Factory Energy Management System) for factories, and HEMS (Home Energy Management System) for homes.

[0004] Among these, HEMS refers to a system that provides energy management services for monitoring, controlling, and optimizing energy use such as electricity and gas from the user's perspective.

[0005] Technologies being discussed in energy management systems include energy demand prediction technologies such as peak power demand and energy usage, energy optimization technologies such as energy savings or efficiency improvements, and HVAC automatic control technologies that control heating, cooling, and ventilation devices with energy management in mind.

[0006] Among these, HVAC control technology requires control that takes into account various factors such as user comfort, energy optimization, and indoor environment.

[0007] For example, when the outside temperature is very low, significantly lowering the indoor temperature or turning off the heater can reduce occupant comfort. Furthermore, if occupants feel the cold and set the temperature higher than usual due to automatic heating control, this can actually result in higher energy consumption.

[0008] The present invention has been made in response to the above-described needs, and an object of the present invention is to propose a system, method, computer program, and computer-readable recording medium for generating modeling data of a building (data including at least one of a wall temperature gradient, an indoor surface temperature, and an indoor temperature gradient) and controlling the HVAC of the building using the generated modeling data.

[0009] According to an embodiment of the present invention for achieving the above-described object, a method for controlling HVAC (heating, ventilating, and air conditioning) of a building includes a step of acquiring indoor environment data, outdoor environment data, and wall data, a step of generating modeling data corresponding to the building based on the acquired data, and a step of controlling HVAC of the building based on the generated modeling data, wherein the step of generating modeling data includes a step of inputting the acquired data into a first model to estimate a wall temperature gradient for each section of the building.

[0010] In addition, the method may further include a step of obtaining the indoor object arrangement data and a step of inputting the estimated wall temperature gradient and the obtained indoor object arrangement data into a second model to estimate the indoor surface temperature for each section.

[0011] Additionally, the step of controlling the HVAC may include a step of comparing the dew point temperature of the indoor space with at least one of the wall surface temperature and the indoor surface temperature obtained based on the estimated wall temperature gradient to determine the possibility of surface condensation occurring in the compartment.

[0012] And, the step of controlling the HVAC may include a step of controlling at least one of the ventilation device and the heating device to operate when it is determined that there is a possibility of surface condensation occurring.

[0013] In addition, the method may include a step of estimating the indoor temperature gradient of the building by inputting the indoor surface temperature estimated by the second model, the indoor object arrangement data, and the section detail data into the third model.

[0014] And, the step of controlling the HVAC may include the step of dividing the estimated indoor temperature gradient into a plurality of areas and the step of determining the degree of temperature imbalance based on the temperature difference of the plurality of areas divided.

[0015] In addition, the step of controlling the HVAC may include a step of comparing a vertical temperature imbalance degree with a horizontal temperature imbalance degree when the temperature imbalance information is greater than a preset value, a step of controlling a ventilation device when the vertical temperature imbalance degree is greater than the horizontal temperature imbalance degree, and a step of controlling at least one of a cooling device and a heating device when the vertical temperature imbalance degree is less than the horizontal temperature imbalance degree.

[0016] Meanwhile, an HVAC (heating, ventilating, and air conditioning) control system of a building according to an embodiment of the present invention for achieving the above-described purpose includes a data collection unit that acquires indoor environment data, outdoor environment data, and wall data, a modeling unit that generates modeling data corresponding to the building based on the acquired data, and an HVAC control unit that controls the HVAC of the building based on the generated modeling data, and the modeling unit may include a first modeling unit that inputs the acquired data into a first model to estimate a wall temperature gradient for each section of the building.

[0017] In addition, the data collection unit may obtain the indoor object arrangement data, and the modeling unit may include a second modeling unit that inputs the estimated wall temperature gradient and the obtained indoor object arrangement data into a second model to estimate the indoor surface temperature for each section.

[0018] In addition, the modeling unit may include a third modeling unit that inputs the indoor surface temperature estimated by the second model, the indoor object arrangement data, and the section detail data into a third model to estimate the indoor temperature gradient of the building.

[0019] Meanwhile, a computer-readable recording medium according to an embodiment of the present invention for achieving the above-described purpose may record a program for executing the above-described control method.

[0020] In addition, a program according to an embodiment of the present invention for achieving the above-described purpose may include a program code for executing the above-described control method.

[0021] According to one embodiment of the present invention, by controlling at least one of heating and ventilation based on at least one estimated value of a wall temperature gradient of a modeling unit and an indoor surface temperature, the possibility of indoor surface condensation and mold occurrence can be reduced, thereby improving the comfort of an indoor environment of a building.

[0022] According to one embodiment of the present invention, by controlling at least one of cooling, heating, and ventilation so that the temperature is uniformly distributed throughout the entire space of the room based on an indoor temperature gradient estimation value of a modeling unit, both comfort and energy efficiency of the interior of a building can be achieved under optimal conditions.

[0023] FIG. 1 is a drawing showing a building to which an HVAC control system according to one embodiment of the present invention is applied.

[0024] FIG. 2 is a block diagram illustrating an HVAC control system according to one embodiment of the present invention.

[0025] FIG. 3 is a flowchart illustrating the operation of an HVAC control system according to one embodiment of the present invention.

[0026] Figure 4 is a drawing for explaining a conventional mathematical formula-based wall temperature gradient calculation process.

[0027] FIG. 5 is a drawing for explaining a wall temperature gradient estimation process of a first modeling unit according to one embodiment of the present invention.

[0028] FIG. 6 is a drawing showing a wall including a wooden structure using a vacuum insulation material according to one embodiment of the present invention.

[0029] FIG. 7 is a diagram for explaining an indoor surface temperature estimation process of a second modeling unit according to an embodiment of the present invention.

[0030] FIG. 8 is a diagram for explaining an indoor temperature gradient estimation process of a third modeling unit according to an embodiment of the present invention.

[0031] FIG. 9 is a flowchart illustrating an HVAC control method based on an estimation result of at least one of a first modeling unit and a second modeling unit according to an embodiment of the present invention.

[0032] FIG. 10 is a flowchart illustrating an HVAC control method based on the estimation results of the third modeling unit according to one embodiment of the present invention.

[0033] The following merely exemplifies the principles of the invention. Therefore, those skilled in the art will be able to implement the principles of the invention and invent various devices within the scope and spirit of the invention, even if not explicitly described or illustrated herein. Furthermore, all conditional terms and embodiments listed herein are expressly intended, in principle, to facilitate understanding of the invention, and are not intended to be limiting to the specifically enumerated embodiments and conditions.

[0034] The above-described purposes, features and advantages will become clearer through the following detailed description with reference to the attached drawings, so that a person having ordinary skill in the art to which the invention pertains can easily practice the technical idea of ​​the invention.

[0035] Furthermore, when describing the invention, detailed descriptions of known technologies related to the invention will be omitted if they are deemed to unnecessarily obscure the gist of the invention. Below, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0036]

[0037] Figure 1 is a drawing illustrating a building to which an HVAC control system according to one embodiment of the present invention is applied. In this specification, the building (10) may include a residential building in which people reside, such as a house, villa, apartment, or officetel. However, the HVAC control system of the present invention is not limited to residential buildings and may also be applied to non-residential buildings, such as commercial buildings, buildings, and factories.

[0038] A building may be divided into multiple sections, where a section may refer to a physical and / or functional division unit that divides the physical space within the building, such as a floor unit, a room unit, and / or a use unit.

[0039] For example, as shown in Fig. 1(a), a building (10) may be composed of multiple floors including a first floor (11) and a second floor (12). In this case, the building (10) may be divided into two sections, the first floor (11) and the second floor (12).

[0040] As another example, referring to FIG. 1(b), a building (10) may be composed of multiple rooms on a single floor. In this case, the building (10) may be divided into sections according to multiple rooms, such as a study, a living room, and a master bedroom.

[0041] As another example, a division may be determined by combining floor and room units. In this case, each room on each of the multiple floors may constitute a single division unit.

[0042] Meanwhile, various sensors (e.g., indoor temperature sensor, outdoor temperature sensor, wind speed sensor, sunlight sensor, etc.) that detect the indoor and outdoor environments of the building (10) may be installed in the building (10).

[0043] The HVAC server (100) collects data from various sensors installed in the building (10) as well as various information providers such as an external weather server, analyzes the collected data to generate modeling data for the building (10), and can control at least one of cooling, heating, and ventilation of the building (10) based on the generated modeling data.

[0044]

[0045] FIG. 2 is a block diagram illustrating an HVAC control system according to an embodiment of the present invention. Referring to FIG. 2, the HVAC control system (100) may include all or part of a data collection unit (110), a modeling unit (120), and an HVAC control unit (130).

[0046] The data collection unit (110) can collect various data for modeling the building (10). At this time, the data collection unit (110) can collect various data for modeling the building (10) by linking with at least one of various sensors installed in the building (10), an architectural design specification database such as an architectural design drawing for the building (10), and an external server providing environmental information such as a weather service server.

[0047] Here, the data collected by the data collection unit (110) may include indoor environment data, outdoor environment data, wall data, and indoor object arrangement data.

[0048] Indoor environmental data includes indoor temperature and may further include indoor humidity, window location, number of windows, and window size. Window location may also refer to the window's orientation (e.g., south-facing, east-facing, north-facing, or west-facing).

[0049] Outdoor environmental data includes outdoor temperature and may further include outdoor humidity, outdoor air volume, outdoor wind speed, outdoor sunlight, and radiant energy.

[0050] Wall data may include the material composition of the wall, the thermal conductivity of the material, and the thickness of the material. Here, the material composition of the wall may refer to the type of material that constitutes the wall.

[0051] Indoor object placement data may include indoor placement information of objects such as furniture and curtains, and size information of indoor objects.

[0052] The compartment detail data may include the compartment type, compartment location, compartment size, compartment layout, etc. For example, if the compartment is a room, the compartment location may include the direction of the room (e.g., south-facing, east-facing, north-facing, west-facing), the compartment size may include the three-dimensional size of the room, and the compartment layout may include the number of floors of the room and the room layout type (plate-type, corridor-type).

[0053] The modeling unit (120) can generate modeling data for a building (10) based on data acquired from the data collection unit (110). Here, the modeling unit (120) can include a first modeling unit (121) that estimates a wall temperature gradient for each section of the building (10), a second modeling unit (122) that estimates an indoor surface temperature for each section of the building (10), and a third modeling unit (123) that estimates an indoor temperature gradient inside the building (10).

[0054] Specifically, the first modeling unit (121) can estimate the wall temperature gradient using the first model modeled by learning the correlation between the “collected indoor environment data, outdoor environment data, and wall data” and the “wall temperature gradient” in the data collection unit (110).

[0055] In addition, the second modeling unit (122) can estimate the indoor surface temperature by using the second model modeled by learning the correlation between the “wall temperature gradient and indoor object arrangement data” and the “indoor surface temperature.”

[0056] In addition, the third modeling unit (123) can estimate the indoor temperature gradient by using the third model modeled by learning the correlation between the indoor surface temperature, indoor object arrangement data, and compartment detail data and the “indoor temperature gradient.”

[0057] Here, the first, second, and third models of the modeling unit (120) can be trained using machine learning and deep learning methods. Deep learning refers to a machine learning algorithm that attempts a high level of abstraction through a combination of various nonlinear transformation techniques.

[0058] In addition, the first model, the second model, and the third model of the modeling unit (120) described above can be trained using a supervised learning method. In addition, the artificial neural network model according to the present invention can be trained through unsupervised learning that discovers judgment criteria by learning on its own using learning data without guidance. In addition, the artificial neural network model according to the present invention can be trained through reinforcement learning using feedback on whether the result of the situation judgment according to the learning is correct. In addition, the artificial neural network model according to the present invention can be trained using a learning algorithm including error back-propagation or gradient descent.

[0059]

[0060] The HVAC control unit (130) can control the operation of at least one of a cooling device, a heating device, and a ventilation device based on the estimation result of the modeling unit (120).

[0061] For example, the HVAC control unit (130) can determine the possibility of surface condensation based on at least one of the wall temperature gradient estimated by the first modeling unit (121) and the indoor surface temperature estimated by the second modeling unit (122), and control the operation of at least one of the cooling device, the heating device, and the ventilation device based on the determination result.

[0062] As another example, the HVAC control unit (130) can determine the degree of temperature imbalance based on the indoor temperature gradient estimated by the third modeling unit (121), and control the operation of at least one of the cooling device, heating device, and ventilation device based on the determination result.

[0063]

[0064] FIG. 3 is a flowchart illustrating the operation of an HVAC system according to an embodiment of the present invention. Referring to FIG. 3, a data collection unit (110) may acquire various data for modeling a building (10) (S11), and a modeling unit (120) may perform modeling of the building (10) based on the acquired data. Here, the modeling step may include a process in which the modeling unit (120) estimates a wall temperature gradient (S12), estimates an indoor surface temperature of the building (10) (S13), and estimates an indoor temperature gradient of the building (10) (S14). In addition, the HVAC control unit (130) may include a step (S14) in which the HVAC control unit (130) controls at least one operation of cooling, heating, and ventilation of the building (10) based on the generated modeling data.

[0065] The modeling steps (S12, S13, S14) illustrated in Fig. 3 will be described in more detail later with reference to the drawings.

[0066]

[0067] Figure 4 is a diagram illustrating a conventional mathematical formula-based process for calculating a wall temperature gradient. The wall temperature gradient refers to calculating the temperature change within a wall when the indoor and outdoor temperatures are determined. The wall temperature gradient can be used to prevent moisture buildup during building design and to repair defects such as condensation.

[0068] The process of calculating the conventional wall temperature gradient is described in more detail with reference to Fig. 4 as follows.

[0069] 1) Calculating total thermal conductivity resistance

[0070] First, the thermal conductivity of each material constituting the wall is calculated, and here, the thermal conductivity of each material can be used as a previously calculated value. For example, the previously calculated thermal conductivity for the finishing material is 0.55 W / mk, for the insulation material is 0.036 W / mk, and for the concrete is 2.4 W / mk.

[0071] In this case, the thermal conductivity resistance calculated for each material can be calculated by dividing the thickness of the material by the thermal conductivity, as shown in Table 1 below.

[0072] Distinctive thermal conduction resistance (m) 2 k / W)Outdoor surface 0.043Finishing material 0.1 / 0.55 = 0.18Insulation 0.12 / 0.036 = 3.33Concrete 0.2 / 2.4 = 0.083Indoor surface 0.11Total thermal conductivity resistance 3.746

[0073] 2) Calculation of heat flow per unit area of ​​material layer (Ri) When the outdoor temperature is -10℃ and the indoor temperature is +20℃, the heat flow per unit area of ​​material layer (Ri) can be calculated based on the following mathematical formula 1.

[0074] [Mathematical Formula 1]

[0075] Heat flow per unit area of ​​material layer (Ri) = Indoor / outdoor temperature difference / Total thermal conductivity = 30 / 3.746 = 8.0 W / ㎡

[0076] 3) Calculating temperature changes

[0077] The temperature change calculated for each material can be calculated based on the mathematical expression 2 below, and the results are as shown in Table 2 below.

[0078] [Equation 2]

[0079] Temperature change = Ri x thermal resistance of each material

[0080]

[0081] Classification Temperature change (℃)Temperature change from outside (℃)Outdoor surface 8 x 0.043 = 0.344-9.656Finishing material 8 x 0.18 = 1.44-8.216Insulation 8 x 3.33 = 26.64+18.424Concrete 8 x 0.083 = 0.664+19.088Indoor surface 8 x 0.11 = 0.88+19.968

[0082] In the example of Fig. 4, the concrete surface temperature can be determined to be approximately 19.968℃ based on the conventional method.

[0083] According to the example of the above-described drawing 4, the wall temperature gradient can be calculated using a conventional predetermined methodology, but the wall temperature gradient calculated in this way does not reflect various indoor and outdoor environmental values, so it does not reflect the actual environment in which the wall is installed, and there is also the problem that it is difficult to measure the internal temperature situation with a temperature sensor due to the nature of the wall.

[0084] The wall temperature gradient can vary depending on various indoor and outdoor environmental factors such as indoor temperature, outdoor temperature, wall material composition, material thermal conductivity, and material thickness, as well as the location and number of indoor windows, window size, window position, outdoor wind index, outdoor sunlight, and radiant energy.

[0085] FIG. 5 is a diagram illustrating a wall temperature gradient estimation process of the first modeling unit according to one embodiment of the present invention. Referring to FIG. 5 , since the indoor and outdoor environmental data for the walls of the living room, bedroom, and study differ, even if they are constructed of the same wall material, the wall temperature gradient may vary.

[0086] Accordingly, the first modeling unit (121) according to one embodiment of the present invention can learn the correlation between the “indoor environment data, outdoor environment data, and wall data” collected by the data collection unit (110) and the “wall temperature gradient” to generate the first model (200). In this case, the first model generated by the first modeling unit (121) may be a model that is learned so that the weights are different for each section.

[0087] In addition, the first modeling unit (121) can input indoor environment data, outdoor environment data, and wall data collected from the data collection unit (110) into the learned first model (200) and output a wall temperature gradient estimation value. That is, the first modeling unit (121) can estimate the wall temperature gradient for each of the “master bedroom,” “living room,” and “study,” which are each compartments constituting the building (10).

[0088]

[0089] Meanwhile, the wall of a building (10) to which the HVAC system (100) of the present invention is applied may include a wooden structure using vacuum insulation. This will be described in more detail with reference to FIG. 6.

[0090] Wood has many pores and contains a lot of air in its cells, making it an excellent natural insulator. The insulating performance of wood, a natural insulator, is 8 times better than concrete and 400 times better than steel, so it has been proven to be an effective structure for increasing energy efficiency by using excellent insulating materials such as mineral or glass wool.

[0091] Referring to FIG. 6, the materials constituting the wall of a building (10) to which an HVAC system (100) according to one embodiment of the present invention is applied may be arranged in the following order from the exterior to the interior: exterior material, air layer, vacuum insulation, air layer, and interior material. In this case, the vacuum insulation may be supported by structural timber.

[0092] Referring to Figure 6, due to the higher insulation performance of the vacuum insulation compared to the existing insulation, the temperature gradient in the vacuum insulation is formed as a steeper slope compared to the insulation.

[0093] Due to these characteristic differences, the first modeling unit (121) according to one embodiment of the present invention can be trained to provide higher performance in estimating the temperature gradient of a wall including a vacuum insulation material.

[0094]

[0095] FIG. 7 is a drawing for explaining the operation of the second modeling unit (122) according to one embodiment of the present invention.

[0096] According to the conventional wall temperature gradient calculation process mentioned in the above-described Figure 4, the indoor surface temperature can be calculated.

[0097] However, although the indoor surface temperature can be calculated using a conventional, predetermined methodology, the indoor surface temperature calculated in this way cannot guarantee the accuracy of the calculated indoor surface temperature because it is calculated based on the temperature gradient of the wall calculated using the predetermined methodology (i.e., the wall temperature gradient calculated without reflecting various indoor and outdoor environmental values).

[0098] Furthermore, the indoor surface temperature calculated using conventional, predetermined methodologies does not reflect the arrangement of indoor furniture, curtains, etc., and therefore cannot guarantee the accuracy of the calculated indoor surface temperature. In other words, if curtains or built-in closets are placed on the indoor wall, the layer of static air thickens and acts as a thermal resistance, which affects the indoor surface temperature.

[0099] If multiple temperature sensors are installed near the wall to measure the indoor surface temperature, accurate values ​​can be obtained, but installing temperature sensors on every wall is not an appropriate solution because it is not appropriate in terms of unit cost or economy.

[0100] Accordingly, the second modeling unit (122) according to one embodiment of the present invention can learn the correlation between “wall temperature gradient and indoor object placement data” and “indoor surface temperature” to generate a second model (300). In this case, the second model generated by the second modeling unit (122) may be a model that is learned so that weights differ for each section.

[0101] And, the second modeling unit (122) can input the wall temperature gradient estimated through the first model (200) of the first modeling unit (121) and the indoor object arrangement data collected from the data collection unit (110) into the learned second model (300) and output an indoor surface temperature estimation value. Referring to Fig. 6, the second modeling unit (122) can estimate the indoor surface temperature for each of the “master bedroom,” “living room,” and “study” by using the furniture arrangement or curtain installation status and the temperature gradient of the wall constituting the corresponding section.

[0102]

[0103] Figure 8 is a drawing for explaining the operation of the third modeling unit (123) according to one embodiment of the present invention.

[0104] Building (10) If temperature sensors are installed at various locations inside the building to measure the temperature, the indoor temperature gradient can be estimated, but since many sensors are required for accurate estimation, this is not appropriate in terms of unit cost or economy.

[0105] Accordingly, the third modeling unit (123) according to one embodiment of the present invention can estimate the indoor temperature gradient using the third model modeled by learning the correlation between the indoor surface temperature, indoor object arrangement data, and compartment detail data and the indoor temperature gradient.

[0106] More specifically, referring to FIG. 8(a), the third model may be composed of a 3-1 model (410) modeled by learning the correlation between “indoor object arrangement data and compartment detail data” and “indoor air flow”, and a 3-2 model (420) modeled by learning the correlation between “indoor surface temperature and indoor air flow” and “indoor temperature gradient”.

[0107] Accordingly, the third modeling unit (123) can input the indoor surface temperature estimated by the second model (300) of the second modeling unit (121) and the indoor object arrangement data and section detail data collected by the data collection unit (110) into the learned third model (410, 420) and output an indoor temperature gradient estimation value.

[0108] Here, the indoor temperature gradient estimated through the third model (410, 420) may be a temperature gradient value for a three-dimensional indoor space.

[0109] Meanwhile, the third modeling unit (123) can generate an indoor temperature gradient map based on the indoor temperature gradient estimation value, as shown in Fig. 8(b). Here, the indoor temperature gradient map generated by the third modeling unit (123) can be provided to a user terminal device.

[0110]

[0111] Figures 9 and 10 are flowcharts showing in more detail an HVAC control method based on modeling results according to one embodiment of the present invention.

[0112] FIG. 9 is a flowchart illustrating an HVAC control method based on an estimation result of at least one of a first modeling unit and a second modeling unit according to an embodiment of the present invention.

[0113] Condensation occurs when water droplets form on walls, ceilings, or other surfaces due to water vapor in the air. Condensation can be categorized into surface condensation and interstitial condensation. Surface condensation occurs on surfaces such as walls, windows, ceilings, and floors. Interstitial condensation occurs when the surface temperature is below the dew point. This type of surface condensation creates conditions that favor mold growth, significantly harming the indoor environment.

[0114] Referring to FIG. 9, the HVAC control unit (130) can calculate the indoor dew point temperature (S110). The dew point temperature refers to the temperature at which water vapor in the air becomes saturated and dew forms when the temperature of the air is lowered at a constant pressure. The HVAC control unit (130) can calculate the dew point temperature using the indoor temperature, indoor humidity, etc. collected by the data collection unit (110).

[0115] And, the HVAC control unit (130) can obtain at least one of the wall surface temperature estimated from the wall temperature gradient estimated from the first modeling unit (121) and the indoor surface temperature estimated from the second modeling unit (122) (S120).

[0116] In addition, the HVAC control unit (130) can determine the possibility of surface condensation by comparing at least one of the wall surface temperature and the indoor surface temperature with the dew point temperature (S130) (S140). Specifically, the HVAC control unit (130) can determine that there is a possibility of surface condensation if at least one of the wall surface temperature and the indoor surface temperature is lower than the dew point temperature. In addition, the HVAC control unit (130) can determine that there is no possibility of surface condensation if both the wall surface temperature and the indoor surface temperature are lower than the dew point temperature.

[0117] Here, the possibility of surface condensation can be judged on a compartment-by-compartment basis.

[0118] If it is determined that there is no possibility of surface condensation (S140: No), the temperature comparison process in step S130 can be repeated. If at least one of the heating device, the cooling device, and the ventilation device was operating in a state where there is no possibility of surface condensation, the HVAC control unit (130) can maintain the existing setting value of at least one of the heating, cooling, and ventilation without changing it. That is, the HVAC control unit (130) can maintain the existing setting value (e.g., temperature, ventilation amount, heating and cooling intensity, etc.) as is.

[0119] If it is determined that there is a possibility of surface condensation (S140:Yes), the HVAC control unit (130) can operate the ventilation device to remove moist air in the room (S150).

[0120] In addition, the HVAC control unit (130) can operate a heating device to raise the indoor temperature above the dew point temperature (S160). Here, the heating device can be implemented as at least one of a floor heating method that heats by dividing the area by installing hot water pipes or heating wires on the floor, and an air heating method that heats using a radiator.

[0121] The HVAC control unit (130) can control to operate the floor heating near the wall surface among the plurality of floor areas divided into multiple parts to increase the temperature near the wall surface. In addition, the HVAC control unit (130) can control to release the heated air of the radiator toward the wall surface to increase the temperature near the wall surface. In this case, the HVAC control unit (130) can control to maintain the heating time for a long time at a low temperature preset temperature (for example, a value higher than the dew point temperature but lower than the limit temperature that determines human comfort) to increase the surface condensation removal effect.

[0122] According to the present invention, by controlling at least one of heating and ventilation based on at least one estimated value of the wall temperature gradient and the indoor surface temperature of the modeling unit (120), the possibility of indoor surface condensation and mold occurrence can be reduced, thereby increasing the comfort level of the indoor environment of a building.

[0123]

[0124] FIG. 10 is a flowchart illustrating an HVAC control method based on the estimation results of the third modeling unit according to one embodiment of the present invention.

[0125] Indoor temperature gradient represents the temperature distribution in the indoor space of a building. Although a uniform temperature distribution throughout the entire indoor space is optimal in terms of human comfort and energy efficiency, the temperature distribution throughout the entire indoor space is generally not uniform.

[0126] Referring to FIG. 10, the HVAC control unit (130) can divide the indoor temperature gradient estimated by the third modeling unit (123) into multiple regions (S210). Specifically, the indoor temperature gradient estimated by the third modeling unit (123) may be a three-dimensional temperature gradient, and the three dimensions may be divided into multiple regions to divide the indoor temperature gradient into multiple regions. Here, the region may be a unit square plane or a unit square space. In addition, a temperature value may be assigned to each of the multiple regions.

[0127] The HVAC control unit (130) can determine the degree of temperature imbalance based on the temperature differences between multiple areas (S220). Specifically, the HVAC control unit (130) can use the indoor temperature gradient estimated by the third modeling unit (123) to generate a temperature difference map for each of the multiple areas constituting the indoor space, and can determine the degree of temperature imbalance described above based on this map.

[0128] Here, the degree of temperature imbalance may not be the temperature difference value, but rather the temperature imbalance level determined based on the range within which the temperature difference falls.

[0129] If the temperature imbalance is less than the preset value (S230: No), the process of determining the temperature imbalance may be repeated in step S220. If at least one of the heating device, the cooling device, and the ventilation device was operating while the temperature imbalance was less than the preset value, the HVAC control unit (130) may maintain the existing setting value of at least one of the heating, cooling, and ventilation without changing it. That is, the HVAC control unit (130) may maintain the existing setting value (e.g., temperature, ventilation amount, heating / cooling intensity, etc.) as is.

[0130] If the degree of temperature imbalance is greater than the preset value (S230: Yes), the degree of temperature imbalance in the vertical direction and the degree of temperature imbalance in the horizontal direction can be compared (S240).

[0131] If the vertical temperature imbalance is greater than the horizontal temperature imbalance (S250: Yes), the HVAC control unit (130) can control the ventilation device to circulate air in the vertical direction (S260). That is, since warm air tends to gather upward and cold air tends to gather downward, the HVAC control unit (130) can circulate air by forcibly creating an air flow.

[0132] If the horizontal temperature imbalance is greater than the vertical temperature imbalance (S250: No), the HVAC control unit (130) can control at least one of the cooling device and the heating device to make the horizontal temperature uniform (S270). For example, the heating device or the cooling device can be implemented in at least one of a method of dividing the area by installing hot (or cold) water pipes or heating wires on the floor to provide heating and cooling, and a method of using an air conditioner to provide heating and cooling.

[0133] The HVAC control unit (130) can control the heating and cooling operation based on the temperature difference among multiple floor areas divided into multiple sections to make the horizontal temperature uniform. Alternatively, the HVAC control unit (130) can control the air conditioner to make the temperature uniform among multiple areas constituting the indoor space.

[0134] Meanwhile, when the horizontal temperature imbalance is the same as the vertical temperature imbalance, the HVAC control unit (130) can increase energy efficiency by first operating the ventilation device to create forced air flow and then operating the cooling and heating devices.

[0135] According to the present invention, by controlling at least one of cooling, heating, and ventilation so that the temperature is uniformly distributed throughout the entire indoor space based on the indoor temperature gradient estimation value of the modeling unit (120), both the comfort level and energy efficiency of the indoor space of a building can be achieved under optimal conditions.

[0136]

[0137] Meanwhile, the various embodiments described herein may be implemented in a recording medium readable by a computer or similar device, for example, using software, hardware, or a combination thereof.

[0138] In terms of hardware implementation, the embodiments described herein can be implemented using at least one of ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), processors, controllers, micro-controllers, microprocessors, and other electrical units for performing functions. In some cases, the embodiments described herein can be implemented as a control module itself.

[0139] In a software implementation, the procedures and functions described herein, as well as other embodiments, may be implemented as separate software modules. Each of these software modules may perform one or more of the functions and operations described herein. The software code may be implemented as a software application written in a suitable programming language. The software code may be stored in a memory module and executed by a control module.

[0140] The above description is merely an example of the technical idea of ​​the present invention, and those skilled in the art will appreciate that various modifications, changes, and substitutions can be made without departing from the essential characteristics of the present invention.

[0141] Accordingly, the embodiments disclosed in the present invention and the accompanying drawings are intended to illustrate, rather than limit, the technical concept of the present invention, and the scope of the technical concept of the present invention is not limited by these embodiments and the accompanying drawings. The protection scope of the present invention should be interpreted by the following claims, and all technical concepts within the scope equivalent thereto should be interpreted as being included within the scope of the rights of the present invention.

Claims

1. In a method for controlling HVAC (heating, ventilating, and air conditioning) of a building, A step of acquiring indoor environment data, outdoor environment data and wall data; A step of generating modeling data corresponding to the building based on the acquired data; and A step of controlling the HVAC of the building based on the generated modeling data; The step of generating the above modeling data is: A control method characterized by including a step of inputting the acquired data into a first model to estimate the wall temperature gradient for each section of the building.

2. In paragraph 1, A step of acquiring the indoor object placement data; and A control method further comprising a step of inputting the estimated wall temperature gradient and the acquired indoor object arrangement data into a second model to estimate the indoor surface temperature for each section.

3. In paragraph 2, The steps of controlling the above HVAC are: A control method characterized by comprising a step of comparing the dew point temperature of the indoor space with at least one of the wall surface temperature obtained based on the estimated wall temperature gradient and the indoor surface temperature; and determining the possibility of surface condensation occurring in the compartment.

4. In paragraph 3, The steps of controlling the above HVAC are: A control method characterized by comprising a step of controlling operation of at least one of a ventilation device and a heating device when it is determined that there is a possibility of surface condensation occurring.

5. In paragraph 2, A control method comprising: a step of estimating an indoor temperature gradient of the building by inputting the indoor surface temperature estimated by the second model, the indoor object arrangement data, and the section detail data into a third model.

6. In paragraph 5, The steps of controlling the above HVAC are: A step of dividing the above estimated indoor temperature gradient into multiple regions; and A control method characterized by comprising a step of determining the degree of temperature imbalance based on the temperature difference of the plurality of regions distinguished above.

7. In paragraph 6, The steps of controlling the above HVAC are: A step of comparing the vertical temperature imbalance degree and the horizontal temperature imbalance degree when the above temperature imbalance information is greater than a preset value; A step of controlling a ventilation device when the vertical temperature imbalance is greater than the horizontal temperature imbalance; and A control method characterized by comprising a step of controlling at least one of a cooling device and a heating device when the vertical temperature imbalance is smaller than the horizontal temperature imbalance.

8. In the HVAC (heating, ventilating, and air conditioning) control system of a building, A data collection unit that acquires indoor environment data, outdoor environment data, and wall data; A modeling unit that generates modeling data corresponding to the building based on the acquired data; and An HVAC control unit that controls the HVAC of the building based on the generated modeling data; A control system characterized in that the above modeling unit includes a first modeling unit that inputs the acquired data into a first model to estimate the wall temperature gradient for each section of the building.

9. In paragraph 8, The above data collection unit obtains the indoor object placement data, The above modeling section, A control system characterized by including a second modeling unit that inputs the estimated wall temperature gradient and the acquired indoor object arrangement data into a second model to estimate the indoor surface temperature for each section.

10. In paragraph 9, The above modeling section, A control system characterized by including a third modeling unit that estimates the indoor temperature gradient of the building by inputting the indoor surface temperature estimated by the second model, the indoor object arrangement data, and the section detail data into a third model.

11. A computer-readable recording medium having recorded thereon a program for executing a method for controlling HVAC (heating, ventilating, and air conditioning) of a building, The above control method is, A step of acquiring indoor environment data, outdoor environment data and wall data; A step of generating modeling data corresponding to the building based on the acquired data; and A step of controlling the HVAC of the building based on the generated modeling data; The step of generating the above modeling data is: A computer-readable recording medium characterized by including a step of inputting the acquired data into a first model to estimate the wall temperature gradient for each section of the building.

12. In paragraph 11, A step of acquiring the indoor object placement data; and A computer-readable recording medium further comprising a step of inputting the estimated wall temperature gradient and the acquired indoor object arrangement data into a second model to estimate the indoor surface temperature for each section.

13. In paragraph 12, The steps of controlling the above HVAC are: A computer-readable recording medium characterized by comprising a step of comparing the dew point temperature of the indoor space with at least one of the wall surface temperature obtained based on the estimated wall temperature gradient and the indoor surface temperature; and determining the possibility of surface condensation occurring in the compartment.

14. In paragraph 13, The steps of controlling the above HVAC are: A computer-readable recording medium characterized by comprising a step of controlling operation of at least one of a ventilation device and a heating device when it is determined that there is a possibility of surface condensation occurring.

15. In paragraph 12, A computer-readable recording medium comprising a step of estimating an indoor temperature gradient of the building by inputting the indoor surface temperature estimated by the second model, the indoor object arrangement data, and the section detail data into a third model.

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