KR20170079393A - User-factor applied building energy modeling system and method - Google Patents

User-factor applied building energy modeling system and method Download PDF

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KR20170079393A
KR20170079393A KR1020150189897A KR20150189897A KR20170079393A KR 20170079393 A KR20170079393 A KR 20170079393A KR 1020150189897 A KR1020150189897 A KR 1020150189897A KR 20150189897 A KR20150189897 A KR 20150189897A KR 20170079393 A KR20170079393 A KR 20170079393A
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user element
user
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윤근영
송지수
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경희대학교 산학협력단
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Abstract

A building energy modeling system and method with user elements reflected. A user element selection module for receiving and selecting a schedule for a user element and a user element with respect to an input element of the building energy model; A user element boundary condition selection module for selecting a user element boundary condition composed of an input maximum value and an input minimum value for a user element selected by the user element selection module; A user element probability distribution generating module for generating a probability distribution for the user element boundary condition and reflecting the generated probability distribution to the building energy model; A Latin hypercube sampling module based on a user element for executing a simulation of a building energy model by performing Latin hypercube sampling on a building energy model reflected by the user element probability distribution generation module; A building energy model selection module for selecting a high building energy model satisfying the accuracy and reliability of a predetermined criterion among the building energy models in comparison with the result of the simulation executed in the user element-based Latin hypercube sampling module and the actual energy usage do.

Description

TECHNICAL FIELD The present invention relates to a building energy modeling system and method,

The present invention relates to a building energy modeling system and method, and more particularly, to a building energy modeling system and method in which user elements are reflected.

Registered Patent Publication No. 10-1419607 and Registered Patent Publication No. 10-1549349 disclose a building energy modeling system.

Building energy modeling is the simulation and verification of building energy by analyzing energy distribution and flow of buildings. Various ideas have been developed and applied to predict building energy more accurately.

In the case of Patent Registration No. 10-1419607, a method of modeling by layer or by zone is taken to improve the accuracy of energy simulation.

Korean Patent Publication No. 10-1549349 is constructed to enhance the accuracy of data filtering by applying the RANSAC technique in building a building energy model.

In order to improve the accuracy of building energy modeling, various ideas for processes are being developed at each stage of the process. However, despite the efforts to improve accuracy, the actual building energy distribution and flow are different from the simulation results of building energy modeling, and the accuracy is somewhat lacking.

The existing building energy modeling is mainly focused on the calculation methods such as the Gaussian model, or it is configured to focus on the energy of the heating / heating equipment in the building and the material characteristics of the building material constituting the building . Simulation is carried out considering the thermal conductivity, thermal characteristics, size and arrangement of building materials. In addition, simulation is carried out with careful consideration of the heat flow in the space of the door or window arrangement.

Nevertheless, existing building energy modeling is in error with actual building energy use, distribution and flow.

This error is due to the fact that it is difficult to define precisely these difficulties as well as the difficulties of building energy modeling itself, which requires consideration of thousands of factors.

In particular, existing building energy modeling does not take into account changes in the performance of the building envelope that occur after completion of the building, or it is confined to modeling of simplified heating and cooling equipment, .

Although such use factors have a considerable effect on the difference between the building energy model and the actual building energy consumption, the building energy modeling technique that reflects the usage factors has not been introduced or used anywhere.

Patent Registration No. 10-1419607 Patent Registration No. 10-1549349

An object of the present invention is to provide a building energy modeling system in which user elements are reflected.

Another object of the present invention is to provide a building energy modeling method in which a user element is reflected.

The building energy modeling system reflecting the user element according to the object of the present invention may include a user element selection module for receiving and selecting a schedule for a user element and a user element for an input element of a building energy model; A user element boundary condition selection module for selecting a user element boundary condition composed of an input maximum value and an input minimum value for a user element selected by the user element selection module; A user element probability distribution generating module for generating a probability distribution for the user element boundary condition and reflecting the generated probability distribution to the building energy model; A Latin hypercube sampling module based on a user element for executing a simulation of a building energy model by performing Latin hypercube sampling on a building energy model reflected by the user element probability distribution generation module; A building energy model selection module for selecting a high building energy model satisfying the accuracy and reliability of a predetermined criterion among the building energy models in comparison with a result of simulation performed in the user-element-based Latin hypercube sampling module and actual energy consumption .

At this time, the user element selection module may be configured to select a user element based on at least one of a weather condition and a weather condition, a building energy modeling, a thermal zoning, a skin composition, a building use schedule, a material of a structure, a thermal equilibrium equation, a heating element, a heating value, a heating value and a heating value for at least one of an input element, a fan, a coil, a humidifier, a pump, a boiler and a freezer, And may be configured to receive and schedule the corresponding schedule.

The user element selection module selects the input maximum value and the input minimum value for each of the user elements constituted by the set temperature, the heating value of the apparatus, the heating value of the heating and the heating value of the human body in the building energy model, And can be configured to derive the ratio of the radiation heat emission amount and the radiation amount to the human body heat generation amount.

Meanwhile, the user element probability distribution generating module generates and distributes probability distributions for the user elements of the building energy model using the discrete distribution, the uniform distribution, the normal distribution, and the triangular distribution for the selected user element boundary condition Lt; / RTI >

On the other hand, the building energy model selection module uses the statistical indices of NMBE (Normalized Mean Biased Error) and CVRMSE (CVRMSE) to calculate the building energy model satisfying the accuracy and reliability And may be configured to select a building energy model.

If the NMBE value is within ± 6% and the CVRMSE value is within ± 18%, the building energy model selection module determines that the corresponding building energy model is corrected by meeting the accuracy and reliability of the predetermined criteria .

In another aspect of the present invention, there is provided a method for modeling building energy, the method comprising the steps of: selecting and receiving a schedule for a user element and a user element for an input element of a building energy model; Selecting a user element boundary condition that the user element boundary condition selection module is made up of an input maximum value and an input minimum value for a user element selected by the user element selection module; The user element probability distribution generating module generates a probability distribution for the user element boundary condition and reflects the probability distribution on the building energy model; Executing a simulation of a building energy model by performing Latin hypercube sampling on a building energy model reflected by the user element probability distribution generating module by the user element-based Latin hypercube sampling module; A building energy model selection module selects a high building energy model satisfying the accuracy and reliability of a predetermined criterion among the building energy models in comparison with a result of simulation performed in the user element based Latin hypercube sampling module and the actual energy usage . ≪ / RTI >

At this time, the step of selecting and receiving a schedule for the user element and the user element with respect to the input element of the building energy model may include at least one of a climate and a site condition, a building energy modeling, a thermal zoning, At least one of a building use schedule, a material of a structure, a thermal equilibrium equation, an underground temperature, natural light, natural ventilation, instrument control, a fan, a coil, a humidifier, a pump, a boiler, A user element including the set temperature, the heating value of the apparatus, the heating value of the light, and the calorific value of the body and the schedule for the user element may be inputted and selected for the above input elements.

The step of selecting and receiving a schedule for the user element and the user element with respect to the input element of the building energy model includes the steps of: When the elements are reflected in the building energy model, the input maximum value and the input minimum value for each can be selected, and it can be configured to derive the ratio of the radiation amount of the apparatus, the calorific value of the light, and the calorific value of the human body.

Meanwhile, the step of generating the user element probability distribution generating module and generating the probability distribution for the user element boundary condition and reflecting the same on the building energy model may include discrete distribution, uniform distribution, normal distribution, And generate and reflect a probability distribution of the user elements of the building energy model using a triangular distribution.

On the other hand, when the building energy model selection module compares the actual energy usage with the result of the simulation performed in the user-element-based Latin hypercube sampling module, a high building energy model satisfying the accuracy and reliability of a predetermined standard among the building energy models A building energy model satisfying the accuracy and reliability of a predetermined standard among the building energy models is selected using a statistical index of NMBE (Normalized Mean Biased Error) and CVRMSE (Coefficient of Variance of Root Mean Square Error) .

At this time, the building energy model selection module compares the result of the simulation executed in the user-element-based Latin hypercube sampling module with the actual energy usage, and calculates a high building energy model satisfying the accuracy and reliability of a predetermined standard among the building energy models The selecting step may be configured to determine that the corresponding building energy model is corrected by satisfying the accuracy and reliability of the predetermined standard when the NMBE value is within ± 6% and the CVRMSE value is within ± 18% .

According to the building energy modeling system and method in which the above-described user elements are reflected, a user element is added to the existing building energy model to simulate and predict the building energy by reflecting the usage factor of the building, To obtain more accurate and reliable simulation and prediction results.

In particular, unlike the conventional method, by inputting a schedule for the user's body temperature, setting the temperature of the cold device, and calorific value of the lighting, and reflecting this in the building energy modeling, There is an effect that can be performed.

1 is a schematic diagram of a building energy modeling system in which a user element according to the present invention is reflected.
2 is a block diagram of a building energy modeling system in which user elements are reflected according to an embodiment of the present invention.
FIG. 3 is a graph illustrating a correction result of a building energy modeling reflecting a user element according to an exemplary embodiment of the present invention.
FIG. 4 is a graph illustrating a result of verification of building energy modeling in which a user element is reflected according to an exemplary embodiment of the present invention.
FIG. 5 is a flowchart illustrating a method of modeling a building energy using a user element according to an exemplary embodiment of the present invention. Referring to FIG.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail to the concrete inventive concept. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention. Like reference numerals are used for like elements in describing each drawing.

The terms first, second, A, B, etc. may be used to describe various elements, but the elements should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

1 is a schematic diagram of a building energy modeling system in which a user element according to the present invention is reflected.

Referring to FIG. 1, a process of a building energy modeling system 100 with a user element according to the present invention is schematically described.

First, a building energy modeling system 100 in which user elements are reflected utilizes a building energy model reflecting various building energy model elements according to the present invention.

These building energy models make use of various calculation methods and various building energy model elements. You can also use existing building energy models.

The building energy modeling system 100 in which the user element is reflected has such a feature that the building energy model element further includes a user element as well as an element related to the building itself.

The building energy modeling system 100 in which the user elements are reflected is a user element that dynamically reflects the set temperature of the heating and heating equipment, the heating value of the device, the heating value of the lighting device and the heating value of the human body in the building, To predict and predict.

Unlike the existing model, it reflects the user factors, so it can reduce the error range of the existing building energy model and can be predicted similar to actual building energy.

The building energy modeling system 100 in which the user elements are reflected can analyze the user elements, define the boundary conditions of the inputs, input the schedule of the user elements in advance, and accurately and reliably predict the building energy model over time.

Here, the building energy modeling system 100 in which the user elements are reflected generates a probability distribution reflecting user elements and performs Latin hypercube sampling. After reflecting these user factors for various building energy models, each building energy model is configured to select and use the corresponding building energy model when it is within an error range as compared to the actual building energy model.

The building energy modeling system 100 that reflects the user elements can be highly accurate predicted by reflecting the two user factors of temperature setting and internal heat generation.

2 is a block diagram of a building energy modeling system in which user elements are reflected according to an embodiment of the present invention.

2, a building energy modeling system 100 in which a user element is reflected according to an exemplary embodiment of the present invention includes a user element selection module 110, a user element boundary condition selection module 120, a user element probability distribution generation module A user-element-based Latin hyper-cube sampling module 140, and a building energy model selection module 150. In this case,

Hereinafter, the detailed configuration will be described.

The user element selection module 110 may be configured to receive a schedule for a user element and a user element with respect to an input element of the building energy model.

Here, the user element refers to an element that is dynamically expressed by a user's activity rather than the building itself, such as a heating value of a human body in a building, a set temperature of a heating / heating device, a boiler, etc., a heating value of such a device, .

In the present invention, only the building energy model elements such as the building itself or the building itself are considered. In the present invention, the existing building energy model is corrected by reflecting the building energy model factor by the user using the building or the user's activity.

The user elements are more specific in terms of climate and site conditions, building energy modeling, thermal zoning, envelope construction, building use schedules, structural materials, thermal equilibrium equations, underground temperature, natural light, natural ventilation, The heating value of the device, the heating value of the heating, and the heating value of the body with respect to at least one of input elements of the fan, the coil, the humidifier, the pump, the boiler and the freezer.

The user element selection module 110 may be configured to receive not only the user elements but also the schedules of the respective user elements. That is, it can be configured to receive, in advance, operating schedules of air conditioners and the like, schedules that the user will be in the building according to entrance and exit of the user, and the like in advance.

The user element selection module 110 may be configured to receive the schedule of the user element in real time according to the dynamic change of the current user element.

The user element boundary condition selection module 120 may be configured to select a user boundary condition for a user element selected by the user element selection module 110.

The user element boundary condition selection module 120 may be configured to receive and select the input maximum value and the input minimum value of each user element as a user boundary condition.

The user element boundary condition selection module 120 selects the input maximum value and the input minimum value for each of the user elements constituted by the set temperature, the heating value of the device, the heating value of heating, and the heating value of the human body in the building energy model, , And the ratio of radiation emission amount to the amount of light emission of the human body and the calorific value of the human body.

This user boundary condition can be used to calculate the probability distribution.

The user element probability distribution generation module 130 may be configured to generate a probability distribution for the user element boundary condition and reflect the same on the building energy model.

The user element-based Latin hypercube sampling module 140 is configured to perform Latin hypercube sampling on the building energy model reflected by the user element probability distribution generation module 130 to execute a simulation of the building energy model Lt; / RTI >

Programs such as EnergyPlus, DOE, Trnsys, and ESP-r can be used for simulation.

Specifically, the user element probability distribution generating module 140 calculates a discrete distribution, a uniform distribution, a normal distribution, and a triangle distribution of the user element boundary condition, and generates a probability distribution for a user element of the building energy model As shown in FIG.

The building energy model selection module 150 selects a building energy model having high accuracy and reliability for various building energy models that are corrected by reflecting user factors.

For this, the building energy model selection module 150 may be configured to compare the actual energy usage with the results of the simulation performed in the user element-based Latin hypercube sampling module 140.

The building energy model selection module 150 may be configured to select a high building energy model that satisfies the accuracy and reliability of a predetermined criterion among the building energy models that are corrected by reflecting the user factors. Here, the predetermined criterion means an allowable error range.

The building energy model selection module 150 can be configured to select a building energy model using statistical indicators of NMBE (Normalized Mean Biased Error) and CVRMSE (Coefficient of Variance of Root Mean Square Error).

At this time, the building energy model selection module 150 may be configured to select a building energy model having an accuracy and reliability within an error range from among the corrected building energy models.

Illustratively, the building energy model selection module 150 may be configured such that the building energy model is calibrated to meet the accuracy and reliability of the predetermined criteria when the NMBE value is within ± 6% and the CVRMSE value is within ± 18% And select these building energy models.

FIG. 3 is a graph illustrating a correction result of a building energy modeling reflecting a user element according to an exemplary embodiment of the present invention.

Referring to FIG. 3, the result of reflecting user factors in building energy modeling using NMBE and CVRMSE is shown. In other words, it shows the result of calibrating the user factor in building energy modeling. NMBE has an accuracy of ± 5%, and CVRMSE has an accuracy of ± 10%.

Table 1 shows the results before and after applying this technology.

Figure pat00001

FIG. 4 is a graph illustrating a result of verification of building energy modeling in which a user element is reflected according to an exemplary embodiment of the present invention.

Referring to FIG. 4, the difference between the building energy model reflecting the user element and the actual building energy consumption is shown on a day-by-day basis. The estimated values and actual measured values show an error range of about 20-30 kWh.

FIG. 5 is a flowchart illustrating a method of modeling a building energy using a user element according to an exemplary embodiment of the present invention. Referring to FIG.

Referring to FIG. 5, first, the user element selection module 110 receives and inputs a schedule for a user element and a user element with respect to an input element of the building energy model (S101).

Herein, the user element selection module 110 is a module for selecting a user element, which is a module for selecting a user element, such as weather and site conditions, building energy modeling, thermal zoning, envelope composition, building use schedule, the user element and the user element constituted by the set temperature, the heating value of the device, the heating value of the heating and the heating value of the body for at least one of the input elements of the fan, the coil, the humidifier, the pump, the boiler, And may be configured to receive and schedule the corresponding schedule.

More specifically, when the user element selection module 110 reflects the user elements constituted by the set temperature, the heating value of the device, the heating value of the heating, and the heating value of the user in the building energy model, the input maximum value and the input minimum value are selected , The device calorific value, the calorific value of the light, and the ratio of the calorific value to the calorific value of the human body.

Next, the user element boundary condition selection module 120 selects a user element boundary condition composed of the input maximum value and the input minimum value for the user element selected by the user element selection module 110 (S102).

Next, the user element probability distribution generating module 130 generates a probability distribution for the user element boundary condition and reflects the distribution to the building energy model (S103).

At this time, the probability distribution of the user element of the building energy model can be generated and reflected by using the discrete distribution, uniform distribution, normal distribution, and triangular distribution of the user element boundary conditions.

Next, the user element-based Latin hypercube sampling module 140 performs Latin hypercube sampling on the building energy model reflected by the user element probability distribution generation module 130 to execute a simulation of the building energy model ( S104).

Next, the building energy model selection module 150 compares the actual energy usage with the result of the simulation performed in the user element-based Latin hypercube sampling module 140, The building energy model is selected (S105).

Here, a statistical index of NMBE (Normalized Mean Biased Error) and CVRMSE (Coefficient of Variance of Root Mean Square Error) may be used to select a building energy model satisfying the accuracy and reliability of a predetermined standard among the building energy models .

Specifically, when the value of NMBE is within ± 6% and the value of CVRMSE is within ± 18%, the accuracy and reliability of the predetermined standard can be satisfied and the corresponding building energy model can be determined to be corrected.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention as defined in the following claims. There will be.

110: User element selection module
120: User element boundary condition selection module
130: User element probability distribution generation module
140: User-element based Latin hypercube sampling module
150: building energy model selection module

Claims (12)

A user element selection module for receiving and selecting a schedule for a user element and a user element with respect to an input element of the building energy model;
A user element boundary condition selection module for selecting a user element boundary condition composed of an input maximum value and an input minimum value for a user element selected by the user element selection module;
A user element probability distribution generating module for generating a probability distribution for the user element boundary condition and reflecting the generated probability distribution to the building energy model;
A Latin hypercube sampling module based on a user element for executing a simulation of a building energy model by performing Latin hypercube sampling on a building energy model reflected by the user element probability distribution generation module;
A building energy model selection module for selecting a high building energy model satisfying the accuracy and reliability of a predetermined criterion among the building energy models in comparison with a result of simulation performed in the user-element-based Latin hypercube sampling module and actual energy usage A building energy modeling system that reflects user factors. The apparatus of claim 1, wherein the user element selection module comprises:
Fans, Coils, Humidifiers, Climate and Earth Conditions, Building Energy Modeling, Thermal Zoning, Shell Construction, Building Use Schedules, Structural Materials, Thermal Equilibrium Equations, Underground Temperature, A user element constituted by a set temperature, an apparatus calorific value, a calorific value of a heating value, and a calorific value of a human body and a schedule for the user element are inputted and selected for at least one input element among a pump, a pump, a boiler and a refrigerator A building energy modeling system that reflects the user elements. [3] The apparatus of claim 2,
When the user elements constituted by the set temperature, the heating value of the apparatus, the heating value of the heating, and the heating value of the user are reflected in the building energy model, the input maximum value and the input minimum value are selected, And a ratio of the amount of the emission to the amount of the emission of the user. The apparatus of claim 1, wherein the user element probability distribution generating module comprises:
And generating and reflecting a probability distribution for a user element of the building energy model using the discrete distribution, the uniform distribution, the normal distribution, and the triangular distribution for the selected user element boundary condition. Energy modeling system. The building energy model selection module according to claim 1,
A building energy model that satisfies the accuracy and reliability of a predetermined criterion among the building energy models is selected using statistical indices of NMBE (Normalized Mean Biased Error) and CVRMSE (Coefficient of Variance of Root Mean Square Error) A building energy modeling system that reflects user factors. 6. The method of claim 5, wherein the building energy model selection module comprises:
Wherein when the value of the NMBE is within ± 6% and the value of the CVRMSE is within ± 18%, it is determined that the corresponding building energy model is corrected by satisfying the accuracy and reliability of the predetermined criterion. Reflected Building Energy Modeling System. Selecting and receiving a schedule for a user element and a user element for an input element of a building energy model;
Selecting a user element boundary condition that the user element boundary condition selection module is made up of an input maximum value and an input minimum value for a user element selected by the user element selection module;
The user element probability distribution generating module generates a probability distribution for the user element boundary condition and reflects the probability distribution on the building energy model;
Executing a simulation of a building energy model by performing Latin hypercube sampling on a building energy model reflected by the user element probability distribution generating module by the user element-based Latin hypercube sampling module;
A building energy model selection module selects a high building energy model satisfying the accuracy and reliability of a predetermined criterion among the building energy models in comparison with a result of simulation performed in the user element based Latin hypercube sampling module and the actual energy usage A method of modeling a building energy that reflects a user element comprising: The method of claim 1, wherein the user element selection module receives and selects a schedule for a user element and a user element with respect to an input element of the building energy model,
Fans, Coils, Humidifiers, Climate and Earth Conditions, Building Energy Modeling, Thermal Zoning, Shell Construction, Building Use Schedules, Structural Materials, Thermal Equilibrium Equations, Underground Temperature, A user element constituted by a set temperature, an apparatus calorific value, a calorific value of a heating value, and a calorific value of a human body and a schedule for the user element are inputted and selected for at least one input element among a pump, a pump, a boiler and a refrigerator Wherein the building element modeling method is based on a user element. 9. The method of claim 8, wherein the user element selection module selects and receives a schedule for a user element and a user element for an input element of the building energy model,
When the user elements constituted by the set temperature, the heating value of the apparatus, the heating value of the heating, and the heating value of the user are reflected in the building energy model, the input maximum value and the input minimum value are selected, And the ratio of the amount of emission to the energy of the user. 8. The method of claim 7, wherein the user element probability distribution generating module generates a probability distribution for the user element boundary condition and reflects the probability distribution on the building energy model,
And generating and reflecting a probability distribution for a user element of the building energy model using the discrete distribution, the uniform distribution, the normal distribution, and the triangular distribution for the selected user element boundary condition. Energy modeling method. The building energy model selection module according to claim 7, wherein the building energy model selection module compares the actual energy usage with the result of the simulation performed in the user element-based Latin hypercube sampling module, In selecting the building energy model,
A building energy model satisfying the accuracy and reliability of a predetermined criterion among the building energy models is selected using statistical indices of NMBE (Normalized Mean Biased Error) and CVRMSE (Coefficient of Variance of Root Mean Square Error) A method of building energy modeling with user elements. 12. The method according to claim 11, wherein the building energy model selection module compares the actual energy usage with the result of the simulation executed in the user element-based Latin hypercube sampling module, In selecting the building energy model,
Wherein when the value of the NMBE is within ± 6% and the value of the CVRMSE is within ± 18%, it is determined that the corresponding building energy model is corrected by satisfying the accuracy and reliability of the predetermined criterion. Reflected building energy modeling method.
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