WO2014084648A1 - Method for controlling building by predicting building energy in design and operation steps and system for same - Google Patents

Method for controlling building by predicting building energy in design and operation steps and system for same Download PDF

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WO2014084648A1
WO2014084648A1 PCT/KR2013/010957 KR2013010957W WO2014084648A1 WO 2014084648 A1 WO2014084648 A1 WO 2014084648A1 KR 2013010957 W KR2013010957 W KR 2013010957W WO 2014084648 A1 WO2014084648 A1 WO 2014084648A1
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building
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문현준
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단국대학교 산학협력단
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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  • the present invention relates to a method and system for controlling a building by predicting building energy at the design and operation stages.
  • Korea also participates in such a move under the low carbon green growth policy, but there are still few visible outcomes.
  • the building control method must change accordingly. Is the reality.
  • Korean Patent Publication No. 2012-0010474 discloses a method of verifying an energy simulation model after weather information is input and management information is input. Similarly, it is only an afterthought and low accuracy.
  • Japanese Patent Laid-Open No. 2005-158020 utilizes information at the design stage and proposes various alternatives, but has a disadvantage in that changes in the operation stage are not reflected and energy consumption cannot be predicted.
  • Patent Document 1 WO2010-129913 A
  • Patent Document 2 KR2012-0010474 A
  • Patent Document 3 JP2005-158020 A
  • the present invention proposes a method of controlling a building in a direction of optimizing energy consumption by increasing the simulation accuracy by building a model closest to a real building while maximizing the model constructed at the design stage.
  • the present invention (a) the design model building module 100 to build a design model using the building design information; (b) the analysis model building module 200 constructing an analysis model by adding building actual information to the design model; (c) the prediction module 600 determining prediction information of the building for a future unit time; (d) building energy simulation module 300 performing building energy simulation of the analysis model using the determined prediction information; (e) generating, by the control value generation module 400, control values of actual buildings to minimize energy consumption resulting from the simulation; And (f) the building energy management system (BEMS) 500 controlling the actual building for the unit time according to the control value. to provide.
  • BEMS building energy management system
  • the prediction information of the step (c) is preferably occupancy prediction information, performance prediction information, and climate prediction information.
  • the occupancy prediction information is preferably calculated using the number of occupants and occupant information detected by the occupancy sensor installed in the occupancy space of the real building.
  • the performance prediction information is preferably calculated using the building operating time information and internal heat generation information detected by the performance sensor installed in the real building.
  • the climate prediction information is preferably calculated using the local information detected through the climate sensor attached to the actual building and the global information obtained from the climate database.
  • the unit time can be set from 1 minute to 1 hour, and after the step (f), it is preferable that the steps (c) to (f) is repeated in a set time unit.
  • the building energy simulation module 300 further comprises the step of performing a building energy simulation of the design model.
  • step (a) is preferably BIM construction information.
  • the present invention provides a design model building module 100 for building a design model using building design information;
  • An analysis model building module 200 for constructing an analysis model by adding building actual information to the design model;
  • a prediction module 600 for determining prediction information of a building for a future unit time;
  • Building energy simulation module 300 for performing a building energy simulation of the analysis model using the determined prediction information;
  • a control value generation module 400 for generating a control value of an actual building to minimize energy consumption which is a result of the simulation; It provides a system for predicting building energy, including building energy management system (BEMS) 500 that controls the actual building for the future unit time according to the control value.
  • BEMS building energy management system
  • a room sensor In addition, it is preferable to further include a room sensor, a performance sensor and a climate sensor interlocked with the BEMS, located in the building.
  • the prediction module may generate the prediction information by generating occupancy prediction information, performance prediction information, and climate prediction information by using information sensed by the occupancy sensor, the performance sensor, and the climate sensor, and global information obtained from a climate database. It is preferable.
  • the building energy simulation module 300 may further perform building energy simulation of the design model.
  • simulation accuracy can be improved by constructing a model closest to a real building while maximizing the model constructed at the design stage.
  • buildings can be controlled to optimize energy consumption, which can help the landlord to reduce energy consumption as well as reduce national energy.
  • FIG. 1 schematically shows a system according to the invention.
  • FIG. 2 schematically shows a building control method according to the invention.
  • the design model construction module 100 builds a design model using building design information.
  • the building design information used herein may be building information modeling (BIM) building information.
  • BIM building information modeling
  • the building design information may be linked with the BIM building server 10 in which the BIM building information is managed.
  • the design model thus constructed may be used to perform energy simulation in the design phase using the building energy simulation module 300.
  • users can also evaluate a number of alternatives and determine the optimal design model in terms of energy consumption.
  • the present invention creates an analytical model to compensate for this.
  • the analysis model building module 200 builds an analysis model reflecting the actual building by adding building actual information to the previously constructed design model.
  • the air conditioner was operated for three hours a day, but in the actual operation stage, the air conditioner was five hours a day. If the machine is running it can be easily applied.
  • the prediction module 600 functions to predict information determined as the actual building is operated in the future.
  • the prediction module 600 uses information sensed by the indoor sensor and the performance sensor 51 installed inside the building and the climate sensor 52 installed outside the building.
  • the sensors are associated with the BEMS 500, and the prediction module 600 may collect information from the BEMS 500.
  • the prediction module 600 includes an occupancy prediction module 610, a performance prediction module 620, and a climate prediction module 630.
  • the occupancy prediction module 610 calculates occupancy prediction information by using the occupancy number and occupant information sensed by the occupancy sensor.
  • the performance prediction module 620 may perform performance prediction information using building performance information sensed by a performance sensor installed in a heating, ventilation, air conditioning (HVAC) device, and the like, and the building operation time that may be known from the operating time. Calculate
  • This performance prediction information is of course used to perform the energy simulation.
  • the climate prediction module 630 is calculated using global information obtained from the climate database 60 as well as local information detected through the climate sensor 52 installed outside the actual building.
  • the global information here includes the amount of clouds, air pressure changes, and the like used in various climate observation instruments.
  • This climate prediction information can be used to predict whether more heating energy or cooling energy will be consumed, and is used when performing energy simulation.
  • building prediction information Such room prediction information, performance prediction information, and climate prediction information are collectively referred to as building prediction information, which predicts which direction the building will operate in the future and in which direction the energy of the building will be consumed.
  • the building energy simulation module 300 may perform the following two building energy simulations on the constructed model.
  • energy simulation can be performed on the design model built at the design stage.
  • energy simulations can be performed on analytical models built at the operational stage and complemented by design models.
  • the prediction information may be used to confirm the direction of the building energy for the next unit time.
  • Buildings can be controlled using the identified and predicted future building energy directions.
  • the control value generation module 400 generates control values to minimize energy consumption, which is a result of the building energy simulation module 300.
  • control value means an algorithm for controlling the control objects 53 in the building.
  • control object 53 in the building is HVAC
  • the degree of operation may be controlled, in the case of blinds, the degree of opening and closing may be controlled, and in the case of lighting, the degree of dimming may be controlled, and the openings (windows, doors) may be controlled. Etc.), the degree of opening and closing can be controlled.
  • the degree of opening and closing can be controlled.
  • control value can be generated to maximize the comfort similar to the minimum energy consumption.
  • the building energy management system (BEMS) 500 may control the building according to the value generated by the control value generation module 400 in cooperation with the control objects 53 in the building.
  • the sensing information may be transmitted to the prediction module 600 by interworking with the sensors 51 and 52 inside and outside the building.
  • the design model building module 100 builds a design model using the building design information (S110).
  • the BIM establishment information delivered from the BIM establishment server 10 may be used.
  • Building energy simulation module 300 performs a building energy simulation for the design model (S120).
  • the analysis model building module 200 builds an analysis model in which the actual building is reflected by adding building actual information to the previously constructed design model (S210).
  • the prediction module 600 determines the prediction information that is expected to be determined as the actual building is operated in the future, that is, the prediction information for the future unit time (S220).
  • the prediction information includes occupancy prediction information, performance prediction information, and climate prediction information.
  • information detected by the sensors 51 and 52 linked to the BEMS 500 and information obtained from the climate database 60 may be used.
  • the building energy simulation module 300 performs building energy simulation by using prediction information in the analysis model (S230).
  • control value generating module 410 may generate a control value (S240).
  • heating energy consumption is expected to be high, it can be minimized by creating a control value that closes the opening.
  • the BEMS 500 controls the control object 53 of the real building according to the generated control value (S250).

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Abstract

The present invention provides a method for controlling a building by predicting building energy, comprising the steps of: (a) constructing a design model, by a design model construction module (100), using building design information; (b) adding information on an actual building, by an analysis model construction module (200), to the design model to construct an analysis model; (c) determining building prediction information, by a prediction module (600), on the future amount of unit time; (d) simulating the building energy of the analysis model, by a building energy simulation module (300), using the determined prediction information; (e) generating, by a control value generation module (400), an actual building control value which minimizes energy consumption corresponding to the simulation result; and (f) controlling the actual building for the amount of unit time, by a BEMS (Building Energy Management System) (500), according to the control value.

Description

설계 및 운영 단계에서 건물 에너지를 예측하여 건물을 제어하는 방법 및 이를 위한 시스템A method of controlling buildings by estimating building energy at the design and operation stages and a system therefor
본 발명은 설계 및 운영 단계에서 건물 에너지를 예측하여 건물을 제어하는 방법 및 이를 위한 시스템에 관한 것이다.The present invention relates to a method and system for controlling a building by predicting building energy at the design and operation stages.
세계 각국은 온실가스 배출과 화석 에너지 사용을 줄이기 위한 다양한 노력을 펼치고 있다.Countries around the world are making various efforts to reduce greenhouse gas emissions and fossil energy use.
우리나라 역시 저탄소 녹색성장 정책 아래 이같은 움직임에 동참하고 있으나 아직까지 가시적인 성과는 적은 실정이다.Korea also participates in such a move under the low carbon green growth policy, but there are still few visible outcomes.
건물 에너지는 에너지 소비와 탄소 배출에서 가장 큰 부분을 차지하고 있다.Building energy is the largest part of energy consumption and carbon emissions.
설계 기준의 강화와 건물 에너지 합리화 사업 등 다양한 노력에도 불구하고 지난 5년간 건물 에너지 소비는 전체 에너지 소비의 56%로 조사되고 있는 실정이다.Despite various efforts, such as strengthening design standards and building energy rationalization projects, building energy consumption has been surveyed at 56% of total energy consumption over the past five years.
이와 같이 건물 에너지 저감의 노력이 커짐에도 불구하고 실질적인 효과를 거두지 못하는 이유 중 하나로 설계 단계와 운영 단계에서 건물 에너지 접근 방법이 다름을 들 수 있다.One of the reasons why building energy reduction efforts are not being realized is that the building energy approach differs between the design and operation stages.
예를 들어, 설계 단계에서는 건물 에너지를 최적화하는 건물 설계가 이루어졌더라도, 건물이 시공되고 과정에서 많은 값들이 변할 수 있으며, 실재 운영은 설계에서의 가정과는 다르게 수행될 수도 있다.For example, at the design stage, even though the building design is optimized to optimize the building energy, many values can be changed in the building and the process, and the actual operation may be performed differently from the assumptions in the design.
만약, 에너지 저감형 자재를 사용하도록 설계되었지만 시공 단계에서 다른 자재가 사용되었다면, 또는 설계 단계에서 예상하였던 기후 내지 운영 시간과 실재 기후 및 운영 시간이 다른 경우, 건물 제어 방법도 이에 따라 바뀌어야 하는데 그렇지 못하는 것이 현실이다.If the design is designed to use energy-saving materials but other materials are used in the construction phase, or if the climate or operating time and actual climate and operating time expected at the design stage are different, the building control method must change accordingly. Is the reality.
그 이유로서, 운영 단계에서 적합한 모델 구축이 어렵고 과다한 시간이 소요된다는 점, 정밀한 모델이 구축되지 못하는 경우 정확도가 낮아져서 결과 신뢰도가 떨어진다는 점 등을 들 수 있다.The reason for this is that it is difficult and time consuming to build a suitable model at the operation stage, and that the accuracy is low when the precise model is not built, resulting in poor reliability.
관련된 종래 기술을 살펴본다.Consider the related prior art.
국제공개특허번호 제2010/129913호의 경우, 다양한 데이터를 수집하여 입력함으로써 건물 관련 정보를 적절하게 사용하고 에너지 소비를 분석하고 그 비용을 예측하는 방법을 개시한다. 그러나, 비용 예측을 제외하고는 에너지 소비가 이루어진 후 사후적인 고찰에 불과하며, 설계 단계에서 구축된 정보 그대로 사용하기에 운영 단계에서 변경된 점이 적용되지 않아 정확도가 낮다는 단점이 있다.International Publication No. 2010/129913 discloses a method of properly using building related information, analyzing energy consumption, and predicting the cost by collecting and inputting various data. However, with the exception of cost prediction, it is only a post-mortem consideration after energy consumption is made, and it has a disadvantage of low accuracy because no change is applied at the operation stage to use the information constructed at the design stage.
한국공개특허 제2012-0010474호의 경우, 기상정보가 입력되고 관리정보를 입력받은 후 에너지 시뮬레이션 모델을 검증하는 방법을 개시한다. 마찬가지로, 사후적 고찰에 불과하고 정확도가 낮다.Korean Patent Publication No. 2012-0010474 discloses a method of verifying an energy simulation model after weather information is input and management information is input. Similarly, it is only an afterthought and low accuracy.
일본공개특허 제2005-158020호의 경우, 설계 단계에서의 정보를 활용하고 다양한 대안을 제시하나, 운영 단계에서 변경되는 점이 반영되지 못하고 에너지 소비량을 예측하지 못한다는 단점이 있다.Japanese Patent Laid-Open No. 2005-158020 utilizes information at the design stage and proposes various alternatives, but has a disadvantage in that changes in the operation stage are not reflected and energy consumption cannot be predicted.
(특허문헌 1) WO2010-129913 A (Patent Document 1) WO2010-129913 A
(특허문헌 2) KR2012-0010474 A (Patent Document 2) KR2012-0010474 A
(특허문헌 3) JP2005-158020 A (Patent Document 3) JP2005-158020 A
이에 본 발명은 설계 단계에서 구축된 모델을 최대한 활용하면서 실재 건물에 가장 가까운 모델을 구축함으로써 시뮬레이션 정확도를 높이고, 그 결과를 이용하여 에너지 소비량을 최적화하는 방향으로 건물을 제어하는 방법을 제안하고자 한다.Accordingly, the present invention proposes a method of controlling a building in a direction of optimizing energy consumption by increasing the simulation accuracy by building a model closest to a real building while maximizing the model constructed at the design stage.
상기와 같은 과제를 해결하기 위해 본 발명은, (a) 설계 모델 구축 모듈(100)이 건물 설계 정보를 이용하여 설계 모델을 구축하는 단계; (b) 분석 모델 구축 모듈(200)이 상기 설계 모델에 건물 실재 정보를 추가하여 분석 모델을 구축하는 단계; (c) 예측 모듈(600)이 향후의 단위 시간 동안의 건물의 예측 정보를 결정하는 단계; (d) 건물 에너지 시뮬레이션 모듈(300)이 상기 결정된 예측 정보를 이용하여 상기 분석 모델의 건물 에너지 시뮬레이션을 수행하는 단계; (e) 제어값 생성 모듈(400)이 상기 시뮬레이션 수행 결과인 에너지 소비량을 최소화하는 실재 건물의 제어값을 생성하는 단계; 및 (f) BEMS(Building Energy Management System, 건물 에너지 관리 시스템)(500)가 상기 제어값에 따라 실재 건물을 상기 단위 시간 동안 제어하는 단계를 포함하는, 건물 에너지를 예측하여 건물을 제어하는 방법을 제공한다.In order to solve the above problems, the present invention, (a) the design model building module 100 to build a design model using the building design information; (b) the analysis model building module 200 constructing an analysis model by adding building actual information to the design model; (c) the prediction module 600 determining prediction information of the building for a future unit time; (d) building energy simulation module 300 performing building energy simulation of the analysis model using the determined prediction information; (e) generating, by the control value generation module 400, control values of actual buildings to minimize energy consumption resulting from the simulation; And (f) the building energy management system (BEMS) 500 controlling the actual building for the unit time according to the control value. to provide.
또한, 상기 (c) 단계의 예측 정보는, 재실 예측 정보, 성능 예측 정보 및 기후 예측 정보인 것이 바람직하다.In addition, the prediction information of the step (c) is preferably occupancy prediction information, performance prediction information, and climate prediction information.
여기에서, 상기 재실 예측 정보는, 실재 건물의 재실 공간에 부설된 재실 센서를 통해 감지되는 재실자수 및 재실자 정보를 이용하여 연산되는 것이 바람직하다.Here, the occupancy prediction information is preferably calculated using the number of occupants and occupant information detected by the occupancy sensor installed in the occupancy space of the real building.
또한, 상기 성능 예측 정보는, 실재 건물에 부설된 성능 센서를 통해 감지되는 건물 운영 시간 정보 및 내부 발열 정보를 이용하여 연산되는 것이 바람직하다.In addition, the performance prediction information is preferably calculated using the building operating time information and internal heat generation information detected by the performance sensor installed in the real building.
또한, 상기 기후 예측 정보는, 실재 건물에 부설된 기후 센서를 통해 감지된 로컬 정보 및 기후 데이터베이스에서 획득되는 글로벌 정보를 이용하여 연산되는 것이 바람직하다.In addition, the climate prediction information is preferably calculated using the local information detected through the climate sensor attached to the actual building and the global information obtained from the climate database.
한편, 상기 단위 시간은 1분에서 1시간까지 설정 가능하며, 상기 (f) 단계 이후, 상기 (c) 내지 상기 (f) 단계가 설정 시간 단위로 반복되는 것이 바람직하다.On the other hand, the unit time can be set from 1 minute to 1 hour, and after the step (f), it is preferable that the steps (c) to (f) is repeated in a set time unit.
또한, 상기 (a) 단계 이후, (a1) 상기 건물 에너지 시뮬레이션 모듈(300)이 상기 설계 모델의 건물 에너지 시뮬레이션을 수행하는 단계를 더 포함하는 것이 바람직하다.In addition, after the step (a), (a1) it is preferable that the building energy simulation module 300 further comprises the step of performing a building energy simulation of the design model.
또한, 상기 (a) 단계의 건물 설계 정보는 BIM 구축 정보인 것이 바람직하다.In addition, the building design information of step (a) is preferably BIM construction information.
상기와 같은 과제를 해결하기 위해 본 발명은 건물 설계 정보를 이용하여 설계 모델을 구축하는 설계 모델 구축 모듈(100); 상기 설계 모델에 건물 실재 정보를 추가하여 분석 모델을 구축하는 분석 모델 구축 모듈(200); 향후 단위 시간 동안의 건물의 예측 정보를 결정하는 예측 모듈(600); 상기 결정된 예측 정보를 이용하여 상기 분석 모델의 건물 에너지 시뮬레이션을 수행하는 건물 에너지 시뮬레이션 모듈(300); 상기 시뮬레이션 수행 결과인 에너지 소비량을 최소화하는 실재 건물의 제어값을 생성하는 제어값 생성 모듈(400); 실재 건물을 상기 제어값에 따라 상기 향후 단위 시간 동안 제어하는 BEMS(Building Energy Management System)(500)를 포함하는, 건물 에너지를 예측하여 건물을 제어하기 위한 시스템을 제공한다.In order to solve the above problems, the present invention provides a design model building module 100 for building a design model using building design information; An analysis model building module 200 for constructing an analysis model by adding building actual information to the design model; A prediction module 600 for determining prediction information of a building for a future unit time; Building energy simulation module 300 for performing a building energy simulation of the analysis model using the determined prediction information; A control value generation module 400 for generating a control value of an actual building to minimize energy consumption which is a result of the simulation; It provides a system for predicting building energy, including building energy management system (BEMS) 500 that controls the actual building for the future unit time according to the control value.
또한, 상기 BEMS와 연동하며, 건물에 위치하는 재실 센서, 성능 센서 및 기후 센서를 더 포함하는 것이 바람직하다.In addition, it is preferable to further include a room sensor, a performance sensor and a climate sensor interlocked with the BEMS, located in the building.
또한, 상기 예측 모듈은 상기 재실 센서, 성능 센서 및 기후 센서에서 센싱된 정보와 기후 데이터베이스에서 획득되는 글로벌 정보를 이용하여 재실 예측 정보, 성능 예측 정보 및 기후 예측 정보를 생성함으로써 상기 예측 정보를 생성하는 것이 바람직하다.The prediction module may generate the prediction information by generating occupancy prediction information, performance prediction information, and climate prediction information by using information sensed by the occupancy sensor, the performance sensor, and the climate sensor, and global information obtained from a climate database. It is preferable.
또한, 상기 건물 에너지 시뮬레이션 모듈(300)은 상기 설계 모델의 건물 에너지 시뮬레이션을 더 수행하는 것이 바람직하다.In addition, the building energy simulation module 300 may further perform building energy simulation of the design model.
본 발명에 의하여, 설계 단계에서 구축된 모델을 최대한 활용하면서 실재 건물에 가장 가까운 모델을 구축함으로써 시뮬레이션 정확도를 높일 수 있다.According to the present invention, simulation accuracy can be improved by constructing a model closest to a real building while maximizing the model constructed at the design stage.
또한, 에너지 소비량을 최적화하도록 건물을 제어할 수 있어서, 건물주의 에너지 소비량 저감은 물론 국가 에너지 저감에도 도움을 줄 수 있다.In addition, buildings can be controlled to optimize energy consumption, which can help the landlord to reduce energy consumption as well as reduce national energy.
또한, 재실 예측 정보, 성능 예측 정보 및 기후 예측 정보를 종합적으로 사용함으로써 실재 건물 제어의 정확도를 상승시킬 수 있다.In addition, it is possible to increase the accuracy of real building control by comprehensively using the occupancy prediction information, the performance prediction information and the climate prediction information.
또한, 하나의 시스템에서 설계 단계의 대안 수립 및 결정에 도움을 주는 것은 물론 운영 단계의 제어에도 도움을 줄 수 있다.It can also help with the design and decision-making of the design phase in one system, as well as the control of the operational phase.
도 1은 본 발명에 따른 시스템을 개략적으로 도시한다.1 schematically shows a system according to the invention.
도 2는 본 발명에 따른 건물 제어 방법을 개략적으로 도시한다.2 schematically shows a building control method according to the invention.
이하, 도면을 참조하여 본 발명에 따른 건물 제어 방법 및 이를 위한 시스템을 설명한다.Hereinafter, a building control method and a system therefor according to the present invention will be described with reference to the drawings.
시스템의 설명Description of the system
도 1을 참조하여, 본 발명에 따른 건물 제어 방법을 수행하기 위한 시스템을 설명한다.Referring to Figure 1, a system for performing a building control method according to the present invention.
설계 모델 구축 모듈(100)은, 건물 설계 정보를 이용하여 설계 모델을 구축한다.The design model construction module 100 builds a design model using building design information.
여기에서 사용되는 건물 설계 정보는 BIM(Building Information Modeling) 구축 정보일 수 있으며, 이를 위하여 BIM 구축 정보가 관리되는 BIM 구축 서버(10)와 연동될 수 있다.The building design information used herein may be building information modeling (BIM) building information. For this, the building design information may be linked with the BIM building server 10 in which the BIM building information is managed.
이렇게 구축된 설계 모델은 건물 에너지 시뮬레이션 모듈(300)을 이용하여 설계 단계에서의 에너지 시뮬레이션 수행에 사용될 수 있다. The design model thus constructed may be used to perform energy simulation in the design phase using the building energy simulation module 300.
이 과정에서 사용자는 다수의 대안을 평가하고 에너지 소비 측면에서 최적의 설계 모델을 결정할 수도 있다.In the process, users can also evaluate a number of alternatives and determine the optimal design model in terms of energy consumption.
건물 설계 정보를 이용하여 실재 건물이 시공되고 운영되면 건물과 관련된 많은 정보들이 변하는 것이 현실적이다.When the actual building is constructed and operated using the building design information, it is realistic to change a lot of information related to the building.
본 발명은 이를 보완하기 위하여, 분석 모델을 생성한다.The present invention creates an analytical model to compensate for this.
분석 모델 구축 모듈(200)은 앞서 구축된 설계 모델에 건물 실재 정보를 추가하여 실재 건물이 반영된 분석 모델을 구축한다.The analysis model building module 200 builds an analysis model reflecting the actual building by adding building actual information to the previously constructed design model.
예를 들어 시공 단계에서 설계 단계와 달리 자재가 변경된 경우 이를 용이하게 적용할 수 있으며, 다른 예를 들어 설계 단계에서는 1일 3시간의 공조기기 가동을 가정하였지만 실재 운영 단계에서 1일 5시간의 공조기기가 가동된다면 이를 용이하게 적용할 수 있다.For example, it can be easily applied when the material is changed in the construction stage, unlike the design stage. For example, in the design stage, the air conditioner was operated for three hours a day, but in the actual operation stage, the air conditioner was five hours a day. If the machine is running it can be easily applied.
이와 같이 분석 모델 생성 단계를 거침으로써 향후 건물 에너지 시뮬레이션을 실재 건물과 가장 유사하게 생성할 수 있다.By going through the analysis model generation step, it is possible to generate the future building energy simulation most similar to the actual building.
예측 모듈(600)은 실재 건물이 향후 운영됨에 따라 결정되는 정보를 예측하는 기능을 한다. The prediction module 600 functions to predict information determined as the actual building is operated in the future.
이를 위하여 예측 모듈(600)은 건물 내부에 부설되는 재실 센서 및 성능 센서(51)와 건물 외부에 부설되는 기후 센서(52)에서 센싱되는 정보들을 이용한다. 이 과정에서 센서들은 BEMS(500)와 연계되고, 예측 모듈(600)은 BEMS(500)로부터 정보를 수집할 수 있다.To this end, the prediction module 600 uses information sensed by the indoor sensor and the performance sensor 51 installed inside the building and the climate sensor 52 installed outside the building. In this process, the sensors are associated with the BEMS 500, and the prediction module 600 may collect information from the BEMS 500.
예측 모듈(600)은 재실 예측 모듈(610), 성능 예측 모듈(620) 및 기후 예측 모듈(630)을 포함한다.The prediction module 600 includes an occupancy prediction module 610, a performance prediction module 620, and a climate prediction module 630.
재실 예측 모듈(610)은, 재실 센서에서 센싱되는 재실자수 및 재실자 정보를 이용하여 재실 예측 정보를 연산한다.The occupancy prediction module 610 calculates occupancy prediction information by using the occupancy number and occupant information sensed by the occupancy sensor.
재실자수와 재실자 정보를 이용하면, 종래의 공지된 방법을 이용하여 향후 단위 시간(예를 들어, 1시간) 동안의 각각의 재실 공간의 재실자를 연산할 수 있는데, 이는 재실 발열 수치로 환산되어 에너지 시뮬레이션 수행시 사용된다.Using the number of occupants and information on the occupants, it is possible to calculate the occupants of each occupancy space for a future unit time (for example, one hour) using a conventionally known method, which is converted into an occident heat value and converted into energy. It is used when performing simulation.
성능 예측 모듈(620)은, HVAC(heating, ventilation, air conditioning; 냉난방공조) 기기 등에 부설되는 성능 센서에서 센싱되는 건물 성능 정보 및 그 운영 시간을 통해 알 수 있는 건물 운영 시간을 이용하여 성능 예측 정보를 연산한다.The performance prediction module 620 may perform performance prediction information using building performance information sensed by a performance sensor installed in a heating, ventilation, air conditioning (HVAC) device, and the like, and the building operation time that may be known from the operating time. Calculate
이와 같은 성능 예측 정보는 에너지 시뮬레이션 수행에 사용됨은 물론이다.This performance prediction information is of course used to perform the energy simulation.
기후 예측 모듈(630)은, 실재 건물의 외부에 부설된 기후 센서(52)를 통해 감지된 로컬 정보는 물론 기후 데이터베이스(60)에서 획득되는 글로벌 정보를 이용하여 연산된다.The climate prediction module 630 is calculated using global information obtained from the climate database 60 as well as local information detected through the climate sensor 52 installed outside the actual building.
여기에서 글로벌 정보는 각종 기후 관측 기구에서 사용되는 구름의 양, 기압의 변화 등을 포함한다.The global information here includes the amount of clouds, air pressure changes, and the like used in various climate observation instruments.
이와 같은 기후 예측 정보를 이용하여 난방 에너지가 더 소비될 것인지 또는 냉방 에너지가 더 소비될 것인지 등을 예측할 수 있는바, 에너지 시뮬레이션 수행시 사용된다.This climate prediction information can be used to predict whether more heating energy or cooling energy will be consumed, and is used when performing energy simulation.
이와 같은 재실 예측 정보, 성능 예측 정보 및 기후 예측 정보를 통칭하여 건물의 예측 정보로 지칭하며, 이는 향후 건물이 어떠한 방향으로 운영되고 건물의 에너지가 어떠한 방향으로 소비될 것인지를 예측하게 한다.Such room prediction information, performance prediction information, and climate prediction information are collectively referred to as building prediction information, which predicts which direction the building will operate in the future and in which direction the energy of the building will be consumed.
건물 에너지 시뮬레이션 모듈(300)은 구축된 모델에 대하여 다음의 두 가지의 건물 에너지 시뮬레이션을 수행할 수 있다.The building energy simulation module 300 may perform the following two building energy simulations on the constructed model.
첫째, 설계 단계에서 구축된 설계 모델에 대한 에너지 시뮬레이션을 수행할 수 있다.First, energy simulation can be performed on the design model built at the design stage.
이를 통하여, 사용자는 다수의 설계 대안 중 에너지 측면에서 최적인 설계를 결정하는데 도움을 받을 수 있다.This allows the user to help determine the optimal design in terms of energy among a number of design alternatives.
둘째, 운영 단계에서 구축된, 그리고 설계 모델에서 보완된 분석 모델에 대한 에너지 시뮬레이션을 수행할 수 있다. 이 과정에서, 예측 정보를 이용하여 향후 단위 시간 동안의 건물 에너지 방향을 확인할 수 있다.Second, energy simulations can be performed on analytical models built at the operational stage and complemented by design models. In this process, the prediction information may be used to confirm the direction of the building energy for the next unit time.
확인되고 예측되는 향후 건물 에너지 방향을 이용하여 건물을 제어할 수 있다.Buildings can be controlled using the identified and predicted future building energy directions.
제어값 생성 모듈(400)은 건물 에너지 시뮬레이션 모듈(300)에서 수행된 결과인 에너지 소비량을 최소화하도록 제어값을 생성한다.The control value generation module 400 generates control values to minimize energy consumption, which is a result of the building energy simulation module 300.
여기에서 "제어값"이란 건물 내 제어 객체(53)들을 제어하는 알고리즘을 의미한다.Here, the "control value" means an algorithm for controlling the control objects 53 in the building.
예를 들어, 건물 내 제어 객체(53)가 HVAC인 경우 작동 정도가 제어될 수 있으며, 블라인드인 경우 개폐 정도가 제어될 수 있으며, 조명인 경우 조광 정도가 제어될 수 있으며, 개구(창, 문 등)인 경우 개폐 정도가 제어될 수 있다. 기재하지 않았으나, 건물 내 제어가 가능한 모든 객체(53)의 제어가 가능함은 물론이다.For example, when the control object 53 in the building is HVAC, the degree of operation may be controlled, in the case of blinds, the degree of opening and closing may be controlled, and in the case of lighting, the degree of dimming may be controlled, and the openings (windows, doors) may be controlled. Etc.), the degree of opening and closing can be controlled. Although not described, of course, it is possible to control all the objects 53 that can be controlled in the building.
또한, 에너지 소비량이 최소인 것과 유사하게 쾌적도를 최대화하도록 제어값이 생성될 수 있음은 물론이다.Also, of course, the control value can be generated to maximize the comfort similar to the minimum energy consumption.
BEMS(Building Energy Management System, 건물 에너지 관리 시스템)(500)은 건물 내 제어 객체(53)들과 연동하여, 제어값 생성 모듈(400)에서 생성된 값에 따라 건물을 제어할 수 있다.The building energy management system (BEMS) 500 may control the building according to the value generated by the control value generation module 400 in cooperation with the control objects 53 in the building.
또한, 건물 내외의 센서들(51, 52)과 연동되어, 센싱된 정보들을 예측 모듈(600)에 전달할 수 있다.In addition, the sensing information may be transmitted to the prediction module 600 by interworking with the sensors 51 and 52 inside and outside the building.
건물 제어 방법의 설명Description of the building control method
도 2를 참조하여, 본 발명에 따른 건물 제어 방법을 설명한다.Referring to Figure 2, the building control method according to the present invention will be described.
먼저, 설계 모델 구축 모듈(100)이 건물 설계 정보를 이용하여 설계 모델을 구축한다(S110). First, the design model building module 100 builds a design model using the building design information (S110).
BIM 구축 서버(10)로부터 전달된 BIM 구축 정보가 사용될 수 있다.The BIM establishment information delivered from the BIM establishment server 10 may be used.
건물 에너지 시뮬레이션 모듈(300)은 설계 모델에 대한 건물 에너지 시뮬레이션을 수행한다(S120).Building energy simulation module 300 performs a building energy simulation for the design model (S120).
이 과정에서 다수의 대안들이 각각 평가될 수도 있다.In the process, a number of alternatives may each be evaluated.
다음, 건물이 시공되고 실재로 운영되면, 분석 모델 구축 모듈(200)은 앞서 구축된 설계 모델에 건물 실재 정보를 추가하여 실재 건물이 반영된 분석 모델을 구축한다(S210).Next, when the building is constructed and actually operated, the analysis model building module 200 builds an analysis model in which the actual building is reflected by adding building actual information to the previously constructed design model (S210).
다음, 예측 모듈(600)은 실재 건물이 향후 운영됨에 따라 결정될 것이 예상되는 예측 정보, 즉 향후 단위 시간 동안의 예측 정보를 결정한다(S220). Next, the prediction module 600 determines the prediction information that is expected to be determined as the actual building is operated in the future, that is, the prediction information for the future unit time (S220).
여기에서 예측 정보는 재실 예측 정보, 성능 예측 정보 및 기후 예측 정보를 포함한다. 또한, BEMS(500)에 연동되는 센서들(51, 52)에서 감지된 정보들과 기후 데이터베이스(60)에서 획득된 정보들이 사용될 수 있다.Here, the prediction information includes occupancy prediction information, performance prediction information, and climate prediction information. In addition, information detected by the sensors 51 and 52 linked to the BEMS 500 and information obtained from the climate database 60 may be used.
다음, 건물 에너지 시뮬레이션 모듈(300)은 분석 모델에 예측 정보를 이용하여 건물 에너지 시뮬레이션을 수행한다(S230).Next, the building energy simulation module 300 performs building energy simulation by using prediction information in the analysis model (S230).
그 결과 향후 단위 시간 동안의 건물 에너지를 결정할 수 있는데, 이를 최소화하도록 제어값 생성 모듈(410)은 제어값을 생성할 수 있다(S240).As a result, the building energy for the future unit time may be determined. To minimize this, the control value generating module 410 may generate a control value (S240).
예를 들어, 난방 에너지 소비가 많아질 것이 예상된다면, 개구부를 폐쇄시키는 제어값을 생성함으로써 이를 최소화할 수 있다. For example, if heating energy consumption is expected to be high, it can be minimized by creating a control value that closes the opening.
다음, BEMS(500)는 생성된 제어값에 따라 실재 건물의 제어 객체(53)를 제어한다(S250).Next, the BEMS 500 controls the control object 53 of the real building according to the generated control value (S250).
추가 예측 내지 제어가 필요한 경우(S260) 상기의 과정이 반복된다.If additional prediction or control is required (S260), the above process is repeated.
상기에서는 본 발명의 바람직한 실시 예를 참조하여 설명하였지만, 당업계에서 통상의 지식을 가진 자라면 이하의 특허 청구범위에 기재된 본 발명의 사상 및 영역을 벗어나지 않는 범위 내에서 본 발명을 다양하게 수정 및 변경시킬 수 있음을 이해할 수 있을 것이다.Although described above with reference to a preferred embodiment of the present invention, those of ordinary skill in the art various modifications and variations of the present invention within the scope and spirit of the present invention described in the claims below It will be appreciated that it can be changed.

Claims (12)

  1. (a) 설계 모델 구축 모듈(100)이 건물 설계 정보를 이용하여 설계 모델을 구축하는 단계; (a) the design model building module 100 constructing the design model using the building design information;
    (b) 분석 모델 구축 모듈(200)이 상기 설계 모델에 건물 실재 정보를 추가하여 분석 모델을 구축하는 단계; (b) the analysis model building module 200 constructing an analysis model by adding building actual information to the design model;
    (c) 예측 모듈(600)이 향후의 단위 시간 동안의 건물의 예측 정보를 결정하는 단계; (c) the prediction module 600 determining prediction information of the building for a future unit time;
    (d) 건물 에너지 시뮬레이션 모듈(300)이 상기 결정된 예측 정보를 이용하여 상기 분석 모델의 건물 에너지 시뮬레이션을 수행하는 단계; (d) building energy simulation module 300 performing building energy simulation of the analysis model using the determined prediction information;
    (e) 제어값 생성 모듈(400)이 상기 시뮬레이션 수행 결과인 에너지 소비량을 최소화하는 실재 건물의 제어값을 생성하는 단계; 및(e) generating, by the control value generation module 400, control values of actual buildings to minimize energy consumption resulting from the simulation; And
    (f) BEMS(Building Energy Management System, 건물 에너지 관리 시스템)(500)가 상기 제어값에 따라 실재 건물을 상기 단위 시간 동안 제어하는 단계를 포함하는, (f) the building energy management system (BEMS) 500 controlling the actual building for the unit time according to the control value;
    건물 에너지를 예측하여 건물을 제어하는 방법.How to control a building by predicting building energy.
  2. 제 1 항에 있어서, The method of claim 1,
    상기 (c) 단계의 예측 정보는, The prediction information of step (c) is
    재실 예측 정보, 성능 예측 정보 및 기후 예측 정보인 것을 특징으로 하는, Characterized in that it is occupancy prediction information, performance prediction information and climate prediction information,
    건물 에너지를 예측하여 건물을 제어하는 방법.How to control a building by predicting building energy.
  3. 제 2 항에 있어서, The method of claim 2,
    상기 재실 예측 정보는, 실재 건물의 재실 공간에 부설된 재실 센서를 통해 감지되는 재실자수 및 재실자 정보를 이용하여 연산되는 것을 특징으로 하는, The occupancy prediction information is calculated using the number of occupants and occupant information detected by the occupancy sensor attached to the occupancy space of the real building,
    건물 에너지를 예측하여 건물을 제어하는 방법.How to control a building by predicting building energy.
  4. 제 2 항에 있어서, The method of claim 2,
    상기 성능 예측 정보는, 실재 건물에 부설된 성능 센서를 통해 감지되는 건물 운영 시간 정보 및 내부 발열 정보를 이용하여 연산되는 것을 특징으로 하는, The performance prediction information, characterized in that it is calculated using the building operating time information and internal heat generation information detected through the performance sensor installed in the actual building,
    건물 에너지를 예측하여 건물을 제어하는 방법.How to control a building by predicting building energy.
  5. 제 2 항에 있어서, The method of claim 2,
    상기 기후 예측 정보는, 실재 건물에 부설된 기후 센서를 통해 감지된 로컬 정보 및 기후 데이터베이스에서 획득되는 글로벌 정보를 이용하여 연산되는 것을 특징으로 하는,The climate prediction information is calculated using local information detected through a climate sensor attached to a real building and global information obtained from a climate database.
    건물 에너지를 예측하여 건물을 제어하는 방법.How to control a building by predicting building energy.
  6. 제 1 항 내지 제 5 항 중 어느 한 항에 있어서, The method according to any one of claims 1 to 5,
    상기 단위 시간은 1시간이며, The unit time is 1 hour,
    상기 (f) 단계 이후, 상기 (c) 내지 상기 (f) 단계가 1시간 단위로 반복되는 것을 특징으로 하는, After the step (f), characterized in that the (c) to (f) step is repeated in units of 1 hour,
    건물 에너지를 예측하여 건물을 제어하는 방법.How to control a building by predicting building energy.
  7. 제 6 항에 있어서, The method of claim 6,
    상기 (a) 단계 이후, After the step (a),
    (a1) 상기 건물 에너지 시뮬레이션 모듈(300)이 상기 설계 모델의 건물 에너지 시뮬레이션을 수행하는 단계를 더 포함하는 것을 특징으로 하는, (a1) The building energy simulation module 300 may further include performing building energy simulation of the design model.
    건물 에너지를 예측하여 건물을 제어하는 방법.How to control a building by predicting building energy.
  8. 제 7 항에 있어서, The method of claim 7, wherein
    상기 (a) 단계의 건물 설계 정보는 BIM 구축 정보인 것을 특징으로 하는, Building design information of step (a) is characterized in that the BIM construction information,
    건물 에너지를 예측하여 건물을 제어하는 방법.How to control a building by predicting building energy.
  9. 건물 설계 정보를 이용하여 설계 모델을 구축하는 설계 모델 구축 모듈(100); A design model building module 100 for building a design model using building design information;
    상기 설계 모델에 건물 실재 정보를 추가하여 분석 모델을 구축하는 분석 모델 구축 모듈(200); An analysis model building module 200 for constructing an analysis model by adding building actual information to the design model;
    향후 단위 시간 동안의 건물의 예측 정보를 결정하는 예측 모듈(600);A prediction module 600 for determining prediction information of a building for a future unit time;
    상기 결정된 예측 정보를 이용하여 상기 분석 모델의 건물 에너지 시뮬레이션을 수행하는 건물 에너지 시뮬레이션 모듈(300); Building energy simulation module 300 for performing a building energy simulation of the analysis model using the determined prediction information;
    상기 시뮬레이션 수행 결과인 에너지 소비량을 최소화하는 실재 건물의 제어값을 생성하는 제어값 생성 모듈(400);A control value generation module 400 for generating a control value of an actual building to minimize energy consumption which is a result of the simulation;
    실재 건물을 상기 제어값에 따라 상기 향후 단위 시간 동안 제어하는 BEMS(Building Energy Management System)(500)를 포함하는, It includes a building energy management system (BEMS) 500 for controlling the actual building for the future unit time according to the control value,
    건물 에너지를 예측하여 건물을 제어하기 위한 시스템.A system for controlling buildings by estimating building energy.
  10. 제 9 항에 있어서, The method of claim 9,
    상기 BEMS와 연동하며, 건물에 위치하는 재실 센서, 성능 센서 및 기후 센서를 더 포함하는 것을 특징으로 하는, In conjunction with the BEMS, characterized in that it further comprises a room sensor, a performance sensor and a climate sensor located in the building,
    건물 에너지를 예측하여 건물을 제어하기 위한 시스템.A system for controlling buildings by estimating building energy.
  11. 제 10 항에 있어서, The method of claim 10,
    상기 예측 모듈은 상기 재실 센서, 성능 센서 및 기후 센서에서 센싱된 정보와 기후 데이터베이스에서 획득되는 글로벌 정보를 이용하여 재실 예측 정보, 성능 예측 정보 및 기후 예측 정보를 생성함으로써 상기 예측 정보를 생성하는 것을 특징으로 하는, The prediction module generates the prediction information by generating occupancy prediction information, performance prediction information, and climate prediction information using information sensed by the occupancy sensor, the performance sensor, and the climate sensor and global information obtained from a climate database. Made,
    건물 에너지를 예측하여 건물을 제어하기 위한 시스템.A system for controlling buildings by estimating building energy.
  12. 제 10 항에 있어서, The method of claim 10,
    상기 건물 에너지 시뮬레이션 모듈(300)은 상기 설계 모델의 건물 에너지 시뮬레이션을 더 수행하는 것을 특징으로 하는,The building energy simulation module 300 may further perform building energy simulation of the design model.
    건물 에너지를 예측하여 건물을 제어하기 위한 시스템.A system for controlling buildings by estimating building energy.
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