재실자 예측과 핑퐁 방법을 통한 환기 시스템 최적제어 시뮬레이션

다국어 초록 (Multilingual Abstract)

In general, On-off and Multi step controls are widely applied to DCV-CO₂ ventilation systems. The problem of the on-off and Multi step control is that their controls are not based on an optimal algorithm. Therefore, this study suggests a simulation assisted optimal control. The simulation assisted optimal control uses optimization algorithm to solve for optimal control variables to minimize a cost function over the time horizon. For this study, CONTAMW 2.4 simulation tool and EnergyPlus are coupled in MATLAB platform to simulate thermal and air-flow phenomena using Ping-Pong method. And the optimal control of ERV (Energy Recovery Ventilator) system is performed by a gradient-based search that uses the derivative of the cost function. The cost elements are energy flow and CO₂ concentration (bedroom1, living room). A prominent characteristic presents that occupant’s schedule applies to a stochastic model based prediction of occupants' presence using the Markov Chain method. To perform Markov Chain method, the number of occupants every hour in each of the rooms (20 households) was examined and then the transition probability matrix was generated. By comparing the optimal control with existing controls (On-off and Multi step controls), it is shown that the proposed optimal control can lead to significant improvements for ventilation system performance.

목차 (Table of Contents)

• Abstract
• 1. 서론
• 2. 시뮬레이션 기반의 최적제어
• 3. 시뮬레이션 모델
• 4. 시뮬레이션 결과
• 5. 결론 및 추후 연구내용
• 참고문헌

참고문헌 (Reference)

1 김영진, "확률적 모델을 이용한 재실 인원 예측" 대한건축학회 25 (25): 271-279, 2009

2 김영진, "유전자 알고리즘, 파레토 최적, 환기 시뮬레이션을 통합한 환기 시스템 최적설계" 대한건축학회 24 (24): 237-245, 2008

3 현세훈, "노후 공동주택 구조 및 설비성능 개선기술 개발" 건설교통부 2006

4 박철수, "규범적 건물성능 평가방법" 대한건축학회 22 (22): 337-344, 2006

5 김덕우, "공동주택 환기 시스템의 핑퐁 및 오니언 접근 방식 비교" 대한건축학회 26 (26): 309-316, 2010

6 여명석, "공동주택 온수온돌 바닥복사 난방시스템의 온수온도 제어방법에 관한 연구" 14 (14): 203-210, 1998

7 이윤규, "空氣流動解析에 의한 共同住宅換氣性能豫測모델에 關한 硏究" 연세대학교 1997

8 Saaty, T. L, "The Analytic Hierarchy Process" McGraw-Hill 1980

9 Weber, A, "TRNFLOW, a new tool for the modelling of heat, air and pollutant transport in buildings within TRNSYS" 1363-1368, 2003

10 Mahdavi, A, "Simulation-based control of building systems operation" 36 : 789-796, 2001

11 Clarke, J. A, "Simulation-assisted control in building energy management systems" 34 (34): 933-940, 2002

12 Dorer, V, "Parameters for the design of demand controlled hybrid ventilation systems for residential buildings" 59 : 85-86, 2005

13 Wouters, P, "Outline for a general framework for the assessment of innovative ventilation systems" 2004

14 Athans, M, "Optimal control: An introduction to the theory and its application" McGraw-Hill 1996

15 Stengel. R.F, "Optimal Control and Estimation" Dove Publications, Inc 1994

16 Lewis, F. L, "Optimal Control" John Wiley & Sons 1995

17 김영진, "Nodal flow network 시뮬레이션과 공동주택 환기실험의 비교 분석" 대한건축학회 25 (25): 437-444, 2009

18 Stein, B, "Mechnical and electrical equipment for buildings" John Wiley & Sons, Inc 2006

19 Kim, D.W, "Manual vs. Dynamic Control of Interior/Exterior Blind Systems" 1663-1670, 2009

20 Benayoun, R, "Manual de Reference du Programme Electre, Note de Synthese et Formaton, No.25" Direction Scientifque SEMA 1966

21 KS, "KS F 2292-88: 창호 기밀성 시험 방법"

22 Jeong, J.W., "Improvement in demand-controlled ventilation simulation on multi-purposed facilities under an occupant based ventilation standard" ELSEVIER SCIENCE BV 18 : 51-62, 201001

23 Miller, D. W, "Executive Decisions and Operations Research" Prentice-Hall, INC 1969

24 DOE, "EnergyPlus 5.0 Input/Output Reference: The Encyclopedic Reference to EnergyPlus Input and Output" US Department Of Energy 2009

25 DOE, "EnergyPlus 5.0 Engineering Reference: The Encyclopedic Reference to EnergyPlus Calculations, U.S" Department Of Energy 2009

26 Bryson, A. E, "Dynamic optimization" Addison-Wesley 1998

27 Schell, M, "Demand Control Ventilation Using CO2" 2001

28 Reinhart., C.F, "Daylight availability and manual lighting control in office buildings - Simulation studies and analysis of measurements" Technical University of Karlsruhe 2001

29 Fujii, H, "Coupling building simulation with agent simulation for exploration to environmentally symbiotic architecture" 363-370, 2003

30 Yoon, S.H, "Comparative Study of Static vs. Dynamic Controls of Double-skin Systems" 968-976, 2009

31 Walton, G.N, "CONTAMW 2.4 User Guide and Program Documentation" Gaithersburg, MD, National Institute of Standards and Technology 2005

32 Moon, H.J, "Assessing mold risks in buildings under uncertainty" Georgia Institute of Technology 2005

33 Bryson, A. E, "Applied optimal control" Hemisphere 1975

34 Triantaphyllou, E, "An Examination of the Effectiveness of Multi-Dimensional Decision-Making Methods: A Decision-Making Paradox" (5) : 303-312, 1989

35 Dorer, V, "Air, contaminant and heat transport models: integration and application" 30 : 97-104, 1999

36 Fishburn, P. C, "Additive Utilities with Incomplete Product Set: Applications to Priorities and sharings, Operations Research Society of America (ORSA)" Baltimore 1967

37 Bourgeois, D, "Adding advanced behavioural models in whole building energy simulation: A study on the total energy impact of manual and automated lighting control" 38 (38): 814-823, 2006

38 Astrom, K, "Adaptive control" Addison Wesley 1995

39 ASHRAE, "ASHRAE STANDARD, Ventilation for Acceptable Indoor Air Quality, ANSI/ASHRAE/IESNA Standard 62.1-2004"

40 ASHRAE, "ASHRAE Handbook Fundamentals. Atlanta: American Society of Heating" Refrigerating and Air-Conditioning Engineers, Inc 2001

41 ASHRAE, "ASHRAE Handbook Fundamentals. Atlanta: American Society of Heating" Refrigerating and Air-Conditioning Engineers, Inc 2005

42 Richardson, I, "A high-resolution domestic building occupancy model for energy demand simulations" 40 : 1560-1566, 2008

43 Hensen, J, "A comparison of coupled and de-coupled solutions for temperature and airflow in a building" 105 : 1999