All Issue

2019 Vol.13, Issue 5 Preview Page

Research Article

30 October 2019. pp. 430-443
Abstract
References
1
Corbin, C.D., Henze, G.P., May-Ostendorp, P. (2013). A model predictive control optimization environment for real-time commercial building application. Journal of Building Performance Simulation, 6(3), 159-174.
10.1080/19401493.2011.648343
2
Hao, H., Corbin, C.D., Kalsi, K., Pratt, Robert G. (2017). Transactive control of commercial buildings for demand response. IEEE Transactions on Power Systems, 32(1), 774-783.
10.1109/TPWRS.2016.2559485
3
Huang, S., Wang, W., Brambley, M.R., Goyal, S., Zuo, W. (2018). An agent-based hardware-in-the-loop simulation framework for building controls. Energy and Buildings, 181, 26-37.
10.1016/j.enbuild.2018.09.038
4
Kim, S., Seo, D. (2017). Evaluation of the Lighting Control Performance using Developed MPC Environment with Occupancy Data. Journal of KIAEBS, 11(6), 546-557.
10.12972/jkiaebs.20170024
5
Kwak, Y., Seo, D., Jang, C., Huh, J. (2013). Feasibility study on a novel methodology for short-term real-time energy demand prediction using weather forecasting data. Eenrgy and Building, 57, 250-260.
10.1016/j.enbuild.2012.10.041
6
Macdonald, I., Strachan, P. (2001). Practical application of uncertainty analysis. Energy and Buildings, 33(3), 219-227.
10.1016/S0378-7788(00)00085-2
7
Moon, H., Choi, M. (2014). Continuous commissioning through real-time simulation with a building energy monitoring system. Sensor Letters, 12, 967-973.
10.1166/sl.2014.3202
8
Pang, X. Wetter, M. Bhattacharya, Haves, P. (2012). A framework for simulation-based real-time whole building performance assessment. Build. Environ., 54, 100-108.
10.1016/j.buildenv.2012.02.003
9
Santin, O.G. (2011), Behavioural patterns and user profiles related to energy consumption for heating, Energy and Buildings, 43(10), 2662-2672.
10.1016/j.enbuild.2011.06.024
10
Shen, W., Newsham, G., Gunay, B. (2017). Leveraging existing occupancy-related data for optimal control of commercial office buildings A review. Advanced Engineering Informatics, 33, 230-242.
10.1016/j.aei.2016.12.008
11
Seo, D., Ihm, B. (2018). IoT Information based buidling energy estimation system development for distributed energy management (3rd Year), Daejeon, ETRI.
12
American Society of Heating, Ventilating, and Air Conditioning Engineers (ASHRAE). (2002). Guideline 14-2002, Measurement of Energy and Demand Savings; Technical Report; American Society of Heating, Ventilating, and Air Conditioning Engineers: Atlanta, GA, USA, 2002.
13
Chae, Y., Lee, Y., Longinotte, D. (2013). Smart buildings start from a smarter home -Retrofit plan for T.J. Waton Research Center. IBM internal report, IBM.
14
Chen, Y., Hong, T., Luo, X. (2017). An Agent-Based Stochastic Occupancy Simulator, Building Simulation, May 2017, DOI:10.1007/s 12273-017-0379-7.
Information
  • Publisher :Korean Institute of Architectural Sustainable Environment and Building Systems
  • Publisher(Ko) :한국건축친환경설비학회
  • Journal Title :Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
  • Journal Title(Ko) :한국건축친환경설비학회논문집
  • Volume : 13
  • No :5
  • Pages :430-443
  • Received Date : 2019-10-11
  • Accepted Date : 2019-10-22
Journal Informaiton Journal of Korean Institute of Architectural Sustainable Environment and Building Systems Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close