Smart building management vs. intuitive human control—Lessons learnt from an office building in Hungary

被引:0
作者
Zsofia Belafi
Tianzhen Hong
Andras Reith
机构
[1] Budapest University of Technology and Economics,Pal Csonka Doctoral School, Faculty of Architecture
[2] Lawrence Berkeley National Laboratory,Building Technology & Urban Systems Division
[3] Advanced Building and Urban Design (ABUD),undefined
来源
Building Simulation | 2017年 / 10卷
关键词
occupant behaviour; case study; building operation; optimization; building performance simulation;
D O I
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中图分类号
学科分类号
摘要
Smart building management and control are adopted nowadays to achieve zero-net energy use in buildings. However, without considering the human dimension, technologies alone do not necessarily guarantee high performance in buildings. An office building was designed and built according to state-of-the-art design and energy management principles in 2008. Despite the expectations of high performance, the owner was facing high utility bills and low user comfort in the building located in Budapest, Hungary. The objective of the project was to evaluate the energy performance and comfort indices of the building, to identify the causes of malfunction and to elaborate a comprehensive energy concept. Firstly, current building conditions and operation parameters were evaluated. Our investigation found that the state-of-the-art building management system was in good conditions but it was operated by building operators and occupants who are not aware of the building management practice. The energy consumption patterns of the building were simulated with energy modelling software. The baseline model was calibrated to annual measured energy consumption, using actual occupant behaviour and presence, based on results of self-reported surveys, occupancy sensors and fan-coil usage data. Realistic occupant behaviour models can capture diversity of occupant behaviour and better represent the real energy use of the building. This way our findings and the effect of our proposed improvements could be more reliable. As part of our final comprehensive energy concept, we proposed intervention measures that would increase indoor thermal comfort and decrease energy consumption of the building. A parametric study was carried out to evaluate and quantify energy, comfort and return on investment of each measure. It was found that in the best case the building could save 23% of annual energy use. Future work includes the follow-up of: occupant reactions to intervention measures, the realized energy savings, the measurement of occupant satisfaction and behavioural changes.
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页码:811 / 828
页数:17
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  • [1] Abu Bakar NN(2015)Energy efficiency index as an indicator for measuring building energy performance: A review Renewable and Sustainable Energy Reviews 44 1-11
  • [2] Hassan MY(2014)Simulation optimization: A review of algorithms and applications 4OR 12 301-333
  • [3] Abdullah H(2009)Survey of occupant behaviour and control of indoor environment in Danish dwellings Energy and Buildings 41 11-16
  • [4] Rahman HA(2011)Designing buildings for real occupants: An agent-based approach IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans 41 1077-1091
  • [5] Abdullah MP(2015)Near-optimal transition between temperature setpoints for peak load reduction in small buildings Energy and Buildings 87 123-133
  • [6] Hussin F(2013)A review of computational optimisation methods applied to sustainable building design Renewable and Sustainable Energy Reviews 22 230-245
  • [7] Bandi M(1997)Estimating the inputs of gas transport processes in buildings IEEE Transactions on Control Systems Technology 5 480-89
  • [8] Amaran S(2016)Occupant behavior in building energy simulation: Towards a fit-for-purpose modeling strategy Energy and Buildings 121 188-204
  • [9] Sahinidis NV(2010)Occupants’ behaviour: Determinants and effects on residential heating consumption Building Research & Information 38 318-e38
  • [10] Sharda B(2013)A critical review of observation studies, modeling, and simulation of adaptive occupant behaviors in offices Building and Environment 70 31-47