ME 4343 HVAC Design The Impact of Occupancy Behavior Patterns On the Energy Consumption in...

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ME 4343 HVAC Design The Impact of Occupancy Behavior Patterns On the Energy Consumption in Low- income Residential Buildings Bing Dong 1 , Yifei Duan 1 , Rui Liu 2 , Taeg Nishimoto 2 1 Building Performance and Diagnostics Group, Mechanical Engineering, the University of Texas, San Antonio, TX, USA 2 College of Architecture, the University of Texas, San Antonio, TX, USA

Transcript of ME 4343 HVAC Design The Impact of Occupancy Behavior Patterns On the Energy Consumption in...

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  • ME 4343 HVAC Design The Impact of Occupancy Behavior Patterns On the Energy Consumption in Low-income Residential Buildings Bing Dong 1, Yifei Duan 1, Rui Liu 2, Taeg Nishimoto 2 1 Building Performance and Diagnostics Group, Mechanical Engineering, the University of Texas, San Antonio, TX, USA 2 College of Architecture, the University of Texas, San Antonio, TX, USA
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  • Introduction Large gaps between measured performance and simulated results Source: NBI report 2008 Energy Performance of LEED For New Construction Buildings
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  • Introduction Occupancy behavior (OB) has significant influence on building energy use
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  • Introduction People spend most of time at homes Based on American time user survey data (ATUS)
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  • Introduction Occupancy behavior is a key factor influencing building energy consumption and indoor environment Climate Condition Building Envelope Building Systems Building Occupancy Behavior Occupancy Presence Occupancy Activities Occupancy Operation Energy Consumption
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  • UTSA Occupancy Test-beds Three+1 project for Westside low income houses A collaborative project of UTSA the San Antonio Alternative Housing Corporation, and the Texas Department of Housing and Community Affairs Honorable Mention for Research and Education in Residential Construction, presented by City of San Antonio Green Building Awards, 2013
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  • Introduction SIPs House 1,073sf AAC House 1,019sf Container House 1,106sf Stick House 1,000sf
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  • Instrumentation Powerhouse Dynamics e-Monitor Temperature Sensor Nonintrusive Sensor Network
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  • Energy Consumption Total Monthly Energy Consumption # of Occupants at homes 22443 Stick
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  • Behavior 1: Thermostat Schedule All four houses thermostat schedule August 12 to August 19, 2013 DOE Benchmark
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  • Behavior 1: Thermostat Schedule HVAC working status for 1 week On SIP house AAC house Off
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  • Behavior 1: Thermostat Schedule Energy Consumption of HVAC for 1 week(12/8-19/8) Energy Consumption (kWh)
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  • Behavior 2: Usage of Major Appliances Energy Consumption of Stick House for 5 months Building Energy Data Book (2009) Cooling and Heating 45%
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  • Behavior 2: Usage of Major Appliances (Water Heater) Energy Consumption of Water Heater for 1 week(12/8-19/8) Energy Consumption (kWh)
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  • Behavior 2: Usage of Major Appliances (Water Heater) SIPStickATUS
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  • Behavior 3: Occupancy Movement Occupancy movement in SIP house Temperature Profiles of living room and master bedroom of SIP house Living Room
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  • Behavior 3: Occupancy Movement Living Room in SIP house (aggregated one week data) High Probability
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  • Behavior 3: Occupancy Movement Kitchen in SIP house (aggregated one week data)
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  • Integrate with Energy Models Occupancy Movement Patterns New Thermostat Schedule Building Controls Virtual Test bed (LBNL) Measured Energy and Temperature Data Energy Saving: 15% Comfort time Increase: 25% Appliances
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  • Conclusion and Future Work In this study, we present occupancy behavior and energy usage patterns in four low income houses We also demonstrate possible energy savings based on occupancy movement In future studies, we will: Develop statistical models to describe occupancy behavior in buildings. Integrate with energy consumption patterns
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  • IEA Annex 66 IEA Annex 66 Definition and Simulation of Occupant Behavior in Buildings. 23 countries and regions UTSA BPD group is task leader of subtask 1.
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  • Acknowledgement