Toward A Dynamic Comfort Model for Human-Building Interaction in Grid-Interactive Efficient Buildings: Supported by Field Data
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arXiv
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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| _version_ | 1866915149783236608 |
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| author | Kang, SungKu Sharma, Kunind Pathak, Maharshi Casavant, Emily Bassett, Katherine Pavel, Misha Fannon, David Kane, Michael |
| author_facet | Kang, SungKu Sharma, Kunind Pathak, Maharshi Casavant, Emily Bassett, Katherine Pavel, Misha Fannon, David Kane, Michael |
| contents | Controlling building electric loads could alleviate the increasing grid strain caused by the adoption of renewables and electrification. However, current approaches that automatically setback thermostats on the hottest day compromise their efficacy by neglecting human-building interaction (HBI). This study aims to define challenges and opportunities for developing engineering models of HBI to be used in the design of controls for grid-interactive efficient buildings (GEBs). Building system and measured and just-in-time surveyed psychophysiological data were collected from 41 participants in 20 homes from April-September. ASHRAE Standard 55 thermal comfort models for building design were evaluated with these data. Increased error bias was observed with increasing spatiotemporal temperature variations. Unsurprising, considering these models neglect such variance, but questioning their suitability for GEBs controlling thermostat setpoints, and given the observed 4°F intra-home spatial temperature variation. The results highlight opportunities for reducing these biases in GEBs through a paradigm shift to modeling discomfort instead of comfort, increasing use of low-cost sensors, and models that account for the observed dynamic occupant behavior: of the thermostat setpoint overrides made with 140-minutes of a previous setpoint change, 95% of small changes ( 2°F) were made with 120-minutes, while 95% of larger changes ( 10°F) were made within only 70-minutes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_07206 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Toward A Dynamic Comfort Model for Human-Building Interaction in Grid-Interactive Efficient Buildings: Supported by Field Data Kang, SungKu Sharma, Kunind Pathak, Maharshi Casavant, Emily Bassett, Katherine Pavel, Misha Fannon, David Kane, Michael Computers and Society Systems and Control Controlling building electric loads could alleviate the increasing grid strain caused by the adoption of renewables and electrification. However, current approaches that automatically setback thermostats on the hottest day compromise their efficacy by neglecting human-building interaction (HBI). This study aims to define challenges and opportunities for developing engineering models of HBI to be used in the design of controls for grid-interactive efficient buildings (GEBs). Building system and measured and just-in-time surveyed psychophysiological data were collected from 41 participants in 20 homes from April-September. ASHRAE Standard 55 thermal comfort models for building design were evaluated with these data. Increased error bias was observed with increasing spatiotemporal temperature variations. Unsurprising, considering these models neglect such variance, but questioning their suitability for GEBs controlling thermostat setpoints, and given the observed 4°F intra-home spatial temperature variation. The results highlight opportunities for reducing these biases in GEBs through a paradigm shift to modeling discomfort instead of comfort, increasing use of low-cost sensors, and models that account for the observed dynamic occupant behavior: of the thermostat setpoint overrides made with 140-minutes of a previous setpoint change, 95% of small changes ( 2°F) were made with 120-minutes, while 95% of larger changes ( 10°F) were made within only 70-minutes. |
| title | Toward A Dynamic Comfort Model for Human-Building Interaction in Grid-Interactive Efficient Buildings: Supported by Field Data |
| topic | Computers and Society Systems and Control |
| url | https://arxiv.org/abs/2303.07206 |