Comprehensive assessment of operational performance of coupled natural ventilation and thermally active building system via an extensive sensor network

ENERGY AND BUILDINGS(2022)

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摘要
The thermally active building system (TABS) has emerged as an energy-efficient measure for cooling and heating buildings since it facilitates the use of low-energy technologies, such as free cooling with geothermal sources and heating with low-temperature heat pumps. However, the control of TABS is challenging due to its high thermal inertia. Though a considerable amount of research has been done using simulations or small-scale experiments, few studies have published detailed long-term measured data of TABS operation. In addition, there has been little discussion on the control integration of slow acting TABS with other fast-acting systems, such as natural ventilation. To fill these gaps, this paper presents a comprehensive assessment of the operational performance of the coupled NV and TABS using one-year high-fidelity measured data of an experimental small office building with an extensive sensor network located in Cambridge, Massachusetts. First, the coupled system and control design are described. Then, the thermal, energy and detailed control performance are assessed by comparing with design intents and simulated predictions. It is found that the coupled system demonstrates its effectiveness to control indoor thermal environment while achieving high energy efficiency. The annual energy consumptions are 11.5 kWh/m(2) for heating and 1.3 kWh/m(2) for cooling. The heating COP, including heat pump and two water pumps, is 3.5, and the cooling COP is 18.3 by utilizing free cooling from geothermal resources. The issues in operation are identified, including system/equipment faults, implementation of controls, and settings by building operators. Finally, lessons learned from this project are discussed and the strategies for improvement are summarized.(C) 2022 Elsevier B.V. All rights reserved.
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关键词
Thermal Active Building System (TABS), Natural Ventilation, Operational Performance, Sensor Network
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