The rise of edge computing has promoted the development of the industrial internet of things (IIoT). Supported by edge computing technology, data acquisition can also support more complex and perfect application requirements in industrial field. Most of traditional sampling methods use constant sampling frequency and ignore the impact of changes of sampling objects during the data acquisition. For the problem of sampling distortion, edge data redundancy and energy consumption caused by constant sampling frequency of sensors in the IIoT, a data-driven adaptive sampling method based on edge computing is proposed in this paper. The method uses the latest data collected by the sensors at the edge node for linear fitting and adjusts the next sampling frequency according to the linear median jitter sum and adaptive sampling strategy. An edge data acquisition platform is established to verify the validity of the method. According to the experimental results, the proposed method is more effective than other adaptive sampling methods. Compared with constant sampling frequency, the proposed method can reduce the edge data redundancy and energy consumption by more than 13.92% and 12.86%, respectively.
Ground source (geothermal) heat pumps (GSHPs) can meet the thermal demands of buildings in an energy-efficient manner. The current high installation costs and long payback period limit the attractiveness of GSHP installation in the United States. Vertical borehole ground heat exchangers (VBGHEs), which are commonly used in GSHP systems, contribute most to the cost premium of GSHPs. Reducing cost of VBGHEs could help increase market penetration of GSHP systems. This paper reviews recent developments for VBGHEs, including improvements in borehole heat transfer and borehole field layout, integration with thermal energy storage, and new design tools. Improvements in the borehole design and materials are more likely to be justified when the ground has high thermal conductivity. Integrating thermal energy storage can provide additional value to the GSHP system, especially when flexible electric demand at buildings becomes more valuable. Advanced design tools for VBGHEs that account for the thermal response of irregularly shaped borehole fields and that are more closely integrated with whole building energy simulation programs may facilitate more innovations and optimization of GSHP system designs.
More than 20% of electricity generated in the United States each year is consumed for meeting the thermal demands (e.g., space cooling, space heating, and water heating) in residential and commercial buildings. Integrating thermal energy storage (TES) with building's HVAC systems has the potential to reshape the electric load profile of the building and mitigate the mismatch between the renewable generation and the demand of buildings. A novel ground source heat pump (GSHP) system integrated with underground thermal energy storage (UTES) has been proposed to level the electric demand of buildings while still satisfying their thermal demands. This study assessed the potential impacts of the proposed system with a bottom-up approach. The impacts on the electricity demand in various electricity markets were quantified. The results show that, within the capacity of the existing electric grids, the maximum penetration rate of the proposed system in different wholesale markets could range from 51% to 100%. Overall, about 46 million single-family detached houses can be retrofitted into the proposed system without increasing the annual peak demand of the corresponding markets. By implementing the proposed system at its maximum penetration rate, the grid-level summer peak demand can be reduced by 9.1% to 18.2%. Meanwhile, the annual electricity consumption would change by −12 % to 2%. The nationwide total electricity consumption would be reduced by 9%.
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