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A Study on Winter Season Measurement Results to cope with Dynamic Pricing for the VRF Systemopen accessA Study on Winter Season Measurement Results to cope with Dynamic Pricing for the VRF System

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A Study on Winter Season Measurement Results to cope with Dynamic Pricing for the VRF System
Authors
김환용김민석이제헌송영학
Issue Date
2015
Publisher
대한건축학회
Keywords
TOU(Time On Use); VRF System; Field Measurement; Regression Analysis; Energy Consumption
Citation
Architectural Research, v.17, no.3, pp 109 - 115
Pages
7
Indexed
KCI
Journal Title
Architectural Research
Volume
17
Number
3
Start Page
109
End Page
115
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/17955
DOI
10.5659/AIKAR.2015.17.3.109
ISSN
1229-6163
2383-5575
Abstract
The dynamic pricing of electricity, where the electricity rate increases in a time zone with a high demand for electricity is typically applied to a building whose power reception capacity is greater than a certain size. This includes the time of use(TOU) electricity pricing in Korea which can induce the effect of reducing the power demand of a building. Meanwhile, a VRF (Variable Refrigerant Flow) system that uses electricity is regarded as one of the typical heating and cooling systems along with central air conditioning (central HVAC) for its easy operation and application to the building. Thus, to reduce power energy and operating costs of a building in which the TOU and VRF systems are applied simultaneously, we suggested a control for changing the indoor temperature setting within the thermal comfort range or limiting the rotational speed of an inverter compressor. In this study, to describe the features of the above-mentioned control and verify its effects, we evaluated the results obtained from the analysis of its operation data. Through the actual measurements in winter operations for 73 days since mid- December 2014, we confirmed a reduction of 10.9% in power energy consumption and 12.2% in operating costs by the new control. Also, a reduction of 13.3% in power energy consumption was identified through a regression analysis.
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