Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis

Lee, Soo Jin; Kim, You Jeong; Jin, Hye Jin; Kim, Sung Im; Ha, Soo Yeon; Song, Seung-Yeong

doi:10.3390/en12122327

Cited by 9 publications

(2 citation statements)

References 16 publications

(54 reference statements)

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“…For example, in the U.S. Energy Star benchmarking system [11,21], the predicted energy use intensity (EUI) is calculated by a simple linear regression model which can explain relationship between building operational characteristics and primary energy consumption. Lee et al [22] derived multiple regression for predicting end-use energy consumption such as heating and cooling energy use, etc., based on the survey of 71 residential buildings in Korea. Next, Hong et al [23] analyzed and reviewed various benchmark development methods and gave examples of analyzing relationships through complex top-down methods such as regression analysis.…”

Section: Statistical Techniques Regression Analysismentioning

confidence: 99%

Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database

Kim

2020

Energies

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In an effort to improve the energy efficiency of existing buildings, it is necessary to first evaluate the energy performance of those buildings. Since it is difficult to obtain detailed information on existing buildings, the challenge is how to conduct reliable energy performance assessments with this limited information. As a result, many countries have adopted evaluation systems based on measured energy consumption data for existing buildings. This study aims to analyze the building energy consumption and characteristics using Korea’s national building database and provide an energy performance benchmark for continuous management of the energy performance of existing buildings. We analyzed the relationship between the basic statistical characteristics of the information collected from the national integrated energy database and energy consumption. The total floor area was found to be closely related to energy consumption, and various regression analysis methods were applied and compared to develop a benchmark to explain the trends of energy consumption according to the increase in total floor area. Finally, the developed benchmarks were used to evaluate energy consumption and examine the feasibility of the benchmarks.

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Section: Statistical Techniques Regression Analysismentioning

confidence: 99%

Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database

Kim

2020

Energies

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“…[7]. The proportion of energy consumption related to DHW varies globally, with countries such as the UK, the USA, AUS, and KOR, reporting up to 25% [8], 19% [9], 24% [10], and 15% [11], respectively. Enhancing the energy efficiency of the water sector and reducing associated GHG emissions requires prioritizing measures such as improving the efficiency of water heating processes, adopting renewable energy sources, and implementing water conservation strategies.…”

Section: Introductionmentioning

confidence: 99%

Estimated Impacts of Smart Water Meter Implementation on Domestic Hot Water Consumption and Related Greenhouse Gas Emissions from Case Studies

Msamadya,

Joo,

Lee

et al. 2023

Water

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This study investigates the water–energy–carbon (WEC) nexus in cities across four countries, namely the United Kingdom (UK), the United States of America (USA), Australia (AUS), and South Korea (KOR), over a decade, from 2011 to 2021. The primary objective is to assess the impact of smart water metering (SWM) implementation on the WEC nexus, with a specific focus on domestic hot water (DHW) consumption and associated greenhouse gas (GHG) emissions. The analysis of the collected data reveals diverse patterns among cities with varying levels of SWM implementation. Notably, cities with higher SWM implementation demonstrated significant reductions in water consumption, indicating the effectiveness of the efficient water consumption and demand management achieved through SWM. The study emphasizes the importance of addressing GHG emissions related to water heating, with the carbon intensity of water heating identified as a critical factor in this context. To achieve net reductions in GHG emissions, intensive efforts are required to simultaneously decrease both DHW consumption and the carbon intensity of water heating. The research findings highlight the potential for substantial GHG emissions reductions by combining SWM implementation with the decarbonization of water heating. By recognizing the interdependencies within WEC systems, this study underscores the significance of SWM in advancing toward a carbon-neutral society. In conclusion, this study contributes valuable insights into the WEC nexus and emphasizes the role of SWM in achieving sustainability goals. It advocates for integrated policies to effectively address the interconnected issues of the WEC nexus for effective climate change mitigation.

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Social comparison of home appliance ownership and use and heterogeneous impact on electricity consumption: a case of apartment households in Korea

Park,

Yun

2024

Energy Efficiency

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Efficient energy demand management in the residential sector must be designed based on a sufficient understanding of factors. This study focuses on apartments, a mainstream housing type in Korea. The combination of factor analysis and quantile regression analysis provides insight into the sociocultural meaning of home appliance ownership and use pattern and the differential impact on electricity consumption. The eight representative home appliances closely related to electricity consumption in the household sector are related to household composition, life cycle, economic ability, education, and occupation type. Additionally, the influence of home appliances on electricity consumption is not constant and is differentiated depending on the consumption level of each household. These attempts can provide customized information on specific housing type groups emerging in the future economic development and urban development process. In residential energy demand management, further segmentation and specification of the target and content of information provision will increase the effectiveness of policy achievement.

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Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis

Cited by 9 publications

References 16 publications

Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database

Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database

Estimated Impacts of Smart Water Meter Implementation on Domestic Hot Water Consumption and Related Greenhouse Gas Emissions from Case Studies

Social comparison of home appliance ownership and use and heterogeneous impact on electricity consumption: a case of apartment households in Korea

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