• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.941-953
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• 2022

In this study, monthly water use data were collected for 5 years from the 65 local governments included in the Han-river basin and a typical water usage ratios and patterns were calculated. The difference in water shortage was compared by considering the water usage patterns using the water balance and budget analysis model (MODSIM) and data base. As a result, it was confirmed that the change occurred in the range of -3.120% to +4.322% compared to the monthly constant ratio by period. In addition, when applying the patterns in the water balance model, 17 of the 28 middle watershed showed changes in the quantity of water shortage and the domestic and industrial water shortage would decrease about 8.0% during the maximum drought period. If it is applied in conjunction with predictive research on water usage patterns reflecting climate change, social and regional characteristics in the future, it will be possible to establish a more realistic water supply forecasts and a reliable national water resources plan.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.1-8
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• 2024

Persistent droughts due to climate change will intensify water shortage problems in Korea. According to the 1st National Water Management Plan, the shortage of domestic and industrial waters is projected to be 0.07 billion m³/year under a 50-year drought event. A long-term prediction of water demand is essential for effectively responding to water shortage problems. Unlike industrial water, which has a relatively constant monthly usage, domestic water is analyzed on monthly basis due to apparent monthly usage patterns. We analyzed monthly water usage patterns using water usage data from 2017 to 2021 in Chungcheong, South Korea. The monthly water usage rate was calculated by dividing monthly water usage by annual water usage. We also calculated the water distribution rate considering correlations between water usage rate and climate variables. The division method that divided the monthly water usage rate by monthly average temperature resulted in the smallest absolute error. Using the division method with average temperature, we calculated the water distribution rates for the Chungcheong region. Then we predicted future water usage rates in the Chungcheong region by multiplying the average temperature of the SSP5-8.5 scenario and the water distribution rate. As a result, the average of the maximum water usage rate increased from 1.16 to 1.29 and the average of the minimum water usage rate decreased from 0.86 to 0.84, and the first quartile decreased from 0.95 to 0.93 and the third quartile increased from 1.04 to 1.06. Therefore, it is expected that the variability in monthly water usage rates will increase in the future.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.33 no.12
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• pp.53-63
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• 2017

The purpose of this study is to present an integrated analysis for energy use and its patterns as vertical locations of the dwelling units in apartment buildings which are located in an urban area and constructed by a renowned contractor. In order to enhance the effectiveness of the method, the original data of electricity, water, and gas bills which directly reflect the energy use are sorted and analyzed into several groups as vertical locations in each building. And also, by use of comparing and contrasting the data on a monthly and yearly basis, the accuracy of analyses for seasonal energy use and its patterns is strengthened. Comparative analyses used in this study describe the results that vertical locations of dwelling units do not have much influence on electricity and water usage, but are closely related with gas usage for a heating season. According to the analysis of gas usage, the units on the ground and right above pilotis need enhancement in the insulations for heating to mitigate energy loss. Also, the analysis for the middle floor units in each group describe the fact that the gas usage of the units on the ground is consumes 1.5 times greater than that of the typical floors. Therefore, enhanced insulation strategies need to be considered against the adverse condition that the heat loss increases as the wall facing the outside air increases or as the wind velocity increases through the pilotis.

• Journal of the Korean Solar Energy Society
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• v.37 no.5
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• pp.39-47
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• 2017

In a hot water system using solar energy, solar heat is not simply collected by the heat collecting plate, but by heat exchange between the solar collector (flat or vacuum type) and the hot water storage tank. Therefore, the amount of collected solar energy depends on the hot water usage patterns that determine the temperature of the thermal storage tank. Also, if the temperature of the hot water stored in the storage tank exceeds the dangerous temperature during the summer, the heat must be released for safety. If the temperature of the hot water in the storage tank is low, it is necessary to heat by the auxiliary heat source. In this study, three buildings are defined as hotel, swimming pool, and school facilities. And we calculated the released heat energy, auxiliary heat source, and pure storage heat energy based on different hot water usage patterns and installation angle of the solar collectors.

• Korean Journal of Computational Design and Engineering
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• v.18 no.6
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• pp.451-460
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• 2013

This paper presents the necessary elements and data flow in developing a monitoring system of energy usage for apartment houses with a Smart TV. Energy consumption data in each home are collected and analyzed in the HUB station by way of measuring instruments. And the amount of energy usage, such as electricity, gas, hot water, heating, water and other utilities are displayed through the Smart TV application. Energy consumption Database in the HUB station are processed and displayed in the browser of a Smart TV through XML, JAVASCRIPT and Flash. Smart TV users can get the energy consumption status through the energy consumption analysis display of the Smart TV application and improve the energy efficiency by comparing the usage patterns with neighboring houses. And the application display energy usage information, consumption ranking, rates to user as well. Furthermore, usage of last month or year can be compared to help to reduce the energy usage. The proposed system can provide the information about the amount of energy use to be reduced and the warning on the waste of energy.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1083-1093
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• 2021

It is an essential to predict water usage for establishing an optimal supply operation plan and reducing power consumption. However, the water usage by consumer has a non-linear characteristics due to various factors such as user type, usage pattern, and weather condition. Therefore, in order to predict the water consumption, we proposed the methodology linking various techniques that can consider non-linear characteristics of water use and we called it as KWD framework. Say, K-means (K) cluster analysis was performed to classify similar patterns according to usage of each individual consumer; then Wavelet (W) transform was applied to derive main periodic pattern of the usage by removing noise components; also, Deep (D) learning algorithm was used for trying to do learning of non-linear characteristics of water usage. The performance of a proposed framework or model was analyzed by comparing with the ARMA model, which is a linear time series model. As a result, the proposed model showed the correlation of 92% and ARMA model showed about 39%. Therefore, we had known that the performance of the proposed model was better than a linear time series model and KWD framework could be used for other nonlinear time series which has similar pattern with water usage. Therefore, if the KWD framework is used, it will be possible to accurately predict water usage and establish an optimal supply plan every the various event.

• Spatial Information Research
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• v.19 no.1
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• pp.61-72
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• 2011

Greenhouses gas emission due to usage of fossil fuel has been known as one of the main causes of global warming. Fundamentally, greenhouse gas is a by-product of economic activity. Since majority of economic activity happens in an urban setting, a countermeasure in an urban setting is needed. Therefore, an analysis of relationship between carbon dioxide emission and urban form will be investigated for urban planning and management in the future. The purpose of this study is to analyze the relationship between carbon dioxide emission and urban spatial patterns, and suggesting an urban form with low carbon dioxide emission. In order to achieve this, first theoretical analysis was carried out on urban spatial patterns related to physical size, usage rate, and activity level. Secondly, Seoul's dam on electricity, natural gas, local heating, petroleum, and water usage and mapping a carbon dioxide emission map. Thirdly, relationship between carbon dioxide emission and urban spatial patterns are analyzed and urban spatial patterns that affects energy usage in urban setting was elucidated, and elicited implications on future directions on urban planning based on our analyses above.

• Journal of Energy Engineering
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• v.21 no.4
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• pp.435-443
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• 2012

The combination of space shortage and the high population density concentrated in urban areas of South Korea has resulted in the growth of large-scale high-rise residential complexes, naturally affecting water and hot water usage patterns as well. But the current designs for water and hot water supply in South Korea rely mostly on international design standards and data calculated on site due to the severe shortage of basic data in relation to actual use, which result in the frequent problem of the under-or over-design of water and hot water supply. The following study measures the hot water supplier's conditions and the user's heat usage to realize the amount of time required for hot water supply load generation and the pattern of actual use in order to create basic data for effective hot water supply facility design and maintenance.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.1
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• pp.23-29
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• 2008

Throughout the analysis of field data from water distribution system, valid parameters were determined that can be included in the water service and design plan. This study investigates water consumption patterns to understand the variation of water-demand structures utilizing the pattern analysis of domestic purpose water. Water use data were collected by a public water resources management firm in Korea, Kwater, for 140 houses monitored during three years. Flow meters were installed at the faucet for drinking water, the shower booth, the laundry machine, bathroom sink, toilet, and garden faucet. Data was filtered using multiple physically meaningful criteria to improve analysis credibility. Mann Kendall and Spearman's Rho tests were used to carry out the analysis. Distinct factors of water consumption patterns can be determined for both increasing and decreasing trends of water use. Throughout the data analysis, the characterization of terms was classified and analyzed by the condition of the location of water-demand. Analysis of this data provide a physical basis for the parameter configuration of a reasonable design for a domestic water demand prediction model.

• Journal of Korean Society of Water and Wastewater
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• v.36 no.3
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• pp.149-165
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• 2022

The water consumption data of individual consumers must be analyzed and forecast to establish an effective water demand management plan. A k-mean cluster model that can monitor water use characteristics based on hourly water consumption data measured using automated meter reading devices and demographic factors is developed in this study. In addition, the quantification model that can estimate the daily water consumption is developed. K-mean cluster analysis based on the four clusters shows that the average silhouette coefficient is 0.63, also the silhouette coefficients of each cluster exceed 0.60, thereby verifying the high reliability of the cluster analysis. Furthermore, the clusters are clearly classified based on water usage and water usage patterns. The correlation coefficients of four quantification models for estimating water consumption exceed 0.74, confirming that the models can accurately simulate the investigated demographic data. The statistical significance of the models is considered reasonable, hence, they are applicable to the actual field. Because the use of automated smart water meters has become increasingly popular in recent year, water consumption has been metered remotely in many areas. The proposed methodology and the results obtained in this study are expected to facilitate improvements in the usability of smart water meters in the future.