• Journal of Korean Society of Water and Wastewater
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• v.31 no.2
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• pp.177-186
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• 2017

This study concerned the analysis on the efficiency of the conversion of water tank type supply system to direct water supply system to examine the feasibility of the conversion, as well as the calculation of optimal conversion range that enables the supply of safe, high-quality water at stable pressure in accordance with the standards of water supply facility. The results of this research showed that when converting water supply system from water tank type supply system to direct water supply system, more nodal points could be properly converted and more reduction of electricity usage was expected in case water pressure rather than residence time was fixed. This means that higher efficacy can be obtained by fixing water pressure when converting water supply system. However, since the number of the locations that received on-spot inspection was small and the electricity usage measured was not exclusively by water supply facility, it is difficult to judge that such reduction of electricity usage accurately represents reduced electricity usage by water supply facility alone. therefore, after having secured on-spot information about a larger number of locations in apartment complexes that have converted water supply system, and utilizing information about electricity usage exclusively by water supply facility, the proposed method of this research could be applied to accurately deducing expected reduction of electricity usage by water supply facilities of various other apartment complexes. It is also considered possible to deduce an effective operation method of water supply system by finding out an area that shows low pressure or low residual chlorine concentration in the optimal conversion range of water supply, followed by estimating the proper location of pumping station or the proper chlorine dosage at the power purification plant that supply water to the target area.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.52-59
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• 2020

Currently, the domestic electricity rates for houses are charged by applying a progressive level according to monthly electricity usage. Electricity rates rise sharply wWhen the amount of electricity used is large, electricity rates rise sharply. The standardized electricity rate progressive system has limitations in that it lacks consideration of the consumers' power usage patterns and limits consumers' their options. Accordingly, the Ministry of Trade, Industry and Energy and the Korea Electric Power Corporation have been demonstrating the basis of a rate system for housing, which is a method of charging electricity according to the amount of electricity used by season and time. In this paper, 10 electricity usage patterns were derived through from AMI data analysis for 5 five years of 362 apartment complexes located in metropolitan cities. The patterns were, and then applied to the existing domestic electricity rate and time-by-time rates applied to demonstrations, and by time-by-time rates in the US and Australia. The effect of the optional rate by pattern was compared and analyzed. As a result, it was confirmed that benefits occurred in five5 patterns compared to existing rate plans, and the electricity rates increased in 5 five patterns, and t. This phenomenon shows the same phenomenon withis the same as the overseas rates, including domestic rates being demonstrated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1536-1541
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• 2018

For effective electricity consumption in urban railway station such as peak load shaving, it is important to know each electrical load pattern by various usage. The total electricity consumption in the urban railway substation is already measured in Korea, but the electricity consumption for each usage is not measured. The author proposed the deep learning method to estimate the electrical load pattern for each usage in the urban railway substation with public data such as weather data. GRU (gated recurrent unit), a variation on the LSTM (long short-term memory), was used, which aims to solve the vanishing gradient problem of standard a RNN (recursive neural networks). The optimal model was found and the estimation results with that were assessed.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2008.11a
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• pp.261-265
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• 2008

To solve the lack of housing, our country has supplied an enormous volume of apartments, and these days it occupies 75% of our buildings. As apartments occupy most of our housings, the rate of energy usage from them are also high. On this, setting apartment energy reduction as a target, by researching the actual conditions of energy consumption and drawing a basis data, we can apply this as a way of saving energy, rationalization of the scale of energy supply facilities and a standard when planning facilities. To grasp the present condition of energy usage of the urban rental apartment, this research analysed the use of electricity, gas and water monthly and annually of a rental apartment that is located in Daegu. The results showed that in 2003 the electricity usage was 1,198MWh but 1,315MWh in 2007, which means 9% of electricity usage increases every year. The average of water usage was $85,072m^2$ per year and they used $604.2MJ/m^2$ Typical energy consumption unit on $74.4m^2$ of area and $448.8MJ/m^2$ on $105.8m^2$. By showing the usage of energy and water of the urban rental apartment, understanding the tendency and preparing an Typical energy consumption unit standard through this research, apartments should use energy more efficiently.

• Journal of Soil and Groundwater Environment
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• v.22 no.4
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• pp.1-8
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• 2017

Efficient groundwater management requires accurate information about the water volume used. The pumped volume of groundwater can be indirectly estimated using empirical formulae based on electric power consumption. The purpose of this study is to test the accuracy of this indirect method. The Haean basin in Gangwon is located in a rural area, where majority of the groundwater extracted is used for irrigation. The pumped volume of groundwater indirectly estimated from electricity usage using these empirical formulae was compared with the actual pumped volume determined by conducting experiments on April 29 and May 19, 2017. The field survey collected data on electricity usage, pumped volume, and groundwater levels. Based on this measured data, correlations were calculated between electricity usage and pumping volume, as well as groundwater level and pumping rate. The results show that electricity usage and pumped volume measured for both wells (YHE1 and YHE2) are highly correlated (r=0.99, p<0.001). However, for YHE1, notably, the correlation between the groundwater level and pumping rate was not significant, and only some correlations were identified for these variables for the YHE2 test well. The average error with respect to the estimation of the actual pumped volume from the existing formula (1) and formulae (2) and (3) are +399% and -88%, respectively. To reduce these errors, these formulae need to consider other factors affecting the pumped volume.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.12
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• pp.101-106
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• 2011

An utilization of electricity usage measured data by region and time through the consumer portal system for building and large consumer are suggested. Electricity usage data by region and time can't be measured by traditional approach. A measured data from smart meters which are installed various regions can be utilized to set up a management of electricity peak demand.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.969-977
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• 2021

We cluster the electricity consumption of households in A-apartment in Seoul, Korea using Hierarchical K-means clustering algorithm. The data is recorded from the advanced metering infrastructure (AMI), and we focus on the electricity consumption during evening weekdays in summer. Compare to the conventional clustering algorithms, Hierarchical K-means clustering algorithm is recently applied to the electricity usage data, and it can identify usage patterns while reducing dimension. We apply Hierarchical K-means algorithm to the AMI data, and compare the results based on the various clustering validity indexes. The results show that the electricity usage patterns are well-identified, and it is expected to be utilized as a major basis for future applications in various fields.

• Environmental and Resource Economics Review
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• v.25 no.2
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• pp.141-178
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• 2016

This paper, using AMR (Automatic Meter Reading) electricity data accurately measured in real time, analyses the characteristics and patterns of temperature effect on the industrial electricity usage. For this goal, the paper constructs and estimates a model which captures the properties of AMR time series including long-term trends, mid-term temperature effects, and short-term special day effects. Based on the estimated temperature response function and the temperature effect, we categorize the whole industry into two groups: one group with sharp temperature effect and the other with weak temperature effect. Furthermore, the industry group with sharp temperature effect is classified into a summer peak industry group and a winter peak industry group, based on the estimates of the temperature response function. These empirical results carry practical policy implications on the real time electricity demand management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.97-115
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• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.

• Journal of the Korean housing association
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• v.20 no.6
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• pp.39-46
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• 2009

It has been a serious problem to consume the energy of apartment while increasing to use of heating & cooling System because of residence environmental upgrades. Great attention has been shown to the problem of the rental apartment, so there are few reports of energy consumption about the rental apartment in korea. To solve the lack of housing, our country has supplied an enormous volume of apartments, and these days it occupies 75% of our buildings. As apartments occupy most of our housings, the rate of energy usage from them are also high. On this, setting apartment energy reduction as a target, by researching the actual conditions of energy consumption and drawing a basis data, we can apply this as a way of saving energy, rationalization of the scale of energy supply facilities and a standard when planning facilities. To grasp the present condition of energy usage of the urban rental apartment, this research analysed the use of electricity, gas and water monthly and annually of a rental apartment that is located in Daegu. The results showed that in 2003 the electricity usage was 1,198MWh but 1,315MWh in 2007, which means 9% of electricity usage increases every year. The average of water usage was $85,072\;m^2$ per year and typical energy consumption unit was $604.2\;MJ/m^2$ on $74.4\;m^2$ of area and $448.8\;MJ/m^2$ on $105.8\;M^2$. By showing the usage of energy and water of the urban rental apartment, understanding the tendency and preparing an typical energy consumption unit standard through this research, apartments should use energy more efficiently.