• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.2
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• pp.38-48
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• 2001

Kalman Filter model of demand for residental water and consumption pattern wore tested for their ability to explain the hourly residental demand for water in metro-politan distribution system. The daily residental demand can be obtained from Kalman Filter model which is optimized by statistical analysis of input variables. The hourly residental demand for water is calculated from the daily residental demand and consumption pattern. The consumption pattern which has 24 time rates is characterized by data granulization in accordance with season kind, weather and holiday. The proposed approach is applied to water distribution system of metropolitan areas in Korea and its effectiveness is checked.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.991-994
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• 2016

This paper presents a load management method based on OpenADR of smart grid. Previous demand side algorithm is restricted on reducing peak power. But, in this paper we suggest a method of performing the energy-saving control according to the power price utilizing building automatic control system installed on the customer side in the case of hourly differential pricing signal is transmitted to the open automated demand response system. And, we showed the integrated demand management software for 3 buildings.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.789-794
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• 2006

The potential impacts of climate change on heating and cooling energy demand were investigated by means of transient building energy simulations and hourly weather data scenarios for Inchon. Future trends for the 21 st century was assessed based oil climate change scenarios with 7 global climate models(GCMs), We constructed hourly weather data from monthly temperatures and total incident solar radiation ($W/m^2$) and then simulated heating and cooling load by Trnsys 16 for Inchon. For 2004-2080, the selected scenarios made by IPCC foresaw a $3.7-5.8^{\circ}C$rise in mean annual air temperature. In 2004-2080, the annual cooling load for a apartment with internal heat gains increased by 75-165% while the heating load fell by 52-71%. Our analysis showed widely varying shifts in future energy demand depending on the season. Heating costs will significantly decrease whereas more expensive electrical energy will be needed of air conditioning during the summer.

• Journal of Environmental Science International
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• v.31 no.1
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• pp.33-42
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• 2022

The objective of this study is to determine the appropriate size of the inlet pipe diameter and thereby conduct hydraulic analysis for the Korean water distribution network. To this end, the data tables for equivalent pipe diameters and outflow rates presently employed in Korea were adopted. By incorporating the table of equivalent pipe diameters, it was found that the size of the inlet pipe diameter was overestimated, which can cause shortage of water pressure and malfunctioning or insufficiency of outflow rate in the corresponding adjacent region. However, by conducting hydraulic analysis based on the table of outflow rates, relatively reasonable flow rates were observed. Furthermore, by comparing the real demand-driven analysis (RDDA) approach and demand-driven analysis (DDA) approach toward managing the huge water demand, it was observed that DDA could not effectively respond to real hourly usage conditions, whereas RDDA (which reflects the hourly effects of inlet pipe diameter and storage tanks) demonstrated results similar to that of real water supply.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.29-32
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• 1993

A technique computing short-term load foadcasting is essential for monitoring and controlling power system operation. This paper shows the use of general exponential smoothing to develop an adaptive forecasting system based on observed value of hourly demand. Forecasts of hourly load with lead times of one to twenty-four hours are computed at hourly intervals throughout the week. Standard error for lead times of one to twenty-four hour range from three to four percent average load. Studies are planned to investigate the use of weather influence to increase forecast accuracy.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.11
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• pp.636-642
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• 2009

Energy consumption data are surveyed and measured to develop energy demand models for hospital buildings as part of a complete package. Daily consumption profiles for electricity, heating, cooling and hot water are surveyed for 14 carefully chosen hospitals to establish energy demand patterns for a time span of a year. Then the hourly demand patterns of the 4 loads are field-measured for different seasons and statistically analyzed to provide higher resolution models. Used in conjunction with energy demand models for other types of buildings, the high resolution of 8760 hour energy demand models for a hospital for a typical year will serve as building blocks for the comprehensive model that allows the estimation of the combined loads for arbitrary mixtures of buildings.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.10
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• pp.553-558
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• 2009

Energy demand characteristics of hotel, hospital, and office building are compared to provide guidelines for combining building in community energy system design. The annual, monthly, and daily energy demand patterns for electricity, heating, hot water and cooling are qualitatively compared and important features are delineated based on the energy demand models. Key statistical values such as the mean, the maximum are also provided. Important features of the hourly demand patterns are summarized for weekdays and weekends. Substantial variations in both magnitudes and patterns are observed among the 3 building types and smart grouping or combination of building type and size is essential for a successive energy supply.

• Journal of the Korean Solar Energy Society
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• v.26 no.3
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• pp.119-125
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• 2006

The impacts of climate changes on building energy demand were investigated by means of the degree-days method. Future trends for the 21st century was assessed based on climate change scenarios with 7 global climate models(GCMs). We constructed hourly weather data from monthly temperatures by Trnsys 16. A procedure to estimate heating degree-days (HDD) and cooling degree-days (CDD) from monthly temperature data was developed and applied to three scenarios for Inchon. In the period 1995-2080, HDD would fall by up to 70%. A significant increase in cooling energy demand was found to occur between 1995-2004(70% based on CDD). During 1995-2080, CDD would Increase by up to 120%. Our analysis shows widely varying shifts in future energy demand depending on season. Heating costs in winter will significantly decrease whereas more expensive electrical cooling energy will be needed.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.1051-1064
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• 2015

Currently, the H purification plant determines the hourly water intake amount based on operator experience and skill. Therefore, inevitably, there are deviations among operators. While meeting time-varying demand and maintaining the proper water level in the clean water reservoir, the methodology for minimizing electricity cost, when dealing with different electricity rate time zones, is a very complicated problem, which is beyond an operator's capability. To solve this problem, a linear programming (LP) model is proposed, which can determine the optimal hourly water intake amount for minimizing the daily electricity cost. It is shown that an inaccurate estimate for the hourly water usage in the demand areas causes the water level constraint to be violated, which is the weak point of the proposed LP method. However, several examples with real-field data show that we can practically and safely solve this problem with safety margins. It is also shown that the safety margin method still works effectively whether the estimate is accurate or not. The operators need not attend the site at all times under the proposed LP method, and we can additionally expect reductions in labor costs.

• 전기의세계
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• v.29 no.4
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• pp.260-264
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• 1980

In this paper, a new algorithm is derived for short term load forecasting. The load model is represented by the state variable form to exploit the Kalman filter techniques. The suggested model has advantages that it is unnecessarty to obtain the coefficients of the harmonic components and its coefficients are not explicitly included in the model. Case studies were carried out for the hourly power demand forecasting of the Korea electrical system.