• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1793-1799
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• 2016

As one of the main trends in global industries is eco-friendly energy, the interest on Electric Vehicle(EV) has been increased. However, if large amount of EVs start to charging, it could cause rapid increase in demand power of the power system. To guarantee stable operation of the power system, those unpredictable power consume should be mitigated. In this paper, therefore, we propose a practical smart EVs charging scheme to prevent the rapid increase of the demand power and also provide load flattening function. For that we considered Time-of-Use(ToU) price and actual data such as driving pattern and parameters of distribution system. Simulation results show that the proposed method provides proper load flattening function while preventing the rapid increase of the demand power of the power system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.25-33
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• 2008

This paper presents a new approach of a evaluation of location marginal prices(LMPs) considering demand response resources in the competitive electricity market. The stabilization of the electric power supply and demand balance has been one of the major important activities in electric power industry. Recently, much attention is paid to the demand-side resources which are responsive to incentives or time-varying prices and existing power system planning and operation activities are incorporated with the so-called demand response resources. In this paper, we first present an analytical method for calculation of LMPs considering demand response resources and then break down the LMPs into three components. In this study, we assume that Korean power system consists of two major regions, one which is the metropolitan and the other is non-metropolitan region. In the case study, we have considered several LMPs cases with different use of locational demand response resource and we can obtain a locational signal to demand response resources. Also, the economics of demand response resources are evaluated, compared with the increase of transmission line capacity and of generation capacity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1503-1510
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• 2014

This study organizes scenarios on the power supply plans and electricity load forecasts considering their uncertainties and estimates natural gas quantity for electricity generation, total electricity supply cost and air pollutant emission of each scenario. Also the analysis is performed to check the properness of government's natural gas demand forecast and the possibility of achieving the government's CO2 emission target with the current plan and other scenarios. In result, no scenario satisfies the government's CO2 emission target and the natural gas demand could be doubled to the government's forecast. As under-forecast of natural gas demand has caused the increased natural gas procurement cost, it is required to consider uncertainties of power plant construction plan and electricity demand forecast in forecasting the natural gas demand. In addition, it is found that CO2 emission target could be achieved by enlarging natural gas use and demand-side management without big increase of total costs.

• Journal of The Korean Digital Architecture Interior Association
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• v.3 no.2
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• pp.30-38
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• 2003

The purpose of this study was to analyze the demand estimation erection of lifetime sports facilities for making an accurate estimate of its demand on the basis of the rate of the people participating in lifetime sports activities. Participation rate was determined on the basis of the fact-finding survey [by the Ministry of Culture and Tourism(2000)] as a basis research on facilities demand, and its demand was calculated by making an estimate of facilities demand. An estimate of facilities demand was made in the equation by participation population, facilities demand for each person, sports space area for each person, time of sports, cycle of sports, possible time to use of sports space. Facilities demand for each person by sports event is the following: $swimming;0.03m^2$, $basketball;0.045m^2$, martial arts(taekwondo, judo, korean fencing);0.003 $75m^2$, $aerobics;0.0289m^2,\;health;0.00326m^2,\;badminton;0.00323m^2,\;tennis;0.01429m^2,\;soccer;0.1112m^2,\;squash;0.01323m^2$.

• Atmosphere
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• v.24 no.4
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• pp.515-522
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• 2014

In this study it is attempted to estimate the possible change in energy use for residential and commercial sector in Korea under a future climate change senario. Based on the national energy use and observed temperature data during the period 1991~2010, the optimal base temperature for determining heating and cooling degree days (HDD and CDD) is calculated. Then, net changes in fossil fuel and electricity uses that are statistically linked with a temperature variation are quantified through regression analyses of HDD and CDD against the energy use. Finally, the future projection of energy use is estimated by applying the regression model and future temperature projections by the CMIP5 results under the RCP8.5 scenario. The results indicate that, overall, the net annual energy use will decrease mostly due to a large decrease in the fossil fuel use for heating. However, a clear seasonal contrast in energy use is anticipated in the electricity use; there will be an increase in a warm-season demand for cooling but a decrease in a cold-season demand for heating.

• IE interfaces
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• v.16 no.4
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• pp.400-410
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• 2003

Most of the demand forecasting which have been studied is about long-term time series over 15 years demand forecasting. In this paper, we set up the most optimal ARIMA model for the short-term time series demand forecasting and suggest demand forecasting system for short-term time series by appraising suitability and predictability. We are going to use the univariate ARIMA model in parallel with the bivariate transfer function model to improve the accuracy of forecasting. We also analyze the effect of advertisement cost, scale of branch stores, and number of clerk on the establishment of marketing policy by applying statistical methods. After then we are going to show you customer's needs, which are number of buying products. We have applied this method to forecast the annual sales of refrigerator in four branch stores of A company.

• Environmental and Resource Economics Review
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• v.11 no.3
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• pp.447-463
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• 2002

The heat demand prediction is an essential issue in management of district heating system. Without an accurate prediction through the lead-time period, it might be impossible to make a rational decision on many issues such as heat production scheduling and heat exchange among the plants which are very critical for the district heating company. The heat demand varies with the temperature as well as the time nonlinearly. And the parametric specification of the heat demand model would cause a misspecification bias in prediction. A nonparametric model for the short-term heat demand prediction has been developed as an alternative to avoiding the misspecification error and tested with the actual data. The prediction errors are reasonably small enough to use the model to predict a few hour ahead heat demand.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1956-1963
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• 2010

Studies on the development of various energy management programs and real-time bidirectional information infrastructures have been actively conducted to promote the reduction of power demands and CO2 emissions effectively. In the conventional energy management programs, the demand response program that can transition or transfer the power use spontaneously for power prices and other signals has been largely used throughout the inside and outside of the country. For measuring the effect of such demand response program, it is necessary to exactly estimate short-term loads. In this study, the power consumption patterns in both individual and group consumers were analyzed to estimate the exact short-term loads, and the relationship between the actual power consumption and seasonal factors was also analyzed.

• Land and Housing Review
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• v.3 no.4
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• pp.343-355
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• 2012

The purpose of this paper is to propose reasonable improvements of demand estimation methods of commercial site through the case study. Thus, we investigated the problems and limitation of demand estimation methods and process applied to primary and secondary new towns in Korea. And we suggested the way to reduce error of demand estimation and to raise its objectivity. The result of case analysis is as follows; firstly, it was insufficient to consider location, hierarchy and change of land use like mixed-use development in commercial site. Secondly, improper comparable group or operated relevant index data in the same light were selected the aggregated unit requirement method such as comparative analogy method and planning guidelines. Thirdly, there were many cases that demand estimation value was amended arbitrarily, and it tends to occur a serious reliability problem. Therefore, to improve these problems and to make better use of demand estimation hereafter are required the sublation of arbitrary commercial sphere's settings, the making of comparative group considered development conditions, and putting forward objective revision basis.

• Environmental and Resource Economics Review
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• v.33 no.1
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• pp.59-86
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• 2024

Recently, research on city gas demand is increasing by reflecting the characteristics of each region. The similarity of the social structure of the adjacent region and the density of the supply infrastructure induce spatial correlation with the clustering that has a microscopic relationship between regions. Accordingly, as a result of analyzing the spatial correlation after dividing the demand for city gas for civilian use into a total of 54 regions based on the jurisdiction of 34 city gas companies, it was confirmed that there was a positive spatial correlation from a global and local perspective. In this study, the demand for city gas for civilian use for 54 regions from January 2014 to December 2022 was composed of panel data, and the spatial panel regression analysis and the general panel regression analysis were compared, and it was found that the spatial error model (SEM) was the most suitable model. This presents policy and practical implications by confirming that the demand for city gas for civilian use in one region has a significant relationship with the adjacent region.