• 대한전기학회논문지
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• 제34권10호
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• pp.389-398
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• 1985

Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

• 대한전기학회논문지:전력기술부문A
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• 제55권12호
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• pp.570-575
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• 2006

This paper develops methodology in order to consider CHP(Combined Heat and Power) capacity in the Basic Plan of Long Term Electricity Supply & Demand. We develop generating cost of CHP considering electric and heat. Also we develop mixed load duration curve which includes the electric load and heat load and then apply CHP capacity to SCM(Screening Curve Method) considering CHP feature. Accordingly, it decide the optimal CHP capacity in the Basic Plan of Long Term Electricity Supply & Demand. Also, We perform the sensitivity analysis according to cost variation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.165-167
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• 2004

End-user electric power consumption trends shows various load curves dependant on industry, contract, season, day and time. Analysis of end-user electric power consumption trends has a key role to efficiently meet electricity demand. There are several factors of change in electricity demand such as the change of weather, international conflict, and industrial trends during summer. This paper has analyzed the analysis the end-user electric power consumption trends using the load curve during international conflict. We observed that international conflict decreased electric demand by $5.4\%$. This increase is not significant, and therefore we conclude that the international conflict has not greatly affected Korea's electricity demands. This paper provides useful information so as to mon: efficiently perform demand side management.

• 전기학회논문지
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• 제61권4호
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• pp.534-541
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• 2012

This paper tries to elicit an optimal generation mix of Korea. Two approaches, using the screening curve method and taking advantage of a generation expansion planning tool, WASP-IV, are applied in getting the mix. The data used in this study is based on the 5th basic plan for long-term electricity supply and demand. The Load Duration Curve, that is needed for applying Screening Curve Method(SCM), is made based on the load profile in 2010. In our using SCM, the nuclear plant's operation characteristic, carbon emission cost and spinning reserve are considered. In using WASP-IV to get the adequate generation mix, the base and target demand forecasts in the 5th basic plan are used and the carbon emission cost is also considered. In this paper, It introduces the domestic adequacy generation mix in 2024 though SCM and WASP-IV.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 춘계학술대회 논문집 전력기술부문
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• pp.89-91
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• 2001

This paper presents the result of pattern classification of load demand for distribution transformer in domestic. The field data of load demand is measured using the load acquisition device and the measurement data is used for the database system for load management of distribution transformed. For the pattern classification, the load data and the customer information data are also used. The K-MEAN method is used for the pattern classification algorithm. The result of pattern classification is used for the 2-step format of load demand curve.

• Journal of Electrical Engineering and Technology
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• 제12권4호
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• pp.1427-1434
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• 2017

Since the late 2000s, there has been growing preparation in South Korea for a sudden reunification of South and North Korea. Particularly in the power industry field, thorough preparations for the construction of a power infrastructure after reunification are necessary. The first step is to estimate the peak load demand. In this paper, we suggest a new peak demand estimation methodology by integrating existing correlation analysis methods between economic indicators and power generation quantities with a power supply interruption model in consideration of power consumption patterns. Through this, the potential peak demand and actual peak demand of the Nation, which experiences power supply interruption can be estimated. For case studies on North Korea after reunification, the potential peak demand in 2015 was estimated at 5,189 MW, while the actual peak demand within the same year was recorded as 2,461 MW. The estimated potential peak demand can be utilized as an important factor when planning the construction of power system facilities in preparation for reunification.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2006년도 추계학술대회
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• pp.561-565
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• 2006

The paper presents a method of assessing the adequate tapaclty of photovoltaic generation systems for public buildings based on analysis of load variation patterns of customers. When PV systems are installed for supplying power for the customer load, reverse power relay is required by the guideline to be installed at the point of common coupling with the power network. The suggested method analyzes daily, weekly and monthly load demand of the customer that Irishes PV system installation, and determines the appropriate rating of the PV system for preventing PV generation from exceeding the customer demand. This work is expected to support renewable energy dissemination projects of public organizations.

• 대한전기학회논문지
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• 제41권9호
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• pp.994-1002
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• 1992

With regard to price elasticity and cross elasticity of electricity, optimal generation expansion planning method including load management effect is suggested. In addition, optimal peak time price can be determined simultaneously, and we adopt peak time tariff as load management strategy. Instead of using hourly marginal demand curves where we can get customer surplus, we used chronological load curve with constraints to preserve social welfare. This method is proved useful in short-term generation expansion planning.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.301-303
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• 2000

This paper presents Kohonen neural network and wavelet transform analysis based technique for industrial peak load forecasting for the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a six-scale synthesis technique.

• 한국농공학회논문집
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• 제60권5호
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• pp.17-27
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• 2018

The objective of this study is to identify the priority area where the nonpoint source pollution (NPS) management is required and to set up the load reduction goals for the identified priority area. In this study, the load duration curve (LDC) was first developed using the flow and water quality data observed at 286 monitoring stations. Based on the developed LDC, the priority area for the NPS pollution management was determined using a three-step method. The 24 watersheds were finally identified as the priority areas for the NPS pollution management. The water quality parameters of concern in the priority areas were the total phosphorus or chemical oxygen demand. The load reduction goals, which were calculated as the percent reduction from current loading levels needed to meet target water quality, ranged from 67.9% to 97.2% during high flows and from 40.3% to 69.5% during moist conditions, respectively. The results from this study will help to identify critical watersheds for NPS program planning purposes. In addition, the process used in this study can be effectively applied to identify the pollutant of concern as well as the load reduction target.