• KIEE International Transactions on Power Engineering
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• 제2A권4호
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• pp.136-144
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• 2002

Load models are very important for improving the accuracy of stability analysis and load flow studies. Various loads are connected to a power bus and their characteristics of power consumption change with voltage and frequency. Thus, the effect of voltage/frequency changes must be considered in load modeling. In this work, artificial neural networks-ANNs- were used to construct the component load models for more accurate modeling. A typical residential load was selected and subjected to a test under variable voltage/frequency conditions. Acquired data were used to construct component models by ANNs. The aggregation process of separately determined load models is also presented in the paper. Furthermore, this paper proposes a method to transform a single load model constructed by the aggregation method into a mathematical load model that can be used in traditional power system analysis software.

• 전기학회논문지
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• 제65권5호
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• pp.718-723
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• 2016

The temperature changes are very important in improving the accuracy of the load forecasting during the summer. It is because the cooling load in summer contribute to the increasing of the load. This paper proposes a weekend load forecasting algorithm using the temperature change characteristic in a summer of Jeju. The days before and after weekends in Jeju, when the load curves are quite different from those of normal weekdays. The temperature change characteristic are obtained by using weekends peak load and high temperature data. And load forecasted based on the sensitivity between unit temperature changes and load variations. Load forecast data with better accuracy are obtained by using the proposed temperature changes than by using the ordinary daily peak load forecasting. The method can be used to reduce the error rate of load forecast.

• 전기학회논문지
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• 제65권9호
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• pp.1486-1492
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• 2016

This study presents the electrical load forecasting and error correction method using a real building load pattern, and the way to manage the energy storage system with forecasting results for economical load operation. To make a unique pattern of target load, we performed the Hierarchical clustering that is one of the data mining techniques, defined load pattern(group) and forecasted the demand load according to the clustering result of electrical load through the previous study. In this paper, we propose the new reference demand for improving a predictive accuracy of load demand forecasting. In addition we study an error correction method for response of load events in demand load forecasting, and verify the effects of proposed correction method through EMS scheduling simulation with load forecasting correction.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 B
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• pp.1260-1262
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• 2004

Direct Load Control(DLC) system is a load management program for stablization of electric power supply-demand. It is a series of acts limiting the demand of selected demand side at peak load or other time periods. Recently, power supply-demand instability due to dramatic increase in power usage such as summertime air-conditioning load has brought forecasts of decrease in power supply capability. Therefore heightening the load factor through systematic load management, in other words, Direct Load Control became necessary. By examining the composition and operation of the DLC system, this paper provides conceptional understanding of the DLC system and help in system research.

• Journal of Electrical Engineering and Technology
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• 제3권3호
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• pp.331-336
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• 2008

Electric load components have different characteristics according to the variation of voltage and frequency. This paper presents the load modeling of an electric locomotive by the parameter identification method. The proposed method for load modeling is very simple and easy for application. The proposed load model of the electric locomotive is represented by the combination of the loads that have static and dynamic characteristics. This load modeling is applied to the KTX in Korea to verify the effectiveness of the proposed method. The results of proposed load modeling by the parameter identification follow the field measurements very exactly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 추계학술대회 논문집 전력기술부문
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• pp.371-373
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• 2001

In this paper, we present 2-step load cycle for daily load curve of up to and including 100kVA distribution transformer in domestic. Daily load patterns are classified by two methods dependent upon possession information. In case we possess daily load profiles make use of K-mean algorithm and in case we have not daily load profiles, make use of customer information of KEPCO. As the parameters of the load pattern classification, we use are daily load profiles and customer information of each distribution transformers. Data management system is used for NT oracle. We can present peak load magnitude, initial load magnitude and peak load duration for daily load patterns by 2-step load cycle for daily load curve of up to and including 100kVA distribution transformer in domestic. We think that this paper contributes to enhancing the distribution transformer overload criterion.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1230-1232
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• 1999

In this research, ANN load model was built on results of field test using residential load, and then proposed ANN load model was applied to transient analysis. The results of this research are as follows. The first, component load modeling using ANN was implemented. The second, group load model was proposed by aggregation of component load. The third, proposed load model was applied to power system analysis. Therefore, Importance of load modeling and precise load modeling method was suggested in this paper.

• 전기학회논문지
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• 제67권3호
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• pp.460-466
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• 2018

For the efficient energy consumption in an urban railway station, it is necessary to know the patterns of electrical loads for each usage in detail. The electrical loads in an urban railway station have different characteristics from other normal electrical load, such as the peak load timing during a day. The lighting, HVAC, communication, and commercial loads make up large amount of electrical load for equipment in an urban railway station, and each of them has the unique specificity. These loads for each usage were estimated without measuring device by the polynomial regression method with big data such as total amount of electrical load and weather data. In the simulation with real data, the optimal polynomial regression model was third order polynomial regression model with 9 or 10 independent variables.

• 설비공학논문집
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• 제23권4호
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• pp.265-272
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• 2011

The electrical load profiles of end-users must be analysed properly to introduce distributed generation system efficiently. In this study, numerical simulation for predicting a residential electrical load profile was developed to satisfy categorized electricity consumption range. We applied bottom-up approach to compose electrical load profile by using data from official reports and statistics. The electrical load profile produced from the simulation predicted peak times of public report accurately and agreed well with the standard residential electrical load profile of official reports within average error of 16.2%.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2005년도 전력전자학술대회 논문집
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• pp.149-151
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• 2005

Recently, power supply-demand instability due to the dramatic increase in power usage suchas air-conditioning load at summertime has brought forecasts of decrease in power supply capability. Therefore improving the load factor through systematic load management, in other words, Direct Load Control became necessary. Direct Load Control(DLC) system is kind of a load management program for stabilization of electric power supply-demand. It's purpose is limiting the demand of the demand side selected at peak load or other time periods. The paper presented a Design of Direct Load Controller for control the amount of power demand in demand side. The proposed Controller is cheaper and has ability of storing more power data than pre-existing device.