• 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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 A
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• pp.395-397
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• 2002

Recently, electric heating using midnight power has brought a rapid increase. Therefore, the increase of midnight power use has much influenced on midnight load pattern and share more than 20% of total midnight electricity consumption. Hence, the distortion of load by using midnight power apparatus is severe and made the usage pattern ineffective electricity usage pattern. This paper analyze the load pattern of midnight power apparatus and policies that can effectively build midnight load. In addition, it provides policies on shifting midnight power apparatus load.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.502-505
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• 2005

To overcome some of the limitations in the conventional photolithography technique, MC-SPL which has advantages such as flexibility and high speed was developed in the past. To make a fine pattern using MC-SPL, there are many variables to control, for example, applied load, scribing speed, chemical etching condition, and etc. In this work, the effect of contact load on the width of the pattern was investigated. The load not only influences the width of the pattern but it also affects the wear of the probe tip. It was found that it is beneficial to load the tip in two stages. Futhermore, the experimental results showed that the pattern width was more sensitive to the initial contact force.

• Tribology and Lubricants
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• 제18권3호
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• pp.211-218
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• 2002

The effect of characteristic of surface roughness and roughness patterns on friction was studied experimentally in boundary lubrication with reciprocating tribometer. Roughness was changed from Ra=0.2($\mu\textrm{m}$)to Ra=1.2($\mu\textrm{m}$). Three roughness pattern-transverse, oblique, longitudinal- were tested for various load and velocity. The experimental results show that the scuffing resistance of surfaces with transversal roughness pattern is higher than that of surface with longitudinal and obliq pattern. under the conditions of the roughness values of Ra=0.2, 0.5,1.0 and 1.2. surfacer roughness (Ra) was decreased with the normal load increased before scuffing occurred. oblique pattern and longitudinal pattern with Ra=0.2 and Ra=1.0 was higher scuffing load under low sliding velocity, but with Ra=0.5 was higher scuffing load under high sliding velocity.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 정기총회 및 추계학술대회 논문집 학회본부
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• pp.29-31
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• 1993

This paper presents Neural Network(NN) approach to short-term load forecasting. Input to the NN are past loads and the output is the predicted load for a given day. The NN is used to learn the relationship among past, current and future temperature and loads. Three different cases are presented. Case 1 divides into weekday and weekendday load pattern. Case 2 forcasts 24-hour ahead load. Case 3 searchs for the same load pattern as present load pattern in past load pattern. From result of forecasting, an average absolute percentage errors of case 1 shows 2.0%. That of case 2 shows 2.2, and That of case 3 shows 1.6%.

• 전기학회논문지
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• 제57권11호
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• pp.1916-1921
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• 2008

This paper presents the temporal classification method based on data mining techniques for discovering knowledge from measured load patterns of distribution transformers. Since the power load patterns have time-varying characteristics and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Therefore, we propose a temporal classification rule for analyzing and forecasting transformer load patterns. The main tasks include the load pattern mining framework and the calendar-based expression using temporal association rule and 3-dimensional cube mining to discover load patterns in multiple time granularities.

• 전기학회논문지
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• 제65권7호
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• pp.1144-1150
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• 2016

Short-term load forecasting is essential to the electricity pricing and stable power system operations. The conventional weekday 24-hour load forecasting algorithms consider the temperature model to forecast maximum load and minimum load. But 24-hour load pattern forecasting models do not consider temperature effects, because hourly temperature forecasts were not present until the latest date. Recently, 3 hour temperature forecast is announced, therefore hourly temperature forecasts can be produced by mathematical techniques such as various interpolation methods. In this paper, a new 24-hour load pattern forecasting method is proposed by using similar day search considering the hourly temperature. The proposed method searches similar day input data based on the anomalous weather features such as continuous temperature drop or rise, which can enhance 24-hour load pattern forecasting performance, because it uses the past days having similar hourly temperature features as input data. In order to verify the effectiveness of the proposed method, it was applied to the case study. The case study results show high accuracy of 24-hour load pattern forecasting.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.832-837
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• 2015

The group method of data handling (GMDH) algorithm has proven to be a powerful and effective way to extract rules or polynomials from an electric load pattern. However, because it is nonstationary, the load pattern needs to be decomposed using a discrete wavelet transform. In addition, if a load pattern has a complicated curve pattern, GMDH should use a higher polynomial, which requires complex computing and consumes a lot of time. This paper suggests a method for short-term electric load forecasting that uses a wavelet transform and a GMDH algorithm. Case studies with the proposed algorithm were carried out for one-day-ahead forecasting of hourly electric loads using data during the years 2008-2011. To prove the effectiveness of our proposed approach, the results were evaluated and compared with those obtained by Holt-Winters method and artificial neural network. Our suggested method resulted in better performance than either comparison group.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2474-2476
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• 2003

An algorithm was embodied to automatic pump operation Pattern for remote control located in 60 km far. This automation pattern included least cost operation, peak load time response, pump operation time balancing etc. It was programmed four kind of operation mode as following; normal operation nude, before peak load time nude, peak load time operation, after peak load time operation.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2009년도 춘계학술대회 논문집
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• pp.64-67
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• 2009

Vibrational micro-forming of pyramidal shape patterns was conducted for an Al superplastic alloy, Al 5083 and a Zr-based bulk metallic glass, $Zr_{62}Cu_{17}Ni_{13}Al_8$. A vibrational micro-forming system was specially designed for generating vibrational load by combining a PZT actuator with a signal generator. Single crystal Si micro dies with wet-etched pyramidal patterns were used as master dies for vibrational micro-forming. The micro-formed pattern height was increasing with increasing the frequency of the vibrational load. In particular, the vibrationally-microformed pattern height was similar or even higher than the statically-microformed pattern height when the load frequency exceeded about 125 kHz. It was also observed that the crystal grains affect the surface quality of the microformed pattern and the distribution of the pattern height in the die cavity array.