• 전기학회논문지
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• 제66권2호
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• pp.347-353
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• 2017

In order to prohibit global warming, various kinds of regulatory policies have been established in the whole world. One example is the establishment of the Renewable Portfolio Standard. It requires the increased portion in energy production from renewable energy sources. The Republic of Korea adopted the act on the promotion of the development, use, and diffusion of new and renewable energy since 2012. However, in spite of the effort on the consideration of the renewable energy sources, it was reported the carbon intensity of electricity in Korea was not that low in 2015. Thus, it is required to examine the recent state of the utilization degree of the renewable energy sources in Korea. This paper analyzed the statistical data provided by Korea Power Exchange (KPX) to examine any problems and solutions for generating electricity from the renewable energy sources. We focused on the generation capacity provided by the power plants participated in the market, the electric power trading amount, and the utilization coefficient for 10 years. By analyzing the data, we provide an alternative to solve some imbalance among the factors contributing to renewable energy use.

• 대한전기학회논문지:전력기술부문A
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• 제54권3호
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• pp.144-151
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• 2005

This paper presents a forecasting technique of the short-term marginal price (SMP) using an Artificial Neural Network (ANN). The SW forecasting is a very important element in an electricity market for the optimal biddings of market participants as well as for market stabilization of regulatory bodies. Input data are organized in two different approaches, time-axis and day-axis approaches, and the resulting patterns are used to train the ANN. Performances of the two approaches are compared and the better estimate is selected by a composition rule to forecast the SMP. By combining the two approaches, the proposed composition technique reflects the characteristics of hourly, daily and seasonal variations, as well as the condition of sudden changes in the spot market, and thus improves the accuracy of forecasting. The proposed method is applied to the historical real-world data from the Korea Power Exchange (KPX) to verify the effectiveness of the technique.

• 대한전기학회논문지:전력기술부문A
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• 제55권2호
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• pp.85-93
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• 2006

Since the SMP(System Marginal Price) is a vital factor to the market participants who intend to maximize the their profit and to the ISO(Independent System Operator) who wish to operate the electricity market in a stable sense, the short-term marginal price forecasting should be performed correctly. In an electricity market the short-term market price affects considerably the short-term trading between the market entities. Therefore, the exact forecasting of SMP can influence on the profit of market participants. This paper presents a new methodology for a day-ahead SMP forecasting using ARIMA(Autoregressive Integrated Moving Average) model based on the time-series method. And also the correction algorithm is proposed to minimize the forecasting error in order to improve the efficiency and accuracy of the SMP forecasting. To show the efficiency and effectiveness of the proposed method, the case studies are performed using historical data of SMP in 2004 published by KPX(Korea Power Exchange).

• 한국융합학회논문지
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• 제9권5호
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• pp.1-6
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• 2018

스마트그리드에서 정확한 단기 부하 예측을 통한 자원의 이용 계획은 에너지 시스템 운영의 불확실성을 줄이고 운영 효율을 높이는데 있어서 매우 중요하다. 단기 부하 예측에 얕은 신경회로망을 포함한 다수의 머신 러닝 기법이 적용되어왔지만 예측 정확도의 개선이 요구되고 있다. 최근에는 컴퓨터 비전이나 음성인식 분야에서 심층 신경회로망의 뛰어난 연구 결과로 인해 심층 신경회로망을 단기 전력수요 예측에 적용해 예측 정확도를 개선하려는 시도가 주목 받고 있다. 본 논문에서는 일별 전력 부하 첨두치를 예측하기 위한 다층신경회로망 구조의 심층 신경회로망 모델을 제안한다. 제안된 심층 신경회로망은 층별 학습이 선행된 후 전체 모델의 학습이 이루어진다. 한국전력거래소에서 얻은 4년 동안의 일별 전력 수요 데이터를 사용, 하루 및 이틀 앞선 전력수요 첨두치를 예측하는 심층 신경회로망 모델을 구축하고 예측 정확도를 비교, 평가한다.

• 전기학회논문지
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• 제66권3호
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• pp.475-485
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• 2017

This paper develops a conversion function and method transforming from daily peak load curve used $LOLE_D$ [days/year] to hourly load curve used $LOLE_H$[hours/year]and describes relationship between $LOLE_D$ [days/year] and $LOLE_H$ [hours/year]. The indices can not only be transformed just arithmetically but also have different characteristics physically because of using their different load curves. The conversion function is formulated as variables of capacity and forced outage rate of generator, hourly load daily load factor and daily peak load yearly load factor, etc. Therefore, the conversion function (${\gamma}={\varphi}$(.)) can not be simple. In this study, therefore, the function is formulated as linear times of separated two functions. One is an exponential formed conversion function of daily load factor. Another is formulated with an exponential typed conversion function of daily peak load yearly load factor. Futhermore, this paper presents algorithm and flow chart for transforming from $LOLE_D$[days/year] to $LOLE_H$[hours/year]. The proposed conversion function is applied to sample system and actual KPS(Korea Power System) in 2015. The exponent coefficients of the conversion functions are assessed using proposed method. Finally, assessment errors using conversion function for case studies of sample system and actual system are evaluated to certify the firstly proposed method.

• 한국산학기술학회논문지
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• 제18권2호
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• pp.23-30
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• 2017

건설산업 분야에서 빌딩정보모델링(BIM)은 단지 설계를 보다 쉽게 지원하고, 3차원 모델을 구현하기 위한 도구만은 아니다. 왜냐하면, 설계, 시공, 유지관리 및 철거에 이르는 건설 생애주기 동안의 다양한 데이터를 입력하고 관리가 가능하도록 구조화 되어 있기 때문이다. 이렇게 구조화된 모델을 가지고 다양한 분석 및 해석이 가능해지기 때문에 BIM의 역할은 점점 더 증대되어 가고 있다. 노르웨이 베스트바넨의 국립예술박물관 현상설계 경기를 시작으로 국내외적으로 BIM을 설계 경기 및 평가에 적용하려는 노력이 다각적으로 발생하고 있다. 이때, 기존 방식의 설계경기와는 다르게 BIM기반으로 전사적인 시뮬레이션을 통한 자동적이며, 신뢰성이 높고 효율적인 평가가 가능하게 된다. 이를 위하여 각 BIM 도구를 대상으로 하는 모델링 가이드가 필요하며 이를 검증할 수 있는 평가시스템의 요구가 생기게 되었다. 본 논문은 건설산업 분야에 새로운 패러다임을 이끌고 있는 BIM 기술을 이용한 새로운 방식의 설계평가 및 절차의 방향에 대해, 전력거래소 본사사옥 등의 이전 설계경기 사례를 비교분석하고 이에 대한 개선방안을 설명함으로써 향후 발주될 BIM기반 건축설계경기 평가의 방향을 제시하고자 한다.