• 한국컴퓨터정보학회논문지
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• 제23권10호
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• pp.57-63
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• 2018

The operating system for an isolated microgrid, which is completely disconnected from the central power system, aims at preventing blackouts and minimizing power generation costs of diesel generators through efficient operation of the energy storage system (ESS) that stores energy produced by renewable energy generators and diesel generators. In this paper, we predict the amount of renewable energy generation using the weather forecast and build an optimal diesel power generation plan using a genetic algorithm. In order to avoid inefficiency due to inaccurate prediction of renewable energy generation, our search algorithm imposes penalty on candidate diesel power generation plans that fail to maintain the SOC (state of charge) of ESS at an appropriate level. Simulation experiments show that our optimization method for maintaining an appropriate SOC balance can prevent the blackout better when compared with the previous method.

• 전기학회논문지P
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• 제64권1호
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• pp.1-6
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• 2015

Factors that have influence on solar power generation are specified into three aspects such as meteorological, geographical factors as well as equipment installation. Meteorological factors influence the most among the three. Insolation, sunshine hours, and cloud directly influence on solar power generation, whereas temperature and wind speed have impacts on equipment installation. This paper provides explanation over temperature-wind speed equation by calculating influence of temperature and wind speed on equipment installation. In order to conduct a research, pyranometer, anemometer, air thermometer, module thermometer are installed in 2MWp solar power plant located in South Cholla province, so that real-time meteorological data and generating amount can be analyzed through monitoring system. Besides, if existing and new methods are applied together, accuracy of prediction for generating amount is improved.

• 한국산업융합학회 논문집
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• 제26권4_2호
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• pp.715-724
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• 2023

Solar energy forecasting is essential for (1) power system planning, management, and operation, requiring accurate predictions. It is crucial for (2) ensuring a continuous and sustainable power supply to customers and (3) optimizing the operation and control of renewable energy systems and the electricity market. Recently, research has been focusing on developing solar energy forecasting models that can provide daily plans for power usage and production and be verified in the electricity market. In these prediction models, various data, including solar energy generation and climate data, are chosen to be utilized in the forecasting process. The most commonly used climate data (such as temperature, relative humidity, precipitation, solar radiation, and wind speed) significantly influence the fluctuations in solar energy generation based on weather conditions. Therefore, this paper proposes a hybrid forecasting model by combining the strengths of the Prophet model and the GRU model, which exhibits excellent predictive performance. The forecasting periods for solar energy generation are tested in short-term (2 days, 7 days) and medium-term (15 days, 30 days) scenarios. The experimental results demonstrate that the proposed approach outperforms the conventional Prophet model by more than twice in terms of Root Mean Square Error (RMSE) and surpasses the modified GRU model by more than 1.5 times, showcasing superior performance.

• 한국전자통신학회논문지
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• 제16권4호
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• pp.735-742
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• 2021

최근 정부에서 역점 적으로 추진하고 있는 '재생에너지 3020', '그린뉴딜', '2050 탄소중립', 'K-RE100' 정책에 의해 재생에너지 관련 발전설비들이 급증하고 있다. 재생에너지 설비들은 대부분 소규모이고, 분산되어 있어서 효율적인 관리가 어렵고, 1MW 미만의 소규모 분산자원은 판매량 제한, 거래회피 등으로 시장참여에 큰 어려움을 겪고 있다. 특히, 재생에너지의 간헐성 때문에 전력망의 안정성 저하에도 큰 영향을 끼치고 있다. 정부에서는 '소규모 분산자원 중개거래'를 통해서 변동성 및 간헐성 문제를 해결하고, 이종의 대량 소규모 분산자원들의 계통 자원화와 수용성 확대를 추구하고 있다. 본 연구에서는 AI에 기반한 발전량 예측 모델을 분산자원 중개거래 시스템에 적용하여 최적의 운영 솔루션을 제시하고, 에너지신사업 시장 개척의 기반 플랫폼으로 활용될 수 있도록 하고자 한다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2010년도 춘계학술대회
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• pp.942-945
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• 2010

분산형 전원은 에너지 실수요자 근처 혹은 건물 내부에 소형 발전설비(태양광, 풍력 발전을 포함하는 신재생에너지 발전)를 설치해 에너지 손실과 송 배전 설비를 줄이려는 노력에서 출발했다. 최근 세계적으로 기후 환경 변화에 대처하기 위해 다양한 신재생에너지를 활용하기 위한 댁내 분산형 전원 환경 시대를 예고하고 있다. 특히 태양광, 풍력 발전은 댁내에 설치하기 용이하고 가장 경제성이 뛰어나 많은 기업들이 적극적으로 사업에 진출하고 있다. 하지만 풍력 발전의 경우 바람의 세기에 따라 발전량의 변화가 심하고, 태양광은 일사량 및 일조량의 영향을 많이 받기 때문에 기후 상황에 따라 출력이 불안정하다는 단점이 있기 때문에 균일한 전력품질을 제공하기 위해 해결해야 할 기술적인 과제를 가지고 있다. 본 논문에서는 댁내에서 운용이 용이한 풍력 에너지, 태양광 에너지 및 기존 전력으로 구성되는 분산형 전원시스템에서 기후변화에 민감한 신재생에너지 발전량의 예측 방법에 대해 제안한다. 이를 바탕으로 효율적인 분산전력 관리를 가능하게 하며, 궁극적으로 제로에너지 홈을 구현하기 위한 기본 요소 기술을 제공하는 것이 본 논문의 목표이다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 A
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• pp.737-739
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• 2004

The domestic power system established with Cost-Based-Pricing(CBP) from April 2001. The system is a uniform pricing system. System Operator(50) establishes a Price Setting Schedule by the prediction of consumption and the presented bid price(generation cost) of the generation utility. But the Price Setting Schedule doesn't take account of the constraint of the system. This cause a transmission congestion, constrained-on generation and constrained-off generation. This Paper search the way of the increasing efficiency of domestic power system through the redemption of congestion charge.

• 조명전기설비학회논문지
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• 제29권7호
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• pp.80-86
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• 2015

As wind farm outputs depend on natural wind resources that vary over space and time, spatial correlation analysis is needed to estimate power outputs of wind generation resources. As a result, geographic information such as latitude and longitude plays a key role to estimate power outputs of spatially distributed wind farms. In this paper, we introduce spatial correlation analysis to estimate the power outputs produced by wind farms that are geographically distributed. We present spatial correlation analysis of empirical power output data for the JEJU Island and ERCOT ISO (Texas) wind farms and propose the Correlation Decay Distance (CoDecDist) model based on geographic correlation analysis to enhance the estimation of wind power outputs.

• 신재생에너지
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• 제10권2호
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• pp.19-28
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• 2014

Wind power generation of 5 MW wind turbine was predicted by using wind measurement data from HeMOSU-1 which is at south west coast of Korea. Time histories of turbulent wind was generated from 10-min mean wind speed and then they were used as input to Bladed to estimated electric power. Those estimated powers are used in both polynominal regression and neural network training. They were compared with each other for daily production and yearly production. Effect of mean wind speed and turbulence intensity were quantitatively analyzed and discussed. This technique further can be used to assess lifetime power of wind turbine.

• 전기학회논문지P
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• 제63권4호
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• pp.295-300
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• 2014

The frequency is an important operating parameter of a power system. There is an increasing importance of constant monitoring of frequency to achieve stable power supply by WAMS(wide area monitoring system) and FNET(Frequency Monitoring Network). This paper is part of development of a network-based frequency monitoring and failure prediction system for wide-area intelligent protection relaying. In this paper, analysis of propagation speed of power frequency by generation drop using the PSS/E was carried out. For dynamic analysis, the 11 metropolitan areas offices of KEPCO divided into five groups of Seoul, Gangwon, Chungcheong, Honam, and Yeongnam group, study was performed.

• Journal of Advanced Marine Engineering and Technology
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• 제36권1호
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• pp.51-56
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• 2012

본 논문은 고파워 전자소자의 폐열로부터 에너지 수확을 목적으로 하는 열전생성기의 생성효율과 열적 성능에 대하여 논한다. 열경계저항을 포함하는 열전모델이 적용되어 생성효율과 고전력 전자소자의 junction 온도를 예측하였고 그 결과는 실험치로 검증되어진다. 검증결과는 예측치와 계측치의 오차가 작음을 보인다. 검증후 열전모델은 다양한 로드저항과 열원의 열율에서 생성효율, 열전생성기 양면의 온도차, 소자의 junction 온도를 예측한다. 본 연구는 로드저항이 생성효율, 열전생성기 양면의 온도차, junction 온도에 미치는 영향에 대해서도 탐구한다.