• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.457-459
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• 2018

Solar power generation system is a energy generation technology that produces electricity from solar power, and it is growing fastest among renewable energy technologies. It is of utmost importance that the solar power system supply energy to the load stably. However, due to unstable energy production due to weather and weather conditions, accurate prediction of energy production is needed. In this paper, an Artificial Neural Network(ANN) that predicts solar energy using 15 kinds of meteorological data such as precipitation, long and short wave radiation averages and temperature is implemented and its performance is evaluated. The ANN is constructed by adjusting hidden parameters and parameters such as penalty for preventing overfitting. In order to verify the accuracy and validity of the prediction model, we use Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE) as performance indices. The experimental results show that MAPE = 19.54 and MAE = 2155345.10776 when Hidden Layer $Sizes=^{\prime}16{\times}10^{\prime}$.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.159-172
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• 2014

As greenhouse gas emissions have been increasing in the world, global warming is being recognized as a cause of the global problems like climate change. This is closely associated the fossil fuels. Thus renewable energy has been brought to the attention of many people as the upcoming alternative energy source to cope with the fossil drain and increased environmental regulations. Especially, the solar energy among renewable energy has drastically increased. In this study, we calculate on daylight ratio about the solar energy for buildings based on digital surface model. The digital surface model was made using the spatial information data. And it was simulated the shadow analysis using SAS. Therefore, it was suitable places to utilize the solar energy in the Gyeongsan city. Consequently, the daylight ratio was considered important factor to select region of the industry of the solar light power generation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.782-785
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• 2011

Needs for MG(Microgrid) development are increasing all over the world as a solution to the problems including the depletion problem of energy resources, the growing demand for electric power and the climatic and environmental change. Especially Photovoltaic power is one of the most general renewable energy resources. However there is a problem of the uniformity of power quality because the power generated from solar light is very sensitive to climate fluctuation (variation of insolation and duration of sunshine, etc). As a solution to the above problem, ESS(Energy Storage System) is considered generally, but it has some limitations. To solve this problem this paper suggests a hybrid estimation method of photovoltaic power generation according to two climatic factors, i.e. insolation and sunshine. This result seems to help design the appropriate capacity of ESS and estimate the proper switching time between DC and AC power in the premises power system and thus maintain the uniformity of power quality.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.467-495
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• 2019

Uncertainty of renewable energy such as photovoltaic(PV) power is detrimental to the flexibility of the power system. Therefore, precise prediction of PV power generation is important to make the power system stable. The purpose of this study is to forecast PV power generation using meteorological data including particulate matter(PM). In this study, PV power generation is predicted by support vector machine using RBF kernel function based on machine learning. Comparing the forecasting performances by including or excluding PM variable in predictor variables, we find that the forecasting model considering PM is better. Forecasting models considering PM variable show error reduction of 1.43%, 3.60%, and 3.88% in forecasting power generation between 6am~8pm, between 12pm~2pm, and at 1pm, respectively. Especially, the accuracy of the forecasting model including PM variable is increased in daytime when PV power generation is high.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.33-41
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• 2023

Recently, global warming has accelerated climate change, increased extreme weather phenomena, and increased the frequency and intensity of weather disasters, leading to increasing uncertainty about the power production of new and renewable energy that is sensitive to weather. In fact, it has been reported that a number of damage to hydroelectric power generation have occurred due to weather disasters. Therefore, using the hydroelectric power generation performance data of Chungju Dam, meteorological data of Chungju Meteorological Observatory, and operation data of Chungju Dam, this study investigated the effect of meteorological disasters on hydroelectric power generation through structural equation modeling considering the number and intensity of meteorological disasters per month. The results indicated that the increased drought occurrence affected the decreased hydroelectric power generation by about 38.3 %, however the increased hydroelectric power generation could not explained by the increased flood occurrence. In conclusion, an increased drought occurrence in future may significantly influence hydroelectric power generation.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.977-983
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• 2013

Based on the consideration of the hourly patterns of the electricity power consumption, this study predicted the effectiveness of hybrid power generation system, which is composed with wind power generator and photovoltaic generator. And this case study is performed at Konrido, which is a affiliated island of Kyeongsangnam-do. As the results, it is obvious that it is not efficient to cover the whole electricity power consumption only with any single power generating system, because the hourly patterns of electricity power consumption, wind power generation and photovoltaic generation are quite different. And because the wind is being through almost 24 hours, it is also found out that wind power generating system with storage battery is the most efficient combination for this case study.

• Transactions of the Korean hydrogen and new energy society
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• v.30 no.4
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• pp.303-311
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• 2019

Reversible solid oxide fuel cell (RSOFC) has become a prospective device for energy storage and hydrogen production. Many studies have been conducted around the world focusing on system efficiency improvement and realization. The system should have not only high efficiency but also a certain level of simplicity for stable operation. External waste steam utilization was proved to remarkably increase the efficiency at solid oxide electrolysis system. In this study, RSOFC system coupled with waste steam was proposed and optimized in term of simplicity and efficiency. Ejector for fuel recirculation is selected due to its simple design and high stability. Three system configurations using ejector for fuel recirculation were investigated for performance of design condition. In parametric study, the system efficiencies at different current density were analyzed. The system configurations were simulated using validated lumped model in EBSILON(R) program. The system components, balance of plants, were designed to work in both electrolysis and fuel cell modes, and their off-design characteristics were taken into account. The base case calculation shows that, the system with suction pump results in slightly lower efficiency but stack can be operated more stable with same inlet pressure of fuel and air electrode.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.692-693
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• 2011

국가의 녹색성장 정책으로 풍력 및 태양광 등의 신 재생 에너지가 배전계통에 지속적으로 연계 운용될 것이다. 하지만 태양광 및 풍력의 출력변동으로 배전계통 전압품질에 상당한 영향을 미칠 수 있다. 여기에 더하여 부하특성에 의한 부하전류 변동 또한 전압문제에 직접적으로 영향을 미친다. 이에 따라 본 논문에서는 PSCAD/EMTDC를 통해 가장 많이 이용되고 있는 부하모델인 ZIP모델을 이용하여 각각의 부하 특성과 3MW의 풍력이 배전계통 말단에 연계된 경우를 상정하여 풍속3[m/s]에서 12[m/s]로 급속한 변동시, 순시전압 데이터와 계통연계가이 드라인 의 순시전압변동 기준과 비교/분석을 통해 부하별 풍력발전의 전압변동특성을 해석하고자 한다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.490_491
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• 2009

전력시장의 규제완화와 고효율, 신재생 에너지 관련 기술의 발전으로 분산전원의 가격경쟁력이 높아지면서 최근 배전계통 내에 분산전원의 보급이 급속히 확대되고 있다. 또한, 탄소배출에 대한 국제적 환경규제의 본격화는 분산전원 보급을 더욱 가속화 시키고 있다. 탄소배출량이 손실금액으로 환산될 경우 현재의 분산전원 운영방식과는 전혀 다른 시간별 분산전원의 발전전략이 재정립되어야 한다. 본 논문에서는 배전계통 내 관할 구역의 수용가에 유 무효전력 및 열을 공급하는 구역전기사업자의 분산전원별 탄소배출량을 고려한 최적 운영에 대해서 소개할 것이다.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.235-237
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• 2007

최근 신재생 에너지로 풍력 발전 시스템이 중요시 되고 있다. 이에 본 논문에서는 풍력발전 시스템의 Wind Turbine System을 영구자석형 동기기를 이용하여 시뮬레이션 모델을 구현하였다. 시뮬레이션 모델은 회전자 모델, MPPT 알고리즘, 영구자석형 동기기(PMSM) 등으로 구성되어있다. Wind Blade Rotor의 유체역학적 특성 및 가감속 제어전략을 이용하여 Wind Turbine System의 특성을 시뮬레이션 할 수 있도록 하였다. 본 연구 결과는 이후 영구자석형 동기기를 이용한 풍력발전기의 기초 자료로서 이용될 수 있을 것으로 기대된다.