• Current Photovoltaic Research
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• 제5권1호
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• pp.33-37
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• 2017

Today, photovoltaic power generation mostly uses Si crystalline solar cell modules. The most vulnerable part of the Si solar cell module is that the power generation decreases due to the temperature rise. But, it is widely used because of low installation cost. In the solar market, where Si crystalline solar cell modules are widely used. The CPV (Concentrated Photovoltaic) module appeared in the solar market. The CPV module reduces the manufacturing cost of the solar cell by using non-Si in the solar cell. Also, there is an advantage that a rise in temperature does not cause a drop in power generation. But this requires high technology to install and has a disadvantage that the initial installation cost is expensive compared to normal Si solar cell module. So that we built a testbed to see these characteristics. The testbed was used to measure the amount of power generation in a long-term outdoor environment and compared with the general Si solar cell module.

• 한국태양에너지학회 논문집
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• 제33권6호
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• pp.62-69
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• 2013

In this paper, Korea Institute of Energy Research, building integrated renewable energy monitoring system that utilizes solar power generation forecast data forecast model is proposed. Renewable energy integration of real-time monitoring system based on monitoring data were building a database and the database of the weather conditions and to study the correlation structure was tailoring. The weather forecast cloud cover data, generation data, and solar radiation data, a data mining and time series analysis using the method developed models to forecast solar power. The development of solar power in order to forecast model of weather forecast data it is important to secure. To this end, in three hours, including a three-day forecast today Meteorological data were used from the KMA(korea Meteorological Administration) site offers. In order to verify the accuracy of the predicted solar circle for each prediction and the actual environment can be applied to generation and were analyzed.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2011년도 춘계학술대회 초록집
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• pp.60.2-60.2
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• 2011

This study is to develop a 1kW-class small wind turbine blade which will be applicable to relatively low speed regions. For this blade, a high efficiency wind turbine blade is designed and a light and low cost composite structure blade is adopted considering fatigue life. In this study, shape design of 1kW-class small wind turbine blade for hybrid power generation system is carried out by BEMT(blade element momentum theory). X-FOIL open software was used to acquire lift and drag coefficients of the 2D airfoils used in power prediction procedure. Moreover, pressure and velocity distributions are investigated according to TSR by CFD analysis.

• 한국수소및신에너지학회논문집
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• 제31권4호
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• pp.380-386
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• 2020

This paper represents an analysis of the economic impact of firing natural gas/diesel and natural gas/by-product oil mixtures in diesel engine power plants. The objects of analysis is a power plant with electricity generation capacity (300 kW). Using performance data of original diesel engines, the fuel consumption characteristics of the duel fuel engines were simulated. Then, economic assessment was carried out using the performance data and the net present value method. A special focus was given to the evaluation of fuel cost saving when firing natural gas/diesel and natural gas/by-product oil mixtures instead of the pure diesel firing case. Analyses were performed by assuming fuel price changes in the market as well as by using current prices. The analysis results showed that co-firing of natural gas/diesel and natural gas/by-product oil would provide considerable fuel cost saving, leading to meaningful economic benefits.

• Environmental Engineering Research
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• 제22권2호
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• pp.175-185
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• 2017

As the energy and environmental problems are increasingly severe, researches about carbon dioxide emissions has aroused widespread concern. The accurate prediction of carbon dioxide emissions is essential for carbon emissions controlling. In this paper, we analyze the relationship between carbon dioxide emissions and influencing factors in a comprehensive way through correlation analysis and regression analysis, achieving the effective screening of key factors from 16 preliminary selected factors including GDP, total population, total energy consumption, power generation, steel production coal consumption, private owned automobile quantity, etc. Then fruit fly algorithm is used to optimize the parameters of least squares support vector machine. And the optimized model is used for prediction, overcoming the blindness of parameter selection in least squares support vector machine and maximizing the training speed and global searching ability accordingly. The results show that the prediction accuracy of carbon dioxide emissions is improved effectively. Besides, we conclude economic and environmental policy implications on the basis of analysis and calculation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제12권2호
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• pp.108-112
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• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• 동력기계공학회지
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• 제2권1호
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• pp.39-44
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• 1998

Computational grids used in the numerical simulation of multi staged turbomachinery flow fields are generated. A multiblock structure simplifies the creation of structured H-grids about complex turbomachinery geometries and facilitate the creation of a grid for multi-row topologies. The numerical algorithm adopts the combination of the algebraic and elliptic method to create the internal grids efficiently and quickly. The input module is made of the results of the preliminary design, i.e., flow-path, aerodynamic conditions along the spanwise direction, and the blade profile data. The final grids generated from each module of the system are used as the preprocessor for the performance prediction of the single row cascades and the flow simulation inside the multi staegd blade passage. Application to low pressure compressor of industrial gas turbine engines was demonstrated to be very reliable and practical in support of design activities.

• 중소기업융합학회논문지
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• 제6권4호
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• pp.93-98
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• 2016

최근 스마트 그리드와 관련된 프로젝트가 선진국을 중심으로 활발하게 연구되고 있다. 특히, 전력 문제의 장기적 안정 대책으로 분산전원이 주목받고 있다. 본 논문에서는 분산형 전원의 출력 예측을 위해서 물리모델과 통계모델을 조합하여 예측 정보 오차율을 비교분석할 수 있는 3차원 기상 수치 모델을 제안한다. 제안 모델은 분산형 전원의 예측정보를 향상시킬 수 있어 안정적인 전력계통 연계를 위한 예측시스템을 가능하다. 성능평가 결과, 제안모델은 발전량 예측 정확도가 4.6% 개선되었고, 온도보정 예측 정확도는 3.5% 향상되었다. 마지막으로 일사량 보정 정확도는 1.1% 향상되었다.

• 조명전기설비학회논문지
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• 제28권10호
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• pp.95-100
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• 2014

To solve the problem of conventional fossil energy, utilization of renewable energy is growing rapidly. Solar energy as an energy source is infinite, and a variety of research is being conducted into its utilization. To change solar energy into electrical energy, we need to build a solar power plant. The efficiency of such a plant is strongly influenced by meteorological factors; that is, its efficiency is determined by solar radiation. However, when analyzing observed generation data, it is clear that the generated amount is changed by various factors such as weather, location and plant efficiency. In this paper, we proposed a solar power generation prediction algorithm using geographical factors such as latitude and elevation. Hence, changes in generated amount caused by the installation environment are calculated by curve fitting. Through applying the method to calculate this generation amount, the difference between real generated amount is analyzed.

• 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.