• Journal of the Korean Solar Energy Society
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• v.35 no.3
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• pp.17-25
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• 2015

The main objective of this study is to predict the wind power generation at the wind farm using various wake models. Modeling of wind farm is a prerequisite for prediction of annual energy production at the wind farm. In this study, we modeled 20 MW class Seongsan wind farm which has 10 wind turbines located at the eastern part of Jeju Island. WindSim based on the computational fluid dynamics was adopted for the estimation of power generation. The power curve and thrust coefficient with meteorology file were prepared for wind farm modelling. The meteorology file was produced based on the measured data of the Korea Wind Atlas provided by Korea Institute of Energy Research. Three types of wake models such as Jensen, Larsen, and Ishihara et al. wake models were applied to investigate the wake effects. From the result, Jensen and Ishihara wake models show nearly the same value of power generation whereas the Larsen wake model shows the largest value. New positions of wind turbines are proposed to reduce the wake loss, and to increase the annual energy production of the wind farm.

• Journal of the Korean Solar Energy Society
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• v.34 no.3
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• pp.98-106
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• 2014

The effect of blockage ratio on wind tunnel testing of small vertical-axis wind turbine has been investigated in this study. Height and rotor diameter of the three blades Darrieus vertical axis wind turbine used in present test were 0.4m and 0.35m respectively. We measured the wind speeds and power coefficient at three different wind tunnels where blockage ratio were 3.5%, 13.4% and 24.7% respectively. The test results show that the measured powers have been strongly influenced by blockage ratio, generally increased as the blockage ratio increases. The maximum power at higher blockage ratio has been obtained at relatively high tip speed ratio compared with that at low blockage ratio. The measured power coefficients under high blockage ratio can be improved from proper correction using the simple correction equation based on blockage factor. In present study, the correction error for power coefficient can be less than 5%, however correction effectiveness reveals relatively poor at high blockage ratio and low wind speed.

• Journal of the Korean Solar Energy Society
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• v.26 no.2
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• pp.53-59
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• 2006

The number of wind generation installations are growing substantially in Jeju, Korea. Many of these installations are significant in size and directly connected to the distribution system. Utility grid interconnection standards for interconnecting non-utility distributed generation systems are essential to both power system company and generation company. These interconnection standards are important to utilities, customers, wind generation manufactures and nation. In this paper, it is investigated the voltage quality and the suitability of Jeju-Hangwon wind power generation farm by network interconnection technology standard.

• Journal of the Korean Solar Energy Society
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• v.30 no.2
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• pp.54-64
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• 2010

Interest in new and renewable energies like solar energy and wind energy is increasing throughout the world due to the rapidly expanding energy consumption and environmental reasons. An essential requirement for wind force power generation is estimating the size of wind energy accurately. Wind energy is estimated usually using meteorological data or field measurement. This study attempted to estimate wind energy density using meteorological data on daily mean wind speed and the Weibull parameters in Seoul, a representative inland city where over 60% of 15 story or higher apartments in Korea are situated, and Busan, Incheon, Ulsan and Jeju that are major coastal cities in Korea. According to the results of analysis, the monthly mean probability density distribution based on the daily mean wind speed agreed well with the monthly mean probability density distribution based on the Weibull parameters. This finding suggests that the Weibull parameters, which is highly applicable and convenient, can be utilized to estimate the wind energy density distribution of each area. Another finding was that wind energy density was higher in coastal cities Busan and Incheon than in inland city Seoul.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.97-102
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• 2005

Because of the limited fossil resources and the need to avoid emissions and toxic waste the future energy supply will be based on a large portion of renewable energies: wind-, solar-, biomass- and geothermal energy. Focus is on the utilization of wind energy coming from onshore- and offshore-sites. Generating electricity from wind is state of the art and feeding large amounts of wind power into the electrical grid will create some additional problems. Suggestions concerning energy storage will be made and the problem of power quality is discussed.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.233-239
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• 2018

Since solar power generation is intermittent depending on weather conditions, it is necessary to predict the accurate generation amount of solar power to improve the efficiency and economical efficiency of solar power generation. This study proposes a short - term deep learning prediction model of solar power generation using meteorological data from Mokpo meteorological agency and generation data of Yeongam solar power plant. The meteorological agency forecasts weather factors such as temperature, precipitation, wind direction, wind speed, humidity, and cloudiness for three days. However, sunshine and solar radiation, the most important meteorological factors for forecasting solar power generation, are not predicted. The proposed model predicts solar radiation and solar radiation using forecast meteorological factors. The power generation was also forecasted by adding the forecasted solar and solar factors to the meteorological factors. The forecasted power generation of the proposed model is that the average RMSE and MAE of DNN are 0.177 and 0.095, and RNN is 0.116 and 0.067. Also, LSTM is the best result of 0.100 and 0.054. It is expected that this study will lead to better prediction results by combining various input.

• Journal of the Korean Solar Energy Society
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• v.34 no.1
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• pp.81-90
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• 2014

The Jeju-Korea power system is a small-sized network with a system demand ranging from a autumn minimum of 350MW to a summer peak of 716MW. Because Jeju island is well exposed to north-east winds with high speed, applications to connect to Jeju power system are flooded. Considering physical/environmental constraints, Jeju Self-governing Province has also target for the wind power capacity of 1,350MW by 2020. It amounts to two or three times of Jeju average-demand power and wind power limit capacity announced by Korea Power Exchange (KPX) company. Wind farm connection agreements will be signed to maximize utilization of wind resource. In spite of submarine cable HVDC connected to Korea mainland, Jeju power system is independently operated by frequency and reserve control. This study reevaluates wind power limit based on the KPX criteria from 2016 to 2020. First of all wind power generation limit are affected by off-peak demand in Jeju power system. Also the possibility capacity rate of charging wind power output is evaluated by using energy storage system (ESS). As a result, in case of using 110MWh ESS, wind power limit increases 33~55MW(30~50% of ESS), wind power constraint energy decreases from 68,539MWh to 50,301MWh and wind farm capacity factor increases from 25.9 to 26.1% in 2020.

• Journal of the Korean Solar Energy Society
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• v.34 no.4
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• pp.67-74
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• 2014

The fluctuation of the output power of wind farms will be able to cause the impact on the Jeju power system such as power quality and stability. To settle the matter, many researchers have proposed the use of the BESS(Battery Energy Storage System) in the wind farm. In this paper, The BESS is applied to each wind farms for mitigating the fluctuation of wind power output. The BESS is controlled for smoothing the output of wind farms. Two kinds of simulation will be carried out. First, the simulation results by using PSCAD/EMTDC simulation program are compared to the measured data from the real power grid in Jeju Island. The other is to analyze the output of wind farms when the BESS is applied to the simulation works. The simulation results will demonstrate the effectiveness of using BESS to stabilize for power grid in Jeju Island.

• Solar Energy
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• v.5 no.2
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• pp.3-10
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• 1985

This paper is concerned with the characterized method of wind speed distribution for calculation of wind power density of regional group and wind potential in Korea. It is shown that the Rayleigh distribution, K = 2, is not suitable for analyzing wind data in Korea. Simple relationship, K = 0.21 V + 0.84, is derived from Weibull wind distribution by analyzing wind data obtained from 24 meteorological station and is a suitable tool for estimation of wind power density. Application of this result, the domestic ideal and actual wind potential are estimated as $3.16{\times}10^9$ KWH/year and $7.14{\times}$10^8 KWH/year respectively for the case of 10 meter height, $1m^2$ swept area and $0.1{\times}0.1Km^2$ land area. And for the case of 50 meter height, ideal and actual wind potential are increased as $7.56{\times}10^9$ KWH/year and $2.37{\times}10^9$ KWH/year respectively.

• Journal of The Korean Astronomical Society
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• v.37 no.1
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• pp.55-59
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• 2004

We have developed a two fluid solar wind model from the Sun to 1 AU. Its basic equations are mass, momentum and energy conservations. In these equations, we include a wave mechanism of heating the corona and accelerating the wind. The two fluid model takes into account the power spectrum of Alfvenic wave fluctuation. Model computations have been made to fit observational constraints such as electron($T_e$) and proton($T_p$) temperatures and solar wind speed(V) at 1 AU. As a result, we obtained physical quantities of solar wind as follows: $T_e$ is $7.4{\times}10^5$ K and density(n) is $1.7 {\times}10^7\;cm^{-3}$ in the corona. At 1 AU $T_e$ is $2.1 {\times} 10^5$ K and n is $0.3 cm^{-3}$, and V is $511 km\;s^{-1}$. Our model well explains the heating of protons in the corona and the acceleration of the solar wind.