• The Korean Journal of Applied Statistics
• /
• v.22 no.5
• /
• pp.943-960
• /
• 2009

This study suggests an algorithm for generating TMY(typical meteorological year) for the Korean peninsula, and generates the TMY based on the algorithm using 11 years(1998~2008) wind data observed at 77 sites of Regional Meteorological Offices(RMO). The algorithm consists of computing TMM scores based on the various statistics defined by the Fikenstein-Shafer statistical model and, in turn, generating TMY based on the TMM scores. Also the algorithm has two stages designed to yield the best representation of the regional wind characteristics appeared during the 11 years(1998~2008). The first stage is designed for the representation of each of 77 regions of RMO and the second is for the Korean peninsula. Various comparison studies are provided to demonstrate the properties of the TMY like its utility and typicality.

• New & Renewable Energy
• /
• v.8 no.2
• /
• pp.14-23
• /
• 2012

The TMY (Typical Meteorological Year) for the solar energy study is generated using observation data with 22 solar sites from KMA (Korea Meteorological Administration) during 11 years (2000-2010). The meteorological data for calculation the TMY are used solar radiation, temperature, dew point temperature, wind speed and humidity data. And the TMY is calculated to apply the FS (Finkelstein and Schafer) statistics and RMSE (Root Mean Squared Error) methods. FS statistics performed with each point and each variable and then selected top five candidate TMM months with statistical analysis and normalization. Finally TMY is generated to select the highest TMM score with evaluation the average errors for the 22 whole points. The TMY data is represented average state and long time variations with 22 sites and meteorological data. When TMY validated with the 11-year daily solar radiation data, the correlation coefficient was about 0.40 and the highest value is 0.57 in April and the lowest value is 0.23 in May. Mean monthly solar radiation of TMY is 411.72 MJ which is 4 MJ higher than original data. Average correlation coefficient is 0.71, the lowest correlation is 0.43 in May and the highest correlation is 0.90 in January. Accumulated annual solar radiation by TMY have higher value in south coast and southwestern region and have relatively low in middle regions. And also, differences between TMY and 11-year mean of is distributed lower 100 MJ in Kyeongbuk, higher 200 MJ in Jeju and higher 125 MJ in Jeonbuk and Jeonnam, respectively.

• Journal of the Korean Solar Energy Society
• /
• v.39 no.3
• /
• pp.67-79
• /
• 2019

The reliable Typical Meteorological Year (TMY) data, sometimes called Test Reference Year (TRY) data, are necessary in the feasibility study of renewable energy installation as well as zero energy building. In Korea, there are available TMY data; TMY from Korea Institute of Energy Research (KIER), TRY from the Korean Solar Energy Society (KSES) and TRY from Passive House Institute Korea (PHIKO). This study aims at examining their characteristics by using Principle Component Analysis (PCA) at six ground observing stations. First step is to investigate the annual averages of meteorological elements from TMY data and their standard deviations. Then, PCA is done to find which principle components are derived from different TMY data. Temperature and solar irradiance are determined as the main principle component of TMY data produced by KIER and KSES at all stations whereas TRY data from PHIKO does not show similar result from those by KIER and KSES.

• New & Renewable Energy
• /
• v.20 no.1
• /
• pp.102-109
• /
• 2024

The Typical Meteorological Year (TMY) dataset compiles 12 months of data that best represent long-term climate patterns, focusing on global horizontal irradiance and other weather-related variables. However, the irradiance measured on the plane of the array (POA) shows certain distinct distribution characteristics compared with the irradiance in the TMY dataset, and this may introduce some biases. Our research recalculated POA irradiance using both the Isotropic and DIRINT models, generating an updated dataset that was tailored to POA characteristics. Our analysis showed a 28% change in the selection of typical meteorological months, an 8% increase in average irradiance, and a 40% reduction in the range of irradiance values, thus indicating a significant shift in irradiance distribution patterns. This research aims to inform stakeholders about accurate use of TMY datasets in potential decision-making. These findings underscore the necessity of creating a typical dataset by using the time series of POA irradiance, which represents the orientation in which PV panels will be deployed.

• Journal of the Korean Solar Energy Society
• /
• v.38 no.6
• /
• pp.27-36
• /
• 2018

Typical Meteorological Year Dataset is necessary for the renewable energy feasibility study. Since National Renewable Energy Laboratory has been built Typical Meteorological Year Dataset in 1978, gridded datasets taken from numerical weather prediction or satellite imagery are employed to produce Typical Meteorological Year Dataset. In general, Typical Meteorological Year Dataset is generated by using long-term in-situ observations. However, solar insolation is not usually measured at synoptic observing stations and therefore it is limited to build the Typical Meteorological Year Dataset with only in-situ observation. This study attempts to build the Typical Meteorological Year Dataset with satellite derived solar insolation as an alternative and then we evaluate the Typical Meteorological Year Dataset made by using satellite derived solar irradiance at Daejeon ground station. The solar irradiance is underestimated when satellite imagery is employed.

• Journal of the Korean Solar Energy Society
• /
• v.39 no.3
• /
• pp.81-89
• /
• 2019

Long-term solar irradiance data are required for reliable performance evaluation and feasibility analysis of solar photovoltaic systems. However, measurement data of the global horizontal irradiance (GHI) are only available for major cities in Korea. Neither the direct normal irradiance (DNI) nor the diffuse horizontal irradiance (DHI) are available, which are also needed to calculate the irradiance on the tilted surface of PV array. It is a simple approach to take advantage of the decomposition model that extracts DNI and DHI from GHI. In this study, we investigate variations of solar PV power estimation due to the choice of decomposition model. The GHI data from Korea Meteorological Administration (KMA) were used and different sets of typical meteorological year (TMY) data using some well-known decomposition models were generated. Then, power outputs with the different TMY data were calculated, and a variation of 3.7% was estimated due to the choice of decomposition model.

• The Korean Journal of Applied Statistics
• /
• v.23 no.6
• /
• pp.1157-1167
• /
• 2010

This paper details a method for establishing a wind energy map having($1Km{\times}1Km$) resolution. The map is essential for measurement and efficiency-testing of wind energy resources and wind site analysis. To this end, a statistical wind field model is estimated that covers 345,682 regions obtained by $1Km{\times}1Km$ lattices made over South Korea. The paper derives various characteristics of a regional wind energy resource under the statistical wind field model and estimates them to construct the wind energy map. Kolmogorov-Smirnov test, based on TMY(typical meteorological year) wind data of 76 weather station areas, shows that a Log-normal model is adequate for the statistical wind field model. The model is estimated by using the wind speed data of 345,682 regions provided by the National Institute of Meteorological Research(NIMR). Various wind energy statistics are studied under the Log-normal wind field model. As an application, the wind energy density(W$/m^2$) map of South Korea is constructed with a resolution of $1Km{\times}1Km$ and its utility for the wind site analysis is discussed.

• Journal of the Korean Solar Energy Society
• /
• v.32 no.2
• /
• pp.64-73
• /
• 2012

The angle of solar panels is calculated using solar radiation model for the efficient solar power generation. In ideal state, the time of maximum solar radiation is represented from 12:08 to 12:40 during a year at Gangneung and it save rage time is12:23. The maximum solar radiation is 1012$W/m^2$ and 708$W/m^2$ inc lear sky and cloudy sky, respectively. Solar radiation is more sensitive to North-South (N-S) slope angle than East-West (E-W) azimuth angle. Daily solar radiation on optimum angle of solar panel is higher than that on horizontal surface except for 90 days during summer. In order to apply to the real atmosphere, the TMY (typical meteorological Year) data which obtained from the 22 solar sites operated by KMA(Korea Meteorological Administration) during 11 years(2000 to 2010) is used as the input data of solar radiation model. The distribution of calculated solar radiation is similar to the observation, except in Andong, where it is overestimated, and in Mokpo and Heuksando, where it is underestimated. Statistical analysis is performed on calculated and observed monthly solar radiation on horizontal surface, and the calculation is overestimated from the observation. Correlationis 0.95 and RMSE (Root Mean Square Error) is10.81 MJ. The result shows that optimum N-S slope angles of solar panel are about $2^{\circ}$ lower than station latitude, but E-W slope angles are lower than ${\pm}1^{\circ}$. There are three types of solar panels: horizontal, fixed with optimum slope angle, and panels with tracker system. The energy efficiencies are on average 20% higher on fixed solar panel and 60% higher on tracker solar panel than compared to the horizontal solar panel, respectively.

• Journal of Institute of Convergence Technology
• /
• v.7 no.2
• /
• pp.7-12
• /
• 2017

At present, the Korea Meteorological Administration (KMA) measures the horizontal solar irradiation and meteorological data with time in 33 areas. Among these measured data, this study analyzed the tendency of applying the new analysis method by using the horizontal solar irradiation and meteorological data with the time which was measured in many regions across the country for thirty years from 1985 to 2014. The method applied to the analysis is to compare the value of the annual total horizontal solar irradiance and meteorological data for one year with the value of those for the previous year of each year, and give +1 when it is higher, and -1 when it is lower. The characteristics and relationships the horizontal solar irradiation and meteorological data in Daegu were evaluated and analyzed. Through the analysis results, the analysis method applied in this study could be well describe the characteristics and relationships of the solar irradiance and meteorological data during some years.

• Journal of Bio-Environment Control
• /
• v.20 no.2
• /
• pp.83-92
• /
• 2011

This study is about an analysis of surplus solar energy by important greenhouse type using Typical Meteorological Year (TMY) data which was secured in order to provide basic data for designing an optimum thermal storage system to accumulate surplus solar energy generated in greenhouses during the daytime. The 07-auto-1 and 08-auto-1 types showed similar heat budget tendencies regardless of greenhouse types. In other words, the ratios of surplus solar energy were about 20.0~29.0% regardless of greenhouse type. About 54.0~225.0% and 53.0~218.0% of required heating energy will be able to be supplemented respectively according to the greenhouse types. The 07-mono-1 and 07-mono-3 types also showed similar heat budget tendencies regardless of greenhouse types. In other words, the ratios of surplus solar energy were about 20.0~26.0% and 21.0~27.0% respectively by greenhouse type. About 57.0~211.0% and 62.0~228.0% of required heating energy will be able to be supplemented by greenhouse type. Except for Daegwallyeong and Suwon area, other regions can cover heating energy only by surplus solar energy, according to the study.