Myeongchan Oh

A Hybrid Wind Speed Forecasting Framework Based on Downscaled Multi-Model Forecasts and Machine Learning for Day-Ahead Wind Power Applications

Donggun Oh, Minkyu Lee, Myeongchan Oh, Chang Ki Kim et autres

Accurate day-ahead wind speed forecasting is essential for wind power forecasting and electricity market participation under increasing renewable energy penetration. This study proposes a hybrid forecasting framework that combines raw global forecasts from GFS and IFS, the KMA KIM-RDAPS regional forecast, and …

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Estimation of Spectral Solar Irradiance Toward Deriving Spectral Mismatch Factor Across Diverse Photovoltaic Technologies by Using Aerosol Optical Properties

Chang Ki Kim, Hyun‐Goo Kim, Myeongchan Oh, Boyoung Kim et autres

This study presents a machine-learning framework for predicting spectral solar irradiance from 300 to 1100 nm using the random forest and neural network models. Two approaches were compared: one using the real aerosol optical depth at discrete wavelengths and the other using …

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Assessing the photovoltaic potential on building facades and roofs in Korea using 3D building shadow simulation

Chang-Yeol Yun, Myeongchan Oh, Chang Ki Kim, Yongil Kim

This study presents a comprehensive framework to assess the photovoltaic (PV) potential of building facades and rooftops in South Korea, including theoretical, technical, and market perspectives. Ground-level solar irradiance data were obtained from the COMS-2 (Cheollian-2) satellite and processed on a 100 …

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Short-term Load Forecasting of Jeju Island Considering the Behind-the-Meter Solar Power

Hyun‐Goo Kim, Chang Ki Kim, Myeongchan Oh, Dae‐Jin Kim et autres

Developing an Energy Self-Reliance Model in a Sri Lankan Rural Area

Donggun Oh, Yong-Heack Kang, Boyoung Kim, Chang-yeol Yun et autres

56.9 55.0 Coal 1.8 2.0 Major hydro 30.9 51.9

A novel model to estimate regional differences in time-series solar and wind forecast predictability across small regions: A case study in South Korea

Myeongchan Oh, Chang Ki Kim, Boyoung Kim, Hyun‐Goo Kim

Forecasting techniques for solar and wind energy are essential for controlling their variability and are being heavily researched. However, regional differences in predictability in these forecast models have rarely been studied. Regional differences refer to differences in forecast performance based on location. …

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Toward Improved Site-Adaptation for Direct Normal Irradiance: Exploiting Sky-Condition Classification for Improved Regression-Based, Quantile-Based, and Neural Network Models

Elvina Faustina Dhata, Chang Ki Kim, Myeongchan Oh, Hyun‐Goo Kim

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Developing Prediction Models for Solar Photovoltaic Energy Generation Using Statistical and Machine Learning Methods

Yoo-Jung Kim, Na-Hyeong Kim, So‐Yeon Park, Chang Ki Kim et autres

As renewable energy generation prediction systems have been introduced into the energy trading market, accurate prediction of solar photovoltaic (PV) energy generation has become a crucial challenge for ensuring stable trade of variable energy. Therefore, it is essential to quantitatively investigate and …

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Comprehensive Analysis of Spectral Mismatch Factor for Solar Cells Based on In Situ Observation of Aerosol Optical Depth Spectra and Solar Spectral Irradiance in Korea

Chang Ki Kim, Hyun‐Goo Kim, Yong-Heack Kang, Myeongchan Oh

The spectral mismatch factor for solar cells quantifies their relative performance in converting solar irradiance between the incident and reference solar spectra into electricity. This study attempted to evaluate the spectral mismatch factor for eight types of solar cells and investigate their …

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Real-Time Terrain Correction of Satellite Imagery-Based Solar Irradiance Maps Using Precomputed Data and Memory Optimization

Myeongchan Oh, Chang Ki Kim, Boyoung Kim, Yong-Heack Kang et autres

Satellite imagery-based solar irradiance mapping studies are essential for large-scale solar energy assessments but are limited in spatial resolution and accuracy. Despite efforts to increase map resolution by correcting inaccuracies caused by shadows on the terrain, the computational time of these models …

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BIPV Market Potential Analysis with Building Shadow Simulation

Chang-Yeol Yun, Myeongchan Oh, Boyoung Kim, Je-Hyun Lee et autres

Photovoltaic potential is directly affected by solar radiation. In particular, in the case of densely populated areas, the shadow effect has a fatal effect on the reduction of insolation on the building surface. In this study, in order to calculate the building-type …

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Developing Prediction Models for Solar Photovoltaic Energy Generation Using GBM

Yoo-Jung Kim, Na-Hyeong Kim, So‐Yeon Park, Jin Young Kim et autres

As renewable energy generation prediction system has been introduced into the energy trading market, making a model to accurately predict the quantity of solar photovoltaic (PV) energy generation has become a significant problem. Moreover, to encourage an accurate prediction of the quantity …

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