Ramp Characteristics of Photovoltaic and Wind Power in South Korea

Kim, Shin Young; Kim, Hyun‐Goo; Kim, Bo Young; Kim, Chang Ki; Kang, Yong-Heack; Jang, Gil Soo

doi:10.1109/honet.2019.8908000

2019 IEEE 16th International Conference on Smart Cities: Improving Quality of Life Using ICT &Amp; IoT and AI (HONET-ICT) 2019

DOI: 10.1109/honet.2019.8908000

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Ramp Characteristics of Photovoltaic and Wind Power in South Korea

Shin Young Kim

Hyun‐Goo Kim

Bo Young Kim

et al.

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“…Based on the PV power potential, according to the seasonal analysis of the four cities, Jeju Island produced the lowest generation in winter, unlike the other three cities. In addition, in the previous study, when the PV power generation ramp analysis was conducted on 1450 PV power plants in Korea, the average ramp rate of Jeju Island was 11.5%, which was the most variable region in Korea [27]. Therefore, when the PV penetration level increased, especially in Jeju Island, it was necessary to thoroughly prepare for the worst case and take complementary measures when estimating backup facility capacity and reserve.…”

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Prefeasibility Study of Photovoltaic Power Potential Based on a Skew-Normal Distribution

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Solar energy does not always follow the normal distribution due to the characteristics of natural energy. The system advisor model (SAM), a well-known energy performance analysis program, analyzes exceedance probabilities by dividing solar irradiance into two cases, i.e., when normal distribution is followed, and when normal distribution is not followed. However, it does not provide a mathematical model for data distribution when not following the normal distribution. The present study applied the skew-normal distribution when solar irradiance does not follow the normal distribution, and calculated photovoltaic power potential to compare the result with those using the two existing methods. It determined which distribution was more appropriate between normal and skew-normal distributions using the Jarque–Bera test, and then the corrected Akaike information criterion (AICc). As a result, three places in Korea showed that the skew-normal distribution was more appropriate than the normal distribution during the summer and winter seasons. The AICc relative likelihood between two models was more than 0.3, which showed that the difference between the two models was not extremely high. However, considering that the proportion of uncertainty of solar irradiance in photovoltaic projects was 5% to 17%, more accurate models need to be chosen.

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Prefeasibility Study of Photovoltaic Power Potential Based on a Skew-Normal Distribution

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Ramp Characteristics of Photovoltaic and Wind Power in South Korea

Cited by 1 publication

References 3 publications

Prefeasibility Study of Photovoltaic Power Potential Based on a Skew-Normal Distribution

Prefeasibility Study of Photovoltaic Power Potential Based on a Skew-Normal Distribution

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