국내 풍력단지 증가에 따른평활효과(Smoothing Effect) 정량화
Quantitative Analysis of the Smoothing Effect According to the Number of Wind Farms in Korea
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초록
The number of wind farms in Korea is expected to increase due to the pressure of the post-2020 climate targets. However, this may result in some difficulties for the operation and expansion planning of our power system, due to the characteristicsof wind energy, such as its intermittency and non-dispatchability. Generally, a decrease in these characteristics is called the‘smoothing effect’. In this study, the smoothing effect is defined as a decrease in the variability of the power output. it is well knownthat the variability of the power output from wind farms is reduced when more wind farms are integrated into the system. Aquantitative analysis of the smoothing effect is necessary to predict the variability of wind energy and this can help the power systemto be operated or planned more efficiently. In this study, the methodologies of previous studies were applied to 6 wind farms in Korea. As a result, it was found that the smoothing effect in spring and winter was more effective than that in summer and fall and increasedwith increasing distance between the wind farms. The expected variability obtained from the equation estimated using the quantitativeanalysis of the smoothing effect was analogous to the variability of the aggregate power output from the entire wind farms in thepower system.
Abstract
The number of wind farms in Korea is expected to increase due to the pressure of the post-2020 climate targets. However, this may result in some difficulties for the operation and expansion planning of our power system, due to the characteristicsof wind energy, such as its intermittency and non-dispatchability. Generally, a decrease in these characteristics is called the‘smoothing effect’. In this study, the smoothing effect is defined as a decrease in the variability of the power output. it is well knownthat the variability of the power output from wind farms is reduced when more wind farms are integrated into the system. Aquantitative analysis of the smoothing effect is necessary to predict the variability of wind energy and this can help the power systemto be operated or planned more efficiently. In this study, the methodologies of previous studies were applied to 6 wind farms in Korea. As a result, it was found that the smoothing effect in spring and winter was more effective than that in summer and fall and increasedwith increasing distance between the wind farms. The expected variability obtained from the equation estimated using the quantitativeanalysis of the smoothing effect was analogous to the variability of the aggregate power output from the entire wind farms in thepower system.
참고문헌 (13)
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