• Journal of the Korean Solar Energy Society
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• v.37 no.5
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• pp.13-26
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• 2017

Solar power is expected to account for a considerable proportion of domestic renewable energy compared to other renewable energy sources. In this study, capacity credits, which are the most important factors for evaluating the effective capacity of photovoltaic power, are estimated by capacity factor-based approximation method. To do this, we use the data of solar power generation and capacity over many years and calculate the capacity factors of the domestic solar power. The results of the existing methods and ours proposed in this paper are compared and analyzed.

• Journal of the Korean Solar Energy Society
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• v.39 no.4
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• pp.79-91
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• 2019

The capacity credit (CC) is a key metric for mid- to long-term power system capacity planning. The purpose of this study is to estimate the CCs of domestic wind turbines. Based on hourly capacity factor (CF) data during the seven years from 2011 to 2017, the new so-called probabilistic CF scheme is introduced to effectively reflect the variability of CFs on CC estimation. The CCs are then estimated through the CF-based method and the ELCC (Effective Load Carrying Capability) method reflecting the probabilistic CF scheme, and the results are compared. The results show that the CC value 0.019 for domestic wind turbines proposed in the $8^{th}$ Basic Plan for Electricity Supply and Demand corresponds to the CC with a confidence level slightly lower than 95%.