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http://dx.doi.org/10.1016/j.net.2022.03.021

Examination of excess electricity generation patterns in South Korea under the renewable initiative for 2030  

Kim, Philseo (Department of Nuclear and Quantum Engineering, KAIST)
Cho, So-Bin (Department of Nuclear Engineering and Radiological Sciences, University of Michigan)
Yim, Man-Sung (Department of Nuclear and Quantum Engineering, KAIST)
Publication Information
Nuclear Engineering and Technology / v.54, no.8, 2022 , pp. 2883-2897 More about this Journal
Abstract
According to the Renewable Energy 3020 Implementation Plan announced in 2017 by the South Korean government, the electricity share of renewable energy will be expanded to 20% of the total electricity generation by 2030. Given the intermittency of electricity generation from renewable energy, realization of such a plan presents challenges to managing South Korea's isolated national electric grid and implies potentially large excess electricity generation in certain situations. The purpose of this study is: 1) to develop a model to accurately simulate the effects of excess electricity generation from renewables which would arise during the transition, and 2) to propose strategies to manage excess electricity generation through effective utilization of domestic electricity generating capabilities. Our results show that in periods of greater PV and wind power, namely the spring and fall seasons, the frequency of excess electricity generation increases, while electricity demand decreases. This being the case, flexible operation of coal and nuclear power plants along with LNG and pumped-storage hydroelectricity can be used to counterbalance the excess electricity generation from renewables. In addition, nuclear energy plays an important role in reducing CO2 emissions and electricity costs unlike the fossil fuel-based generation sources outlined in the 8th Basic Plan.
Keywords
Renewable energy resources; Nuclear energy; Energy system modeling and optimization; Excess electricity;
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Times Cited By KSCI : 4  (Citation Analysis)
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