Optimal Hybrid Renewable Airport Power System: Empirical Study on Incheon International Airport, South Korea
Seoin Baek,
Heetae Kim and
Hyun Joon Chang
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Seoin Baek: KAIST (Korea Advanced Institute of Science and Technology), Graduate School of Innovation and Technology, 2225, N5, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea
Heetae Kim: KAIST (Korea Advanced Institute of Science and Technology), Graduate School of Innovation and Technology, 2225, N5, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea
Hyun Joon Chang: KAIST (Korea Advanced Institute of Science and Technology), Graduate School of Innovation and Technology, 2225, N5, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea
Sustainability, 2016, vol. 8, issue 6, 1-13
Abstract:
In response to global energy problems (e.g., the oil crisis, the Fukushima accident, the Paris Agreement), the South Korean government has executed a strict renewable energy plan to decrease the country’s dependence on fossil fuel. Public facilities, such as international airports, which use substantial amounts of electricity, are the most in need of government regulation. In this study, we attempt to determine the optimal hybrid electricity generation system for South Korea’s largest airport: Incheon International Airport. In the analysis, we use three scenarios: the current load, 120% of the current load, and 140% of the current load, according to the plan to expand Incheon International Airport. According to the COE (cost of electricity) and the NPC (net present cost) of the result, it is economically feasible to completely cover the potential increase in the electric load with PV power. Government policy implications and limitations are discussed.
Keywords: HOMER; economic feasibility; scenario analysis; photovoltaic; airport (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (8)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:8:y:2016:i:6:p:562-:d:72192
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