4.7 Article

Plant siting and economic potential of ocean thermal energy conversion in Indonesia a novel GIS-based methodology

期刊

ENERGY
卷 224, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2021.120121

关键词

Renewable energy; OTEC; Economic potential; Geographic information system; LCOE

资金

  1. Dutch research council NWO
  2. Indonesian Endowment Fund for Education (Lembaga Pengelola Dana Pendidikan e LPDP)

向作者/读者索取更多资源

Indonesia aims to achieve a 23% share of renewable energy by 2025, with Ocean Thermal Energy Conversion (OTEC) being considered as a potential contributor. The economic potential of OTEC depends on technical, economic, and natural variables, with the study proposing a novel methodology to assess this potential at different levels in Indonesia.
Indonesia strives for a renewable energy share of 23% by 2025. One option to contribute to this goal is Ocean Thermal Energy Conversion (OTEC). Despite a global theoretical potential of up to 30 TW, its economically deployable share remains unknown. This paper proposes a novel methodology, which enables to determine OTEC's economic potential for any regional scope considering technical, economic and natural variables. The methodology was tested for 100 MWe OTEC in Indonesia on a provincial and national level. Against a regionally variable electricity tariff of 6.67-18.14 US$ct.(2018)/kWh, the national economic potential is 0-2 GWe with a Levelized Cost of Electricity (LCOE) as low as 15.6 US$ct.(2018)/kWh. With an annual electricity production of 0-16 TWh, OTEC could provide up to 6% of Indonesia's electricity demand in 2018. The capacity factor, capital expenses and discount rate are the most sensitive variables of the LCOE on average. A nationally uniform feed-in tariff of 18 US$ct.(2018)/kWh or more could increase the economic potential significantly. The proposed methodology can be a helpful quick scan tool for determining economically interesting OTEC sites for follow-up in-depth feasibility studies. Limitations are discussed and future research, amongst others upscaling scenarios with cost reducing effects like technological learning, is recommended. (C) 2021 The Author(s). Published by Elsevier Ltd.

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