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Renewable Energy Options for a Rural Village in North Korea

Author

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  • Dahyun Kang

    (Graduate School of International Studies, Yonsei University, Seoul 03722, Korea)

  • Tae Yong Jung

    (Graduate School of International Studies, Yonsei University, Seoul 03722, Korea)

Abstract

The national electrification rate of North Korea is extremely low and the situation in rural areas is even worse. Thus, this study designs a virtual electrification project for a rural village in North Pyongan and compares an off-grid energy system and on-grid system in terms of net present cost (NPC) and levelized cost of energy (LCOE) to define the most cost-effective energy system. Using Hybrid Optimization of Multiple Energy Resources (HOMER), this study designs two off-grid systems that apply different types of batteries—lead–acid and lithium-ion energy storage systems (ESS)—and determines the NPC and LCOE of the most cost-effective system. Then, it calculates the NPC and LCOE of grid extension by adding necessary costs required for generation, transmission, and distribution. The result shows that the hybrid energy system (HES) of solar photovoltaic (PV), wind turbines, lead–acid batteries, and diesel generators is the most cost-effective option for the selected location. The range of breakeven grid-extension distance is from 9.69 km to 20.57 km. The sensitivity analysis based on different discount rates shows that a higher discount rate means a shorter breakeven distance. This analysis suggests that deploying an HES is one way to improve the electrification rate for remote and rural areas in North Korea.

Suggested Citation

  • Dahyun Kang & Tae Yong Jung, 2020. "Renewable Energy Options for a Rural Village in North Korea," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2452-:d:334966
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    References listed on IDEAS

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    Cited by:

    1. Maksymilian Homa & Anna Pałac & Maciej Żołądek & Rafał Figaj, 2022. "Small-Scale Hybrid and Polygeneration Renewable Energy Systems: Energy Generation and Storage Technologies, Applications, and Analysis Methodology," Energies, MDPI, vol. 15(23), pages 1-52, December.
    2. Tamjid Shabestari, Sara & Kasaeian, Alibakhsh & Vaziri Rad, Mohammad Amin & Forootan Fard, Habib & Yan, Wei-Mon & Pourfayaz, Fathollah, 2022. "Techno-financial evaluation of a hybrid renewable solution for supplying the predicted power outages by machine learning methods in rural areas," Renewable Energy, Elsevier, vol. 194(C), pages 1303-1325.
    3. Jann Michael Weinand & Maximilian Hoffmann & Jan Gopfert & Tom Terlouw & Julian Schonau & Patrick Kuckertz & Russell McKenna & Leander Kotzur & Jochen Lin{ss}en & Detlef Stolten, 2022. "Global LCOEs of decentralized off-grid renewable energy systems," Papers 2212.12742, arXiv.org, revised Mar 2023.

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