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A multi-period MILP model for the investment and design planning of a national-level complex renewable energy supply system

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  • Han, Seulki
  • Kim, Jiyong

Abstract

This study presents a comprehensive approach to plan and analyze strategic investment for the design of an integrated renewable energy source-based energy supply system. Initially, the renewable energy source-based energy supply system superstructure was generated, which included 1) different energy sources (wind, solar, and biomass), 2) various energy facilities (for production, storage, and transportation), and 3) three types of final energy demand (electricity, hydrogen, and liquid fuel). A network optimization model was then developed using a mixed integer linear programming. The optimization model was used to determine the investment timing and allocation to the underlying energy supply system, which includes the type and quantity of utilized renewable sources, in addition to the timing of installation, number and location and of energy facilities installed. The capability of the proposed approach is validated through a case study of future Korea. As a result, we identified the optimal configuration and the investment timing of a complex renewable energy supply system, which was determined by regional resource potentials and cost-effectiveness of the involved technologies. The case study results can be used as a guideline to support decision-making of energy industry stakeholders and government policymakers in the strategic planning of a sustainable energy system.

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  • Han, Seulki & Kim, Jiyong, 2019. "A multi-period MILP model for the investment and design planning of a national-level complex renewable energy supply system," Renewable Energy, Elsevier, vol. 141(C), pages 736-750.
    • Handle: RePEc:eee:renene:v:141:y:2019:i:c:p:736-750
    DOI: 10.1016/j.renene.2019.04.017
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    Cited by:

    1. Kim, Sunwoo & Choi, Yechan & Park, Joungho & Adams, Derrick & Heo, Seongmin & Lee, Jay H., 2024. "Multi-period, multi-timescale stochastic optimization model for simultaneous capacity investment and energy management decisions for hybrid Micro-Grids with green hydrogen production under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    2. Okada, Masaki & Onishi, Terumi & Obara, Shin’ya, 2020. "A design algorithm for an electric power system using wide-area interconnection of renewable energy," Energy, Elsevier, vol. 193(C).
    3. You, Chanhee & Han, Seulki & Kim, Jiyong, 2021. "Integrative design of the optimal biorefinery and bioethanol supply chain under the water-energy-food-land (WEFL) nexus framework," Energy, Elsevier, vol. 228(C).
    4. Haikarainen, Carl & Pettersson, Frank & Saxén, Henrik, 2020. "Optimized phasing of the development of a regional energy system," Energy, Elsevier, vol. 206(C).
    5. Sgarbossa, Fabio & Arena, Simone & Tang, Ou & Peron, Mirco, 2023. "Renewable hydrogen supply chains: A planning matrix and an agenda for future research," International Journal of Production Economics, Elsevier, vol. 255(C).
    6. Shen, Feifei & Zhao, Liang & Du, Wenli & Zhong, Weimin & Qian, Feng, 2020. "Large-scale industrial energy systems optimization under uncertainty: A data-driven robust optimization approach," Applied Energy, Elsevier, vol. 259(C).
    7. Sgarbossa, Fabio & Arena, Simone & Tang, Ou & Peron, Mirco, 2022. "Reprint of: Renewable hydrogen supply chains: A planning matrix and an agenda for future research," International Journal of Production Economics, Elsevier, vol. 250(C).
    8. Potrč, Sanja & Čuček, Lidija & Martin, Mariano & Kravanja, Zdravko, 2021. "Sustainable renewable energy supply networks optimization – The gradual transition to a renewable energy system within the European Union by 2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).

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