IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v282y2023ics0360544223022521.html
   My bibliography  Save this article

Flexible renewable energy planning based on multi-step forecasting of interregional electricity supply and demand: Graph-enhanced AI approach

Author

Listed:
  • Kim, SangYoun
  • Heo, SungKu
  • Nam, KiJeon
  • Woo, TaeYong
  • Yoo, ChangKyoo

Abstract

Jeju Island faces curtailment problems when renewable energy generation exceeds the facility capacity. In addition, the renewable energy system cannot achieve consistent operation because of the uncertainty of renewable energy sources (RES) and their complex spatiotemporal patterns. Climate change and extreme meteorological phenomena also affect the energy system of the island. Therefore, it is essential to maximize RES exploitation to accomplish carbon-free energy production. This study developed a rolling horizon optimization–based flexible renewable energy distribution planning (FxRE-Plan) based on an artificial intelligence-driven spatiotemporal RES prediction model. An adaptive graph convolutional recurrent network (AGCRN) was used to develop a spatiotemporal prediction model. Then, FxRE-Plan was determined using a multiobjective genetic algorithm to maximize the RES potential under climate change scenarios. The FxRE-Plan was evaluated and compared with the current operation of the electric grid in Jeju Island through economic, environmental cost, and climate change vulnerability assessment index. The results of this research show that the AGCRN–based spatiotemporal prediction model exhibited superior prediction performance, achieving a 95% R2. In addition, the FxRE-Plan reduced greenhouse gas emissions by approximately 11.5% at maximum and climate change vulnerability. Hence, the proposed FxRE-Plan can be used to solve curtailments in real electric grids by pursuing carbon-free islands.

Suggested Citation

  • Kim, SangYoun & Heo, SungKu & Nam, KiJeon & Woo, TaeYong & Yoo, ChangKyoo, 2023. "Flexible renewable energy planning based on multi-step forecasting of interregional electricity supply and demand: Graph-enhanced AI approach," Energy, Elsevier, vol. 282(C).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223022521
    DOI: 10.1016/j.energy.2023.128858
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223022521
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128858?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Naik, Jyotirmayee & Dash, Pradipta Kishore & Dhar, Snehamoy, 2019. "A multi-objective wind speed and wind power prediction interval forecasting using variational modes decomposition based Multi-kernel robust ridge regression," Renewable Energy, Elsevier, vol. 136(C), pages 701-731.
    2. Maroufmashat, Azadeh & Elkamel, Ali & Fowler, Michael & Sattari, Sourena & Roshandel, Ramin & Hajimiragha, Amir & Walker, Sean & Entchev, Evgueniy, 2015. "Modeling and optimization of a network of energy hubs to improve economic and emission considerations," Energy, Elsevier, vol. 93(P2), pages 2546-2558.
    3. Changgun Lee & Seunghyuk Im & Jaeyeop Jung & Byongjun Lee, 2020. "BESS Deployment Strategy in Jeju Carbon-Free Islands for Reducing Renewable Energy Curtailment," Energies, MDPI, vol. 13(22), pages 1-13, November.
    4. Braungardt, Sibylle & Bürger, Veit & Zieger, Jana & Bosselaar, Lex, 2019. "How to include cooling in the EU Renewable Energy Directive? Strategies and policy implications," Energy Policy, Elsevier, vol. 129(C), pages 260-267.
    5. Jae-Hyup Lee & Jisuk Woo, 2020. "Green New Deal Policy of South Korea: Policy Innovation for a Sustainability Transition," Sustainability, MDPI, vol. 12(23), pages 1-17, December.
    6. Nematollahi, Omid & Kim, Kyung Chun, 2017. "A feasibility study of solar energy in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 566-579.
    7. Glomb, Lukas & Liers, Frauke & Rösel, Florian, 2022. "A rolling-horizon approach for multi-period optimization," European Journal of Operational Research, Elsevier, vol. 300(1), pages 189-206.
    8. Sofia Spyridonidou & Georgia Sismani & Eva Loukogeorgaki & Dimitra G. Vagiona & Hagit Ulanovsky & Daniel Madar, 2021. "Sustainable Spatial Energy Planning of Large-Scale Wind and PV Farms in Israel: A Collaborative and Participatory Planning Approach," Energies, MDPI, vol. 14(3), pages 1-23, January.
    9. Nam, KiJeon & Hwangbo, Soonho & Yoo, ChangKyoo, 2020. "A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
    10. Bischi, Aldo & Taccari, Leonardo & Martelli, Emanuele & Amaldi, Edoardo & Manzolini, Giampaolo & Silva, Paolo & Campanari, Stefano & Macchi, Ennio, 2019. "A rolling-horizon optimization algorithm for the long term operational scheduling of cogeneration systems," Energy, Elsevier, vol. 184(C), pages 73-90.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Heo, SungKu & Byun, Jaewon & Ifaei, Pouya & Ko, Jaerak & Ha, Byeongmin & Hwangbo, Soonho & Yoo, ChangKyoo, 2024. "Towards mega-scale decarbonized industrial park (Mega-DIP): Generative AI-driven techno-economic and environmental assessment of renewable and sustainable energy utilization in petrochemical industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ifaei, Pouya & Tayerani Charmchi, Amir Saman & Loy-Benitez, Jorge & Yang, Rebecca Jing & Yoo, ChangKyoo, 2022. "A data-driven analytical roadmap to a sustainable 2030 in South Korea based on optimal renewable microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    2. Łukasz Jarosław Kozar & Robert Matusiak & Marta Paduszyńska & Adam Sulich, 2022. "Green Jobs in the EU Renewable Energy Sector: Quantile Regression Approach," Energies, MDPI, vol. 15(18), pages 1-21, September.
    3. Lim, Juin Yau & Safder, Usman & How, Bing Shen & Ifaei, Pouya & Yoo, Chang Kyoo, 2021. "Nationwide sustainable renewable energy and Power-to-X deployment planning in South Korea assisted with forecasting model," Applied Energy, Elsevier, vol. 283(C).
    4. Aleksandra Matuszewska-Janica & Dorota Żebrowska-Suchodolska & Urszula Ala-Karvia & Marta Hozer-Koćmiel, 2021. "Changes in Electricity Production from Renewable Energy Sources in the European Union Countries in 2005–2019," Energies, MDPI, vol. 14(19), pages 1-27, October.
    5. József Kádár & Martina Pilloni & Tareq Abu Hamed, 2023. "A Survey of Renewable Energy, Climate Change, and Policy Awareness in Israel: The Long Path for Citizen Participation in the National Renewable Energy Transition," Energies, MDPI, vol. 16(5), pages 1-16, February.
    6. Joseph Uchenna Ezekwugo & Anthony Ibe & Alwell Nteegah, 2022. "Optimization of Integrated Energy Systems in a Developing Economy using Technology," American Journal of Economics and Business Administration, Science Publications, vol. 14(1), pages 1-11, March.
    7. Lee, Yoonjae & Ha, Byeongmin & Hwangbo, Soonho, 2022. "Generative model-based hybrid forecasting model for renewable electricity supply using long short-term memory networks: A case study of South Korea's energy transition policy," Renewable Energy, Elsevier, vol. 200(C), pages 69-87.
    8. Doyeon Lee & Keunhwan Kim, 2021. "Research and Development Investment and Collaboration Framework for the Hydrogen Economy in South Korea," Sustainability, MDPI, vol. 13(19), pages 1-28, September.
    9. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Yang, Shanlin, 2020. "A robust optimization approach for coordinated operation of multiple energy hubs," Energy, Elsevier, vol. 197(C).
    10. Mokhinabonu Mardonova & Yosoon Choi, 2019. "Assessment of Photovoltaic Potential of Mining Sites in Uzbekistan," Sustainability, MDPI, vol. 11(10), pages 1-13, May.
    11. Chen, Xue-Jun & Zhao, Jing & Jia, Xiao-Zhong & Li, Zhong-Long, 2021. "Multi-step wind speed forecast based on sample clustering and an optimized hybrid system," Renewable Energy, Elsevier, vol. 165(P1), pages 595-611.
    12. Capone, Martina & Guelpa, Elisa & Verda, Vittorio, 2021. "Multi-objective optimization of district energy systems with demand response," Energy, Elsevier, vol. 227(C).
    13. Rezaei, Navid & Pezhmani, Yasin & Khazali, Amirhossein, 2022. "Economic-environmental risk-averse optimal heat and power energy management of a grid-connected multi microgrid system considering demand response and bidding strategy," Energy, Elsevier, vol. 240(C).
    14. Chen, Zhen & Archibald, Thomas W., 2024. "Maximizing the survival probability in a cash flow inventory problem with a joint service level constraint," International Journal of Production Economics, Elsevier, vol. 270(C).
    15. Kyungho Song & Hyun Kim & Jisoo Cha & Taedong Lee, 2021. "Matching and Mismatching of Green Jobs: A Big Data Analysis of Job Recruiting and Searching," Sustainability, MDPI, vol. 13(7), pages 1-15, April.
    16. Wakui, Tetsuya & Akai, Kazuki & Yokoyama, Ryohei, 2022. "Shrinking and receding horizon approaches for long-term operational planning of energy storage and supply systems," Energy, Elsevier, vol. 239(PD).
    17. Zhengwei Huang & Jin Huang & Jintao Min, 2022. "SSA-LSTM: Short-Term Photovoltaic Power Prediction Based on Feature Matching," Energies, MDPI, vol. 15(20), pages 1-16, October.
    18. Saletti, Costanza & Morini, Mirko & Gambarotta, Agostino, 2022. "Smart management of integrated energy systems through co-optimization with long and short horizons," Energy, Elsevier, vol. 250(C).
    19. Khan, Zulfiqar Ahmad & Khan, Shabbir Ahmad & Hussain, Tanveer & Baik, Sung Wook, 2024. "DSPM: Dual sequence prediction model for efficient energy management in micro-grid," Applied Energy, Elsevier, vol. 356(C).
    20. Geon Hwa Ryu & Young-Gon Kim & Sung Jo Kwak & Man Soo Choi & Moon-Seon Jeong & Chae-Joo Moon, 2022. "Atmospheric Stability Effects on Offshore and Coastal Wind Resource Characteristics in South Korea for Developing Offshore Wind Farms," Energies, MDPI, vol. 15(4), pages 1-23, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223022521. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.