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Probabilistic modeling of wind energy potential for power grid expansion planning

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  • Kim, Gyeongmin
  • Hur, Jin

Abstract

The increasing integration of wind energy generation into energy systems has led to difficulties in power flow calculations due to uncertainty and variability, which significantly affect the stability and reliability of power grids. Consequently, it is critical to evaluate the energy security limit of power grids based on probabilistic approaches. In this paper, we propose the probabilistic modeling of wind energy potential for power grid expansion planning. The proposed probabilistic model estimates wind energy potential through Weibull distribution, Monte Carlo Simulation (MCS), and the enhanced spatial modeling based on universal kriging. It can be used to establish the expansion plan for transmission and distribution facilities to resolve the variability and uncertainty issues of wind generation resources, which is expected to increase the penetration levels of renewable energy. To validate the proposed model, the empirical data from the Jeju Island's wind farms are considered in South Korea.

Suggested Citation

  • Kim, Gyeongmin & Hur, Jin, 2021. "Probabilistic modeling of wind energy potential for power grid expansion planning," Energy, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:energy:v:230:y:2021:i:c:s0360544221010793
    DOI: 10.1016/j.energy.2021.120831
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    References listed on IDEAS

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    1. Park, BeomJun & Hur, Jin, 2018. "Spatial prediction of renewable energy resources for reinforcing and expanding power grids," Energy, Elsevier, vol. 164(C), pages 757-772.
    2. Jamil, M. & Parsa, S. & Majidi, M., 1995. "Wind power statistics and an evaluation of wind energy density," Renewable Energy, Elsevier, vol. 6(5), pages 623-628.
    3. Iribarren, Diego & Martín-Gamboa, Mario & Dufour, Javier, 2013. "Environmental benchmarking of wind farms according to their operational performance," Energy, Elsevier, vol. 61(C), pages 589-597.
    4. Deane, J.P. & Chiodi, Alessandro & Gargiulo, Maurizio & Ó Gallachóir, Brian P., 2012. "Soft-linking of a power systems model to an energy systems model," Energy, Elsevier, vol. 42(1), pages 303-312.
    5. Schaber, Katrin & Steinke, Florian & Hamacher, Thomas, 2012. "Transmission grid extensions for the integration of variable renewable energies in Europe: Who benefits where?," Energy Policy, Elsevier, vol. 43(C), pages 123-135.
    6. Gorenstein Dedecca, João & Hakvoort, Rudi A. & Herder, Paulien M., 2017. "Transmission expansion simulation for the European Northern Seas offshore grid," Energy, Elsevier, vol. 125(C), pages 805-824.
    7. Kim, Deockho & Hur, Jin, 2018. "Short-term probabilistic forecasting of wind energy resources using the enhanced ensemble method," Energy, Elsevier, vol. 157(C), pages 211-226.
    8. Dadkhah, Mojtaba & Jahangoshai Rezaee, Mustafa & Zare Chavoshi, Ahmad, 2018. "Short-term power output forecasting of hourly operation in power plant based on climate factors and effects of wind direction and wind speed," Energy, Elsevier, vol. 148(C), pages 775-788.
    9. Pei, Wei & Chen, Yanning & Sheng, Kun & Deng, Wei & Du, Yan & Qi, Zhiping & Kong, Li, 2015. "Temporal-spatial analysis and improvement measures of Chinese power system for wind power curtailment problem," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 148-168.
    10. Al kez, Dlzar & Foley, Aoife M. & McIlwaine, Neil & Morrow, D. John & Hayes, Barry P. & Zehir, M. Alparslan & Mehigan, Laura & Papari, Behnaz & Edrington, Chris S. & Baran, Mesut, 2020. "A critical evaluation of grid stability and codes, energy storage and smart loads in power systems with wind generation," Energy, Elsevier, vol. 205(C).
    11. Bertsch, Valentin & Hall, Margeret & Weinhardt, Christof & Fichtner, Wolf, 2016. "Public acceptance and preferences related to renewable energy and grid expansion policy: Empirical insights for Germany," Energy, Elsevier, vol. 114(C), pages 465-477.
    12. Lim, Hee-Chang & Jeong, Tae-Yoon, 2010. "Wind energy estimation of the Wol-Ryong coastal region," Energy, Elsevier, vol. 35(12), pages 4700-4709.
    13. Wais, Piotr, 2017. "A review of Weibull functions in wind sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1099-1107.
    14. Collins, Seán & Deane, J.P. & Ó Gallachóir, Brian, 2017. "Adding value to EU energy policy analysis using a multi-model approach with an EU-28 electricity dispatch model," Energy, Elsevier, vol. 130(C), pages 433-447.
    15. Mabel, M. Carolin & Raj, R. Edwin & Fernandez, E., 2010. "Adequacy evaluation of wind power generation systems," Energy, Elsevier, vol. 35(12), pages 5217-5222.
    16. Panwar, N.L. & Kaushik, S.C. & Kothari, Surendra, 2011. "Role of renewable energy sources in environmental protection: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1513-1524, April.
    17. Diuana, Fabio A. & Viviescas, Cindy & Schaeffer, Roberto, 2019. "An analysis of the impacts of wind power penetration in the power system of southern Brazil," Energy, Elsevier, vol. 186(C).
    18. Deetjen, Thomas A. & Rhodes, Joshua D. & Webber, Michael E., 2017. "The impacts of wind and solar on grid flexibility requirements in the Electric Reliability Council of Texas," Energy, Elsevier, vol. 123(C), pages 637-654.
    19. Ahmed, Ahmed Shata, 2010. "Wind energy as a potential generation source at Ras Benas, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2167-2173, October.
    20. Gutiérrez-Martín, F. & Da Silva-Álvarez, R.A. & Montoro-Pintado, P., 2013. "Effects of wind intermittency on reduction of CO2 emissions: The case of the Spanish power system," Energy, Elsevier, vol. 61(C), pages 108-117.
    21. Wagner, Hermann-Josef & Baack, Christoph & Eickelkamp, Timo & Epe, Alexa & Lohmann, Jessica & Troy, Stefanie, 2011. "Life cycle assessment of the offshore wind farm alpha ventus," Energy, Elsevier, vol. 36(5), pages 2459-2464.
    22. Schaber, Katrin & Steinke, Florian & Mühlich, Pascal & Hamacher, Thomas, 2012. "Parametric study of variable renewable energy integration in Europe: Advantages and costs of transmission grid extensions," Energy Policy, Elsevier, vol. 42(C), pages 498-508.
    23. Bilgili, Mehmet & Ozbek, Arif & Sahin, Besir & Kahraman, Ali, 2015. "An overview of renewable electric power capacity and progress in new technologies in the world," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 323-334.
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    4. Zhong, Mingwei & Xu, Cancheng & Xian, Zikang & He, Guanglin & Zhai, Yanpeng & Zhou, Yongwang & Fan, Jingmin, 2024. "DTTM: A deep temporal transfer model for ultra-short-term online wind power forecasting," Energy, Elsevier, vol. 286(C).
    5. Sun, X.Y. & Zhong, X.H. & Zhang, M.Y. & Zhou, T., 2022. "Experimental investigation on a novel wind-to-heat system with high efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    6. Juseung Choi & Hoyong Eom & Seung-Mook Baek, 2022. "A Wind Power Probabilistic Model Using the Reflection Method and Multi-Kernel Function Kernel Density Estimation," Energies, MDPI, vol. 15(24), pages 1-17, December.
    7. Huang, Nantian & Zhao, Xuanyuan & Guo, Yu & Cai, Guowei & Wang, Rijun, 2023. "Distribution network expansion planning considering a distributed hydrogen-thermal storage system based on photovoltaic development of the Whole County of China," Energy, Elsevier, vol. 278(C).

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