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Optimal planning for wind power capacity in an electric power system

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  • Xu, M.
  • Zhuan, X.

Abstract

The optimization of wind power capacity for an electric power system is studied with the system operation, economy and reliability emphasized. The economic aspect is evaluated in view of the system-wide social cost, which includes the social cost of conventional and wind electricity generation, the reserve cost, the value of lost load and the opportunity cost of wind curtailments. The probabilistic methods are adopted to assess the system reliability in terms of the loss-of-load probability (LOLP) and to estimate the spinning reserve depending on the uncertainty of wind power generation and load demand forecast. Within the probabilistic framework, the wind power capacity planning problem is addressed by the chance constrained programming (CCP) approach, which is capable to handle with such an optimization problem containing random variables and probabilistic constraints. The CCP-based wind power capacity planning problem aims at minimizing the system social cost while satisfying the reliability criteria and operational constraints. A case study is done to determine the optimal wind power installation for a typical isolated power system. This paper provides system planners and policy makers with an approach to initiating wind power investment and incentives in order to facilitate the development of a cost-effective wind market.

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  • Xu, M. & Zhuan, X., 2013. "Optimal planning for wind power capacity in an electric power system," Renewable Energy, Elsevier, vol. 53(C), pages 280-286.
    • Handle: RePEc:eee:renene:v:53:y:2013:i:c:p:280-286
    DOI: 10.1016/j.renene.2012.11.015
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    References listed on IDEAS

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    Cited by:

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    2. Ranjbar, Hossein & Kazemi, Mostafa & Amjady, Nima & Zareipour, Hamidreza & Hosseini, Seyed Hamid, 2022. "Maximizing the utilization of existing grids for renewable energy integration," Renewable Energy, Elsevier, vol. 189(C), pages 618-629.
    3. Karamarković, Vladan M. & Nikolić, Miloš V. & Karamarković, Rade M. & Karamarković, Miodrag V. & Marašević, Miljan R., 2018. "Techno-economic optimization for two SHPPs that form a combined system," Renewable Energy, Elsevier, vol. 122(C), pages 265-274.
    4. Sansavini, G. & Piccinelli, R. & Golea, L.R. & Zio, E., 2014. "A stochastic framework for uncertainty analysis in electric power transmission systems with wind generation," Renewable Energy, Elsevier, vol. 64(C), pages 71-81.
    5. Hui Li & Gengyin Li & Siwei Liu & Yuning Wang & Zhidong Wang & Jiaming Wang & Ning Zhang, 2017. "Research on Optimal Planning of Access Location and Access Capacity of Large-Scale Integrated Wind Power Plants," Energies, MDPI, vol. 10(4), pages 1-13, April.
    6. Dahu Li & Xiaoda Cheng & Leijiao Ge & Wentao Huang & Jun He & Zhongwei He, 2022. "Multiple Power Supply Capacity Planning Research for New Power System Based on Situation Awareness," Energies, MDPI, vol. 15(9), pages 1-24, April.
    7. Mitra, Arghya & Chatterjee, Dheeman, 2013. "A sensitivity based approach to assess the impacts of integration of variable speed wind farms on the transient stability of power systems," Renewable Energy, Elsevier, vol. 60(C), pages 662-671.
    8. Chinmoy, Lakshmi & Iniyan, S. & Goic, Ranko, 2019. "Modeling wind power investments, policies and social benefits for deregulated electricity market – A review," Applied Energy, Elsevier, vol. 242(C), pages 364-377.
    9. Panda, Ambarish & Tripathy, M., 2015. "Security constrained optimal power flow solution of wind-thermal generation system using modified bacteria foraging algorithm," Energy, Elsevier, vol. 93(P1), pages 816-827.
    10. Jadidoleslam, Morteza & Ebrahimi, Akbar & Latify, Mohammad Amin, 2017. "Probabilistic transmission expansion planning to maximize the integration of wind power," Renewable Energy, Elsevier, vol. 114(PB), pages 866-878.
    11. Oree, Vishwamitra & Sayed Hassen, Sayed Z. & Fleming, Peter J., 2017. "Generation expansion planning optimisation with renewable energy integration: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 790-803.
    12. Adel F. Alrasheedi & Ahmad M. Alshamrani & Khalid A. Alnowibet, 2023. "Investing in Wind Energy Using Bi-Level Linear Fractional Programming," Energies, MDPI, vol. 16(13), pages 1-14, June.
    13. Fan, Xiao-chao & Wang, Wei-qing & Shi, Rui-jing & Li, Feng-ting, 2015. "Review of developments and insights into an index system of wind power utilization level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 463-471.
    14. Platero, C.A. & Nicolet, C. & Sánchez, J.A. & Kawkabani, B., 2014. "Increasing wind power penetration in autonomous power systems through no-flow operation of Pelton turbines," Renewable Energy, Elsevier, vol. 68(C), pages 515-523.

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