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Coordination of hydro units with wind power generation based on RAROC

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  • Liu, Yangyang
  • Jiang, Chuanwen
  • Shen, Jingshuang
  • Hu, Jiakai
  • Luo, Yifan

Abstract

Generating companies (GENCOs) with wind farms always suffer from the variations of wind power and energy prices. The coordination of wind power with hydro units is an effective way for GENCOs to enhance the ability of wind power dispatch, increase profit, and reduce risk. However, GENCOs still need to prepare a certain amount of economic capital to cover the possible losses and keep them operating even in a worst-case scenario. In this paper, bidding strategies' value at risk is adopted to determine the economic capital requirement, and the risk adjusted return on capital (RAROC) which represents the return of economic capital is introduced. Then, this paper proposes a coordination bidding strategy for wind farms and hydro stations in a GENCO based on RAROC optimization. RAROC can measure the performance of risk management and estimate the tradeoff between profit and risk. Compared to the risk-neutral strategies, the proposed method prevents the GENCO from huge losses by risk management. Compared to the traditional risk-averse strategies, the proposed method does not need to quantify the GENCO's risk aversion and it is helpful for economic capital determination. Numerical example illustrates the proposed bidding strategy, as well as the comparison analysis and sensitivity analysis.

Suggested Citation

  • Liu, Yangyang & Jiang, Chuanwen & Shen, Jingshuang & Hu, Jiakai & Luo, Yifan, 2015. "Coordination of hydro units with wind power generation based on RAROC," Renewable Energy, Elsevier, vol. 80(C), pages 783-792.
    • Handle: RePEc:eee:renene:v:80:y:2015:i:c:p:783-792
    DOI: 10.1016/j.renene.2015.02.062
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    References listed on IDEAS

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    Cited by:

    1. Ji, Ling & Huang, Guo-He & Huang, Lu-Cheng & Xie, Yu-Lei & Niu, Dong-Xiao, 2016. "Inexact stochastic risk-aversion optimal day-ahead dispatch model for electricity system management with wind power under uncertainty," Energy, Elsevier, vol. 109(C), pages 920-932.
    2. Ruijie Liu & Zhejing Bao & Jun Zheng & Lingxia Lu & Miao Yu, 2021. "Two-Stage Robust and Economic Scheduling for Electricity-Heat Integrated Energy System under Wind Power Uncertainty," Energies, MDPI, vol. 14(24), pages 1-25, December.
    3. Lu, Na & Wang, Guangyan & Su, Chengguo & Ren, Zaimin & Peng, Xiaoyue & Sui, Quan, 2024. "Medium- and long-term interval optimal scheduling of cascade hydropower-photovoltaic complementary systems considering multiple uncertainties," Applied Energy, Elsevier, vol. 353(PA).
    4. Mahtab Kaffash & Glenn Ceusters & Geert Deconinck, 2021. "Interval Optimization to Schedule a Multi-Energy System with Data-Driven PV Uncertainty Representation," Energies, MDPI, vol. 14(10), pages 1-20, May.
    5. Yinuo Huang & Chuangxin Guo & Yi Ding & Licheng Wang & Bingquan Zhu & Lizhong Xu, 2016. "A Multi-Period Framework for Coordinated Dispatch of Plug-in Electric Vehicles," Energies, MDPI, vol. 9(5), pages 1-16, May.
    6. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.

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