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Scheduling of wind-battery hybrid system in the electricity market using distributionally robust optimization

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  • Xu, Xiao
  • Hu, Weihao
  • Cao, Di
  • Huang, Qi
  • Liu, Zhou
  • Liu, Wen
  • Chen, Zhe
  • Blaabjerg, Frede

Abstract

With the liberation of the electricity market, a growing number of investors participate in market bidding. However, due to the inaccurate prediction of wind power, the interest of the investors can be damaged. In order to solve such problem, a distributionally robust chance-constrained (DRCC) scheduling for a wind-battery hybrid system in the day-ahead electricity market is developed by considering the uncertain wind power. The overall objectives of this paper contain revenue calculation from the electricity market, curtailment penalty caused by the wind power, and degradation cost of the battery. When selling/buying electricity is to/from the electricity market, the available power is limited by the capacity of the transmission line. This paper develops a chance constraint for the transmission line and introduces the moment ambiguity set to capture the uncertain wind power generation. The chance constraint can be reformulated into a standard second-order conic programming problem (SOCP) via a distributionally robust optimization method. The model is tested with a case study and the results indicate that the battery plays an important role in wind power scheduling in the electricity market. In the end, comparison with the stochastic optimization with normal distribution (SND) is conducted to prove the performance and robustness of the proposed model based on a distributionally robust optimization (DRO) method.

Suggested Citation

  • Xu, Xiao & Hu, Weihao & Cao, Di & Huang, Qi & Liu, Zhou & Liu, Wen & Chen, Zhe & Blaabjerg, Frede, 2020. "Scheduling of wind-battery hybrid system in the electricity market using distributionally robust optimization," Renewable Energy, Elsevier, vol. 156(C), pages 47-56.
    • Handle: RePEc:eee:renene:v:156:y:2020:i:c:p:47-56
    DOI: 10.1016/j.renene.2020.04.057
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    References listed on IDEAS

    as
    1. Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "GHG-mitigation oriented and coal-consumption constrained inexact robust model for regional energy structure adjustment – A case study for Jiangsu Province, China," Renewable Energy, Elsevier, vol. 123(C), pages 549-562.
    2. Brancucci Martinez-Anido, Carlo & Brinkman, Greg & Hodge, Bri-Mathias, 2016. "The impact of wind power on electricity prices," Renewable Energy, Elsevier, vol. 94(C), pages 474-487.
    3. Gomes, I.L.R. & Pousinho, H.M.I. & Melício, R. & Mendes, V.M.F., 2017. "Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market," Energy, Elsevier, vol. 124(C), pages 310-320.
    4. Kou, Peng & Gao, Feng & Guan, Xiaohong, 2015. "Stochastic predictive control of battery energy storage for wind farm dispatching: Using probabilistic wind power forecasts," Renewable Energy, Elsevier, vol. 80(C), pages 286-300.
    5. Khalid, Muhammad & Aguilera, Ricardo P. & Savkin, Andrey V. & Agelidis, Vassilios G., 2018. "On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting," Applied Energy, Elsevier, vol. 211(C), pages 764-773.
    6. Hou, Peng & Hu, Weihao & Soltani, Mohsen & Chen, Cong & Chen, Zhe, 2017. "Combined optimization for offshore wind turbine micro siting," Applied Energy, Elsevier, vol. 189(C), pages 271-282.
    7. Rahimiyan, Morteza, 2014. "A statistical cognitive model to assess impact of spatially correlated wind production on market behaviors," Applied Energy, Elsevier, vol. 122(C), pages 62-72.
    8. Hemmati, Reza & Saboori, Hedayat & Saboori, Saeid, 2016. "Assessing wind uncertainty impact on short term operation scheduling of coordinated energy storage systems and thermal units," Renewable Energy, Elsevier, vol. 95(C), pages 74-84.
    9. Pandžić, Hrvoje & Morales, Juan M. & Conejo, Antonio J. & Kuzle, Igor, 2013. "Offering model for a virtual power plant based on stochastic programming," Applied Energy, Elsevier, vol. 105(C), pages 282-292.
    10. Erick Delage & Yinyu Ye, 2010. "Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems," Operations Research, INFORMS, vol. 58(3), pages 595-612, June.
    11. Pereira, Adelino J.C. & Saraiva, João Tomé, 2013. "Long term impact of wind power generation in the Iberian day-ahead electricity market price," Energy, Elsevier, vol. 55(C), pages 1159-1171.
    Full references (including those not matched with items on IDEAS)

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    2. Karakoyun, Ece Cigdem & Avci, Harun & Kocaman, Ayse Selin & Nadar, Emre, 2023. "Deviations from commitments: Markov decision process formulations for the role of energy storage," International Journal of Production Economics, Elsevier, vol. 255(C).
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    5. Zhang, Mengling & Jiao, Zihao & Ran, Lun & Zhang, Yuli, 2023. "Optimal energy and reserve scheduling in a renewable-dominant power system," Omega, Elsevier, vol. 118(C).
    6. Khaloie, Hooman & Anvari-Moghaddam, Amjad & Contreras, Javier & Siano, Pierluigi, 2021. "Risk-involved optimal operating strategy of a hybrid power generation company: A mixed interval-CVaR model," Energy, Elsevier, vol. 232(C).
    7. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2022. "Modelling and optimal energy management for battery energy storage systems in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    8. Graça Gomes, João & Jiang, Juan & Chong, Cheng Tung & Telhada, João & Zhang, Xu & Sammarchi, Sergio & Wang, Shuyang & Lin, Yu & Li, Jialong, 2023. "Hybrid solar PV-wind-battery system bidding optimisation: A case study for the Iberian and Italian liberalised electricity markets," Energy, Elsevier, vol. 263(PD).
    9. Fallahi, F. & Bakir, I. & Yildirim, M. & Ye, Z., 2022. "A chance-constrained optimization framework for wind farms to manage fleet-level availability in condition based maintenance and operations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    10. Zhang, M.Y. & Chen, J.J. & Yang, Z.J. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Stochastic day-ahead scheduling of irrigation system integrated agricultural microgrid with pumped storage and uncertain wind power," Energy, Elsevier, vol. 237(C).
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