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Evaluation Method for the Firm Power Escalation of a Wind-Storage Hybrid Power System

Author

Listed:
  • Sanli Zhu

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electric Engineering of Chongqing University, Shapingba District, Chongqing 400000, China)

  • Jiping Lu

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electric Engineering of Chongqing University, Shapingba District, Chongqing 400000, China)

  • Zheng Li

    (State Key Laboratory of Power Transmission Equipment & System Security and New Technology, School of Electric Engineering of Chongqing University, Shapingba District, Chongqing 400000, China)

  • Junyi Lin

    (State Grid Chongqing Yongchuan Electric Power Supply Branch, Chongqing 400000, China)

Abstract

To improve the controllability of the electric power output and the economic performance of a large-scale wind farm, an auxiliary energy storage system is required. This paper deals with the rule of planning reasonable energy storage power and capacity based on the historical annual mean wind speed data, the probability density of the pulsating wind power output, and the warranted firm power provided by the wind farm. Specifically, the evaluation index of the fluctuation degree of the firm power is defined in order to optimize the planned energy storage capacity. After that, the firm power escalation affected by the energy storage power and the conversion rate of the storage device are quantitatively evaluated. All of these analyses contribute in a significant way towards determining the acceptable energy conversion rate with the condition of limited energy storage space of a wind-storage hybrid power system. The proposed evaluation method of the firm power escalation is verified by MatLab simulation results.

Suggested Citation

  • Sanli Zhu & Jiping Lu & Zheng Li & Junyi Lin, 2017. "Evaluation Method for the Firm Power Escalation of a Wind-Storage Hybrid Power System," Energies, MDPI, vol. 10(10), pages 1-12, October.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:10:p:1539-:d:114133
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    References listed on IDEAS

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    1. Douglas Halamay & Michael Antonishen & Kelcey Lajoie & Arne Bostrom & Ted K. A. Brekken, 2014. "Improving Wind Farm Dispatchability Using Model Predictive Control for Optimal Operation of Grid-Scale Energy Storage," Energies, MDPI, vol. 7(9), pages 1-16, September.
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