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Hybrid Model-Based BESS Sizing and Control for Wind Energy Ramp Rate Control

Author

Listed:
  • Abebe Tilahun Tadie

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
    School of Electrical and Computer Engineering, Debre Markos University, Debre Markos 269, Ethiopia)

  • Zhizhong Guo

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
    Harbin Institute of Technology at Zhangjiakou ITRIZ, Zhangjiakou 075400, China)

  • Ying Xu

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

Abstract

This paper presents a hybrid model constituting dynamic smoothing technique and particle swarm optimization techniques to optimally size and control battery energy storage systems for wind energy ramp rate control and power system frequency performance enhancement. In today’s modern power system, a high-proportion renewable energy grid is inevitable. This high-proportion renewable energy grid is a power system with abundant integration of renewable energy resources under the presence of energy storage tools. Energy storage tools are integrated into such power systems to balance the fluctuation and intermittence of renewable energy sources. One of the requirements in a high-proportion renewable energy grid is the fractional power balance between generation and load. One of the requirements set by power system regulators is the generation variation between two time points. A power producer is mandated to satisfy the ramp rate requirement set by the grid owner. This paper proposes dynamic smoothing techniques for initial size determination and particle swarm optimization based on optimal sizing and control of battery energy storage systems for ramp rate control and frequency regulation performance of a power system integrated with a large percentage of wind energy systems. Wind energy data taken from Zhangjiakou wind farm in China are used. The results indicate that the battery energy storage system improves the ramp rate characteristics of the wind farm. In addition, the virtual inertia capability of the battery energy storage system enabled the transient and steady-state frequency response of the test power system to improve significantly.

Suggested Citation

  • Abebe Tilahun Tadie & Zhizhong Guo & Ying Xu, 2022. "Hybrid Model-Based BESS Sizing and Control for Wind Energy Ramp Rate Control," Energies, MDPI, vol. 15(23), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9244-:d:994985
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    References listed on IDEAS

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    1. João Martins & Sergiu Spataru & Dezso Sera & Daniel-Ioan Stroe & Abderezak Lashab, 2019. "Comparative Study of Ramp-Rate Control Algorithms for PV with Energy Storage Systems," Energies, MDPI, vol. 12(7), pages 1-15, April.
    2. Abebe Tilahun Tadie & Zhizhong Guo, 2019. "Optimal Planning of Grid Scale PHES Through Characteristics-Based Large Scale Data Clustering and Emission Constrained Optimization," Energies, MDPI, vol. 12(11), pages 1-19, June.
    3. van Haaren, Rob & Morjaria, Mahesh & Fthenakis, Vasilis, 2015. "An energy storage algorithm for ramp rate control of utility scale PV (photovoltaics) plants," Energy, Elsevier, vol. 91(C), pages 894-902.
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