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Identification of the Most Effective Point of Connection for Battery Energy Storage Systems Focusing on Power System Frequency Response Improvement

Author

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  • Thiago Pieroni

    (Department of Systems and Energy, University of Campinas, Campinas 13083-852, Brazil)

  • Daniel Dotta

    (Department of Systems and Energy, University of Campinas, Campinas 13083-852, Brazil)

Abstract

With the massive penetration of intermittent generation (wind and solar), the reduction of Electrical Power Systems’ (EPSs) inertial frequency response represents a new challenge. One alternative to deal with this scenario may be the application of a Battery Energy Storage System (BESS). However, the main constraint for the massive deployment of BESSs is the high acquisition cost of these storage systems which in some situations, can preclude their use in transmission systems. The main goal of this paper is to propose a systematic procedure to include BESSs in power system aiming to improve the power system frequency response using full linear models and geometric measures. In this work, a generic battery model is developed in a two-area test system with assumed high wind penetration and full conventional generators models. The full power system is linearized, and the geometric measures of controllability associated with of the frequency regulation mode are estimated. Then, these results are used to identify the most effective point of connection for a BESS aiming at the improvement of the power system frequency response. Nonlinear time-domain simulations are carried out to evaluate and validate the results.

Suggested Citation

  • Thiago Pieroni & Daniel Dotta, 2018. "Identification of the Most Effective Point of Connection for Battery Energy Storage Systems Focusing on Power System Frequency Response Improvement," Energies, MDPI, vol. 11(4), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:4:p:763-:d:138380
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    References listed on IDEAS

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    1. Fabio Massimo Gatta & Alberto Geri & Regina Lamedica & Stefano Lauria & Marco Maccioni & Francesco Palone & Massimo Rebolini & Alessandro Ruvio, 2016. "Application of a LiFePO 4 Battery Energy Storage System to Primary Frequency Control: Simulations and Experimental Results," Energies, MDPI, vol. 9(11), pages 1-16, October.
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    Cited by:

    1. Haiteng Han & Hantao Cui & Shan Gao & Qingxin Shi & Anjie Fan & Chen Wu, 2018. "A Remedial Strategic Scheduling Model for Load Serving Entities Considering the Interaction between Grid-Level Energy Storage and Virtual Power Plants," Energies, MDPI, vol. 11(9), pages 1-19, September.

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