Optimal Allocation of Primary Frequency Modulation Capacity of Battery Energy Storage Based on Antlion Algorithm

Hui Yang, Renshuang Huang, Ming Shi, Zutai Yan () and Laiqing Yan
Additional contact information
Hui Yang: Shanxi Longyuan New Energy Co., Ltd., Taiyuan 030013, China
Renshuang Huang: Shanxi Longyuan New Energy Co., Ltd., Taiyuan 030013, China
Ming Shi: Shanxi Longyuan New Energy Co., Ltd., Taiyuan 030013, China
Zutai Yan: School of Electric Power, Civil Engineering and Architecture, Shanxi University, Taiyuan 030031, China
Laiqing Yan: School of Electric Power, Civil Engineering and Architecture, Shanxi University, Taiyuan 030031, China

Energies, 2023, vol. 16, issue 19, 1-16

Abstract: Currently, the integration of new energy sources into the power system poses a significant challenge to frequency stability. To address the issue of capacity sizing when utilizing storage battery systems to assist the power grid in frequency control, a capacity optimal allocation model is proposed for the primary frequency regulation of energy storage. Due to the requirement of a large number of actual parameters for the optimal allocation model, a simulation model of energy storage capacity is constructed based on the characteristics of primary frequency control to provide the necessary parameters. Subsequently, the primary frequency modulation output model of energy storage is established by considering the basic action output, the action in the frequency modulation dead zone, and a certain capacity margin. The antlion algorithm is employed to solve the capacity optimal allocation model. Finally, three groups of experiments are designed and compared to demonstrate the effectiveness of the proposed method in setting the capacity margin, which can increase profit to a certain extent.

Keywords: battery energy storage system; capacity configuration; primary frequency modulation; antlion algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/19/6778/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/19/6778/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:19:p:6778-:d:1246099

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().