Battery Energy Storage System Based on Incremental Cost Consensus Algorithm for the Frequency Control

Chen Chen; Yu-Qing Bao; Xue-Hua Wu; Beibei Wang; Cheng Shen

doi:10.1109/ACCESS.2019.2946458

IEEE Access (Jan 2019)

Battery Energy Storage System Based on Incremental Cost Consensus Algorithm for the Frequency Control

Chen Chen,
Yu-Qing Bao,
Xue-Hua Wu,
Beibei Wang,
Cheng Shen

Affiliations

Chen Chen: ORCiD; NARI School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing, China
Yu-Qing Bao: ORCiD; NARI School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing, China
Xue-Hua Wu: ORCiD; School of Electrical Engineering, Southeast University, Nanjing, China
Beibei Wang: School of Electrical Engineering, Southeast University, Nanjing, China
Cheng Shen: NARI School of Electrical Engineering and Automation, Nanjing Normal University, Nanjing, China

DOI: https://doi.org/10.1109/ACCESS.2019.2946458
Journal volume & issue: Vol. 7
pp. 147362 – 147372

Abstract

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In the past few years, Battery Energy Storage System (BESS) has been found of great potential in supporting the frequency control. Increasing attentions have been given to the control strategy of BESS. In this paper, a distributed control method considering the life-loss cost is proposed for BESS. Based on the multi-agent system, the Incremental Cost Consensus (ICC) algorithm is applied to minimize the life-loss cost of BESS. In order to improve the control performance, parameters of the system are optimized by Genetic Algorithm (GA). The simulation results are provided to verify the effectiveness of the proposed approach.

Published in IEEE Access

ISSN: 2169-3536 (Online)
Publisher: IEEE
Country of publisher: United States
LCC subjects: Technology: Electrical engineering. Electronics. Nuclear engineering
Website: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639

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