Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation

Jin-Sun Yang, Jin-Young Choi, Geon-Ho An, Young-Jun Choi, Myoung-Hoe Kim and Dong-Jun Won
Additional contact information
Jin-Sun Yang: Department of Electrical Engineering, Inha University, Incheon 22212, Korea
Jin-Young Choi: Department of Electrical Engineering, Inha University, Incheon 22212, Korea
Geon-Ho An: Department of Power Grid Integration of Research and Development (R&D) Center, Hyosung Corporation, Anyang 14080, Korea
Young-Jun Choi: Department of Power Grid Integration of Research and Development (R&D) Center, Hyosung Corporation, Anyang 14080, Korea
Myoung-Hoe Kim: Department of Power Grid Integration of Research and Development (R&D) Center, Hyosung Corporation, Anyang 14080, Korea
Dong-Jun Won: Department of Electrical Engineering, Inha University, Incheon 22212, Korea

Energies, 2016, vol. 9, issue 12, 1-13

Abstract: An energy storage system (ESS) in a power system facilitates tasks such as renewable integration, peak shaving, and the use of ancillary services. Among the various functions of an ESS, this study focused on frequency regulation (or secondary reserve). This paper presents an optimal scheduling algorithm for frequency regulation by an ESS. This algorithm determines the bidding capacity and base point of an ESS in each operational period to achieve the maximum profit within a stable state-of-charge ( SOC ) range. However, the charging/discharging efficiency of an ESS causes SOC errors whenever the ESS performs frequency regulation. With an increase in SOC errors, the ESS cannot respond to an automatic generation control (AGC) signal. This situation results in low ESS performance scores, and finally, the ESS is disqualified from performing frequency regulation. This paper also presents a real-time SOC management algorithm aimed at solving the SOC error problem in real-time operations. This algorithm compensates for SOC errors by changing the base point of the ESS. The optimal scheduling algorithm is implemented in MATLAB by using the particle swarm optimization (PSO) method. In addition, changes in the SOC when the ESS performs frequency regulation in a real-time operation are confirmed using the PSCAD/EMTDC tool. The simulation results show that the optimal scheduling algorithm manages the SOC more efficiently than a commonly employed planning method. In addition, the proposed real-time SOC management algorithm is confirmed to be capable of performing SOC recovery.

Keywords: energy storage system (ESS); frequency regulation (FR); optimal scheduling; state-of-charge ( SOC ); energy management (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: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://www.mdpi.com/1996-1073/9/12/1010/pdf (application/pdf)
https://www.mdpi.com/1996-1073/9/12/1010/ (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:9:y:2016:i:12:p:1010-:d:84059

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 ().