Optimal Scheduling of Battery Energy Storage Systems and Demand Response for Distribution Systems with High Penetration of Renewable Energy Sources
Xuehan Zhang,
Yongju Son and
Sungyun Choi
Additional contact information
Xuehan Zhang: School of Electrical Engineering, Korea University, Seoul 02841, Korea
Yongju Son: School of Electrical Engineering, Korea University, Seoul 02841, Korea
Sungyun Choi: School of Electrical Engineering, Korea University, Seoul 02841, Korea
Energies, 2022, vol. 15, issue 6, 1-18
Abstract:
The penetration of renewable energy sources (RESs) is increasing in modern power systems. However, the uncertainties of RESs pose challenges to distribution system operations, such as RES curtailment. Demand response (DR) and battery energy storage systems (BESSs) are flexible countermeasures for distribution-system operators. In this context, this study proposes an optimization model that considers DR and BESSs and develops a simulation analysis platform representing a medium-sized distribution system with high penetration of RESs. First, BESSs and DR were employed to minimize the total expenses of the distribution system operation, where the BESS model excluding binary state variables was adopted. Second, a simulation platform based on a modified IEEE 123 bus system was developed via MATLAB/Simulink for day-ahead scheduling analysis of the distribution system with a high penetration of RESs. The simulation results indicate the positive effects of DR implementation, BESS deployment, and permission for electricity sales to the upper utility on decreasing RES curtailment and distribution system operation costs. Noticeably, the RES curtailments became zero with the permission of bidirectional power flow. In addition, the adopted BESS model excluding binary variables was also validated. Finally, the effectiveness of the developed simulation analysis platform for day-ahead scheduling was demonstrated.
Keywords: battery energy storage systems; demand response; distribution systems; optimization; simulation platform; renewable energy sources (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: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1996-1073/15/6/2212/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/6/2212/ (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:15:y:2022:i:6:p:2212-:d:773763
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 ().