Optimal sizing of battery storage for cost-effective peak shaving in regional distribution networks
Battery energy storage system (BESS) is a crucial technology for managing various uncertainties and key challenges particularly, peak shaving, inherent in regional distribution networks (RDNs). However, an improperly sized BESS can lead to unreasonable installation, operation, and maintenance costs. Considering that these costs may exceed the operational benefits of the battery, this work establishes an analytical approach for the optimal sizing of BESS aimed at cost-effective peak-shaving applications, especially in an Australian RDN. The procedure utilizes the RDN load profiles, characterized by a determined time resolution, while accounting for various billing rates and electricity costs. Utilizing real load and cost data, this approach systematically determines the optimal battery capacity from various BESS configurations, enhancing the overall efficiency and performance of the BESS. The proposed analytical method is evaluated using a rule-based technique, ensuring practical applicability and reliability. The results, tested on a real Australian RDN, demonstrate that the approach can significantly determine the most economically suitable BESS configuration, reduce system operational costs, and achieve effective peak shaving during high-demand periods. Additionally, to evaluate the feasibility of the technique, load profiles and associated cost factors also have been collected from a Malaysian RDN, tested in the case study. • An analytical approach is developed for optimal sizing of BESS for peak shaving in regional distribution networks. • The proposed method is tested using real load profiles and electricity cost data from Australian and Malaysian RDNs. • A rule-based evaluation confirms the practical applicability and economic benefits of the optimal size of BESS. • Results demonstrate that the approach effectively reduces operational costs and enhances system efficiency.
Authors
- Daoyi Dong (ORCID: https://orcid.org/0000-0002-7425-3559)
- Md Masud Rana (ORCID: https://orcid.org/0000-0001-8228-4390)
- GM Shafiullah (ORCID: https://orcid.org/0000-0002-2211-184X)
- Huadong Mo (ORCID: https://orcid.org/0000-0002-7782-2884)
- Li Qiao (ORCID: https://orcid.org/0000-0003-1038-9366)
Institutions
- University of Technology Sydney (AU)
- Murdoch University (AU)
- University of Canberra (AU)
- UNSW Sydney (AU)
Publication Details
- Journal
- Journal of Energy Storage
- Published
- 2025-11-20
- DOI
- https://doi.org/10.1016/j.est.2025.119502
- Primary Topic
- Microgrid Control and Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00