Enhanced Battery Degradation-Aware Scheduling for Distribution Network with Electric Vehicle Load
Batteries play a key role in today's power grid. In this paper, we investigate the impact of battery degradation on the distribution network. We formulate a multi-objective framework for optimizing battery scheduling with the goals of minimizing monetary costs and improving network performance. Our frame-work incorporates energy purchase and battery degradation into the costs and measures the network performance through energy losses and voltage deviation. We propose Bach for battery degradation-aware scheduling based on s-constraint and fuzzy logic methods. Bach is implemented for the IEEE 33-bus network for an experimental study. The results show the effectiveness of Bach in optimizing costs and performance simultaneously with battery degradation awareness and demonstrate the flexibility of further customization.
Authors
- Kuan Tak Tan (ORCID: https://orcid.org/0000-0002-0578-7098)
- Vijay Babu Pamshetti (ORCID: https://orcid.org/0000-0003-4850-5369)
- Junjie Yan (ORCID: https://orcid.org/0000-0001-8016-2277)
- Wei Zhang (ORCID: https://orcid.org/0000-0002-3323-4095)
- Man-Fai Ng Andy
Institutions
- Agency for Science, Technology and Research (SG)
- Singapore Institute of Technology (SG)
- Nanyang Technological University (SG)
Publication Details
- Published
- 2024-12-01
- DOI
- https://doi.org/10.1109/tencon61640.2024.10902673
- Primary Topic
- Electric Vehicles and Infrastructure
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- College of Science, Technology, Engineering, and Mathematics, Youngstown State University
- Agency for Science, Technology and Research