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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhanced Battery Degradation-Aware Scheduling for Distribution Network with Electric Vehicle Load

Kuan Tak Tan, Vijay Babu Pamshetti, Junjie Yan, Wei Zhang et al.
Electric Vehicles and Infrastructure
article

Enhanced Battery Degradation-Aware Scheduling for Distribution Network with Electric Vehicle Load

Kuan Tak Tan, Vijay Babu Pamshetti, Junjie Yan, Wei Zhang, Man-Fai Ng Andy
article en

Abstract

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.

Agency for Science, Technology and Research (SG), Singapore Institute of Technology (SG), Nanyang Technological University (SG)
College of Science, Technology, Engineering, and Mathematics, Youngstown State University, Agency for Science, Technology and Research
Affordable and clean energy
Openalex Percentile: Top 74%
Electric Vehicles and Infrastructure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Enhanced Battery Degradation-Aware Scheduling for Distribution Network with Electric Vehicle Load — Kuan Tak Tan, Vijay Babu Pamshetti, et al. · (2024) | TGRS Research Map | TGRS