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

TL;DR

This paper presents a multi-objective framework and a novel scheduling method called Bach for optimizing battery use in power grids, considering degradation, costs, and network performance, demonstrated on a standard test network.

Contribution

It introduces Bach, a new battery scheduling method that incorporates degradation awareness using e-constraint and fuzzy logic, enhancing cost and performance optimization.

Findings

Bach effectively balances costs and network performance.

Incorporating degradation improves scheduling accuracy.

Flexible customization of the scheduling framework is demonstrated.

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 framework 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 cheduling based on e-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.