Evaluation of Battery Energy Storage System to Provide Virtual Transmission Service

TL;DR

This paper evaluates the use of battery energy storage systems as virtual transmission to improve power transfer, reduce costs, and alleviate congestion, offering a promising alternative to physical transmission upgrades.

Contribution

It introduces day-ahead energy scheduling models for virtual transmission, comparing its effectiveness with traditional methods and demonstrating its economic and operational benefits.

Findings

VT achieves 14% cost reduction and 34% congestion relief.

VT performs comparably to physical lines in congestion mitigation.

The proposed models are computationally efficient and effective.

Abstract

An immediate need in the transmission system is to find alternative solutions that improve system operation and defer the need for new transmission lines. This study comprehensively evaluates the performance and economic benefits of short-term operation of using battery energy storage systems (BESS) as virtual transmission (VT) to promote power transfer across distant regions. Specifically, this work implements various day-ahead energy scheduling models to analyze the impact of VT on system operation cost, network congestion, model computational time, and market performance. The performance of VT is compared with three alternative network congestion mitigation methods, including building new high-voltage physical transmission lines, cost-driven battery energy storage systems, and network reconfiguration, as well as combinations of two of the aforementioned methods. The benchmark dayahead scheduling model is a traditional security-constrained unit commitment model without system upgrades or other network congestion mitigation. Numerical simulations conducted on the IEEE 24-bus system demonstrate that VT provides a 14% operational cost reduction and 34% congested line relief compared to the base case. Compared to other examined schemes, VT is the only one comparable to physical transmission lines that can provide satisfying congestion relief and operation cost reduction without significantly sacrificing computing time and load payment.