Exploring the Use of Autonomous Unmanned Vehicles for Supporting Power Grid Operations
Yuqi Zhou, Cong Feng, Mingzhi Zhang, Rui Yang
TL;DR
This work investigates deploying autonomous unmanned vehicles as mobile energy storage to support power grid operations. It presents a two-layer framework that first computes optimal vehicle routing on a transportation network and then solves a grid-dispatch problem that blends traditional generation with vehicle-based power, using a McCormick-relaxed reformulation to handle nonlinearities in the coupled problem. The approach yields an exact, tractable MILP that supports offline routing and online dispatch, demonstrated via simulations on IEEE 14-bus and much larger networks, achieving substantial cost reductions and real-time solution capabilities. The results suggest that mobile batteries can meaningfully enhance grid resilience and operational efficiency with minimal changes to existing infrastructure.
Abstract
This paper explores the use of autonomous unmanned vehicles to support power grid operations. With built-in batteries and the capability to carry additional battery energy storage, the rising number of autonomous vehicles can represent a substantial amount of capacity that is currently underutilized in the power grid. Unlike traditional electric vehicles that require drivers, the operations of autonomous vehicles can be performed without human intervention. To guide idle vehicles to autonomously support power grids, we propose a tractable optimization-based method to effectively integrate these "mobile batteries" into grid operations. During real-time operations, the vehicles are strategically routed to target locations to maintain power balance and reduce operating costs. Numerical studies have confirmed both the validity and the scalability of the proposed algorithm to efficiently integrate autonomous vehicles into routine power system operations.