Optimal Co-Design of a Hybrid Energy Storage System for Truck Charging

TL;DR

This paper introduces a co-design framework for hybrid energy storage systems in truck charging microgrids, jointly optimizing technology, size, and operation to reduce costs and grid dependency.

Contribution

It presents a mixed-integer linear programming approach for the joint optimization of hybrid energy storage systems and operational strategies in truck charging microgrids.

Findings

Hybrid systems reduce total costs compared to battery-only setups.

Adding supercapacitors or flywheels decreases costs and increases energy resale.

Fully hybrid solutions achieve the best cost savings and grid independence.

Abstract

The major challenges to battery electric truck adoption are their high cost and grid congestion.In this context, stationary energy storage systems can help mitigate both issues. Since their design and operation are strongly coupled, to make the best out of them, they should be jointly optimized. This paper presents a co-design framework for hybrid energy storage systems where their technology and sizing are optimized jointly with their operational strategies. Specifically, we consider a microgrid supporting truck chargers that consists of utility grid, solar panels, and energy storage systems including batteries, supercapacitors and flywheels. We frame the co-design problem as a mixed-integer linear program that can be solved with global optimality guarantees. We showcase our framework in a case-study of a distribution center in the Netherlands. Our results show that although the battery-only configuration is already competitive, adding supercapacitors or flywheel storage decrease total cost and increase energy sold back to the grid. Overall, the fully hybrid solution (Battery+Supercapacitors+Flywheel) offers the best outcomes, achieving the lowest overall cost (1.96\% lower compared to battery-only) and reduced grid dependency, but at a higher (2.6\%) initial investment.