Co-optimization of Battery Routing and Load Restoration for Microgrids with Mobile Energy Storage Systems

TL;DR

This paper presents a mixed integer second order cone programming model that optimizes both the routing of mobile energy storage systems and load restoration in microgrids, enhancing resilience and operational efficiency.

Contribution

It introduces a novel integrated model for simultaneous MESS routing and load restoration, considering battery state of charge and capacity bounds, validated on a standard benchmark system.

Findings

Effective load restoration with optimized MESS routing.

Model demonstrates improved resilience in microgrid simulations.

Validated on IEEE 123-bus system with positive results.

Abstract

Mobile energy storage systems (MESS) offer great operational flexibility to enhance the resiliency of distribution systems in an emergency condition. The optimal placement and sizing of those units are pivotal for quickly restoring the curtailed loads. In this paper, we propose a model for load restoration in a microgrid while concurrently optimizing the MESS routes required for the same. The model is formulated as a mixed integer second order cone program by considering the state of charge and evolution of the lower and upper bounds of battery capacities. Simulation results tested on the IEEE 123- bus benchmark system demonstrate the efficacy of the proposed model.