High-Resolution PTDF-Based Planning of Storage and Transmission Under High Renewables
Abstract
Transmission Expansion Planning (TEP) optimizes power grid upgrades and investments to ensure reliable, efficient, and cost-effective electricity delivery while addressing grid constraints. To support growing demand and renewable energy integration, energy storage is emerging as a pivotal asset that provides temporal flexibility and alleviates congestion. This paper develops a multiperiod, two-stage PTDF formulation that co-optimizes transmission upgrades and storage siting/sizing. To ensure scalability, a trust-region, multicut Benders scheme warm-started from per-representative-day optima is proposed. Applied to a 2,000-bus synthetic Texas system under high-renewable projections, the method attains final optimality gaps below 2% and yields a plan with storage at 167 nodes (32% of peak renewable capacity). These results demonstrate that the proposed PTDF-based methodology efficiently handles large distributed storage fleets, demonstrating scalability at high spatial resolution.
Keywords
Cite
@article{arxiv.2510.14696,
title = {High-Resolution PTDF-Based Planning of Storage and Transmission Under High Renewables},
author = {Kevin Wu and Rabab Haider and Pascal Van Hentenryck},
journal= {arXiv preprint arXiv:2510.14696},
year = {2026}
}