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Bibliographic Details
Main Authors: Wu, Kevin, Haider, Rabab, Van Hentenryck, Pascal
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2510.14696
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author Wu, Kevin
Haider, Rabab
Van Hentenryck, Pascal
author_facet Wu, Kevin
Haider, Rabab
Van Hentenryck, Pascal
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2510_14696
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle High-Resolution PTDF-Based Planning of Storage and Transmission Under High Renewables
Wu, Kevin
Haider, Rabab
Van Hentenryck, Pascal
Systems and Control
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.
title High-Resolution PTDF-Based Planning of Storage and Transmission Under High Renewables
topic Systems and Control
url https://arxiv.org/abs/2510.14696