Work

Data-driven robust transmission expansion planning against rising temperatures*

Year: 2025

Type: article

Abstract: The evidence of ongoing rising temperatures has been accumulating for years. It is, therefore, essential to utilize recent climate data to inform future investment decisions. Perhaps nowhere is this more important than in improving the aging power grid infrastructure. This work presents a novel data-driven robust optimization approach to guide transmission expansion planning and transmission capacity expansion planning decisions focused on mitigating the effects of globally and regionally rising temperatures. The proposed methodology is tested on a large-scale realistic test case of the power transmission grid in Arizona, and two classes of valid inequality are used to accelerate the computation time. The effects of temperature are modeled at a regional level in the feastured test case using a k-means clustering method. Results demonstrate that more accurate regional temperature modeling results in more focused investment plans.

Source: Environmental Research Infrastructure and Sustainability

DOI: 10.1088/2634-4505/adb5b3

Authors: J Kyle Skolfield, Ahmad Alnakhli, Ali Alawad, Adolfo R Escobedo, Payman Dehghanian

Institutions: Sandia National Laboratories, George Washington University, North Carolina State University

Language: English

Topic: Electric Power System Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Climate action, Affordable and clean energy, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,515