Distributionally Robust Chance-Constrained Optimal Transmission Switching for Renewable Integration

TL;DR

This paper develops a distributionally robust chance-constrained optimal transmission switching framework to improve renewable integration, reduce curtailment, and ensure grid reliability under uncertainty, with scalable MILP formulations suitable for real-time operations.

Contribution

It introduces a novel DRCC-OTS approach using moment-based and Wasserstein ambiguity sets, providing scalable, scenario-free MILP models for robust grid optimization.

Findings

Improved constraint violation guarantees and reduced renewable curtailment.

Moment-based MILP approach offers computational efficiency for real-time use.

Numerical tests on IEEE systems validate the effectiveness of the proposed methods.

Abstract

Increasing integration of renewable generation poses significant challenges to ensure robustness guarantees in real-time energy system decision-making. This work aims to develop a robust optimal transmission switching (OTS) framework that can effectively relieve grid congestion and mitigate renewable curtailment. We formulate a two-stage distributionally robust chance-constrained (DRCC) problem that assures limited constraint violations for any uncertainty distribution within an ambiguity set. Here, the second-stage recourse variables are represented as linear functions of uncertainty, yielding an equivalent reformulation involving linear constraints only. We utilize moment-based (mean-mean absolute deviation) and distance-based (infinity-Wasserstein distance) ambiguity sets that lead to scalable mixed-integer linear program (MILP) formulations. Numerical experiments on the IEEE 14-bus and 118-bus systems have demonstrated the performance improvements of the proposed DRCC-OTS approaches in terms of guaranteed constraint violations and reduced renewable curtailment. In particular, the computational efficiency of the moment-based MILP approach, which is scenario-free with fixed problem dimensions, has been confirmed, making it suitable for real-time grid operations.