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Co-Optimization of Network Topology and Variable Impedance Devices under Dynamic Line Ratings in Power Transmission Systems

Junseon Park, Hyeongon Park, Rahul K. Gupta

TL;DR

The paper tackles transmission-congestion challenges by jointly optimizing Network Topology Optimization (NTO), Dynamic Line Rating (DLR), and Variable Impedance Devices (VIDs) within a unified framework based on DC power flow and a node-breaker topology model. It formulates a single objective combining generation cost and load shedding while enforcing NTO, DLR, and VID constraints, explicitly addressing VID-induced bilinearities and leveraging weather-driven capacity for DLR. Validation on IEEE Case24 and Case118 demonstrates substantial cost reductions, with up-to approximately 65% improvement for Case24 when NTO, DLR, and VID are deployed on multiple lines, and around 28–31% for Case118 under favorable wind conditions; DLR often dominates, while VID provides complementary but sometimes limited gains when topology is already optimized. The work highlights the value of coordinating grid-enhancing technologies for congestion relief and dispatch efficiency, and notes computational challenges due to bilinear terms, suggesting future work on explicit linearization and optimal placement/sizing of GETs to improve scalability and guarantees.

Abstract

Power system operators are increasingly deploying Grid Enhancing Technologies (GETs) to mitigate operational challenges such as line and transformer congestion, and voltage violations. These technologies, including Network Topology Optimization (NTO), Variable Impedance Devices (VIDs), and Dynamic Line Rating (DLR), enhance system flexibility and enable better utilization of existing network assets. However, as the deployment of multiple GETs grows, effective coordination among them becomes essential to fully realize their potential benefits. This paper presents a co-optimization framework that models and coordinates NTO, VID, and DLR within a unified optimization scheme to alleviate network congestion and minimize operational costs. The NTO formulation is developed using a node-breaker model, offering finer switching granularity and improved operational flexibility. The inclusion of VIDs introduces nonlinear and non-convex relationships in the optimization problem. DLR takes into account of weather conditions, primarily wind speed and ambient temperature, enabling adaptive utilization of transmission capacity. The proposed framework is validated on standard IEEE benchmark test systems, demonstrating its effectiveness under varying numbers and placements of impedance controllers.

Co-Optimization of Network Topology and Variable Impedance Devices under Dynamic Line Ratings in Power Transmission Systems

TL;DR

The paper tackles transmission-congestion challenges by jointly optimizing Network Topology Optimization (NTO), Dynamic Line Rating (DLR), and Variable Impedance Devices (VIDs) within a unified framework based on DC power flow and a node-breaker topology model. It formulates a single objective combining generation cost and load shedding while enforcing NTO, DLR, and VID constraints, explicitly addressing VID-induced bilinearities and leveraging weather-driven capacity for DLR. Validation on IEEE Case24 and Case118 demonstrates substantial cost reductions, with up-to approximately 65% improvement for Case24 when NTO, DLR, and VID are deployed on multiple lines, and around 28–31% for Case118 under favorable wind conditions; DLR often dominates, while VID provides complementary but sometimes limited gains when topology is already optimized. The work highlights the value of coordinating grid-enhancing technologies for congestion relief and dispatch efficiency, and notes computational challenges due to bilinear terms, suggesting future work on explicit linearization and optimal placement/sizing of GETs to improve scalability and guarantees.

Abstract

Power system operators are increasingly deploying Grid Enhancing Technologies (GETs) to mitigate operational challenges such as line and transformer congestion, and voltage violations. These technologies, including Network Topology Optimization (NTO), Variable Impedance Devices (VIDs), and Dynamic Line Rating (DLR), enhance system flexibility and enable better utilization of existing network assets. However, as the deployment of multiple GETs grows, effective coordination among them becomes essential to fully realize their potential benefits. This paper presents a co-optimization framework that models and coordinates NTO, VID, and DLR within a unified optimization scheme to alleviate network congestion and minimize operational costs. The NTO formulation is developed using a node-breaker model, offering finer switching granularity and improved operational flexibility. The inclusion of VIDs introduces nonlinear and non-convex relationships in the optimization problem. DLR takes into account of weather conditions, primarily wind speed and ambient temperature, enabling adaptive utilization of transmission capacity. The proposed framework is validated on standard IEEE benchmark test systems, demonstrating its effectiveness under varying numbers and placements of impedance controllers.
Paper Structure (24 sections, 15 equations, 5 figures, 6 tables)

This paper contains 24 sections, 15 equations, 5 figures, 6 tables.

Table of Contents

  1. Introduction
  2. Motivation
  3. Existing literature
  4. Problem Statement and Contributions
  5. Modeling Grid Enhancing Technologies
  6. Transmission grid model
  7. Network Topology Optimization Model
  8. Dynamic Line Rating Model
  9. Variable Impedance Devices Model
  10. Co-optimization Framework
  11. Objective function
  12. Generation cost
  13. Load shedding cost
  14. Final Optimization Problem
  15. Simulation Setup and Results
  16. ...and 9 more sections

Figures (5)

  • Figure 1: Generalized breaker-and-half model
  • Figure 2: Weather data on temperature and wind speed for modeling the DLR.
  • Figure 3: Average system cost under varying numbers of applied DLR and VID lines (fixed topology).
  • Figure 4: Comparison of mean line loading between the baseline and (a) DLR-only, (b) VID-only, and (c) DLR+VID. Each dot is a transmission line; axes show line loading (p.u.). The 45° line indicates no change.
  • Figure 5: Average system cost under varying numbers of applied DLR and VID lines (optimized topology using NTO).