Topology optimization for grid congestion management
Topology optimization software identifies optimal grid reconfiguration actions, such as opening or closing circuit breakers to redirect power flows, relieve congestion and unlock unused transmission capacity. By rapidly evaluating large numbers of feasible switching combinations, these tools propose configurations that improve transfer capability without requiring new transmission lines or physical upgrades. In practice, topology optimization functions as a decision-support layer that guides operators toward congestion relief actions using the existing network.
Modern topology optimization platforms integrate near-real-time data, power-flow models and contingency analysis to detect congestion patterns and identify cost-effective switching options. By continuously assessing system conditions, they help operators relieve bottlenecks, reduce costly redispatch and increase the flexibility of existing networks while respecting system protection and security criteria. These capabilities are particularly valuable in renewable-rich systems, where variable generation and shifting flow patterns create dynamic congestion that conventional tools cannot resolve effectively. They are also valuable to help mitigate congestion and increase system resilience during extreme events with high demand and multiple outages.
As major power systems face rising demand, slow transmission build-out and increasing congestion costs, topology optimization offers a digital-first approach to improve grid performance, increase utilization of existing assets and reduce operational expenditure.
Main outcomes of the solution
- Affordability: Reduces system costs by lowering congestion-related redispatch, improving use of existing infrastructure and deferring selected transmission upgrades.
- Reliability & Flexibility: Improves grid stability by optimizing power-flow distribution, mitigating overloads and supporting management of variable generation and changing demand patterns.
- Institutional Efficiency & Transparency: Supports data-driven operations through automated analysis, providing clear switching recommendations and reducing manual engineering workload.
Key Deployment and Scaling Factors
- Maintain accurate network models and state to simulate power flows and assess switching actions with sufficient precision.
- Integrate seamlessly with EMS so recommendations can be validated, approved and executed safely in live operations.
- Define operational and protection rules specifying which breakers may be switched, under what conditions and with what verification steps.
- Ensure secure, interoperable software architectures that meet utility cybersecurity requirements and integrate with existing systems.
- Enable regulatory and operational frameworks that allow algorithm-supported congestion relief as part of standard grid-management practice.
Case Study
NewGrid and Midcontinent Independent System Operator (MISO) (2024), USA
Topology optimization has been applied within the MISO transmission footprint to support congestion management using existing network infrastructure. The approach uses analytical tools to identify feasible network reconfiguration actions, such as switching operations, that can redirect power flows and mitigate congestion while complying with security and protection constraints.
These activities leveraged MISO’s formal economic reconfiguration request framework, which provides a standardized process for submission, screening, evaluation and implementation of topology-based congestion mitigation actions. The framework is designed to ensure consistent operational assessment and coordination across transmission operators and market participants.
During 2023-2024, reconfigurations implemented under this framework were associated with regional congestion cost reductions exceeding USD 100 million across the MISO system. In one example, during a three-week planned outage of a 345 kV transmission line between Iowa and Minnesota, an implemented reconfiguration reduced regional congestion costs by approximately USD 3.5 million over the outage period, based on ex-post evaluation using state estimator data. The same reconfiguration was associated with substantially lower wind curtailment (reduced by 86%) during the outage window, improving utilization of available renewable generation.[1]
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