Congestion Management in Power Systems
Summary
Congestion in electrical transmission networks arises when power flows exceed the transfer capacities of lines, leading to reliability risks, higher operating costs and market inefficiencies. Management strategies combine technical and economic tools to relieve overloaded corridors while maintaining system security. Traditional measures include real-time redispatch of generation, where output from less expensive or strategically located units is adjusted to reroute flows away from congested links. Market-based approaches such as nodal or zonal pricing signal scarcity by reflecting the cost of constraint relief in locational marginal prices, incentivising demand response and generation siting. Flexible AC Transmission Systems (FACTS) and high-voltage DC (HVDC) links offer dynamic flow control, enhancing transfer capability and enabling ancillary services. Recent advances leverage optimisation-based frameworks, from optimal power flow (OPF) formulations to meta-heuristics and machine-learning methods for rapid congestion relief in evolving power systems with high penetrations of renewable energy, distributed generation and storage. Effective congestion management underpins secure operation, facilitates market liquidity and supports the transition to low-carbon grids worldwide.
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Congestion Management in Power Systems publication trend
The graph below shows the total number of articles in congestion management in power systems across all publications each year (not limited to Nature Index journals).
Technical terms
Congestion cost: The incremental expense incurred to reroute or reschedule power flows when line capacities are breached.
Generator Sensitivity Factor (GSF): A measure of how a change in a generator’s output affects the flow on a specific transmission line, used to identify effective participants in redispatch.
Generation rescheduling: The adjustment of generator outputs from their scheduled set-points to relieve network constraints while balancing supply and demand.
References
- A Novel Improved Manta Ray Foraging Optimization Approach for Mitigating Power System Congestion in Transmission Network. IEEE Access (2023).
- Hybrid Deep Neural Network-Based Generation Rescheduling for Congestion Mitigation in Spot Power Market. IEEE Access (2022).
- Transmission Congestion Management Using Generator Sensitivity Factors for Active and Reactive Power Rescheduling Using Particle Swarm Optimization Algorithm. IEEE Access (2022).
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