Congestion forecast tool


We are developing a congestion forecast tool for the distribution system operators (DSOs) in order to assist them in forecasting voltage issues and network congestion. The tool also includes development of different visualization features which allows DSOs in identifying the exact location and severity of congestion.

The problem of network congestion is becoming more realistic due to higher percentage of power generation from distributed energy resources. The tool will assist DSOs in network planning and congestion management. It will allow DSO to manage the possible congestion, e.g. by procuring flexibility in order to avoid costly grid reinforcement and timely manage congestion by employing market and tariff-based flexibility solutions. Thus, the system’s resiliency will be enhanced, and additional congestion cost will be reduced.

The tool incorporates a photovoltaics (PV) forecast based on image processing of cloud movement and a load forecast using artificial neural network combined with load models and operating modes of PV inverters. These forecasts are then used in a probabilistic power flow model, using the backward-forward sweep algorithm. The congestion is forecasted in terms of nodes voltages, branches and transformers loading levels.

The tool will be demonstrated at the French demonstration site of SOREA in Saint-Jean-de-Maurienne.

Benefits for the DSOs

  • Accurate and timely forecast of network congestion
  • Congestion management
  • Reduced component overloading
  • Differ costly grid reinforcement in the long-term
  • Detect and manage emergency situations closer to real-time
  • Reduce additional congestion cost
  • Reduce voltage limit violations
  • Improve power quality

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This project has received funding from the European Community's Horizon 2020 Framework Programme under grant agreement 773717

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