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GridOS® Digital Dynamic Line Rating (DDLR)

GE Vernova

GridOS® Digital Dynamic Line Rating (DDLR)

GE Vernova

Lowering Transmission Congestion Costs & Maintaining High Reliability of the Grid

Conventionally, most Line Ratings are computed based on conservative assumptions about weather conditions, and are not regularly updated to reflect the actual impact of weather on such ratings. This causes problems such as congestion on the grid, compliance with FERC881, curtailment, and CAPEX deferral.


The traditional hardware-based approach to estimating and increasing line ratings is far from an exact science –and hardly economical. An alternative can be found in GE Vernova’s Digital Dynamic Line Rating (DDLR) solution. With DDLR, real-time temperature and wind speed data from weather data providers are fed into algorithms that can dynamically adjust the line rating based on actual line conditions at any given time. DDLR technology can help increase transmission line capacity, reducing the need for new infrastructure and improving grid efficiency. It can also help reduce the risk of power outages by allowing transmission lines to safely operate at higher capacities.


Key Features within DDLR:

· Full network coverage with a unique approach to combine GIS model into effective EMS rating calculation for the conductors and facilities.

· A field sensor free computation of Realtime & 10-day Forecasted Dynamic Line Ratings in compliance with IEEE standards.

· Two Configurable modes:

o Basic FERC 881 Compliance mode: Ambient Adjusted Rating

o Dynamic Line Rating mode – additional 20-30% system capacity

· Computes Actual Dynamic Ratings for multiple modes (i.e. Normal, Emergency, N-Modes)

· Configurable Effective Dynamic Ratings to comply with the FAC-008 (identifies next most limiting components) for the substation equipment.


Digital Dynamic Line Rating is designed to combine Geospatial Information System (GIS) and Energy Management System (EMS) asset data with weather data to generate ratings at high speed and volume. DDLR utilizes observed (measured) weather data and 10-day forecast, with accessible geospatial data (4X4 km grids) via cloud APIs will calculate entire network footprint in minutes. Flexible weather data ingestion is also available, with hourly refreshed values for temperature, wind speed, direction, and atmospheric conditions to dynamically calculate ratings.

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