High maintenance costs
Expanding Transmission Grid Capacity for Clean Energy
How do we create the bridge to the future?
We are the authority on applying Computational Fluid Dynamics over complex terrain
Validated DLR deployments and shown 40% enhanced ampacities
Actively engaged in industry and standards organizations
A big part of the world’s electricity decarbonization challenge lies in expanding transmission capacity for renewables — and according to energy experts, Europe and the US are falling behind on that task. Meanwhile, US consumers pay more than $6B in transmission congestion costs, resulting in hundreds of GW (gigawatts) of renewable energy stuck in interconnection queues, waiting to connect to the grid.
At the same time, grid utilization rates are often as low as 30-50%, meaning there is excess capacity on today’s wires that could be leveraged to solve these problems.
Solutions will require game-changing technology that can significantly increase the utilization of the electric grid.
WindSim Power understands that grid-enhancing technologies (GETS) are cost-effective tools to unlock capacity and bridge current infrastructure to the future.
That’s what Dynamic Line Ratings (DLR) technologies do.
With the WindSim Power Line solution, the transmission owner can scale this technology to improve utilization, reduce costly grid congestion, and speed interconnection of renewables.
DLR and GETS both serve to facilitate energy transition and decrease CO2 emissions. These attributes increase long-term investor attractiveness founded on the incorporation of Environmental Sustainable and Governance (ESG) metrics into their capital allocation and stewardship criteria.
GETs and DLR can bridge the timing gap while waiting for a more permanent solution.
WindSim has years of experience in the wind and solar industries and has co-developed WindSim Power Line with the Idaho National Laboratory and other industry partners. They are leaders in operationalizing data, information technology, and cybersecurity.
WindSim Power is backed by 20 years of Computational Fluid Dynamics (CFD) experience and proven forecasting methodologies that yield actionable and reliable results.