WEMO 2025 (complet) - Flipbook - Page 36
W E M O 202 5
O U T LO O K
√ Data and software-based solutions
— DLR uses real-time weather data and sensors to
assess the true capacity of transmission lines.
Its e昀케ciency gains are substantial in congested
regions. A comprehensive review269 found that
traditional static transmission lines capacity
ratings are signi昀椀cantly more conservative than
necessary. DLR ratings exceed static limits by
15-30% about half the time, with some studies
showing capacity increases up to a remarkable
45%, particularly valuable during peak congestion
periods.
— Transmission Topology Optimization uses software
to recon昀椀gure power 昀氀ows, reducing congestions.
These technologies, still underutilized, have
shown signi昀椀cant promises, with potential to save
billions in congestion costs.
●
— APFC, part of Flexible AC Transmission Systems
(FACTS), employs devices like phase-shifting
transformers or Smart Wires technology to
reroute power and balance overloaded lines.
267
268
269
https://www.smart-energy.com/industry-sectors/smart-grid/
solving-the-grids-ai-power-struggle-with-virtual-power-plants/
https://www.forbes.com/sites/je昀昀mcmahon/2020/05/31/
thanks-to-renewables-and-machine-learning-google-now-forecasts-the-wind/#49c7e94e1865
273
https://www.energy.gov/sites/default/昀椀les/2021-12/CRISP%20Fact%20Sheet_508.pdf
271
Additionally, AI can simulates cyberattack scenarios,
as seen in the US’s CRISP program, strengthening grid
defences by generating robust security protocols.273
272
35
https://www.sciencedirect.com/science/article/abs/pii/S0378779624001925
https://acore.org/resources/assessment-and-evaluation-of-grid-enhancing-technologies-gets/
https://www.forbes.com/sites/annabroughel/2025/03/27/
dynamic-line-rating-grid-technology-to-reduce-your-electric-bills/
270
A Virtual Power Plant (VPP) is a network of decentralized, medium-scale power generating units
as well as 昀氀exible power consumers and storage systems
How can arti昀椀cial intelligence help? Arti昀椀cial intelligence
(AI) enhances the integration of distributed energy
resources (DERs) by coordinating microgrids, improving
heating and cooling e昀케ciency particularly for data
centers and buildings, reduces computation for
cryptocurrency mining, and optimizes charging for
electric vehicles, and home batteries. Adding AI
to Virtual Power Plants (VPP) management270
allows precise energy forecasting and demand
response optimization. The Department of Energy
estimates that tripling the scale of VPPs by 2030 could
help meet electricity demand growth and save annual
grid costs on the order of $10 billion.271 By analyzing
weather, consumption, and production data, AI
improves renewable output predictions, reducing
curtailment. As an example, Google combined
weather data with power data from 700 megawatts
of wind energy sourced in the Central United States.
It then used machine learning, to better predict wind
production and electricity supply and demand. This has
resulted in a 20% increase in revenue for wind farms.272
WEMO 2025
— Grid Enhancing Technologies (GETs):267,268 They
are hardware and software solutions designed to
optimize the capacity, e昀케ciency, and reliability of
existing power transmission and distribution. the
US Department of Energy is presently investing
nearly $84 million in these advanced technologies.
Examples of GETs include Dynamic Line Rating
(DLR), Advanced Power Flow Control (APFC), and
Transmission Topology Optimization.
