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Corinex and Plexigrid team up to deliver the most accurate digital-twin solution for grid visibility and flexibility to date

06 luglio 2026 | 09.34
LETTURA: 4 minuti

VANCOUVER, BC and GIJÓN, Spain, July 6, 2026 /PRNewswire/ -- Corinex Corp. and Plexigrid S.L. have signed a strategic cooperation agreement to market Corinex Plexigrid Intelligence, a platform for low-voltage and medium-voltage power grids, built on the most accurate and granular power data.

As power-hungry AI unfolds, the electrification of industry, transport and heating/cooling accelerates, and the penetration of distributed energy resources explode, grid operators are facing the largest technological challenge in decades: planning, operating and orchestrating in real-time a distributed, intermittent and bidirectional electricity system with millions of DERs. Successfully solving this requires the next level of real time visibility, intelligence and control through their mid and low voltage sections of the grid. This strategic cooperation is aimed at delivering exactly that.

Corinex products observe and act on the physical grid, while Plexigrid software models and optimizes it. The partnership brings these complementary capabilities together, connecting real-time field intelligence with digital twin analysis, capacity decisions and flexibility actions.

The integrated solution helps utilities see real time voltage grid conditions, find available capacity, and act on network limits.

Built around Corinex's BPL architecture and edge-computing capabilities, the solution places sensing, processing and intelligence across the grid. This gives Plexigrid's digital twin richer and more accurate information from grid assets.

Why BPL Improves the Value of Digital Twins

Transmission grids are modelled and operated in real time using redundant, high-resolution instrumentation at every node and an exact electrical topology, manually curated by a dedicated topology team. This creates the "observability" requirements that transmission control systems need to operate. Scaling that approach from thousands of transmission nodes to tens of millions of distribution nodes would cost hundreds of billions and require hundreds of thousands of people. It is simply not feasible, which is why 99% of the nodes in the electricity grid remain unmodelled.

Plexigrid delivers a more realistic answer to this problem: a digital twin equipped with a layer of Bayesian AI that reconstructs the electrical topology and the state of the grid from systems DSOs already have in place, such as GIS (used for field operations and asset management) and AMI (used for billing). This creates unprecedented visibility and control in parts of the grid that were previously unobserved or only partially observed, using data from systems that were never designed for real time grid observability and control. But while these Bayesian digital twins provide game changing capabilities and are fast and cheap to adopt at scale, they do not reach the time resolution and accuracy of transmission control systems.

Corinex's BPL takes the performance and inference quality of these digital twins to the next level by adding a layer of low-latency, high-resolution instrumentation and control that complements what DSOs already have across meters, feeders, transformers and other unmetered or partially observed grid assets. The result is a level of time resolution, accuracy and real-time capabilities never seen before in distribution grids. Besides, Corinex's Grid Intelligence Node installed on the low voltage lines expands the number of the measuring points and adds further detailed measurements from the physical network, giving the twin a clearer view of loading, voltage, power quality, and emerging constraints.

Digital Twin Capability

Typical performance with PLC smart-meter data

Performance with Corinex BPL

Time Resolution

5-60 min

1 min

Estimation accuracy

~90–95%

~99%

Operational uncertainty

~5-10%

 ~1%

Required safety margin

~10-20%

~2%-5%

Asset utilization

Conservative, approximately 80% of limits

Optimized, closer to true limits

Built for Edge and Distributed Intelligence

Corinex and Plexigrid use BPL as an architectural foundation for distributed grid intelligence. The platform processes data near substations, feeders, and grid assets. The grid intelligence is embedded in both Corinex and Plexigrid solutions and is architected to provide the best performance and value for DSOs. This supports real time data checks, local analysis, and earlier warnings of abnormal conditions. The platform continues to handle wider models, forecasts, planning, reports, and links to other utility systems.

The result is a distributed intelligence layer. It links field conditions to digital models and utility decisions.

"Utilities need more than connectivity and more than a cloud-based view of the network. They need an intelligence layer that can observe the physical grid, understand changing conditions, and support action at the speed required by modern distribution systems," said Peter Sobotka, Founder and CEO of Corinex Corp. "Corinex delivers BPL, GIN, and edge capabilities across the grid. Plexigrid adds advanced digital twin and flexibility management capabilities that drive better capacity, investment, and operational decisions."

"This partnership allows our models to be continuously grounded in high-resolution information from the physical network. Combining that information with distributed processing and advanced grid analytics creates a stronger foundation for planning, flexibility, and day-to-day operations." said Alberto Méndez, CEO and Co-founder of Plexigrid.

About Corinex Corp.

Corinex Corp. provides technology that helps reinforce low-voltage and medium-voltage power grids. Its platform serves as digital grid capacity infrastructure. It gives utilities the data and control needed to manage congestion, add usable capacity, and get more from existing assets.

About Plexigrid

Plexigrid develops AI-powered digital twins and orchestrators for grid visibility, planning, and flexibility management to help utilities model grid conditions, find constraints, assess available capacity, and coordinate flexible resources.

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