envelio Unlocks More Grid Capacity and Accelerates Speed to Power with Game-Changing GPU-based Power Flow Solver
KEY BENEFITS
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Up to 20,000 times faster: The new GPU-based solver significantly accelerates power flow calculations compared to industry standard legacy tools
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Transparency & reliability: Physics-first results instead of AI "black box" approach
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Game-changer to unlocking grid capacity: The patent-pending solution is key to more flexible grids and faster access to grid capacity for distributed generation and loads
envelio has achieved a technological breakthrough: the grid tech company has developed a GPU-based power flow solver that cuts the time required for annual time-series simulations from days or weeks to less than 30 seconds — up to 20,000 times faster than industry-standard processes relying on desktop grid calculation tools. For the first time, distribution grid operators can run continuous, large-scale grid simulations as part of their daily operations, fundamentally changing how grid capacity is assessed, unlocked, and managed.
The timing could not be more critical. More than 2,500 gigawatts (GW) of generation, storage, and large industrial projects are currently waiting in grid connection queues worldwide — and that figure only counts large-scale requests in the megawatt range. EV charging infrastructure, heat pumps, and renewable generation assets are all stuck in the same bottleneck.
This is precisely the problem that envelio’s new GPU-based power flow solver addresses: "Flexible, transparent grid management relies on complex time-series simulations, a process that traditionally took days or even weeks with legacy desktop grid calculation tools and fragile scripting around the solver core," says Simon Koopmann, CEO of envelio. "Our new solver reduces annual time-series simulations to less than 30 seconds, achieving performance up to 20,000 times faster than conventional desktop solvers.”
This high-performance solver allows DSOs to simulate in real time how the grid will behave when new loads such as electric vehicle (EV) charging stations, heat pumps or generators such as solar systems, wind farms, or battery storage systems want to get connected. Combined with the underlying digital twin of the power grid within envelio’s Intelligent Grid Platform (IGP), it enables new use cases that were previously not feasible.
Unlike black-box, AI-based estimation approaches, the new technology solves the real physics of the grid on a digital grid model. This gives grid operators results their engineers can trust while making large-scale scenario simulations, faster grid connection assessments, more flexible grid operation, and more robust grid investment decisions part of everyday practice.
DSOs are under growing pressure to evaluate significantly more connection requests, scenarios and flexibility options within tight timelines.
"Grid operators are under growing pressure to evaluate significantly more connection requests, scenarios and flexibility options within tight timelines,” Koopmann said. “Our GPU-based solver fundamentally changes how DSOs approach grid planning by replacing periodic, worst-case analysis with continuous, time-series-based decision-making. This enables distribution grid operators to make better use of existing grid capacity, prioritize investments more effectively, and help keep the energy transition affordable."
Physics-first trust at GPU speed instead of AI-based estimation
Some providers have responded to the demand for faster simulations by turning to AI-based estimation — trading accuracy for speed. envelio has taken a fundamentally different approach.
"The need for faster simulation is so high that solutions have emerged in the industry that rely on AI-based estimation just to speed things up. We have opted to still accurately solve the real physics in the grid — but with a new technology that is at least as fast as, if not faster than, AI-based estimation approaches out there," explains Dr. Fabian Potratz, CTO of envelio GmbH.
envelio's solver is built on deterministic, physics-based models grounded in established electrical engineering principles — not statistical approximations trained on synthetic data. For dependable grid decisions, envelio uses a true AC power flow model, capturing complex voltage behavior and reactive power effects in distribution grids.
Results are fully transparent and auditable, giving grid engineers outputs they can verify, trust, and stand behind.
GPU architecture delivers this engineering-grade reliability through massive parallelization, simultaneously computing across scenarios, time steps, and grid segments. Speed without trust is not a solution.
APPROACH COMPARISON
Two paths to faster simulation
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AI-BASED ESTIMATION |
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ENVELIO GPU SOLVER Physics-based, parallelized |
| Fast Speed through estimation |
Equally fast Up to 20,000× via GPU parallelization |
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| Black box Results hard to verify or audit |
Fully transparent Auditable outputs engineers can trust |
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| Approximated Trained on synthetic data, not real physics |
Deterministic True AC power flow, real electrical principles |
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| Misses edge cases Voltage & reactive power effects not fully captured |
Massively parallel Simultaneous scenarios, time steps & grid segments |
Speed without trust is not a solution.
envelio delivers both — physics-grade accuracy at GPU speed.
Unlocking new potential for power grid infrastructure
The high-performance solver delivers tangible benefits across key areas of power grid planning and operations:
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Faster grid connection studies: New loads and distributed energy resources (DERs) can be evaluated significantly faster, reducing waiting times and allowing the analysis of more complex connection solutions based on flexible operating agreements. This helps shorten project timelines for developers while reducing engineering workloads for distribution grid operators.
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Advanced hosting capacity analysis: DSOs gain a detailed and time series–based understanding of how much additional load or generation each grid section can accommodate before limits are reached, instead of relying only on worst case evaluations. This reduces uncertainty for DER, data center, and battery storage developers while enabling more reliable site selection without unexpected costs.
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Better utilization of existing infrastructure: More comprehensive simulations enable DSOs to maximize available power grid capacity before investing in expansion.
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Improved investment decisions: Instead of relying on a few standard scenarios, grid operators can now run millions of scenarios to identify the most targeted grid investments—and save billions in unnecessary upgrade costs.
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Flexibility embedded end-to-end into grid processes: The increased computational performance enables more flexible grid management throughout the core processes, from planning to operation.
The GPU-based solver enhances the IGP’s existing Grid Hub functionality. It has been integrated into select time-series and hosting capacity workflows and is currently available. Further expansion to additional use cases is planned throughout the year.
| AI-based | Physics-based | envelio GPU-based Power Flow Solver | |
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| Speed | High | Limited | High |
| Scalability | High | Limited | High |
| Constraint Awareness | No | Yes |
High |
| Validation | Limited | High | High |
"We see the GPU-based solver as a major breakthrough for the industry. It enables entirely new approaches to grid planning, connection studies, and grid operations, including large-scale scenario analysis and smarter grid connection assessments that were not previously feasible. We will leverage this technology across the entire Intelligent Grid Platform to help distribution grid operators modernize grid planning and operations while supporting rising electricity demand driven by EV charging, heat pumps, industrial electrification, and new large loads such as data centers," Koopmann concluded.
About the Intelligent Grid Platform (IGP)
envelio's Intelligent Grid Platform (IGP) is a comprehensive software solution for the efficient planning and operational management of power grids, providing a digital twin that processes, corrects and visualizes existing data. As the need for grid investment and complexity increases amid a high volume of connections, the platform’s holistic approach ensures that grid data and planning drive effective investments, enhance grid reliability, and enable scalable processes. Thanks to the modular architecture of the award-winning software, it adapts to DSOs of all sizes, making it a unique solution to the challenges of decentralized energy supply and distribution grid expansion. envelio's IGP empowers grid operators to optimize and automate processes, laying the foundation for a rapid and decentralized global energy transition.
About envelio:
envelio was founded in 2017 as a spin-off from RWTH Aachen University and develops software for grid operators. With its proprietary Intelligent Grid Platform (IGP), the company gives grid operators transparent insights into actual grid conditions. The digital twin helps utilities automate and digitalize processes, identify grid vulnerabilities, manage grid connections more efficiently, and plan distribution grid expansion based on actual needs. Headquartered in Cologne, Germany, envelio provides the foundation for flexible smart grids and a rapid, decentralized energy transition.