Open grid modeling for technology-neutral clean energy analysis.

Why it matters

The dominant tools shaping state and national energy policy are category-based capacity-expansion models: they aggregate generation by type — “nuclear,” “solar” — with no geographic detail, limited temporal fidelity, and no representation of physical grid constraints. They underpin binding state and national energy plans, yet are rarely accompanied by peer-reviewed methods — their assumptions documented, when at all, in regulatory filings rather than published, replicable science. These are limits of the category-based paradigm, not any one tool's bugs. Climate Synthesis exists to provide an open, physics-based, independently verifiable alternative.

What we build

At the center of our work is the Open Framework: a physics-based, AI-accelerated grid simulation platform built on GridLAB-D. It is built to evaluate clean energy transition scenarios at distribution-level resolution, with full temporal continuity and a coherent system of metrics — economic cost, carbon intensity, reliability, health, equity, land use, and others as they emerge — all derived from the same simulation run.

"Open" in Open Framework is not a licensing detail — it names the method the work is built under. Open science is a well-established principle; the discipline here is applying it in full to grid modeling, where three conditions have to hold at once for a result to be credible and reusable. Every module is developed to meet all three:

• Open source software

  Every module is designed for release under a permissive open-source license — no barriers to use, replication, or commercial application. The architectural work is complete; the public release follows once module integration is complete and validated against published analyses and open datasets, with modules intended to be contributed upstream to the Arras Energy project under the Linux Foundation for long-term institutional stewardship.

• Open science publications

  Every module is developed to be released paired with a peer-reviewed journal publication documenting its methods — not internal review, not a regulatory filing, but published science any researcher can scrutinize, replicate, and challenge. Module and publication release together, by design.

• Open data

  Open data is part of the same commitment: the datasets used to build and validate each module will be released under public licenses, so results can be independently replicated — and replication is what separates a tool that can be trusted from one taken on faith.

Few of the tools shaping policy today satisfy all three conditions at once. The Open Framework is designed, from the start, to satisfy all three.

How it's built

At the core is a proven physics engine, not a new one: GridLAB-D, created and funded by the U.S. Department of Energy at Pacific Northwest National Laboratory and in long use across national labs, utilities, and regulators. We build on its Arras Energy distribution, maintained under the Linux Foundation, and will release our own work under the same open-source license. Beside that engine sit modular extensions, focused on the impact metrics that are usually computed by separate tools under separate assumptions: cost, carbon, reliability, health, equity, land use, and others as they emerge. Each is a distinct module — based on published, peer-reviewed methods — that reads from the same simulation run, so a scenario's numbers describe one dispatch rather than separate analyses that may not line up.

Around both sits the AI layer that makes the framework usable for policy questions. It is designed to build simplified grid models that stay faithful to the behavior that matters, to synthesize stress conditions — including modified and fully synthetic weather — and to search scenarios efficiently, concentrating full-fidelity simulation on the cases most relevant to a given policy question, as a basis for planning guidance and sensitivity analysis. The approach rests on a simple, checkable observation: a handful of underlying patterns capture most of how a grid's generation behaves — which is what makes analysis at this depth and breadth practical rather than out of reach.

A note on technology neutrality

Readers familiar with the energy policy landscape may notice that nuclear energy features prominently in our current work. This reflects the state of the analytical problem, not an organizational preference for any particular technology.

For decades, energy policy frameworks treated nuclear as peripheral, and many of the tools regulators rely on still cannot represent the full range of clean energy options — firm and variable alike — at the fidelity fair comparison requires. As decarbonization commitments have tightened, that analytical gap has become consequential. The question isn't whether to prefer nuclear — it's whether the tools can evaluate every option on equal footing. That is one of the gaps the Open Framework is built to close. It does not advocate for any technology; it is designed to evaluate all clean energy options under identical physical and economic constraints. What the analysis shows is what we report.

Contact

For inquiries — collaboration, evaluation, or funding partnerships — write to contact@climate-synthesis.com.

Climate Synthesis LLC was founded by Brian Bramlett.