#grid

A useful climate pack should include one market roadmap, one deployment-focused policy source, one systems-modeling tool, and one example of open infrastructure modeling. That mix helps people study both the technology and the world it has to fit into.

The kinds of materials worth saving in this space:
- market reports that separate hype from adoption
- company breakdowns that include deployment friction
- policy trackers tied to concrete commercial consequences

Read:
- IEA Net Zero by 2050 roadmap: iea.org/reports/net-zero-by-2050-a-roadmap-fo...
A strong system-level reference for where decarbonization pressure and infrastructure limits show up.
- DOE Liftoff reports: liftoff.energy.gov/
Useful for understanding commercialization pathways and deployment bottlenecks in the US.
- NREL publications: nrel.gov/research/publications.html
A good place to keep the technical and systems conversation grounded in public research.

Documents and downloadable guides:
- IEA reports archive: iea.org/reports
One of the best places to ground climate claims in system-level energy data and forecasts.
- DOE Liftoff reports: liftoff.energy.gov/
Strong material for understanding commercialization, financing, and deployment bottlenecks.

Watch:
- NREL video archive: youtube.com/@NRELgov/videos
Talks and explainers that help translate research into deployment context.
- IEA video archive: youtube.com/@IEAorg/videos
Useful when a reader wants short briefings alongside the denser report material.

Build or inspect:
- PyPSA documentation: docs.pypsa.org/
An accessible place to start with open power-system analysis and optimization.
- PyPSA source: github.com/PyPSA/PyPSA
Core open-source toolkit for modeling energy systems and power networks.
- PyPSA-Eur: github.com/PyPSA/pypsa-eur
A richer open model when you want to see the workflow applied at continental scale.

Image references:
- DOE Liftoff charts and pathways: liftoff.energy.gov/
A good visual reference for pathways, system bottlenecks, and category comparisons.

A recurring mistake is treating a pilot as proof of market readiness. Another is discussing climate impact without showing how permitting, procurement, or interconnection timelines shape the commercial path.

Common traps to watch:
- treating prototypes as proof of market readiness
- ignoring permitting or grid interconnection timelines
- using emissions narratives without checking customer economics

References that help correct the drift:
- DOE Liftoff reports: liftoff.energy.gov/
Useful for understanding commercialization pathways and deployment bottlenecks in the US.
- DOE Liftoff charts and pathways: liftoff.energy.gov/
A good visual reference for pathways, system bottlenecks, and category comparisons.

This folio post is meant to be saved and revised. Add examples from your own work whenever one of these mistakes keeps resurfacing.

A practical workflow begins with a clearly bounded emissions problem, then moves through deployment blockers before it gets seduced by TAM language. If a technology cannot survive financing, siting, or interconnection reality, the technical elegance alone will not rescue it.

A sequence I would actually hand to a teammate:
1. Start by defining the emissions problem and the system boundary around it.
2. Track deployment blockers such as supply chain, permitting, and project finance.
3. Compare company claims with market structure, customer behavior, and policy timing.

Useful operating references:
- DOE Liftoff reports: liftoff.energy.gov/
Useful for understanding commercialization pathways and deployment bottlenecks in the US.
- PyPSA documentation: docs.pypsa.org/
An accessible place to start with open power-system analysis and optimization.

If your team has a better workflow, post it with the context around team size, constraints, and exactly where the process tends to break.