Colorado’s clash with Xcel shows how bad grid data is stalling clean energy. Here’s what regulators, developers, and businesses can do to fix it in 2025.
Most utilities say they support clean energy. Then regulators open their data portals and find…nothing useful.
That’s essentially what just happened in Colorado, where regulators blasted Xcel Energy’s grid data as “totally useless” for planning new distributed energy resources (DERs) like rooftop solar, community solar, battery storage, EV chargers and smart buildings.
This matters because green technology only scales when the grid is transparent and predictable. If developers and businesses can’t see where there’s capacity, projects stall, costs rise, and climate goals slip further out of reach.
In this post, I’ll break down what’s going on in Colorado, why grid transparency is now a core green technology issue, and what you can actually do as a developer, business, or policymaker to avoid getting stuck behind “useless” utility data.
The Real Problem: Clean Energy Can’t Connect Without Good Data
The core issue in Colorado isn’t a lack of solar panels or batteries. It’s the lack of reliable, granular grid data that shows where those assets can connect.
Distributed energy resources depend on three things:
- Available capacity on local lines and transformers
- Clear, predictable interconnection rules
- Accurate, up-to-date grid models
When regulators called Xcel’s grid data “totally useless,” they were reacting to exactly the opposite:
- Hosting capacity maps that don’t match real-world conditions
- Data that’s too coarse or outdated to support investment decisions
- Models that can’t be trusted for planning DER portfolios at scale
This isn’t a niche technical problem. It directly affects:
- Solar and storage developers trying to site projects
- Businesses budgeting for EV fleet charging or onsite batteries
- Cities planning smart-grid and resilience investments
- State regulators trying to meet clean energy targets
The reality? Interconnection and grid visibility have become the new bottleneck. Not technology cost. Not consumer interest. Data.
Why Regulators Are Losing Patience With “Black Box” Utilities
Regulators across the US are under pressure: hit climate and reliability targets, keep bills affordable, and modernize infrastructure that was designed for one-way power flow.
When utilities treat the distribution grid like a black box, regulators get boxed in too.
What Colorado Is Reacting To
While the original story focuses on Colorado’s Public Utilities Commission (PUC) and Xcel Energy, the pattern is national:
- Hosting capacity tools that claim to show where DERs can connect, but turn out to be inaccurate when projects are submitted
- Opaque methodologies for how grid models are built and updated
- Slow updates that make the data stale within months or even weeks
- Lack of actionable detail – developers see color-coded maps but not the actual constraints, upgrade costs, or timelines
From a regulator’s perspective, that makes it almost impossible to:
- Evaluate whether interconnection costs are fair
- Confirm that DERs are being treated comparably to traditional grid investments
- Use DERs as a serious alternative to new wires and substations
So you get blunt statements like “totally useless” – because if the data can’t support decisions, it’s worse than nothing. It wastes time and undermines trust.
Why This Blocks Green Technology Adoption
For many businesses in 2025, the economics of clean energy already pencil out:
- Battery costs have fallen dramatically over the last decade
- Commercial solar is often cheaper than retail grid power over its lifetime
- EV fleets can reduce operating costs and emissions at the same time
But here’s the catch: without clear grid visibility, “viable” projects become speculative bets. Developers must pad in risk premiums, design around unknown constraints, or abandon sites entirely.
Most companies get this wrong. They focus entirely on the tech (panels, chargers, inverters) and ignore the grid data and regulatory context that actually determine whether a project moves.
What Good Grid Data Looks Like (And Why AI Is Key)
Accurate, transparent grid data is now a core piece of green technology infrastructure. It’s as important as smart inverters or battery chemistry.
The emerging best practice looks like this:
1. Granular Hosting Capacity Data
Useful hosting capacity tools don’t just show “red, yellow, green” segments on a map. They provide:
- Feeder- and transformer-level capacity in kW or MW
- Thermal, voltage, and protection constraints spelled out clearly
- Time-varying conditions, not just peak snapshots
- Update cycles measured in weeks, not years
That’s the minimum needed for DER developers and businesses to make rational investments.
2. Transparent Modelling Methodologies
Regulators and third parties need to understand:
- Which assumptions go into load forecasts
- How DER behavior (like battery dispatch) is modeled
- How often models are calibrated against real-world data
When the methodology is transparent, regulators can push back on outdated or overly conservative assumptions that artificially limit DERs.
3. AI-Enhanced Grid Analytics
Here’s where green technology and AI really meet.
AI isn’t just a buzzword here. It’s actually well-suited to the messiness of distribution grids:
- Machine learning models can infer hosting capacity from historical voltage, loading, and outage data even where models are incomplete
- Anomaly detection can flag feeders whose real-world performance doesn’t match the modeled limits
- Forecasting models can predict EV charging impacts, solar variability, and demand response potential with much higher accuracy
The combination of good instrumentation (smart meters, sensors, SCADA) plus AI-driven analytics gives regulators and developers something they’ve never had before: near-real-time grid visibility.
That’s the foundation for:
- Smarter interconnection queues
- Dynamic hosting capacity
- Flexible interconnection agreements (for example, limiting exports during only a few constrained hours)
How This Affects Developers, Businesses, and Cities in 2025
If you’re trying to build or use clean energy in Colorado or anywhere facing similar issues, here’s the blunt truth: you need a grid data strategy as much as a technology strategy.
For Solar, Storage, and DER Developers
Developers that thrive in this new landscape treat grid constraints as a design input, not an afterthought.
Practical moves that work:
- Pre-screen sites using all available utility data, but then validate with your own modeling where possible
- Budget time and money for interconnection studies, and treat them as core project milestones
- Use flexible designs – for example, pairing storage with solar to reduce peak exports and avoid upgrades
- Engage regulators and stakeholders with specific data gaps you’re encountering, not just general complaints
The developers who bring credible grid analytics to the table often get faster approvals because they’re helping solve the regulator’s problem, not just adding to it.
For Commercial and Industrial Customers
If you’re planning EV charging, on-site solar, or battery storage for 2026–2030, you can’t just rely on a vendor proposal and a payback period.
Better questions to ask your partners:
- What grid data are you using to assess feasibility?
- How often is that data updated?
- What’s your plan if the interconnection study triggers upgrades or export limits?
- Can your system operate flexibly (for example, adjust charging or exports based on grid signals)?
I’ve found that the customers who push on these questions avoid nasty surprises 18 months into a project when the “simple” interconnection turns into a $1 million upgrade.
For Cities and Public Agencies
Cities pursuing smart city strategies, resilience hubs, and fleet electrification need to treat utilities as data partners, not just infrastructure providers.
Concrete steps:
- Advocate at your PUC for transparent, machine-readable hosting capacity data
- Insist that utilities share non-sensitive grid data to support public planning
- Coordinate DER planning with transit, housing, and resilience investments so you’re not piling load onto already constrained feeders
Green technology isn’t just rooftop solar — it’s how city planners, utilities, and regulators share information to avoid blindly overloading the same parts of the grid.
What Regulators and Policymakers Can Do Differently
Colorado’s frustration points toward a broader shift: grid transparency is becoming a regulated obligation, not a courtesy.
Here’s what’s starting to work in leading states and jurisdictions:
1. Make Hosting Capacity Actionable, Not Just Informational
Regulators can require that:
- Hosting capacity values be used in interconnection decisions
- Utilities explain any deviation between map-based expectations and final study results
- Updates follow a defined schedule and performance metrics (for example, map accuracy targets)
If the data isn’t binding in some way, it’s too easy for it to stay “pretty but useless.”
2. Tie Grid Data Quality to Investment Plans
When utilities file grid modernization or capital plans, regulators can:
- Assess whether proposed investments reduce data gaps
- Ask how new sensors, AMI data, and automation will feed into public-facing tools
- Require explicit budgets and timelines for data and modeling improvements
In other words, grid visibility itself becomes a regulated investment, just like wires and transformers.
3. Encourage AI and Third-Party Analytics
Utilities don’t have to build everything themselves. Regulators can:
- Allow or encourage partnerships with analytics firms that specialize in DER hosting models
- Approve pilot programs that use AI to adjust hosting capacity in near real time
- Clarify rules for data sharing so utilities can work with third parties without endless legal friction
Done well, these steps turn AI from a buzzword into a practical tool: better forecasts, less guesswork, more DERs.
Where This Fits in the Broader Green Technology Story
The Colorado–Xcel conflict is a symptom of a bigger shift in green technology: we’re moving from “build clean stuff anywhere” to “orchestrate clean energy everywhere.”
That orchestration depends on three layers working together:
- Physical infrastructure – lines, transformers, breakers
- Digital intelligence – sensors, data platforms, AI models
- Regulatory rules – transparency, access, and accountability
If any one of those layers falls behind, green technology stalls. Right now, in a lot of places, the weak link is digital intelligence and data access.
For businesses and communities trying to decarbonize, the takeaway is simple:
- Don’t treat grid constraints as an afterthought
- Ask hard questions about data and modeling
- Prefer partners that bring both technical solutions and grid-aware planning
And for utilities, the message from Colorado is even clearer: opaque, low-quality grid data is no longer acceptable. Regulators, developers, and customers are demanding tools they can actually use.
The upside? Once grid data becomes reliable and AI turns it into actionable insight, clean energy projects stop being one-off battles and start looking like normal, repeatable investments. That’s when green technology really scales.
If you’re planning DER projects or building a clean energy strategy and want to avoid getting stuck behind “totally useless” data, now’s the time to build grid visibility into your plans — not as a nice-to-have, but as core infrastructure.