By Bernadette Johnson, General Manager and Head of Power & Renewables, Enverus
In the modern landscape of renewable energy development, the fundamental constraints of the industry have shifted. A few years ago, the primary hurdles were securing land and ensuring favorable solar irradiance. Today, a developer can identify a thousand acres of prime, sun-drenched land with a willing owner in a single afternoon. However, the true bottleneck—the question that determines the viability of every project—remains: Will the grid actually allow a connection?
This chasm between "technically buildable" and "commercially viable" has become the defining challenge of the 2026 energy landscape. As the industry grapples with grid congestion, understanding the nuance of why this gap exists is critical for any developer, investor, or stakeholder hoping to navigate the future of power.
The Grid Constraint: A Structural Reality
There is a common misconception in 2026 that artificial intelligence has already solved the complexities of project siting. It has not. Much of the AI-driven software currently on the market merely produces more aesthetic, user-friendly versions of maps developers have used for years. While helpful for visualization, these tools fail to address the core problem: the grid itself is reaching a point of structural saturation.
According to the 2026 Global Renewable Energy Trends Report, which synthesized data from over 64,000 solar and storage projects, grid saturation and instability have emerged as the single greatest barrier to progress. Roughly 63.7% of surveyed energy professionals identified grid issues as their primary concern, significantly outpacing traditional hurdles like permitting and regulation, which sat at 47.8%.
Crucially, these figures are not anomalies; they reflect a multi-year trend. We are no longer dealing with a temporary backlog that can be cleared by hiring more staff or streamlining bureaucratic processes. Congestion, curtailment, and stalled interconnection are now permanent, structural features of high-penetration markets. They are actively reshaping where projects are built, which technologies are deployed, and, most importantly, how financial risk is priced.
The Two-Terawatt Logjam
The scale of this issue is best illustrated by the current U.S. interconnection queue. More than two terawatts of generation and storage capacity are currently waiting for a path to the grid—a figure that represents more than double the total installed capacity of the entire United States.
The sobering reality is that a vast majority of these projects will never see the light of day. They are doomed to be withdrawn, fail their rigorous grid impact studies, or languish in a state of suspended animation for years. While regulatory shifts like FERC Order 2023 are providing a necessary framework for reform and offer a glimmer of optimism, the fundamental lesson remains: a site selected without deep, granular intelligence regarding grid conditions is a site that may never produce a single kilowatt-hour.
The question for the industry is no longer "Can AI help us find sites?" The question is "Does the AI system you are using incorporate actual grid intelligence?"
A New Paradigm: From Market Thesis to Ranked Sites
When grid intelligence is integrated into the development process from day one, the entire workflow changes. Instead of starting with a parcel of land and hoping for grid access, developers must start with a thesis: a specific region, a technology, an offtake target, and a return threshold.
Using advanced, agentic workflow platforms like Enverus ONE, this thesis acts as the catalyst for an automated generation siting flow. This system screens over 156 million parcels of land, applying rigorous buildability filters, and then ranks the survivors based on the factors that truly dictate a project’s life or death: interconnection access and locational marginal pricing (LMP) signals.
The output is not merely a heat map requiring subjective interpretation. It is a ranked, auditable list of sites upon which a team can immediately act. The market context—decades of LMP patterns, historical congestion events, and queue behavior—is baked into the analysis. It surfaces "grid-ready" zones while flagging basis risk at the individual parcel level. This level of risk management is invisible to the naked eye and absent from standard satellite imagery, yet it is the precise metric that determines whether a project’s economics survive its first year of operation.
The Power of Exclusionary Analysis
Once a developer has a ranked list, the process must move to a rigorous exclusionary phase. This is where the most significant "wasted effort" in the industry is pruned away.
Utilizing over 50 layers of geospatial exclusion analysis—such as wildfire exposure, proximity to existing substations, queue status, and environmental constraints—developers can ensure that every site under consideration has already cleared the hurdles that typically kill projects in the final, most expensive stages of development.
This approach creates a "connected workflow." When a site is vetted against grid reality, it can be passed directly into engineering design software like RatedPower. By removing the need for re-keying data or starting from a blank page, engineers are freed from the trap of designing projects that are fundamentally unviable. In an industry where only a small fraction of queued projects reach commercial operation, this "screen first, design second" sequence is the most underrated lever for success.
Implications for Bankability
When pre-vetted, grid-aware sites feed the design engine, the downstream impact is profound. The platform produces comprehensive layouts, precise equipment selections, and energy yield estimates that provide investors with the data they need to sign off on financing.
Because these designs are grounded in grid reality from the very first iteration, there is no need to reassess the project’s viability halfway through the engineering phase. Investors are presented with a package that is not only technically sound but commercially defensible.
Furthermore, as hybrid solar-plus-storage projects become the industry standard, the ability to design these assets in tandem on sites already proven to be grid-ready is no longer just a competitive advantage—it is a core competency. It allows developers to protect project economics in increasingly volatile and saturated markets.
Conclusion: The Path Forward
The advantage of a connected, AI-driven workflow is the elimination of friction. By removing the handoffs between site identification, grid screening, and engineering design, developers remove potential sources of error, delay, and lost context.
The structural constraint of the grid is real, but it is also solvable for those who approach it with the right data. The developers who will lead the market over the next decade are those who treat the grid as their first question, not their last. By utilizing proprietary energy data that general-purpose AI models cannot replicate, and by grounding every decision in the hard reality of power markets, the industry can move beyond the map and into a new era of sustainable, bankable development.
About the Author
Bernadette Johnson joined Enverus in 2016 following the acquisition of Ponderosa Advisors, where she served as a founding partner. With a career spanning decades, Bernadette is a recognized authority on crude, natural gas, and NGL market fundamentals. Since becoming the General Manager of Power & Renewables in 2022, she has spearheaded the company’s efforts to provide actionable intelligence for the energy transition. She holds an M.S. in International Political Economy of Resources and a B.S. in Economics from the Colorado School of Mines.
