Automation for cost allocation forecasts: A PJM case study. Case Study This case study is drawn from a joint presentation by Nira Energy and Doral at ESIG's i2X STITCH Meeting 4: Automation and Data Harmonization (August 18, 2026). The i2X STITCH initiative - facilitated by Berkeley Lab in collaboration with ESIG and Elevate Energy Consulting as part of the DOE's Interconnection Innovation e-Xchange - brings together industry stakeholders to explore interconnection study practices across U.S. regions and identify opportunities for harmonization. When early cost estimates come in at hundreds of millions of dollars, how do you know whether to hold your position or fold? That's the calculation Doral faced with a project in PJM - and according to Shawn Welch (VP, Interconnection & Transmission), it's a decision that depends less on the sticker-shock number itself and more on understanding what everyone else in the queue is likely to do next. The Problem Doral had 500 MW across two projects in PJM's Decision Point 1 window. Phase 1 study results showed high cost allocations driven by an expensive network upgrade - the kind of early-stage number that can look alarming before the full picture develops. The Automation Rather than react to the initial estimate alone, Doral's team ran sensitivity analysis to forecast high- and low-band network upgrade cost allocation scenarios. That analysis was paired with judgment about the broader queue: other projects carrying even higher cost allocations than Doral's were likely to withdraw, based on Doral's read of those developers and past behavior in similar situations. Doral held its position rather than withdrawing additional megawatts. The bet paid off - when Phase 2 study results came in, the projects' network upgrade costs dropped by $96 million, in part because other high-cost-allocation projects did in fact drop out of the queue as anticipated. The Result The project advanced through Phase 2 and is currently undergoing Phase 3 studies.

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