Recent data indicates that planned battery storage capacity for 2026 is shifting, with nearly 25% of initially projected capacity now delayed or removed from those plans. This is significant for AI/ML practitioners because it highlights the challenges in forecasting energy infrastructure deployment, impacting the accuracy of models predicting grid stability and energy demand. Interestingly, battery projects co-located with solar installations consistently experience delays that mirror those of the solar component, suggesting dependencies in project timelines and potentially revealing broader permitting or supply chain bottlenecks.
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