What if AI predicted equipment failures with 100% accuracy ? [20]
Imagine an electricity system where every impending asset failure is known in advance with perfect precision —time, location, cause, and cascading effects—across transmission, distribution, generation, and behind‑the‑meter devices. In such a world, outages from equipment defects disappear, capital plans re‑optimize around true residual life , spares and crews arrive “just in time,” and regulators recalibrate reliability incentives from SAIDI/SAIFI to assurance of supply under probabilistic risk that excludes random equipment faults. The International Energy Agency (IEA) already frames digitalization as essential to grid reliability and cost control; with perfect prediction, the gains would multiply—reducing outage minutes, deferring capex, and accelerating the clean‑energy transition by unlocking grid headroom without overbuilding . [iea.org] , [iea.org] Evidence from real utilities shows that even non‑perfect predictive analytics deliver 10–20% OPEX savings and 40–60% capex optim...