AI Net Metering Optimization

Machine learning for maximizing value under net metering tariffs

The Problem

“Optimize Net Metering Value Amid Volatile Tariffs”

Organizations face these key challenges:

Tariff complexity (TOU windows, demand charges, export caps, NEM successor rules) makes it difficult to predict customer economics and program cost under changing regulations

Inaccurate interval forecasting of load and PV exports leads to mis-sized systems, suboptimal battery/EV schedules, and unexpected bills and true-up surprises

Limited visibility into feeder-level constraints and localized congestion causes misalignment between customer incentives and grid needs, increasing operational risk and interconnection friction

Impact When Solved

Increase PV+storage customer net savings by 5–20% via interval-optimized dispatch and rate-plan recommendationsReduce utility net metering program cost leakage by 2–8% through better export valuation, targeting, and forecastingCut manual tariff/billing analysis and dispute resolution workload by 30–60% using automated validation and anomaly detection

Real-World Use Cases

AI in Energy Industry: Smart Grid Optimization and Energy Management

This is like giving the entire power system—power plants, grids, and large customers—a real‑time ‘autopilot’ that constantly predicts demand, reroutes electricity, and tunes equipment so you use less fuel, waste less energy, and keep the lights on more reliably.

Time-SeriesEmerging Standard

8.5

AI Grid Congestion Management

This AI helps optimize the layout of power grids to reduce congestion without increasing costs or carbon emissions.

optimizationgrowing

8.0