Omega Transmission consumed HT power on a time-of-day tariff. They were paying for energy they couldn't shift, MD penalties they couldn't avoid, and PF rebates they were leaving on the table. PowerIQ instrumented the site at 5-minute granularity, automated the tariff response, and cut the bill by ~20% in six months.
The problem
Industrial HT power is punitively priced. Time-of-Day tariffs charge more at peak. Maximum Demand floors trigger penalties if you cross them. Power Factor rebates apply only if you maintain PF — most sites don't bother. The result: a site can be paying a 25-30% premium against a perfectly optimised baseline.
Most plants don't see it because their meters report monthly, not at 5-minute granularity. Without visibility, no decisions are made.
The system we built
Raspberry Pi 4 polls the L&T HT meter via Modbus RS485 at 5-minute granularity. AWS IoT Greengrass pre-processes at the edge — anomaly suppression, batched upload, buffer through cloud disconnects. MQTT forwards to the cloud. Time-series store captures 50+ electrical parameters.
The local HT tariff schedule is encoded as executable rules. A load-forecasting ML pipeline runs hourly. The optimiser fires commands back to the edge — load shedding when the MD floor is approaching, load shifting when ToD slabs are crossing, capacitor banks in / out for PF correction.
The outcomes
Six months in, bills came down by about 20%. MD-floor breaches went from monthly to zero. PF rebate captured every cycle. The ESG Scope-2 report exports audit-ready in 60 seconds for compliance reporting.
"We were leaving more money on the table than the cost of the entire system every month. The payback was inside the first quarter."
— Plant Manager
↓ mqtt
iot core · time-series db · forecast ml
↓
tod policy → md-floor automation → pf rebate
↓
command queue → edge → switch panel
↓
esg scope-2 audit report
What's underneath
- Aminobots Lens — PowerIQ (edge controller + cloud watchtower)
- Raspberry Pi 4 + L&T HT meter via Modbus RS485
- AWS IoT Core + Greengrass for edge resilience
- Forecast ML pipeline (Prophet / Darts class)
- Blueprint System (AWS Greengrass + Bedrock target)