The Challenge
A facility had a 450 kWp solar installation feeding an on-grid system with battery backup. Monthly generation was tracked separately from consumption. The only visible metric was 'net consumption from grid,' which showed ₹14 lakhs monthly savings. What was invisible: how much solar was actually being consumed vs. how much was being fed back to the grid.
What Became Visible
Real-time correlation of solar generation with consumption patterns revealed that the system was operating with a self-consumption rate of only 35%. When solar peaked (noon–2pm), consumption was low. When consumption peaked (morning startup, evening shutdown), solar was minimal. The facility was generating 450 kWh during a window when it needed only 200 kWh, feeding 250 kWh back to the grid at ₹0 (or minimal compensation rates). The economic opportunity: shift consumption to match solar generation peaks.
What Changed
Real-time dashboard correlating solar generation with consumption, broken down by production line, process, and equipment. Target: increase self-consumption rate from 35% to 60–65%.
How it worked: Operations were adjusted to shift non-critical consumption (HVAC pre-cooling, water heating, compressor charging) into peak solar windows. Production scheduling was optimized to concentrate high-power processes (heat treatment, heavy machining) during high-solar-generation periods. Within 6 weeks, self-consumption improved from 35% to 58%, reducing grid consumption during peak solar by 150+ kWh daily.
Results
more internal use, less grid export
during peak solar windows
from improved self-consumption
Solar installations generate power when the sun is highest (mid-day). Factories consume the most power during startup and shutdown (morning and evening). The gap between generation and consumption is the core inefficiency. When visibility into this gap exists, factories restructure operations to close it.
Operational Reality
Most solar installations operate with 20–40% self-consumption rates. The installations that achieve 60–70%+ are the ones that actively manage the correlation between generation and consumption.