A gated community with 18 villas. Each home gets a 9 kW three-phase Infozeb inverter + 12 kWp solar. EMS aggregates the fleet for community-level analytics.
A gated villa community in Bengaluru (Whitefield extension) comprised 18 luxury homes, each consuming 8-12 kWh daily. The community had invested ₹2.8 crore in rooftop solar (12 kWp per villa, 216 kWp total) three years prior, but net metering cuts imposed by the DISCOM capped export at 30% of consumption. Homes were exporting 4-5 kWh daily at the unfavourable ₹3.50/kWh buyback rate, while importing grid electricity at ₹8.20/kWh during evening peak hours (6 PM to 10 PM). The RWA estimated annual grid import cost at ₹18 lakh for the 18 homes combined.
The additional frustration was solar seasonality: June-July (southwest monsoon) saw 40% lower solar output due to cloud cover, forcing higher grid reliance precisely when tariffs climbed to peak summer rates. Residents wanted to "store their solar" and time-shift generation into evening, cutting grid import and eliminating the economics of cheap export.
We aggregated 8 weeks of household-level consumption data via smart meter telemetry. Mean daily consumption per home: 9 kWh. Peak evening demand (6 PM to 10 PM): 2.5 kWp per home. The goal was to eliminate evening grid imports entirely. A 9 kW three-phase inverter (IZ-9K-3P) paired with 18 kWh of usable battery storage per home was sized. This allowed 9 kWh of midday solar (typical good-weather day) to be stored and released over the 4-hour evening peak, covering 80-85% of household evening demand.
Capex per home was ₹12 lakh for IZ-9K-3P + battery. Over 18 homes, total investment was ₹2.16 crore. Payback period: 4.2 years, driven by ₹4.2 lakh annual grid import savings per home (reduction from ₹8.20/kWh to ₹1.20/kWh effective evening cost). The RWA approved the investment via a 60-month EMI structure financed at 8.5% interest.
Each home received an IZ-9K-3P cabinet housing LiFePO4 cells in 48 V, 50 Ah modules. The cabinet integrates a 9 kW three-phase inverter/charger and an in-house BMS firmware managing cell health, charge balancing, and thermal control. The system islanded from the grid during sags and transferred to battery supply in under 15 ms, providing some UPS functionality for occasional grid hiccups during monsoon season.
The cloud EMS at portal.infozeb.energy aggregated all 18 homes into a single dashboard. The RWA secretary could view community-wide solar generation, battery state-of-charge, and grid import in near-real-time. The EMS ran a predictive charge algorithm: at 2 PM each day, it estimated remaining daylight solar hours and optimal discharge start time for the evening peak. On cloudy days, it conservative-charged the battery (limit discharge to 70% capacity) to preserve headroom for cloud cover recovery. On sunny days, it fully charged to 100%.
Key technical specifications for the villa community deployment:
Grid bill reduction averaged 74% per home (from ₹1,050/month to ₹270/month for average homes, ranging ₹4,800-6,200 annually per villa). The 18 homes collectively shifted from 450 kWh/day grid import (pre-battery) to 115 kWh/day, a 75% reduction. Evening peak demand stopped triggering demand surcharge escalations (many state DISCOMs apply higher tariffs if single-day peak exceeds a home's monthly average). Community solar self-use improved from 55% to 94%, meaning almost all 216 kWp of solar generation was now consumed on-site rather than exported.
A secondary outcome emerged: the community's aggregate EMS data allowed the RWA to pursue DISCOM rebate schemes. The state of Karnataka offers ₹1 lakh per 5 kW of residential storage for "grid stabilisation". The 18 homes qualified for ₹35 lakh in subsidies, reducing net community capex from ₹2.16 crore to ₹1.81 crore and payback period from 4.2 to 3.1 years. Resident satisfaction increased: quarterly electricity bills became predictable and 40-50% cheaper than previously feared.
Residential community aggregation is fundamentally different from single-home BESS. The next 15-villa expansion benefited from three critical learnings.
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