Report

Extending Life of Grid Scale BESS

In-depth analysis and proven strategies for maximising the operational lifespan of utility-scale Battery Energy Storage Systems.

India's First Grid-Scale BESS: A Real-World Test of Software-Defined Energy Management

This report examines the 10 MW / 10 MWh Battery Energy Storage System (BESS) installed at a 66/11-kV substation in Rohini, New Delhi — India's first grid-scale battery installation. Commissioned in April 2019 for Tata Power Delhi Distribution Limited, the system uses NMC lithium-ion batteries and serves three critical grid functions: Deviation Settlement Mechanism (DSM) balancing, frequency regulation, and reactive power support.

Despite a full battery replacement by 2022, the installation kept experiencing accelerated capacity fade under its existing controls. In the second quarter of 2024, Ingro Energy deployed advanced software-defined controls onto the ageing system — creating a rare natural experiment: can intelligent energy management reverse a degradation trend that a hardware replacement could not?

The "Double Whammy" of Battery Degradation

Utility-scale batteries suffer a self-reinforcing degradation spiral. As State of Health (SoH) declines, the system must cycle more frequently to deliver the same grid services — and that extra cycling accelerates capacity fade even further. Left unchecked, each percentage point of lost capacity compounds the next, driving the system toward end-of-life well ahead of schedule. Delhi's 40°C-plus summers and daily DSM cycling made the Rohini system especially vulnerable.

The Intervention: Three Software Innovations

Ingro Energy replaced conventional sequential control with a cloud-based, AI-driven platform built on three pillars:

  • Asynchronous Energy Management System (EMS) — simultaneous evaluation of multiple grid signals, with AI arbitration that weighs real-time module-level state of charge, temperature, impedance, cycling history, and the degradation cost of each dispatch decision.
  • Cloud-based intelligence — continuous processing of more than 1,700 battery modules and thousands of parameters per second across 124 independent power-conversion units, with machine-learning models that improve over time and remote updates that need no site visits.
  • Predictive battery management — module-level SoH forecasting, real-time State of Performance assessment, and early anomaly detection for predictive maintenance.

Measured Results

Before the intervention, the Rohini system was degrading at roughly 5 percentage points of SoH per year — well above the industry-standard 2–4% range, and accelerating. Once Ingro's controls calibrated to the system, the measured degradation rate fell to under 3 percentage points per year. That is a ~41% reduction in degradation velocity relative to the projected baseline trajectory.

Translated into operational life, the improvement extends the battery's usable lifespan to an 80% SoH threshold by approximately 70% — from around four years of remaining life to nearly seven, on the same hardware.

The Financial Case for Early Deployment

Slower degradation directly defers the single largest lifecycle cost of a BESS: battery replacement. A counterfactual analysis in the full report models what would have happened had Ingro's EMS been deployed at commissioning in 2019 rather than mid-life — preserving several additional percentage points of capacity and roughly doubling the years to end-of-life. For a system of this scale, avoiding a mid-life replacement corresponds to an estimated ~31% reduction in lifecycle CAPEX.

The core finding is simple: degradation is software-controllable. Intelligent cycling, thermal management, and cell balancing outperformed a full hardware replacement — at a fraction of the cost. The full report details the empirical SoH dataset (July 2022–July 2025), the counterfactual model, and the technical methodology behind these results.

Extending Life of Grid Scale BESS | Ingro Energy