Power systems with high shares of wind and solar are transitioning toward inverter-dominated operation within grids originally designed for synchronous generation. This shift introduces challenges including low short-circuit ratio (SCR), reduced inertia, voltage instability, and congestion in renewable-rich corridors. Tamil Nadu, with over 25 GW of installed renewable capacity—including more than 11 GW of wind and 10 GW of solar—serves as a large-scale operational testbed, characterised by seasonal wind variability and significant intra-day solar fluctuations, with peak solar generation exceeding 7 GW.

The state’s industrial ecosystem, including textile clusters and global automotive manufacturing, increasingly relies on renewable energy through captive and open access frameworks, driven by decarbonisation requirements such as the EU Carbon Border Adjustment Mechanism (CBAM). At the same time, emerging loads such as electric vehicle (EV) charging infrastructure and large-scale data centres are increasing demand variability and flexibility requirements. System operations are supported by a Renewable Energy Management Centre (REMC) integrating AI-based forecasting, SCADA, and GIS platforms; however, high renewable penetration combined with dynamic load patterns introduces operational and market complexities.

This paper presents a real-time, data-driven assessment of integrating battery energy storage systems (BESS) with solar photovoltaic (PV) to enhance operational flexibility and renewable integration. The analysis captures intra-day variability, ramping behaviour, and deviation patterns under 15-minute scheduling frameworks. The combined impact of time-of-day (ToD) tariffs and deviation settlement mechanisms is evaluated, highlighting strict schedule adherence requirements and increased financial exposure due to renewable variability and forecast uncertainty. These factors lead to suboptimal solar utilisation, higher peak-period grid dependency, and cost volatility.

A representative PV–BESS configuration is modelled using real-time operational profiles. Results show that BESS enables effective intra-day balancing through peak shaving, load shifting, improved self-consumption, and compliance with import/export limits. Energy costs are reduced by 20–30%, deviation penalties by 25–40%, renewable utilisation improves by 15–20%, and peak demand reduces by 20–30%, with ramp rate reductions of up to 30–35%.

From a system perspective, BESS operating in both grid-following and grid-forming modes enhances voltage and frequency stability, provides synthetic inertia, and supports operation under low-SCR conditions. The approach mitigates reverse power flow, reduces voltage excursions, and facilitates reliable integration of distributed solar.

The paper proposes a scalable framework combining storage integration, advanced forecasting, and market-based flexibility mechanisms to support secure and efficient operation of renewable-rich, inverter-dominated power systems.