Turn raw telemetry from your battery assets into predictive intelligence. TESAS AI platform delivers demand forecasting, optimal charge–discharge scheduling, predictive maintenance, and digital twin simulation — reducing operational costs and extending asset life.
LSTM and Transformer-based models trained on your historical load data, weather, occupancy, and tariff schedules — predicting next-24h demand with <5% MAPE, enabling pre-emptive battery dispatch decisions.
Anomaly detection on cell voltage, temperature, and impedance data using isolation forests and autoencoders — flags early-stage degradation, connector corrosion, and cooling failures 2–6 weeks before breakdown.
Mixed-integer linear programming (MILP) + reinforcement learning combined optimiser that balances ToD tariff arbitrage, demand shaving, frequency regulation revenue, and SoH preservation — recalculated every 15 minutes.
Physics-informed digital twin of your entire BESS system — electrochemical cell model, thermal model, and grid interface model. Run "what-if" scenarios: How does adding 500 kWh change 5-year NPV? What's battery life if ambient temp rises 5°C?
Route-aware charge planning for electric fleets — predict departure SoC requirements per vehicle, schedule overnight charging to minimise tariff cost, and send real-time alerts for unexpected energy drain or range anxiety events.
AI dispatch controller for co-located solar/wind + BESS — maximises capacity utilisation factor (CUF), responds to grid operator dispatch instructions in <200ms, and reduces curtailment to near zero.
Real-time MQTT / Modbus / OPC-UA data pipelines from BMS, EMS, and SCADA — ingested to time-series database (InfluxDB / TimescaleDB) at 1-second granularity.
Python-based ML stack — PyTorch, Scikit-learn, and custom MILP solvers (PuLP / Gurobi). Models retrain weekly on new data; A/B tested against baseline before production rollout.
Hybrid deployment — latency-critical control on edge (Jetson / Raspberry Pi CM4); heavy ML inference on AWS / Azure. Works in sites with intermittent connectivity via local caching.
Grafana-based live dashboards for operations teams. WhatsApp / SMS / email alerts for anomalies. Role-based access for O&M, management, and asset owners.
Pre-built connectors for EMS vendors (ABB, Schneider, Siemens), DISCOM SCADA, ERP systems (SAP), and fleet TMS platforms. REST API for custom integrations.
End-to-end TLS encryption, certificate-based device auth, role-based access control (RBAC), and VAPT-audited cloud infrastructure. Data residency in Indian AWS regions.
We review your existing data infrastructure and identify the highest-value AI use case for your BESS or EV assets — no commitment required.