LLM-Based Monitoring Framework for BESS-Integrated Power Distribution Networks
A recent study published on arXiv presents an innovative AI-based framework for overseeing battery energy storage systems (BESS) in power distribution networks. This approach merges a large language model (LLM) with a structured telemetry database, allowing operators to ask questions in plain language. These queries are transformed into validated SQL queries using a set schema and approved KPI views. The system evaluates metrics like bus voltages, state of charge, and active/reactive power against specific engineering constraints. Validation relies on co-simulation data from a BESS-enabled distribution feeder utilizing reactive power control. This solution helps manage the growing complexity of operational telemetry driven by the increased use of BESS for voltage regulation and demand response. You can find the paper under the identifier 2608.15396 on arXiv.
Key facts
- Paper on arXiv: 2608.15396
- Framework connects LLM interface with structured telemetry database
- Natural language queries translated into validated SQL queries
- Evaluates bus voltages, state of charge, active power, reactive power
- Validated using hardware-in-the-loop co-simulation data
- BESS-equipped distribution feeder under reactive power-based voltage control
- Addresses increased telemetry complexity from BESS integration
- BESS used for voltage regulation and demand response
Entities
Institutions
- arXiv