TwinGridShield: Consequence-Aware Runtime Authorization for LLM Grid-Agent Actions
Large language model (LLM)-assisted energy-management tools can translate natural-language context into structured grid commands, but syntactic validity does not imply physical admissibility. This paper presents TwinGridShield, a model-independent runtime authorization layer that evaluates each proposed action in a deterministic network twin before release. The prototype checks connectivity, branch-flow, generator, and load-shedding invariants and records each decision in a hash-chained log. A controlled IEEE 14-bus study evaluates single-step switching, redispatch, and load-shedding actions using DC power flow and experimentally assigned branch ratings. In the matched-model experiment, a...
| Authors | Md Fazley Rafy |
|---|---|
| Primary category | cs.AI |
| Published | 15 August 2026 |
| Last updated at source | 15 August 2026 |
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