An LLM-based multi-module agent uses experience storage, retrieval, generation, and modification to produce adaptive day-ahead Volt/Var schedules for distribution network voltage control.
Large Language Models for Power Scheduling: A User-Centric Approach
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A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.
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Large Language Model as An Operator: An Experience-Driven Solution for Distribution Network Voltage Control
An LLM-based multi-module agent uses experience storage, retrieval, generation, and modification to produce adaptive day-ahead Volt/Var schedules for distribution network voltage control.
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Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges
A literature survey finds foundation-model agents in industry are 75% at prototype stages with gains in human interaction and uncertainty handling but deficits in negotiation, plus limitations like hallucinations and latency.