Paper Citation Record · LEDGER

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps

As of 13 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2607.28822.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.28822 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T00:21:40.202420Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

verified exact2
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 190e7379-c687-4eb6-954d-f41336d199ae · outbound

This paper cites Datacenters and energy report,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Datacenters and energy report,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:38.363004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d4b7be8-ee9d-4553-a5e0-d4f33bd32765 · outbound

This paper cites [Online].

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps [Online]

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:38.441833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c7d1653-d6e1-4dbc-b7ab-474ba18729d3 · outbound

This paper cites The asian super grid in northeast asia and china’s belt and road initiative,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps The asian super grid in northeast asia and china’s belt and road initiative,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:38.541615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b0ea580-28e0-4ba2-bbf1-0cdd6ab4e4ad · outbound

This paper cites FERC technical conference regarding the challenge of resource ade- quacy in RTO and ISO regions,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps FERC technical conference regarding the challenge of resource ade- quacy in RTO and ISO regions,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:38.664392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98abbb64-c73e-43fd-ae58-c2eee39bff8d · outbound

This paper cites National Association of Manufacturers.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps National Association of Manufacturers

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:38.754238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bca6d489-0a23-44b7-90c4-1b4cc553ddba · outbound

This paper cites Poweragent: A road map toward agentic intel- ligence in power systems: Foundation model, model context protocol, and workflow,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Poweragent: A road map toward agentic intel- ligence in power systems: Foundation model, model context protocol, and workflow,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:38.903584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2495fea1-e4ba-4d75-8f17-cefda79849e8 · outbound

This paper cites Grid-Agent: An LLM-Powered Multi-Agent System for Power Grid Control.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Grid-Agent: An LLM-Powered Multi-Agent System for Power Grid Control

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.004717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bec4a8c-eb3b-49b7-926b-6a592e6b53e6 · outbound

This paper cites Gridmind: Llms-powered agents for power system analysis and operations,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Gridmind: Llms-powered agents for power system analysis and operations,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.097614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ddf8562-4888-40e4-bb75-3549689ebf87 · outbound

This paper cites Large Foundation Models for Power Systems.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Large Foundation Models for Power Systems

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.169720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7f9f2bd-b544-4778-b40a-1d02bcccd8d2 · outbound

This paper cites A large language model for advanced power dispatch,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps A large language model for advanced power dispatch,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.234940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23fac319-0a31-4047-8dcf-40fdafed8b86 · outbound

This paper cites Grid copilot: A large language model (llm) based framework for transforming long-term planning analyses,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Grid copilot: A large language model (llm) based framework for transforming long-term planning analyses,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.293760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abc29334-b19a-4ea1-a629-c2790830b9bf · outbound

This paper cites Generative ai for power grid operations,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Generative ai for power grid operations,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.369020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41fc7b8a-13e3-491e-b93d-79161a9d5dad · outbound

This paper cites Ai for the grid and ai on the grid: Implications, challenges and opportunities,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Ai for the grid and ai on the grid: Implications, challenges and opportunities,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.450400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 458f2ed0-b008-4682-ad9d-2d4f50e022e8 · outbound

This paper cites Review of llms applications in electrical power and energy systems,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Review of llms applications in electrical power and energy systems,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.604290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7794dfea-eb6d-4e0f-a631-d7683154e4eb · outbound

This paper cites A review of large language models for energy systems: Applications, challenges, and future prospects,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps A review of large language models for energy systems: Applications, challenges, and future prospects,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.692450Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8169d8a7-53d6-40ad-900f-2480e451c431 · outbound

This paper cites Agentic artificial intelligence for smart grids: A comprehensive review of autonomous, safe, and explainable control frameworks,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Agentic artificial intelligence for smart grids: A comprehensive review of autonomous, safe, and explainable control frameworks,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.777408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d44d0e21-6337-4001-adb5-1476b617e8f7 · outbound

This paper cites IEEE 118-bus three-area test system,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps IEEE 118-bus three-area test system,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.837068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b862b277-8847-4706-a95b-f918f99c8738 · outbound

This paper cites Real-time optimal power flow with linguistic stipulations: Integrating gpt-agent and deep reinforcement learning,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Real-time optimal power flow with linguistic stipulations: Integrating gpt-agent and deep reinforcement learning,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:39.982443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9107e27d-eb76-4d9d-8a2d-03a2a6f0a769 · outbound

This paper cites Exago v2,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Exago v2,

Reference 19

Resolution: verified exact; doi, observed 2026-08-03T00:23:23.742387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 60e8720c-cb5f-4fbd-bb26-2c34d07c7595 · outbound

This paper cites A real-time operations manual for the ieee 118 bus transmission model,.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps A real-time operations manual for the ieee 118 bus transmission model,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T00:21:40.202420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5e544df-8a1f-48ec-9a07-10595045097a · outbound

This paper cites Available: http://dx.doi.org/10.2139/ssrn.6315298.

Agentic Artificial Intelligence for Power Systems: Strategies to Identify and Close Capability Gaps Available: http://dx.doi.org/10.2139/ssrn.6315298

Reference 2026

Resolution: verified exact; doi, observed 2026-08-03T00:23:23.919463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Pith citing papers

No inbound Pith citation observations are available.