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Paper Citation Record · LEDGER

Learning to Optimize Joint Chance-constrained Power Dispatch Problems

As of 23 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2501.12902.

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

pith.paper-citation-record.v1
2501.12902 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:46:17.766383Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

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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

37 of 37 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 505d41b5-9e60-4243-8092-6b6551891d2c · outbound

This paper cites Coordinating distributed en- ergy resources for reliability can significantly reduce future distribution grid upgrades and peak load,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Coordinating distributed en- ergy resources for reliability can significantly reduce future distribution grid upgrades and peak load,

Reference 1

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Observation a9f8e2bc-ab9b-4e73-8242-e0efa50d4bcd · outbound

This paper cites Power systems optimization under uncertainty: A review of methods and applications,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Power systems optimization under uncertainty: A review of methods and applications,

Reference 2

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Observation 8b77506f-d0ee-44fd-b87e-ea84e5456a34 · outbound

This paper cites Data-driven Decision Making with Probabilistic Guarantees (Part 1): A Schematic Overview of Chance-constrained Optimization.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Data-driven Decision Making with Probabilistic Guarantees (Part 1): A Schematic Overview of Chance-constrained Optimization

Reference 3

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Observation ada26530-4c49-4be0-832d-6ab992ab51fe · outbound

This paper cites Joint chance constraints in ac optimal power flow: Improving bounds through learning,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Joint chance constraints in ac optimal power flow: Improving bounds through learning,

Reference 4

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Source-reported events for the cited work

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Observation dea4b9ba-a351-49ad-a8c0-3040e5eceac5 · outbound

This paper cites Data-driven tuning for chance constrained optimization: analysis and extensions,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Data-driven tuning for chance constrained optimization: analysis and extensions,

Reference 5

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Source-reported events for the cited work

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Observation 0d4505f3-1556-4903-98bc-d668009b1046 · outbound

This paper cites A risk-averse day-ahead bidding strategy of transactive energy sharing microgrids with data- driven chance constraints,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems A risk-averse day-ahead bidding strategy of transactive energy sharing microgrids with data- driven chance constraints,

Reference 6

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Source-reported events for the cited work

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Observation 69f37a6e-217c-40d7-9e32-fdf3b07b3af0 · outbound

This paper cites Joint chance-constrained eco- nomic dispatch involving joint optimization of frequency-related inverter control and regulation reserve allocation,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Joint chance-constrained eco- nomic dispatch involving joint optimization of frequency-related inverter control and regulation reserve allocation,

Reference 7

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Source-reported events for the cited work

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Observation 2cc3e244-c2a0-4c70-bc73-3626231305e9 · outbound

This paper cites Stochastic- distributionally robust frequency-constrained optimal planning for an isolated microgrid,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Stochastic- distributionally robust frequency-constrained optimal planning for an isolated microgrid,

Reference 8

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Observation ae72af22-5770-476d-807f-8b37bf5c5c59 · outbound

This paper cites Efficient scenario generation for chance-constrained economic dispatch considering ambient wind condi- tions,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Efficient scenario generation for chance-constrained economic dispatch considering ambient wind condi- tions,

Reference 9

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Observation cee65f7a-2a87-4b48-baac-775739324b22 · outbound

This paper cites Addressing wind power forecast errors in day-ahead pricing with energy storage systems: A distributionally robust joint chance-constrained approach,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Addressing wind power forecast errors in day-ahead pricing with energy storage systems: A distributionally robust joint chance-constrained approach,

Reference 10

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Observation c160d109-bec8-4f55-8f6d-704de8186ccc · outbound

This paper cites Data- driven joint distributionally robust chance-constrained operation for multiple integrated electricity and heating systems,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Data- driven joint distributionally robust chance-constrained operation for multiple integrated electricity and heating systems,

Reference 11

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Observation 56e61225-5ab0-4509-bf70-ae0b5b4d85fa · outbound

This paper cites The scenario approach to robust control design,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems The scenario approach to robust control design,

Reference 12

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Observation 44ddc82a-efd6-42d1-ad85-c43aff0346ed · outbound

This paper cites Dc optimal power flow with joint chance constraints,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Dc optimal power flow with joint chance constraints,

Reference 13

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Source-reported events for the cited work

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Observation cf4ad7f9-38ea-413f-9b63-0af96775984f · outbound

This paper cites Security Constrained Optimal Power Flow with Distributionally Robust Chance Constraints.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Security Constrained Optimal Power Flow with Distributionally Robust Chance Constraints

Reference 14

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Observation b0a0ccac-9a13-464b-9731-e89db426974b · outbound

This paper cites Data-driven tuning for chance-constrained optimization: Two steps towards probabilistic performance guarantees,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Data-driven tuning for chance-constrained optimization: Two steps towards probabilistic performance guarantees,

Reference 15

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Source-reported events for the cited work

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Observation c0c02fa6-10c9-4984-8f73-40cd65a6270e · outbound

This paper cites Distributionally robust optimal scheduling with heterogeneous uncertainty information: A framework for hydrogen systems,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Distributionally robust optimal scheduling with heterogeneous uncertainty information: A framework for hydrogen systems,

Reference 16

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Observation 9863a82e-d3e5-4959-b909-50caf1d5fa14 · outbound

This paper cites Low-carbon economic dispatch con- sidering wind curtailment: A distributionally robust chance-constrained approach,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Low-carbon economic dispatch con- sidering wind curtailment: A distributionally robust chance-constrained approach,

Reference 17

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Observation b0bb56a2-2075-4df6-8b12-9308002b9332 · outbound

This paper cites Predicting ac optimal power flows: Combining deep learning and lagrangian dual methods,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Predicting ac optimal power flows: Combining deep learning and lagrangian dual methods,

Reference 18

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Observation 72bad09c-5561-45e8-8111-14ae58e2a200 · outbound

This paper cites Deepopf: A deep neural network approach for security-constrained dc optimal power flow,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Deepopf: A deep neural network approach for security-constrained dc optimal power flow,

Reference 19

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Observation 8c10e1e9-efa2-40c5-977c-016ad9fd50ea · outbound

This paper cites Learning-accelerated admm for distributed dc optimal power flow,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Learning-accelerated admm for distributed dc optimal power flow,

Reference 20

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Observation 4ac62c2e-efce-4175-9cf3-34fb8fd542a9 · outbound

This paper cites Learning to optimize distributed optimization: Admm-based dc-opf case study,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Learning to optimize distributed optimization: Admm-based dc-opf case study,

Reference 21

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Observation b1c0de77-cc53-4360-921c-67fc756220ab · outbound

This paper cites Machine Learning Infused Distributed Optimization for Coordinating Virtual Power Plant Assets.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Machine Learning Infused Distributed Optimization for Coordinating Virtual Power Plant Assets

Reference 22

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Observation c8063ffe-3ba5-4706-8fa7-8c9483a6b62d · outbound

This paper cites Energy management of pv-storage systems: Policy approximations using machine learning,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Energy management of pv-storage systems: Policy approximations using machine learning,

Reference 23

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Observation 7e48097a-2dc0-4bd9-acdf-ddd9574526ca · outbound

This paper cites Chance-constrained outage scheduling using a machine learning proxy,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Chance-constrained outage scheduling using a machine learning proxy,

Reference 24

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Observation 965ebaf0-adac-400e-b85c-3a92768d74da · outbound

This paper cites Deep learning based distributionally robust joint chance constrained economic dispatch under wind power uncertainty,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Deep learning based distributionally robust joint chance constrained economic dispatch under wind power uncertainty,

Reference 25

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Observation 940e9af6-03b2-4b6d-b1d7-bb000a802c3f · outbound

This paper cites Joint chance-constrained unit commitment: Statistically feasible robust optimization with learning-to- optimize acceleration,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Joint chance-constrained unit commitment: Statistically feasible robust optimization with learning-to- optimize acceleration,

Reference 26

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Learning to Optimize Joint Chance-constrained Power Dispatch Problems Learning to solve optimization problems with hard linear constraints,

Reference 27

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Source-reported events for the cited work

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Observation eb3ed397-efb4-4d54-b922-d0383187dd22 · outbound

This paper cites Toward Rapid, Optimal, and Feasible Power Dispatch through Generalized Neural Mapping.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Toward Rapid, Optimal, and Feasible Power Dispatch through Generalized Neural Mapping

Reference 28

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Source-reported events for the cited work

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Observation 4cbb2f3b-3f4d-4b22-bcdb-b2d4e1b77e81 · outbound

This paper cites Consensus+ innovations approach for distributed multiagent coordination in a microgrid,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Consensus+ innovations approach for distributed multiagent coordination in a microgrid,

Reference 29

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Learning to Optimize Joint Chance-constrained Power Dispatch Problems Unresolved cited work

Reference 30

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Learning to Optimize Joint Chance-constrained Power Dispatch Problems Deep sets,

Reference 31

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Source-reported events for the cited work

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Observation e2c135e8-c5df-4dd3-a25c-9f41a2362bf8 · outbound

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Learning to Optimize Joint Chance-constrained Power Dispatch Problems Teaching Networks to Solve Optimization Problems

Reference 32

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Source-reported events for the cited work

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Observation 9976ef7d-c552-45be-8992-729b354e4a98 · outbound

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Learning to Optimize Joint Chance-constrained Power Dispatch Problems Fractional order agc for distributed energy resources using robust optimization,

Reference 33

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Source-reported events for the cited work

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Observation e4e76b6e-4f6a-4ed3-8708-8dec74912cb3 · outbound

This paper cites Real-time load data for new york city’s central park,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Real-time load data for new york city’s central park,

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T16:46:17.740400Z digest=sha256:114a100dd63100c1fb2fef0157357b03c1295b02be87e2b41086b7d39110efa3

Observation 300d8afd-7dbf-4aaa-bce0-5ae215d1e1ce · outbound

This paper cites Nrel solar radiation research laboratory (srrl): Baseline measurement system (bms); golden, colorado (data),.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Nrel solar radiation research laboratory (srrl): Baseline measurement system (bms); golden, colorado (data),

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-10T16:46:18.008845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T16:46:17.748842Z digest=sha256:899b5088499c1888be840237e29d46ee228b1e7a6c45a80e7cc72d6ff80d3e29

Observation bd5d90c5-1044-44a7-b047-4a3c6d390e95 · outbound

This paper cites Weather data for new york city’s central park,.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Weather data for new york city’s central park,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:46:17.987893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T16:46:17.755850Z digest=sha256:4c1ca21e5663f08c4a3777fcee445a8d576e6c2f1f8d8d56cf5853d1cb58579c

Observation bf27fc1e-07ac-47e7-a1ed-8d1604e21e62 · outbound

This paper cites Gurobi Optimizer Reference Manual.

Learning to Optimize Joint Chance-constrained Power Dispatch Problems Gurobi Optimizer Reference Manual

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:46:17.966537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T16:46:17.766383Z digest=sha256:e91f0809858acb7e6a7233c679692ebf3ffcf6a21e6e175b1a504017b7e2c8c2

Pith citing papers

No inbound Pith citation observations are available.