Paper Citation Record · LEDGER

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration

As of 22 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2411.15422.

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

pith.paper-citation-record.v1
2411.15422 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:25:21.985857Z

measured 34 of 34 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

34 of 34 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 746f3a51-14e2-4c75-bb0f-654fb7991252 · outbound

This paper cites An overview of genetic algorithms: Part 1, fundamentals.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration An overview of genetic algorithms: Part 1, fundamentals

Reference 1

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Observation fcbdeba2-8031-464d-afca-ae85331fc663 · outbound

This paper cites Dynamic programming.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Dynamic programming

Reference 2

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Observation c0cffb4b-3516-485c-b33d-baa7d4f6dd4d · outbound

This paper cites Deep reinforcement learning-based energy storage arbitrage with accurate lithium-ion battery degradation model.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Deep reinforcement learning-based energy storage arbitrage with accurate lithium-ion battery degradation model

Reference 3

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Observation 9b86b19a-6516-480e-ad1b-8bce7f952157 · outbound

This paper cites Microgrid reliability modeling and battery scheduling using stochastic linear programming.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Microgrid reliability modeling and battery scheduling using stochastic linear programming

Reference 4

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Observation 5168480e-b758-49c7-bc7f-833635275c10 · outbound

This paper cites The challenges of achieving a 100% renewable electricity system in the united states.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration The challenges of achieving a 100% renewable electricity system in the united states

Reference 5

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Observation d19de53c-aa53-41ce-ab7c-6e7bafb6fccd · outbound

This paper cites Data-driven decision making in power systems with probabilistic guarantees: Theory and applications of chance-constrained optimization.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Data-driven decision making in power systems with probabilistic guarantees: Theory and applications of chance-constrained optimization

Reference 6

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Observation f137e941-f94b-425c-a0cb-06ce26665959 · outbound

This paper cites Long short-term memory.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Long short-term memory

Reference 7

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Observation 704f8c54-ad2b-44e1-8fb8-c0db9fde00fe · outbound

This paper cites Deep-learning-and reinforcement-learning-based profitable strategy of a grid-level energy storage system for the smart grid.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Deep-learning-and reinforcement-learning-based profitable strategy of a grid-level energy storage system for the smart grid

Reference 8

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Observation 56cede9c-9e94-47de-8e12-ec2e1c081437 · outbound

This paper cites Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning

Reference 9

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Observation 1f62f285-0104-467b-b1ad-14a156006b45 · outbound

This paper cites Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:25:22.356550Z

Source-reported events for the cited work

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Observation 7398b2d2-028f-4fa9-afbd-9e9c795da8be · outbound

This paper cites Deep-reinforcement-learning-based capacity scheduling for pv-battery storage system.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Deep-reinforcement-learning-based capacity scheduling for pv-battery storage system

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:25:22.341910Z

Source-reported events for the cited work

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Observation 7c14bc0e-e566-4efc-8476-90ee18f15c51 · outbound

This paper cites The economic and reliability impacts of grid-scale storage in a high penetration renewable energy system.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration The economic and reliability impacts of grid-scale storage in a high penetration renewable energy system

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:25:22.326987Z

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Observation 444a4305-d752-4437-a276-c236c0a99a00 · outbound

This paper cites Storage futures study: Grid operational impacts of widespread storage deployment.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Storage futures study: Grid operational impacts of widespread storage deployment

Reference 13

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Observation ebcc11a1-1b1c-449b-8bbe-d9fd3a85697f · outbound

This paper cites Elecsim: Monte-carlo open-source agent-based model to inform policy for long-term electricity planning.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Elecsim: Monte-carlo open-source agent-based model to inform policy for long-term electricity planning

Reference 14

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Observation 645bfd37-4a55-4683-9c9c-ad7a5adfc6dc · outbound

This paper cites Energy storage arbitrage under day-ahead and real-time price uncertainty.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Energy storage arbitrage under day-ahead and real-time price uncertainty

Reference 15

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Observation a4fffdc3-4c71-4c45-a47f-5619b8306abd · outbound

This paper cites Receding horizon control: model predictive control for state models.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Receding horizon control: model predictive control for state models

Reference 16

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Observation 716708ee-3221-4fa7-b429-d61a47d1f009 · outbound

This paper cites Use of battery storage systems for price arbitrage operations in the 15-and 60-min german intraday markets.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Use of battery storage systems for price arbitrage operations in the 15-and 60-min german intraday markets

Reference 17

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This paper cites Human-level control through deep reinforcement learning.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Human-level control through deep reinforcement learning

Reference 18

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This paper cites Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Energy dispatch schedule optimization and cost benefit analysis for grid-connected, photovoltaic-battery storage systems

Reference 19

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Observation 2b3a7a7a-b50b-496d-af2c-c0f89be455b5 · outbound

This paper cites Optimal operation of battery energy storage under uncertainty using data-driven distributionally robust optimization.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Optimal operation of battery energy storage under uncertainty using data-driven distributionally robust optimization

Reference 20

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Observation e143b422-c6cc-4e27-a927-4597d86d1ef3 · outbound

This paper cites Markov decision processes: discrete stochastic dynamic programming.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Markov decision processes: discrete stochastic dynamic programming

Reference 21

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This paper cites Stable-baselines3: Reliable reinforcement learning implementations.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Stable-baselines3: Reliable reinforcement learning implementations

Reference 22

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This paper cites A survey and comparison of leading-edge uncertainty handling methods for power grid modernization.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration A survey and comparison of leading-edge uncertainty handling methods for power grid modernization

Reference 23

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This paper cites Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions

Reference 24

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Observation b79d13bd-2a9b-4618-8181-0ff88992b623 · outbound

This paper cites Exploiting battery storages with reinforcement learning: a review for energy professionals.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Exploiting battery storages with reinforcement learning: a review for energy professionals

Reference 25

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This paper cites Reinforcement learning: An introduction.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Reinforcement learning: An introduction

Reference 26

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This paper cites The economics of planning electricity transmission to accommodate renewables: Using two-stage optimisation to evaluate flexibility and the cost of disregarding uncertainty.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration The economics of planning electricity transmission to accommodate renewables: Using two-stage optimisation to evaluate flexibility and the cost of disregarding uncertainty

Reference 27

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This paper cites The expected revenue of energy storage from energy arbitrage service based on the statistics of realistic market data.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration The expected revenue of energy storage from energy arbitrage service based on the statistics of realistic market data

Reference 28

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Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Stochastic programming models in energy

Reference 29

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Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Energy storage arbitrage in real-time markets via reinforcement learning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:25:22.083286Z

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This paper cites Optimal scheduling of energy storage under forecast uncertainties.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Optimal scheduling of energy storage under forecast uncertainties

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:25:22.068592Z

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Observation a8d11c50-5301-4b97-9f09-ec22069a2531 · outbound

This paper cites Learning from delayed rewards.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Learning from delayed rewards

Reference 32

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Observation 95724147-e398-4c9b-b252-62db271fe24c · outbound

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Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Uncertainty models for stochastic optimization in renewable energy applications

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:25:22.038812Z

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This paper cites Arbitraging variable efficiency energy storage using analytical stochastic dynamic programming.

Learning a local trading strategy: deep reinforcement learning for grid-scale renewable energy integration Arbitraging variable efficiency energy storage using analytical stochastic dynamic programming

Reference 34

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Pith citing papers

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