Distributed Reinforcement Learning and Consensus Control of Energy Systems

Jennifer King; Paul Fleming; Emiliano Dall'Anese; Christopher Bay; Peter Graf

Distributed Reinforcement Learning and Consensus Control of Energy Systems

Jennifer King (Inventor), Paul Fleming (Inventor), Emiliano Dall'Anese (Inventor), Christopher Bay (Inventor), Peter Graf (Inventor)

Research output: Patent

Abstract

Disclosed herein are methods, systems, and devices for utilizing distributed reinforcement learning and consensus control to most effectively generate and utilize energy. In some embodiments, individual turbines within a wind farm may communicate to reach a consensus as to the desired yaw angle based on the wind conditions.

Original language	American English
Patent number	12,331,721 B2
Filing date	17/06/25
State	Published - 2025

NREL Publication Number

NREL/PT-5000-95610

Keywords

ADMM
alternating direction method of multipliers
wind measurement estimate
wind turbine

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Cite this

@misc{214eff3ca78a4f15a68c69a7ba473e8d,

title = "Distributed Reinforcement Learning and Consensus Control of Energy Systems",

abstract = "Disclosed herein are methods, systems, and devices for utilizing distributed reinforcement learning and consensus control to most effectively generate and utilize energy. In some embodiments, individual turbines within a wind farm may communicate to reach a consensus as to the desired yaw angle based on the wind conditions.",

keywords = "ADMM, alternating direction method of multipliers, wind measurement estimate, wind turbine",

author = "Jennifer King and Paul Fleming and Emiliano Dall'Anese and Christopher Bay and Peter Graf",

year = "2025",

language = "American English",

publisher = "National Renewable Energy Laboratory (NREL)",

address = "United States",

type = "Patent",

note = "12,331,721 B2",

}

TY - PAT

T1 - Distributed Reinforcement Learning and Consensus Control of Energy Systems

AU - King, Jennifer

AU - Fleming, Paul

AU - Dall'Anese, Emiliano

AU - Bay, Christopher

AU - Graf, Peter

PY - 2025

Y1 - 2025

N2 - Disclosed herein are methods, systems, and devices for utilizing distributed reinforcement learning and consensus control to most effectively generate and utilize energy. In some embodiments, individual turbines within a wind farm may communicate to reach a consensus as to the desired yaw angle based on the wind conditions.

AB - Disclosed herein are methods, systems, and devices for utilizing distributed reinforcement learning and consensus control to most effectively generate and utilize energy. In some embodiments, individual turbines within a wind farm may communicate to reach a consensus as to the desired yaw angle based on the wind conditions.

KW - ADMM

KW - alternating direction method of multipliers

KW - wind measurement estimate

KW - wind turbine

M3 - Patent

M1 - 12,331,721 B2

Y2 - 2025/06/17

PB - National Renewable Energy Laboratory (NREL)

ER -

Distributed Reinforcement Learning and Consensus Control of Energy Systems

Abstract

NREL Publication Number

Keywords

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Cite this