公开(公告)号：US20200327411A1

公开(公告)日：2020-10-15

申请号：US16842500

申请日：2020-04-07

申请人： Di Shi ,  Jiajun Duan ,  Ruisheng Diao ,  Bei Zhang ,  Xiao Lu ,  Haifeng Li ,  Chunlei Xu ,  Zhiwei Wang

发明人： Di Shi ,  Jiajun Duan ,  Ruisheng Diao ,  Bei Zhang ,  Xiao Lu ,  Haifeng Li ,  Chunlei Xu ,  Zhiwei Wang

IPC分类号： G06N3/08 ,  G06N3/04 ,  G06K9/62 ,  H04L12/40

摘要： Systems and methods are disclosed for controlling a power system by formulating a voltage control problem using a deep reinforcement learning (DRL) method with a control objective of training a DRL-agent to regulate the bus voltages of a power grid within a predefined zone before and after a disturbance; performing offline training with historical data to train the DRL agent; performing online retraining of the DRL agent using live PMU data; and providing autonomous control of the power system below a sub-second after training.

公开(公告)号：US11336092B2

公开(公告)日：2022-05-17

申请号：US17092478

申请日：2020-11-09

申请人： Ruisheng Diao ,  Di Shi ,  Bei Zhang ,  Siqi Wang ,  Haifeng Li ,  Chunlei Xu ,  Desong Bian ,  Jiajun Duan ,  Haiwei Wu

发明人： Ruisheng Diao ,  Di Shi ,  Bei Zhang ,  Siqi Wang ,  Haifeng Li ,  Chunlei Xu ,  Desong Bian ,  Jiajun Duan ,  Haiwei Wu

IPC分类号： H02J3/00 ,  G05B13/04 ,  G05B13/02

摘要： Systems and methods are disclosed for control voltage profiles, line flows and transmission losses of a power grid by forming an autonomous multi-objective control model with one or more neural networks as a Deep Reinforcement Learning (DRL) agent; training the DRL agent to provide data-driven, real-time and autonomous grid control strategies; and coordinating and optimizing power controllers to regulate voltage profiles, line flows and transmission losses in the power grid with a Markov decision process (MDP) operating with reinforcement learning to control problems in dynamic and stochastic environments.

公开(公告)号：US20210367424A1

公开(公告)日：2021-11-25

申请号：US17092478

申请日：2020-11-09

申请人： Ruisheng Diao ,  Di Shi ,  Bei Zhang ,  Siqi Wang ,  Haifeng Li ,  Chunlei Xu ,  Desong Bian ,  Jiajun Duan ,  Haiwei Wu

发明人： Ruisheng Diao ,  Di Shi ,  Bei Zhang ,  Siqi Wang ,  Haifeng Li ,  Chunlei Xu ,  Desong Bian ,  Jiajun Duan ,  Haiwei Wu

IPC分类号： H02J3/00 ,  G05B13/02 ,  G05B13/04

摘要： Systems and methods are disclosed for control voltage profiles, line flows and transmission losses of a power grid by forming an autonomous multi-objective control model with one or more neural networks as a Deep Reinforcement Learning (DRL) agent; training the DRL agent to provide data-driven, real-time and autonomous grid control strategies; and coordinating and optimizing power controllers to regulate voltage profiles, line flows and transmission losses in the power grid with a Markov decision process (MDP) operating with reinforcement learning to control problems in dynamic and stochastic environments.

公开(公告)号：US10985572B2

公开(公告)日：2021-04-20

申请号：US16518619

申请日：2019-07-22

申请人： Jiajun Duan ,  Zhehan Yi ,  Xiao Lu ,  Di Shi ,  Zhiwei Wang

发明人： Jiajun Duan ,  Zhehan Yi ,  Xiao Lu ,  Di Shi ,  Zhiwei Wang

IPC分类号： H02J3/38 ,  H02J3/32 ,  G06N3/04 ,  G05B13/04 ,  G05B13/02

摘要： Systems and methods are disclosed to manage a microgrid with a hybrid energy storage system (HESS) includes deriving a dynamic model of a bidirectional-power-converter (BPC)-interfaced HESS; applying a first neural network (NN) to estimate a system dynamic; and applying a second NN to calculate an optimal control input for the HESS through online learning based on the estimated system dynamics.