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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
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.
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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
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.
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3.发明申请公开(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
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.
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4.发明授权公开(公告)号：US11178610B2
公开(公告)日：2021-11-16
申请号：US16392509
申请日：2019-04-23
申请人： Haifeng Li , Xiao Lu , Yingmeng Xiang , Chunlei Xu , Di Shi , Zhe Yu , Shiming Xu , Xueming Li , Jiangpeng Dai , Zhiwei Wang
发明人： Haifeng Li , Xiao Lu , Yingmeng Xiang , Chunlei Xu , Di Shi , Zhe Yu , Shiming Xu , Xueming Li , Jiangpeng Dai , Zhiwei Wang
IPC分类号： G05B13/04 , H04W52/02 , G06F1/3287 , G06F1/3209 , H02J3/00 , H02J3/14
摘要： Systems and methods are disclosed for power management by estimating power contingency of a grid at a cloud control center; performing decentralized real-time measurement and making local decisions at one more computer controlled outlets connected to the grid; and aggregating distributed loads to provide emergency frequency support to the grid.
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公开(公告)号：US11264799B2
公开(公告)日：2022-03-01
申请号：US16392494
申请日：2019-04-23
申请人： Yishen Wang , Haifeng Li , Di Shi , Qibing Zhang , Chunlei Xu , Zhiwei Wang
发明人： Yishen Wang , Haifeng Li , Di Shi , Qibing Zhang , Chunlei Xu , Zhiwei Wang
摘要： Systems and methods manage electrical loads in a grid by applying Robust principal component analysis (R-PCA) to decompose annual load profiles into low-rank components and sparse components; extracting one or more predetermined features; constructing a similarity graph; selecting submodular cluster centers through the constructed similarity graph; determining a cluster assignment based on selected centers; and applying the clustering assignment for load analysis.
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公开(公告)号：US11114893B2
公开(公告)日：2021-09-07
申请号：US16396546
申请日：2019-04-26
申请人： Xiao Lu , Di Shi , Yingmeng Xiang , Haifeng Li , Chunlei Xu , Zhe Yu , Jiangpeng Dai , Shiming Xu , Xueming Li , Haiyun Han , Zhiwei Wang
发明人： Xiao Lu , Di Shi , Yingmeng Xiang , Haifeng Li , Chunlei Xu , Zhe Yu , Jiangpeng Dai , Shiming Xu , Xueming Li , Haiyun Han , Zhiwei Wang
摘要： Systems and methods are disclosed to control the power grid frequency by capturing the frequency change using an extended Kalman filter method with the distributed smart outlet devices at the low-voltage distribution level; and locally control the relay that provides power to the appliance by comparing the captured frequency with the threshold sent from the cloud control center.
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7.发明申请公开(公告)号：US20220115871A1
公开(公告)日：2022-04-14
申请号：US17065627
申请日：2020-10-08
申请人： Zhe Yu , Yishen Wang , Xiao Lu , Chunlei Xu , Di Shi
发明人： Zhe Yu , Yishen Wang , Xiao Lu , Chunlei Xu , Di Shi
IPC分类号： H02J3/24 , H02J13/00 , G06N3/08 , G05B19/042
摘要： A method is disclosed for identification of the mechanism of power system low-frequency oscillations and distinguish natural oscillations and forced oscillations using machine learning or neural network.
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公开(公告)号：US20180156886A1
公开(公告)日：2018-06-07
申请号：US15787365
申请日：2017-10-18
申请人： Xiao Lu , Xinan Wang , Di Shi , Zhiwei Wang , Jianyu Luo , Chunlei Xu
发明人： Xiao Lu , Xinan Wang , Di Shi , Zhiwei Wang , Jianyu Luo , Chunlei Xu
CPC分类号： G01R35/005 , G01R19/2513 , Y02E60/728 , Y04S10/265
摘要： Data quality of Phasor Measurement Unit (PMU) is receiving increasing attention as it has been identified as one of the limiting factors that affect many wide-area measurement system (WAMS) based applications. In general, existing PMU calibration methods include offline testing and model based approaches. However, in practice, the effectiveness of both is limited due to the very strong assumptions employed. This invention presents a novel framework for online error detection and calibration of PMU measurement using density-based spatial clustering of applications with noise (DBSCAN) based on much relaxed assumptions. With a new problem formulation, the proposed data mining based methodology is applicable across a wide spectrum of practical conditions and one side-product of it is more accurate transmission line parameters for the energy management system (EMS) database and protective relay settings. Case studies are presented to demonstrate the effectiveness of the proposed method.
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公开(公告)号：US10551471B2
公开(公告)日：2020-02-04
申请号：US15787365
申请日：2017-10-18
申请人： Xiao Lu , Xinan Wang , Di Shi , Zhiwei Wang , Jianyu Luo , Chunlei Xu
发明人： Xiao Lu , Xinan Wang , Di Shi , Zhiwei Wang , Jianyu Luo , Chunlei Xu
摘要： Data quality of Phasor Measurement Unit (PMU) is receiving increasing attention as it has been identified as one of the limiting factors that affect many wide-area measurement system (WAMS) based applications. In general, existing PMU calibration methods include offline testing and model based approaches. However, in practice, the effectiveness of both is limited due to the very strong assumptions employed. This invention presents a novel framework for online error detection and calibration of PMU measurement using density-based spatial clustering of applications with noise (DBSCAN) based on much relaxed assumptions. With a new problem formulation, the proposed data mining based methodology is applicable across a wide spectrum of practical conditions and one side-product of it is more accurate transmission line parameters for the energy management system (EMS) database and protective relay settings. Case studies are presented to demonstrate the effectiveness of the proposed method.
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