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Real-time multi-risk assessment of large scale power system with high-penetration renewable energy 3

Real-time multi-risk assessment of large scale power system ...

引用

2024 3rd International Conference on Green Energy and Power Systems, ICGEPS 2024

作者： Zhang, Tingxiang Xu, Ying Yi, Zhongkai Xu, Jianing Cai, Xinlei Wang, Naixiao School of Electrical Engineering and Automation Harbin Institute of Technology Harbin150001 China Electric Power Dispatching and Control Center Guangdong Power Grid Co China Southern Power Grid Company Limited Guangzhou510000 China

To accurately assess the impact of real-time uncertainty of high penetration renewable energy sources on the real-time operation of large-scale power systems, this study proposes an innovative method for real-time multi-risk assessment in power systems. Firstly, by utilizing an improved spectral clustering algorithm and mixture density network to analyze historical operational data, effective clustering of different renewable energy generation curves and accurate fitting of prediction errors were achieved. Next, random sampling was performed from the probability density curves of prediction errors to obtain real-time renewable energy outputs. At the same time, a non-sequential Monte Carlo method was used to incorporate interruptions for each component into the scenario simulation. Subsequently, a state assessment was conducted for each sampled scenario by minimizing load shedding and energy curtailment. On this basis, risk indices that comprehensively consider the real-time flexibility of the system and power supply-demand imbalances were established. Finally, validation in a test system verified the accuracy and speed of the proposed multi-risk assessment method. © Published under licence by IOP Publishing Ltd.

关键词： Renewable energy

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Time-Constrained Cooperative Guidance Based on Deep Neural Network 42

Time-Constrained Cooperative Guidance Based on Deep Neural N...

引用

42nd Chinese control Conference, CCC 2023

作者： Wang, Changhai Yu, Jianglong Dong, Xiwang Li, Qingdong Ren, Zhang Wang, Feifei Hu, Xijing School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Institute of Control and Electronic Technology Beijing100038 China

ISBN: (纸本)9789887581543

Time-constrained cooperative guidance based on deep neural network (DNN) is developed to address the problem of cooperative guidance of multiple missiles against maneuvering targets. Firstly, deep neural network is applied to estimate time-to-go. A simplified dataset is created to improve the estimation effect and the performance of training results is good. Secondly, time-constrained cooperative guidance law is designed. Time-constrained guidance (TCG) law based on variable navigation ratio is proposed and an optimal method of cooperative time is designed. Thirdly, simulation in 3-D space and equivalent experiment in 2-D space are carried out to verify the performance of guidance law. An equivalent experiment platform based on multiple unmanned ground vehicles (Multi-UGVs) is erected and the experiment to achieve cooperative guidance is carried out. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Deep neural networks

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Establishment of Degradation Model and Transfer Model for P-channel Power MOSFETs Under Negative Bias Temperature Stress

Establishment of Degradation Model and Transfer Model for P-...

引用

International Conference on Power Electronics and Motion control (IPEMC)

作者： Cen Chen Haodong Wang Haonan Yin Wei Zheng Guofu Zhai School of Electrical Engineering and Automation Harbin Institute of Technology China Beijing Aerospace Automatic Control Institute China

ISBN: (数字)9798350351330

ISBN: (纸本)9798350351347

Negative Bias Temperature Instability (NBTI) is the main reason for the degradation of gate oxide in P-channel power MOSFETs. Affected by long-term negative bias gate voltage and high temperature, the threshold voltage of power MOSFETs drifts, which in turn affects the performance of the device. Based on the analysis of NBTI failure mechanism, this paper conducted accelerated degradation test on six different types of P-channel power MOSFETs. Secondly, the Iterative Reweighted Least Square (IRLS) method was applied to establish a threshold voltage drift’s degradation model, which can accurately describe actual degradation data. In addition, a transfer model was established using multiple linear regression theory to approximately describe the relationship between the fitting parameters of degradation model and power MOSFETs’ process parameters, providing a new approach for the fast reliability assessment of P-channel power MOSFETs.

关键词： Semiconductor device modeling Degradation Negative bias temperature instability MOSFET Thermal variables control Fitting Life estimation

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PITD3-based Autonomous Evasion Decision-making Method for Aircraft

PITD3-based Autonomous Evasion Decision-making Method for Ai...

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第43届中国控制会议

作者： Chang Liu Liqian Dou Ruilong Zhang Yifan Tang Mengyuan Ren Lun Zhang School of Electrical Engineering and Automation Beijing Aerospace Automatic Control Institute Tianjin Aerospace Institute of Computing Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Outstanding autonomous evasion decision-making capability has an important significance for ensuring flight safety and enhancing the autonomy of the aircraft. In this paper, a prediction information-based TD3(PITD3) evasion decision-making algorithm for aircraft is proposed, which can autonomously evade the interceptors' attack in an antagonistic environment. Firstly,an antagonistic environment is described according to environmental constraints and the dynamics of the aircraft and interceptor. Secondly, the autonomous decision-making process of the aircraft facing the threat target is modelled as a Markov decision process to describe the state information of the aircraft and interceptor. Finally, an autonomous evasion decision-making method based on the twin delayed deep deterministic policy gradient(TD3) is designed to find the optimal strategy, and the effectiveness of the proposed autonomous evasion decision-making method is demonstrated by simulation results and comparative experiments.

关键词： PITD3 Autonomous Evasion Decision-Making Deep Reinforcement Learning Decision Network Aircraft

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Robust Cooperative Guidance Against Maneuvering Target Based on Distributed State Estimation

Robust Cooperative Guidance Against Maneuvering Target Based...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Zheng Yu, Jianglong Dong, Xiwang Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

This paper presents a novel robust cooperative guidance law against high-maneuvering target based on state information obtained from networked distributed estimation. To attack the target accurately, a distributed state estimation algorithm is proposed by two steps: local filter and interaction fusion. During the interaction fusion step, the accurate state information of target can be obtained based on the local neighboring interactions. Then, the guidance law considering maneuvering target acceleration information is designed, which can be used to attack the maneuvering target accurately. Finally, a numerical simulation example for maneuvering target cooperative attack is given to validate the performance of the algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： State estimation

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Spacecraft Integrated Pose Determination with Unknown Noise Covariances

Spacecraft Integrated Pose Determination with Unknown Noise ...

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Chen, Hang Hu, Qinglei Wu, Huai-Ning Duan, Chao Chen, Bin Zhang, Peng School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beihang Hangzhou Innovation Institute Yuhang Hangzhou310023 China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Peng Cheng Laboratory Shenzhen518000 China Beijing Institute of Control Engineering Beijing100094 China

ISBN: (纸本)9789811966125

A novel robust unscented Kalman filter (UKF) is developed for orbiting spacecraft pose determination without knowing prior noise statistical characteristics by using dual quaternion formulation. First, an adjustment coefficient multiplied by a predesigned positive definite matrix is updated iteratively for the process noise covariance adaptation and the moving window of the measurement innovation are adopted for the measurement noise covariance estimation. Then, the adaptation method is incorporated into the dual-quaternion-based UKF procedure where the dual modified Rodrigues parameters (MRPs) are adopted for sigma points description to avoid violating the quaternion normalization constraint. Finally, the effectiveness and practical usefulness of the developed algorithm are verified via numerical simulation examples. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Covariance matrix

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Small-Signal Stability Analysis of Flux-controlled Grid-Forming DFIG Under Symmetrical Fault

Small-Signal Stability Analysis of Flux-Controlled Grid-Form...

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International Conference of electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Li, Weibing Wang, Wenhe Hu, Yufei Li, Junxian Hua, Xiaojun Jiang, Dingguo Huang, Meng Tian, Zhen Laboratory of Hydro-Wind-Solar Multi-Energy Control Coordination Wuhan430014 China School of Electrical Engineering and Automation Wuhan University Wuhan430072 China Institute of Science and Technology China Three Gorges Corporation Beijing100038 China

ISBN: (纸本)9789819620791

Due to the dislocation distribution of wind resources and load centers in China, large-scale wind power stations usually need long-distance transmission to connect with the load center, which leads to the weakening of the power grid strength at the access point of wind power stations and frequent short-circuit faults. In this paper, a small signal state space model of flux-controlled grid-forming DFIG grid-connected system is constructed for the continuous condition of symmetrical fault in weak grid scenario, and the oscillation mode analysis of the system is carried out. Based on the fault ride-through requirements and electromagnetic equations of wind turbines, the calculation method of the balanced operating point of DFIG during symmetrical fault duration is derived. Then, based on the system characteristic root trajectory and the participation factor matrix, the small-disturbance stability of the system under different fault conditions and converter control parameters is analyzed, and the influence of each dynamic link on the small-disturbance stability of the system is explored. Finally, the accuracy of the theoretical analysis results in this paper is verified by simulation analysis and comparison, which provides guidance for parameter optimization of DFIG during fault duration. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Wind turbines

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Low-Frequency Damping Analysis of Flux-controlled Grid-Forming DFIG

Low-Frequency Damping Analysis of Flux-Controlled Grid-Formi...

引用

International Conference of electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Hu, Yufei Li, Weibing Deng, Youhan Jiang, Dingguo Huang, Meng Tian, Zhen Laboratory of Hydro-Wind-Solar Multi-Energy Control Coordination Wuhan430014 China School of Electrical Engineering and Automation Wuhan University Wuhan430072 China Institute of Science and Technology China Three Gorges Corporation Beijing100038 China

ISBN: (纸本)9789819620791

To improve the small-signal stability of system, the damping torque model of flux-controlled grid-forming DFIG is constructed based on the small-signal model. And the low-frequency damping characteristics of system are analyzed by adopting the complex torque coefficient method. Then, analogous to the principle of PSS, a low-frequency oscillation damping method is proposed, which can efficiently optimize the low-frequency damping characteristics of system. Finally, based on the simulation results, the accuracy of theoretical analysis results and the effectiveness of proposed method are verified. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Damping

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Fault Modeling and Diagnosis for Spacecraft Attitude control System Using Deep Learning

Fault Modeling and Diagnosis for Spacecraft Attitude Control...

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Guo, Pengyu Hu, Qinglei Wu, Huai-Ning Duan, Chao Chen, Bin Zhang, Peng School of Automation Science and Electrical Engineering Beihang University Beijing100190 China Beihang Hangzhou Innovation Institute Yuhang Hangzhou310023 China Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100190 China Peng Cheng Laboratory Shenzhen518000 China Beijing Institute of Control Engineering Beijing100094 China

ISBN: (纸本)9789811966125

The health monitoring system is significant for the reliable operation of spacecraft. In this paper, various fault models for controlling torque gyroscopes are established, and the learning network is trained with uniformly sampled data of fault. Then a data-driven fault diagnosis method based on deep learning is proposed. The method fully extracts the features to describe the classification of the multi-modal actuator faults, and trains the fault model with a large amount of spacecraft data under actuator faults. Then the rapid detection and classification of actuator faults are realized by the unknown fault model. Specifically, a spacecraft attitude control model is established to generate the sample data for the problem of insufficient fault data. Besides, the stack encoder is used to automatically reduce the data dimension and extract the main features from each set of data. Further, softmax classifier is introduced for fault model training. Finally, numerical simulations are illustrated to verify the reliability of the fault diagnosis method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Attitude control

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Theoretical Analysis of Value-Iteration-Based Q-Learning with Approximation Errors 12

Theoretical Analysis of Value-Iteration-Based Q-Learning wit...

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12th International Conference on Information Science and technology, ICIST 2022

作者： Liang, Zhantao Ha, Mingming Liu, Derong School of Automation Guangdong University of Technology Guangzhou China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Institute of Control Science and Technology Southern University of Science and Technology Shenzhen China

ISBN: (数字)9781665485821

ISBN: (纸本)9781665485821

In this paper, the value-iteration-based Q-Iearning algorithm with approximation errors is analyzed theoretically. First, based on an upper bound of the approximation errors caused by the Q-function approximator, we get the lower and upper bound functions of the iterative Q-function, which proves that the limit of the approximate Q-function sequence is bounded. Then, we develop a stability condition for the termination of the iterative algorithm, for ensuring that the current control policy derived from the resulting approximate Q-function is stabilizing. Also, we establish an upper bound function of the approximation errors, which is caused by the policy function approximator, to guarantee that the approximate control policy is stabilizing. Finally, the numerical results verifies the theoretical results with a simulation example. © 2022 IEEE.

关键词： Asymptotic stability

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