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2021 IEEE Sustainable Power and Energy Conference, iSPEC 2021

作者： Li, Zhendong Liu, Yutian An, Jun Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control Renewable Energy Technology Ministry of Education Jilin China

ISBN: (纸本)9781665414395

The deep learning algorithm represented by CNN has achieved remarkable results in complex feature extraction, classification and regression. Since the CNN adopts an end-to-end training process, the carrier of acquisition knowledge is a high-dimensional non-linear function, which is hard to understand by humans. Therefore, it is difficult to be widely used in online decision-making engineering scenarios such as the fast assessment of power system transient voltage stability. In this paper, the key input elements extracted by CNN are identified by Grad-CAM, and the key features captured by CNN in the assessment process are enhanced based on AM, so as to finally obtain the visual expression of key areas and variables of the original input data. Besides, a sample construction method based on single line diagram is proposed to improve the visualization effect of Grad-CAM and AM. Simulation results and analyses of IEEE 39bus test system demonstrates the effectiveness of the proposed method. © 2021 IEEE.

关键词： Visualization

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PATH OPTIMIZATION FOR DYNAMIC OBSTACLE AVOIDANCE OF PIONEER ROBOT BASED ON DDPG SMART AGENT

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UPB Scientific Bulletin, Series D: Mechanical Engineering 2023年第2期85卷 29-42页

作者： Zheng, Qingchun Peng, Zhi Zhu, Peihao Zhao, Yangyang Ma, Wenpeng Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin University of Technology Tianjin300384 China China School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

To improve the path efficiency for dynamic obstacle avoidance algorithms of Pioneer robots, this paper proposes an approach to create deep deterministic policy gradient (DDPG) smart agents with recurrent neural networks (RNN) to optimize the path strategy. This approach is realized by training RNN with the backpropagation (BP) algorithm to train the agent. First, the SolidWorks model and obstacle avoidance model of the Pioneer robot is established. The LIDAR sensor is used to obtain environmental information. Further, deep reinforcement learning obstacle avoidance algorithm based on RNN is presented. The dynamic obstacle avoidance path of the Pioneer robot is further simulated in two different virtual robot experiment platform (V-REP) scenarios. The simulation results show that the proposed algorithm shortens the training time by 26.3% compared with the DDPG algorithm. Our proposed scheme can improve the path efficiency for dynamic obstacle avoidance of the Pioneer robot. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Reinforcement learning

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Longitudinal Comparison Protection Method for AC/DC Hybrid Distribution Network Based on Waveform Similarity

Longitudinal Comparison Protection Method for AC/DC Hybrid D...

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International Conference on Power system Technology (POWERCON)

作者： Zhengfei Lu Wei Cong Anlong Zhang Yingqi Huang Yu Zhou Zeqian Wang Shenzhen Power Supply Company China Southern Power Grid Shenzhen China Key Laboratory of Power System Intelligent Dispatch and Control(Shandong University) Jinan China

With the maturity of DC transmission and distribution technology, the future distribution network will gradually develop in the direction of AC/DC hybrid distribution network (AC/DC-HDN). The unique fault coupling characteristics of AC/DC-HDN challenge the adaptability of protection methods. Based on the analysis of the fault coupling characteristics of AC/DC-HDN, this paper proposes a longitudinal comparison protection method for AC/DC-HDN based on waveform similarity. The method chiefly employs electrical quantity of the measurement point to calculate reference voltage of the corresponding reference point. Determine whether the fault location is located between measurement point and reference point or outside by determining whether the wave-form of the measured voltage is similar to that of the reference voltage or not. The longitudinal protection makes a decision on whether the fault occurs internal or external by comparing the results. Finally, the correctness of this protection method was verified by setting different location faults in PSCAD. The method can accurately determine whether the fault occurs internal or external, has a certain resistance to transition resistance, is not affected by unmeasurable load branches, and has good coping ability for calculation errors caused by noise interference.

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The Optimization Method for key control Parameters of Wind Turbines to Suppress Transient Overvoltage in Wind-Fire Bundling AC/DC Power Delivery system

The Optimization Method for Key Control Parameters of Wind T...

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intelligent Power and systems (ICIPS), International Conference on

作者： Zhuohang Liang Wuneng Ling Chengxiang Li Zhencheng Liang Li Xiong Yangdou Liang Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Electric Power Research Institute China Southern Power Grid Guangzhou China Guangxi Power Grid Dispatch and Control Center Nanning China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

This paper analyzes the causes of overvoltage in the sending-end grid due to phase-change failures in the receiving-end grid, based on the operational principles and control methods of conventional high-voltage DC transmission. It systematically examines the operational characteristics of the sending-end grid voltage during transient processes. Considering the control strategy and output power expression of direct-drive wind turbines connected to the grid, and in accordance with current control requirements for voltage transients in wind turbine units, the study identifies parameter values affecting the control performance of voltage transients. It proposes a key control parameter optimization model aimed at minimizing fluctuations in the terminal voltage of wind turbines during voltage faults, integrating a simulated annealing optimization algorithm. Detailed implementation steps for optimizing key parameters are provided. Finally, the effectiveness of the proposed method in suppressing overvoltages at the terminal of wind turbines is validated using a model built on an electromechanical transient simulation platform.

关键词： Optimization models Process control Switches Simulated annealing Power system stability control systems Wind turbines Voltage control Transient analysis Power generation

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Human Reliability Analysis of Professional Theater Based on CREAM

Human Reliability Analysis of Professional Theater Based on ...

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Culture-Oriented Science and Technology (CoST), International Conference on

作者： Huiqin Wang Huiqi Wang Hui Ren Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

In the context of human/equipment interaction processes, human error has become a significant factor influencing performance risk in professional theaters. To address this issue, the Cognitive Reliability and Error Analysis Method (CREAM) is integrated with fuzzy inference to assess the human reliability of theater staff and predict the probability of human error (HEP). Additionally, Grey Relational Analysis (GRA) is introduced to determine the weights of Common Performance Conditions (CPCs) within CREAM. Through this methodological framework, human reliability analysis of theater operators is conducted, enabling the prediction of human error rates across various scenarios. Subsequently, corresponding measures are provided, culminating in an effective solution to enhance performance safety within theatrical environments.

关键词： Fuzzy logic Costs Error analysis Error probability Measurement uncertainty Safety management Lighting

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Application of deep reinforcement learning in power system scheduling strategy simulation 4

Application of deep reinforcement learning in power system s...

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4th International Conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Hu, Binjiang Huang, Libin Hu, Yufeng Zhang, Jie Guo, Haiping Lu, Yuanhong Hong, Zeqi Zhang, Jingyue Luo, Hui Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc Guangzhou China National Energy Power Grid Technology R&d Centre Guangzhou China Electric Power Research Institute China Southern Power Grid Csg Key Laboratory for Power System Simulation Guangzhou China

ISBN: (纸本)9798331518066

With the increasing scale and complexity of power system, the current scheduling strategy methods often have the problems of limited adaptability and unsatisfactory results. Therefore, a power system scheduling method using DQN (Deep Q Network) is introduced in this study. This method uses neural network model to learn and optimize scheduling strategy, and has strong adaptability and enhanced global optimization ability. Comparative evaluations with genetic algorithms and particle swarm algorithms on IEEE-118 and SG-126 datasets show that the proposed method has significant advantages in terms of cumulative reward and stable runtime. © 2024 IEEE.

关键词： Deep reinforcement learning

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The Development of Simulation Mirror system and its Application in HVDC 6

The Development of Simulation Mirror System and its Applicat...

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6th International Conference on HVDC, HVDC 2024

作者： Ou, Kaijian Wu, Wencong Cai, Haiqing State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid National Energy Power Grid Technology R&d Centre. Guangzhou China Guangdong Prov. Key Laboratory of Intelligent Operation and Control for New Energy Power System. Guangzhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350387759

The testing of HVDC new control function and training of HVDC operation personnel require the integration of power system simulation and dispatching automation. This paper presents and builds AC&DC power system simulation mirror system, which is the closed-loop of real-time digital simulation and dispatching automation. Moreover, the applications of simulation mirror system on HVDC new control function testing and HVDC simulation training cabinet are also introduced in this paper. © 2024 IEEE.

关键词： automatic generation control (A GC) automatic HVDC control (ADC) dispatching automation high voltage direct curren t(HVD C) real-time digital simulator(RTDS)

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Preventive control Method of Improving Transient Voltage Stability for Power system Based on the Attention of CNN

Preventive Control Method of Improving Transient Voltage Sta...

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Sustainable Power and Energy Conference (iSPEC)

作者： Zhendong Li Jiongcheng Yan Yutian Liu Li Li Hanbing Qu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Jinan Power Supply Company Jinan China

The widespread integration of renewable generation and the changes in load structure bring significant challenges to the transient voltage stability of large-scale power systems. In order to achieve fast decision of preventive control for improving transient voltage stability, this paper proposes a preventive control method based on the attention of Convolutional Neural Network (CNN). An optimization decision model is established, which not only considers multiple traditional constraints but also introduces the model attention indicator based on Gradient-weighted Class Activation Mapping (Grad-CAM), enabling a more targeted improvement of transient voltage stability. The proposed indicator is capable of extracting the knowledge learned by CNN-based transient voltage assessment model, and utilizing it to guide the optimization decision-making of preventive control. Simulation results of provincial grid of eastern China demonstrate that the optimized control scheme can effectively enhance the transient voltage stability of power systems.

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Impact assessment for large-scale off-grid of renewable energy on weakly interconnected systems

Impact assessment for large-scale off-grid of renewable ener...

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China International Electrical and Energy Conference (CIEEC)

作者： Li Li Changlong Qin Xin Dong Rongfei Qiao Jialun Yang State Grid Jinan Power Supply Company Jinan China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

Under the background of increasingly serious off-grid problems of renewable energy, this paper analyzes the impact of large-scale off-grid of renewable energy and voltage stability in the weakly interconnected system. First, an improved index is proposed based on Simpson formula for assessing transient voltage stability and achieving early warning of instability risk. Then, based on the simulation of a real-life UHV (Ultra-high voltage) weakly interconnected system, two typical cascading failure scenarios are reasonably anticipated. These cascading failures contain a series of renewable energy off-grid and blocking of DC transmission caused by different initial failures, whose voltage stability is evaluated by the proposed index. Besides, the nature of cascading failure evolution is analyzed. Finally, accuracy and efficient of the proposed index are verified.

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Design and Implementation of Power system Simulation Platform Based on Cloud Computing 4

Design and Implementation of Power System Simulation Platfor...

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4th International Conference on Energy, Power and Electrical Engineering, EPEE 2024

作者： Lu, Yuanhong Guo, Haiping Zhao, Yanjun Huang, Libin Hu, Binjiang Luo, Hui Zhang, Jingyue National Energy Power Grid Technology R&d Centre Guangzhou China State Key Laboratory of Hvdc Electric Power Research Institute China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798331518066

Power system simulation involves simulating the operating states and dynamic processes of power systems using mathematical models and computer technology to analyze and predict system behavior. Traditional simulation methods struggle to meet the needs of large-scale, complex power grids due to significant demands for computational resources. Cloud computing, with its high scalability, resource pooling, and on-demand services, is ideally suited for the extensive simulation calculations required by modern power systems. Despite its advantages, the application of cloud computing in power system simulation poses challenges related to data security and privacy, particularly in collaborative simulations involving multiple power entities. This paper presents the design and implementation of a cloud computing-based power system simulation platform. The proposed platform leverages the distributed computing capabilities of cloud computing, integrates federated learning to ensure data privacy, and utilizes advanced power system simulation technologies. This approach significantly enhances simulation efficiency and accuracy while providing data security and privacy protection. The platform offers reliable decision support for power system planning, operation, and control. © 2024 IEEE.

关键词： Cloud platforms

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