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Model Predictive control Strategy of Multi-Port Interline DC power Flow controller

Energy Engineering 2023年第10期120卷 2251-2272页

作者： He Wang Xiangsheng Xu Guanye Shen Bian Jing Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Marketing Department State Grid Jilin Electric Power Co.Ltd.Changchun130061China

There are issues with flexible DC transmission system such as a lack of control freedom over power *** order to tackle these issues,a DC power flow controller(DCPFC)is incorporated into a multi-terminal,flexible DC power *** recent years,a multi-port DC power flow controller based on a modular multi-level converter has become a focal point of research due to its simple structure and robust *** work proposes a model predictive control(MPC)strategy for multi-port interline DC power flow controllers in order to improve their steady-state dynamic ***,the mathematical model of a multi-terminal DC power grid with a multi-port interline DC power flow controller is developed,and the relationship between each regulated variable and control variable is determined;The power flow controller is then discretized,and the cost function and weight factor are built with numerous control *** module sorting method and nearest level approximation modulation regulate the power flow controller;Lastly,theMATLAB/Simulink simulation platformis used to verify the correctness of the establishedmathematicalmodel and the control performance of the suggestedMPC ***,it is demonstrated that the control strategy possesses the benefits of robust dynamic performance,multiobjective control,and a simple structure.

关键词： DC power flow controller model predictive control modular multi-level converter control strategy dynamic performance

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Dynamic Economic Scheduling with Self-Adaptive Uncertainty in Distribution Network Based on Deep Reinforcement Learning

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Energy Engineering 2024年第6期121卷 1671-1695页

作者： Guanfu Wang Yudie Sun Jinling Li Yu Jiang Chunhui Li Huanan Yu He Wang Shiqiang Li State Grid Liaoning Electric Power Co. Ltd.Liaoyang Power Supply CompanyLiaoyang111000China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin132012China Jilin Northeast Electric Power University Science and Technology Development Co. Ltd.Jilin132012China

Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamicdecisions continuously. This paper proposed a dynamic economic scheduling method for distribution networksbased on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distributionnetwork is established considering the action characteristics of micro-gas turbines, and the dynamic schedulingmodel based on deep reinforcement learning is constructed for the new energy distribution network system with ahigh proportion of new energy, and the Markov decision process of the model is defined. Secondly, Second, for thechanging characteristics of source-load uncertainty, agents are trained interactively with the distributed networkin a data-driven manner. Then, through the proximal policy optimization algorithm, agents adaptively learn thescheduling strategy and realize the dynamic scheduling decision of the new energy distribution network ***, the feasibility and superiority of the proposed method are verified by an improved IEEE 33-node simulationsystem.

关键词： Self-adaptive the uncertainty of sources and load deep reinforcement learning dynamic economic scheduling

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Neural Network Technology Applied in Fault Detection and simulation of power systems 8

Neural Network Technology Applied in Fault Detection and Sim...

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8th International Conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2024

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

ISBN: (纸本)9798331506230

With the escalating demand for power inspection and equipment maintenance, developing effective algorithms for power system fault detection is crucial for ensuring the safety and stability of power systems. This paper leveragesthe Trellis network, enhanced with an attention module, to significantly improve the Trellis network's capability in recognizing power fault images, thus better addressing fault identification tasks within power systems. Through testing on a self-constructed dataset and comparative experiments with models such as DCNN, RCNN, and DenseNet, the proposed attention mechanismenhanced Trellis network algorithm has demonstrated its effectiveness and superiority in fault detection. © 2024 IEEE.

关键词： power distribution faults

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CAEFusion: A New Convolutional Autoencoder-Based Infrared and Visible Light Image Fusion Algorithm

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Computers, Materials & Continua 2024年第8期80卷 2857-2872页

作者： Chun-Ming Wu Mei-Ling Ren Jin Lei Zi-Mu Jiang Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationSchool of Electrical EngineeringNortheast Electric Power UniversityJilin132012China School of Electrical Engineering Northeast Electric Power UniversityJilin132012China School of Electronic Information Engineering Bozhou UniversityBozhou236800China

To address the issues of incomplete information,blurred details,loss of details,and insufficient contrast in infrared and visible image fusion,an image fusion algorithm based on a convolutional autoencoder is *** region attention module is meant to extract the background feature map based on the distinct properties of the background feature map and the detail feature map.A multi-scale convolution attention module is suggested to enhance the communication of feature *** the same time,the feature transformation module is introduced to learn more robust feature representations,aiming to preserve the integrity of image *** study uses three available datasets from TNO,FLIR,and NIR to perform thorough quantitative and qualitative trials with five additional *** methods are assessed based on four indicators:information entropy(EN),standard deviation(SD),spatial frequency(SF),and average gradient(AG).Object detection experiments were done on the M3FD dataset to further verify the algorithm’s performance in comparison with five other *** algorithm’s accuracy was evaluated using the mean average precision at a threshold of 0.5(mAP@0.5)*** experimental findings show that CAEFusion performs well in subjective visual and objective evaluation criteria and has promising potential in downstream object detection tasks.

关键词： Image fusion deep learning auto-encoder(AE) infrared visible light

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Overvoltage Suppression Strategy Based on Active control of Current for Half-Wave Commutated Modular Multilevel Converters 14

Overvoltage Suppression Strategy Based on Active Control of ...

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14th International Conference on power and Energy systems, ICPES 2024

作者： Liu, Bao Xu, Yunfei Zhao, Guoliang Fu, Nan Jia, Chen China Electric Power Research Institute State Key Laboratory of Advanced Power Transmission Technology Beijing China Tsinghua University State Key Laboratory of Control and Simulation of Power System and Generation Equipment Beijing China Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. Shenyang China

ISBN: (纸本)9798350391329

Flexible low-frequency AC transmission technology combines the advantages of 50 Hz AC transmission and DC transmission, and has good application scenarios. High voltage and large capacity AC/AC converters are the core equipment of flexible low-frequency AC transmission systems. The proposal of half-wave commutated modular multilevel converters effectively reduces the number of components and improves system economy. In view of this, this paper proposes an overvoltage suppression strategy for active control of inductor current, which effectively reduces the overvoltage level during commutation. The article first introduces the sparse topology and mathematical model of the half-wave commutated modular multilevel converters. Secondly, the mechanism of overvoltage generation is analyzed. Then, overvoltage suppression strategies are proposed. Finally, a PSCAD simulation model is built to verify the effectiveness and feasibility of the proposed method through simulation. © 2024 IEEE.

关键词： Flexible AC transmission systems

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Partial Solution Operator Discretization-Based Methods for Efficiently Computing Least-Damped Eigenvalues of Large Time Delayed power systems

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CSEE Journal of power and Energy systems 2025年第2期11卷 671-682页

作者： Hua Ye Xiaofan Jia Muyang Liu Yutian Liu Sicong Zhang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of EducationShandong UniversityJinan 250061China School of Electrical Engineering Xinjiang UniversityUrumqi 830046China State Grid Jiangsu Electric Power Research Institute Nanjing 211103China

To investigate impact of time delays on the small signal stability of power systems, the least-damped eigenvalues with the smallest damping ratios have been calculated by eigen-analysis methods based on Solution Operator Discretization (SOD) with Pseudo-Spectral collocation (PS) and Implicit Runge-Kutta (IRK) methods. This paper evolves SOD-PSIIRK into their partial counterparts, i.e., PSOD-PSIIRK, with greatly enhanced efficiency and reliability in analyzing large-scale time delayed power systems. Compared with SOD-PSIIRK, PSOD-PSIIRK are characterized in constructing low order discretization matrices of solution operator as well as efficiently and directly solving the embedded Matrix-Inverse-Vector Products (MIVPs). The dimensions of the discretization matrices of solution operator are largely reduced as only the retarded state variables are discretized, rather than all state variables as in SOD-PSIIRK. Meanwhile, the proposed PSOD-PSIIRK optimize the most computationally expensive operations in SOD-PSIIRK by avoiding the iterative solutions to the two embedded MIVPs. PSOD-PS/IRK directly and efficiently compute the MIVPs via factorizing the Kronecker product-like discretization matrices of the solution operator into Schur complements. The Central China-North China ultra-high-voltage power grid with 80577 state variables serves to validate the proposed PSOD-PSIIRK and shows that compared with SOD-PSIIRK, the computational time consumed by PSOD-PSIIRK is cut down by 49.96 times without loss of any accuracy.

关键词： Eigenvalue analysis low frequency oscillation Schur complement decomposition small signal stability solution operator discretization spectral discretization time delay wide-area measurement system

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Research on Comprehensive Assessment Method of Battery Consistency Based on Scaled Energy Storage power Station 9

Research on Comprehensive Assessment Method of Battery Consi...

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9th Asia Conference on power and Electrical Engineering, ACPEE 2024

作者： Kepaiyitulla, Tursun Li, Ming Zheng, Yunping Zong, Sijia Luo, Xingyan Wang, Shangxing Li, Xiangjun Xinjiang Key Laboratory of Whole Process Simulation for Power System State Grid Xinjiang Electric Power Research Institute Urumqi China State Key Laboratory of Operation Ad Control of Renewable Energy and Storage Systems China Electric Power Research Istitute Beijing100192 China

ISBN: (纸本)9798350309638

In the long-term operation of a megawatt-scale energy storage plant composed of series-parallel connections, the single batteries will have different degrees of inconsistency problems. To solve this problem, this paper proposes a comprehensive assessment method based on the consistency of batteries in scaled energy storage power stations. According to the consistency indexes such as single battery voltage and voltage polarity difference in series connection between modules, the consistency evaluation criterion of battery monomer was established. Based on the historical data of a battery energy storage system, the consistency evaluation criterion of a single battery is used to analyze the consistency of a single battery of an energy storage power station at different charging and discharging stages. The results show that this method can accurately assess cell consistency. It provides data support for the health status assessment of energy storage plants and reduces the systematic operational risk of energy storage plants. © 2024 IEEE.

关键词： Digital storage

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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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Capacity Allocation of Hybrid power system with Hot Dry Rock Geothermal Energy,Thermal Storage,and PV Based on Game Approaches

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Journal of Modern power systems and Clean Energy 2023年第1期11卷 290-301页

作者： Yang Si Laijun Chen Xuelin Zhang Xiaotao Chen Shengwei Mei Qinghai Key Lab of Efficient Utilization of Clean Energy(Tus-Institute for Renewable Energy) University of QinghaiXining 810016China State Key Laboratory of Control and Simulation of Power System and Power Generation Equipment(Electric Machinery Department Tsinghua University)Beijing 100084China Technical Institute of Physics and Chemistry Beijing 100190China IEEE

This study utilizes hot dry rock(HDR)geothermal energy,which is not affected by climate,to address the capacity allocation of photovoltaic(PV)-storage hybrid power systems(HPSs)in frigid plateau *** study replaces the conventional electrochemical energy storage system with a stable HDR plant assisted by a flexible thermal storage(TS)*** HPS consisting of an HDR plant,a TS plant,and a PV plant is *** approaches are introduced to establish the game pattern model of the proposed HPS as the *** annualized income of each player is used as the payoff ***,non-cooperative game and cooperative game approaches for capacity allocation are proposed according to the interests of each player in the proposed ***,the proposed model and approaches are validated by performing calculations for an HPS in the Gonghe Basin,Qinghai,China as a case *** results show that in the proposed non-cooperative game approach,the players focus only on the individual payoff and neglect the overall system *** proposed cooperative game approach for capacity allocation improves the flexibility of the HPS as well as the payoff of each game ***,the HPS can better satisfy the power fluctuation rate requirements of the grid and increase the equivalent firm capacity(EFC)of PV plants,which in turn indirectly guarantees the reliability of grid operation.

关键词： Capacity allocation equivalent firm capacity game theory hot dry rock hybrid power system

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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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