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Image Processing, Computer Vision and Machine Learning (ICICML), International Conference on

作者： Jiyuan Yang Kun Gao Qiong Wu Zefeng Zhang Baiyang Hu Yuqing He Key Laboratory of Photoelectronic Imaging Technology and System Ministry of Education Beijing Institute of Technology Beijing China China Ordinance Industry Navigation and Control Technology Research Institute Beijing China

ISBN: (数字)9798350355413

ISBN: (纸本)9798350355420

Bi-temporal change detection (CD) constitutes a vital task within the domain of remote sensing (RS). due to pseudochange caused by factors such as seasonal climate variations, temporary objects, and cloud interference. To address the pseudochange issue stemming from cloud interference, we propose a global-local feature interaction anti-cloud interference change detection network (ACCDNet) based on contrastive learning. To mitigate the scarcity of remote sensing datasets with cloud interference, we leverage contrastive learning principles, using remote sensing images of the same scene at the same time with and without cloud interference as positive sample pairs to pre-train anti-cloud interference capability of the feature extractor. The proposed CD network which bases on a CNN-transformer network, utilizes Resnet to extract multi-scale features from the original input images. We introduce transformer modules and attention mechanisms to effectively extract the contextual information within the input images. To address the pseudochange issue caused by cloud interference, we simulate the effect of thin cloud interference using Perlin noise and add it to classical datasets. Experimental results on LEVIR-CD and LEVIR-CD-cloud datasets augmented with cloud interference demonstrate the priority and efficiency of the proposed method.

关键词： Measurement Attention mechanisms Clouds Noise Interference Contrastive learning Feature extraction Transformers Robustness Remote sensing

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Optimization Study on the control Strategy of DC Line Fault Recovery for Yongren-Funing HVDC 6

Optimization Study on the Control Strategy of DC Line Fault ...

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6th IEEE Conference on Energy Internet and Energy system Integration, EI2 2022

作者： Zhu, Yukun Huang, Libin Li, Shuyong Zhu, Yihua Song, Yantao Liu, Ren State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China Electric Power Research Institute China Southern Power Grid CSG Key Laboratory for Power System Simulation Guangzhou China XJ Electric Co Ltd Xuchang China

ISBN: (纸本)9798350347159

The ±500kV Yongren-Funing HVDC transmission project is the first HVDC project whose sending and receiving ends are both located in the same province. When DC line fault happened under the condition of inter-communication fault between the pole control systems of the rectifier and inverter stations, the HVDC system cannot be blocked because of the frequent repeating actions of the DC line fault recovery in the inverter station. In order to solve the problem, an optimal control strategy of direct blocking HVDC system was proposed to solve the above issue. The optimization control strategy was verified by RTDS simulation. The simulation results showed that the proposed optimization control strategy of the DC line fault recovery could solve the above problems effectively. The proposed strategy has already been implemented on site permanently, which has great significance for the HVDC/UHVDC transmission projects in operation currently. © 2022 IEEE.

关键词： HVDC power transmission

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Peak shaving and power allocation strategies for optimizing lifespan and reducing energy loss in BESS

Peak shaving and power allocation strategies for optimizing ...

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4th Energy Conversion and Economics Annual Forum (ECE Forum 2024)

作者： Gan Guo Junhui Li Gang Mu Gangui Yan Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 People's Republic of China

ISBN: (数字)9781837242924

To manage the challenge of optimizing energy efficiency, an optimization strategy for power allocation in battery clusters is proposed to reduce energy loss in Battery Energy Storage systems (BESS). Meanwhile, an improved peak shaving strategy is also proposed, aiming to increase the utilization of energy storage during the peak shaving process and reduce the ineffective utilization hours of energy storage, thereby extending the lifespan of the storage system. Furthermore, based on real-system data, a Simulink/Simscape model is developed to simulate component losses. Under a peak shaving scenario, the effectiveness of the strategy is demonstrated: it reduces the daily operational loss by 3.84% and improves energy round-trip efficiency by 0.4%.

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Optimal Allocation Strategy of Frequency Modulation Power for Multiple Energy Storage systems Considering Dual Constraints of Frequency Modulation Cost and Frequency Modulation Capability

Optimal Allocation Strategy of Frequency Modulation Power fo...

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Power Science and Technology (ICPST), IEEE International Conference on

作者： Yongming Peng Wenbo Si Haiji Zhao Changlin Lv Chengzhe Liu Fei Xu Ling Hao Junhui Li Northeast Branch of State Grid Corporation of China Shenyang China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin China State Key Laboratory of Power System and Power Generation Equipment Control and Simulation (Tsinghua University) Beijing China

Aiming at the power allocation problem of multiple energy storage power stations distributed at different locations in the regional power grid participating in frequency modulation services, a frequency modulation power optimization allocation strategy for multiple energy storage systems considering the dual constraints of frequency modulation cost and frequency modulation capability is proposed. Firstly, a multi-objective optimization allocation model for frequency modulation power is constructed with the minimum frequency modulation cost and minimum deviation of the state of charge (SOC) for energy storage power plants. Secondly, using Pareto based multi-objective genetic algorithm (MOGA) to solve the model, introduce adaptive weight coefficients and fuzzy membership functions for each objective function regarding the frequency regulation demand of the power grid and the deviation of the SOC of energy storage stations, construct a comprehensive satisfaction function to make decisions on the most advantageous points on the Pareto frontier, in order to obtain the optimal output of each energy storage station that can adapt to the frequency regulation requirements of the power grid. Finally, simulation analysis was conducted on the proposed strategy in this article, and the results showed that: The proposed strategy not only enhances the frequency regulation economy of the regional power grid, but also helps to restore the SOC of the energy storage power station.

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Adaptive Artificial Potential Field Ship Motion Planning Based on DDPG

Adaptive Artificial Potential Field Ship Motion Planning Bas...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Chen, Huimin Liu, Chenguang He, Zhibo Zhang, Guoqing Han, Bing State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan430063 China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan430063 China School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan430063 China Navigation College Dalian Maritime University Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China National Engineering Research Center of Ship & Shipping Control System Shanghai200134 China

ISBN: (纸本)9789819639601

The paper presents a ship motion planning method that adjusts the attractive and repulsive gain parameters of the artificial potential field (APF) algorithm using the deep deterministic policy gradient (DDPG) algorithm, to address the challenges of parameter design and limited adaptability of traditional APF algorithms. This approach leverages the speed advantage of the APF planning algorithm and the exploration capability of the DDPG reinforcement learning algorithm. By optimizing the parameters of APF with DDPG, the local optima problem can be alleviated in complex obstacle environments. simulation results demonstrate that the proposed motion planning algorithm can generate reasonable trajectories and exhibit strong adaptability in complex obstacle scenarios. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Motion planning

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Resilience Assessment of Power Transmission systems Under Extreme Ice Disaster 10th

Resilience Assessment of Power Transmission Systems Under Ex...

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10th Frontier Academic Forum of Electrical Engineering, FAFEE 2022

作者： Li, Dexin Wu, Xinyu Gao, Song Zhuang, Guanqun Wang, Changjiang Electric Power Research Institute State Grid Jilin Electric Power Supply Co. Ltd. Changchun130021 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

ISBN: (纸本)9789819934034

The occurrence of ice disasters poses a great threat to the normal transmission system operation. To better complete the toughness evaluation of the system under ice disaster, firstly, an attack model considering the instantaneous wind speed and accumulated ice thickness of the line is established. Secondly, combined with the disaster degree of the line and the initial design data, the fault probability of the line is estimated, and the system load reduction model is used to determine the affected degree of the system. Then, a resilience evaluation index focusing on the degree of system damage under extreme ice disasters is proposed. Taking the IEEE-39 bus system as an example, the feasibility of the proposed index is verified, and two elastic improvement measures are adopted to verify the practicability of the index. The simulation results of an example show that this resilience evaluation index can directly reflect the impact of extreme ice disasters on the resilience of the transmission system and can better see the effect of different resilience improvement methods on the resilience of the transmission system. © Beijing Paike Culture Commu. Co., Ltd. 2023.

关键词： Disasters

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Research on Partition Method of Distributed Photovoltaic Cluster Based on Modularity Index and Absorption Ability 2

Research on Partition Method of Distributed Photovoltaic Clu...

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2nd International Conference on Smart Grids and Energy systems, SGES 2023

作者： Meng, Tao Lv, Xiangyu Li, Chenggang Li, Dexin Zhang, Yifu Meng, Xiangdong State Grid Jilin Electric Power Co. Ltd. Electric Power Research Institute China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education School of Electrical Engineering Changchun Jilin China

ISBN: (纸本)9798350371659

To achieve large-scale renewable energy, grid friendly coordination and the need to maximize grid-connection and consumption functions, the clustering method has become a forward-looking solution for distribution network planning, construction and dispatching control. In this paper, the modularity index and active power balance index based on electrical distance are taken as the comprehensive classification index. Then genetic algorithm is introduced to divide the distributed PV cluster in the distribution network. Finally, a 10kV distribution system is taken as an example, and the distributed photovoltaic cluster planning is simulated and analyzed, which proves that the distributed photovoltaic cluster division method is effective. © 2023 IEEE.

关键词： Genetic algorithms

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Unbalanced Strategy of Vehicle-to-Grid on Evolution Game

Unbalanced Strategy of Vehicle-to-Grid on Evolution Game

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Annual Conference of Industrial Electronics Society

作者： Xinling Li Yuzhi Zhou Libin Tian Hongwei Li Wei Zhang Hongpeng Liu Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

The utilization of vehicle-to-grid (V2G) technology is an environmentally friendly approach to achieve the transition towards low-carbon energy systems. However, it is still unknown what impact the V2G policy will have on the charging market of electric vehicles (EVs) and whether it is competitive with other electricity sales strategies. Aiming at the above problems, the electricity price model of EVs in electricity market including V2G strategy is established. Firstly, a 2–3 unbalanced strategy evolutionary game (2–3 USEG) model integrating vehicle-network interaction is proposed. The asymptotically stable equilibrium points of asymmetric evolutionary games for two groups with unbalanced game strategies are obtained. Multiple game strategies between the power grid enterprises (PGE) and New power supply entities (NPSE) are studied Besides, the corresponding asymptotic stability conditions are given by the Lyapunov stability criterion. Finally, the simulation proves that the ample implemented V2G strategy not only has strong competitiveness, but also enables the charging electricity price market of electric vehicles to have the “virtual high” electricity price adjustment ability.

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Synergistic PM_(2.5)and O_(3)control to address the emerging global PM_(2.5)-O_(3)compound pollution challenges

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Eco-Environment & Health 2024年第3期3卷 325-337页

作者： Chao He Jianhua Liu Yiqi Zhou Jingwei Zhou Lu Zhang Yifei Wang Lu Liu Sha Peng College of Resources and Environment Yangtze UniversityWuhan 430100China Hubei Key Laboratory of Petroleum Geochemistry and Environment Yangtze UniversityWuhan 430100China School of Geography and Ocean Science Nanjing UniversityNanjing 210023China Hydrology and Environmental Hydraulics Group Wageningen University and ResearchWageningen 6700 HBthe Netherlands State Key Laboratory of Freshwater Ecology and Biotechnology Institute of HydrobiologyChinese Academy of SciencesWuhan 430072China State Key Joint Laboratory for Environmental Simulation and Pollution Control School of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Pollution Control and Resource Reuse School of EnvironmentNanjing UniversityNanjing 210023China Collaborative Innovation Center for Emissions Trading System Co-constructed by the Province and Ministry Hubei University of EconomicsWuhan 430205China

In recent years,the issue of PM_(2.5)-O_(3)compound pollution has become a significant global environmental *** study examines the spatial and temporal patterns of global PM_(2.5)-O_(3)compound pollution and exposure risks,firstly at the global and urban scale,using spatial statistical regression,exposure risk assessment,and trend analyses based on the datasets of daily PM_(2.5)and surface O_(3)concentrations monitored in 120 cities around the world from 2019 to ***,on the basis of the common emission sources,spatial heterogeneity,interacting chemical mechanisms,and synergistic exposure risk levels between PM_(2.5)and O_(3)pollution,we proposed a synergistic PM_(2.5)-O_(3)control framework for the joint control of PM_(2.5)and *** results indicated that:(1)Nearly 50%of cities worldwide were affected by PM_(2.5)-O_(3)compound pollution,with China,South Korea,Japan,and India being the global hotspots for PM2.5-O3 compound pollution;(2)Cities with PM_(2.5)-O_(3)compound pollution have exposure risk levels dominated by ST t ST(Stabilization)and ST t HR(High Risk).Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries,with unequal exposure characteristics;(3)The selected cities showed significant positive spatial correlations between PM_(2.5)and O_(3)concentrations,which were consistent with the spatial distribution of the precursors NOx and VOCs;(4)During the study period,52.5%of cities worldwide achieved synergistic reductions in annual average PM_(2.5)and O_(3)*** average PM_(2.5)concentration in these cities decreased by 13.97%,while the average O_(3)concentration decreased by 19.18%.This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low–carbon transition.

关键词： PM_(2.5)-O_(3)compound pollution Population exposure risk Spatial correlation Synergistic treatment potential

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Uav anti-collision visual detection algorithm

Uav anti-collision visual detection algorithm

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Computer Vision, Image and Deep Learning (CVIDL), International Conference on

作者： Jun Yu Han Zhe Li Sheng Hou Li Bo Shen Zhao Air Traffic Control and Navigation School Air Force Engineering University Xi'an Key Laboratory of Meta-Synthesis for Electornic and Information System Xi'an China

In order to solve the problem of unsafe flight of traditional “low, slow and small” civil UAVs, and reduce pres sure on air traffic control personnel., an improved YOLOv5m target detection algorithm is proposed for active target detection of UAVs. According to the characteristics of low-altitude UAV detection, an attention mechanism was added to the YO LOv5 feature extraction network, and the original weighted NMS was optimized to SOFT_NMS Finally, the accuracy and real-time performance of the model are verified by constructi ng real UAV conflict target detection data set. The experimen tal results show that the average accuracy, recall rate, accura cy are 2.31 %, 3.66% and 5.59% higher than before the impr ovement, meet the anti-collision detection requirements of civi 1 UAV s in low altitude airspace.

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