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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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Hydrochemistry characteristics and genesis of shallow groundwater in diverse industrial agglomeration areas in typical alluvial plain of the Yellow River

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Science of the Total Environment 2025年 958卷 177764页

作者： Zhang, Fan Yuan, Ying Xi, Beidou Lu, Haojie Jiang, Yu Hui, Kunlong Tan, Wenbing Wang, Hui Meng, Fanhua State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental Sciences Beijing100012 China State Environmental Protection Key Laboratory of Simulation and Control of Groundwater Pollution Chinese Research Academy of Environmental Sciences Beijing100012 China

The groundwater environment in the middle and upper reaches of the Yellow River in China has attracted extensive attention. But, the hydrochemistry characteristics and genesis of shallow groundwater in diverse industrial agglomeration areas in typical alluvial plain of the Yellow River are still unknown. In this study, geochemical analysis methods, the positive matrix factorisation model, and the geodetector model were used to multidimensional analyze. The results showed that 78 % of the groundwater samples had high-alkalinity-risk and high-salinity-risk, and the water quality was poor and unsuitable for irrigation. "Very poor" and "undrinkable" samples accounted for 26.31 %. The weathering of calcium magnesium minerals and the dissolution of soluble sulfate were important sources of the main chemical components of the groundwater. However, evaporation and concentration gradually dominated from the inclined plain of the piedmont to the alluvial plain of the Yellow River. Domestic and agricultural activities were important sources of nitrogen species (NO3−, NO2−, and NH4+). The presence of Al, Mn, Zn, and Pb was caused by the production activities of various enterprises. The pollution contributors of natural sources, domestic and agricultural activities, industrial production and other sources were 29.49 %, 17.05 %, 31.41 %, and 22.05 %, respectively. Groundwater velocity and enterprise type were the main factors driving groundwater pollution by these four metal substances. The interaction between enterprise type and groundwater velocity had the greatest influence on the concentrations of Al, Mn, and Zn. Moreover, the interaction between enterprise type and the distance from enterprise had the greatest influence on Pb levels. Overall, groundwater pollution in the study area was the result of both natural and human factors. The findings of this study can offer valuable insights and theoretical support for preventing groundwater pollution in other industrial agglomerat

关键词： Groundwater geochemistry

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Technical Research on simulation and Predictive Analysis of Wind Farms in Power Systems 4

Technical Research on Simulation and Predictive Analysis of ...

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

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

ISBN: (纸本)9798331518066

To address the issue of insufficient accuracy in wind power output forecasting, this paper proposes a Support Vector Machine (VSM) model based on similar day matching and kernel entropy component analysis for wind power prediction. The model effectively extracts similar day features through the similar day approach and optimizes feature representation by combining it with kernel entropy component analysis (KECA), ultimately employing the SVM model for wind farm power forecasting. simulation results demonstrate that using this model for optimizing wind power generation predictions enhances the accuracy of wind power forecasts, surpassing the precision of single-method predictions. The Similar Day-KECA-SVM method leverages historical data from similar days and features extracted through KECA, with SVM performing the final prediction. This approach adeptly handles complex patterns and nonlinear relationships in wind power forecasting, thereby achieving superior predictive performance. © 2024 IEEE.

关键词： Wind forecasting

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A Hybrid Compress Method of STL Mesh for Realtime VR Visulization 7

A Hybrid Compress Method of STL Mesh for Realtime VR Visuliz...

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7th International Conference on Information Science and control Engineering, ICISCE 2020

作者： Zhang, Zhao Lan, Wei Xin, Jiayin Li, Qiang Jilin University State Key Laboratory of Automobile Simulation and Control Changchun China

ISBN: (纸本)9781728164069

In the real time VR rendering and simulation, there are normally two ways to solve the conflict between the large-scale data and the speed: one is to enhance the hardware, which will result high cost, and another is to simplify the data, which will waste labor and time if removing interactively. By solving the practical problem, a hybrid compress method has been presented to compress the triangle mesh. The number of triangles can be greatly reduced by applying the normal oriented algorithm, the color-oriented algorithm, and the correcting algorithm. The normal and ray are often used in the shading. Using z-buffer non-hue rendering, a pixel-based algorithm, the colors displayed in the viewport can be compatible with the triangles one to one. The correcting algorithm can solve the problem of the pixel-based algorithm. A STL Compressor has been prototyped to do this task. It can import/export STL format file to connect with the most modeling and the real time VR systems. This method is applied normally to a series of fixed cameras. © 2020 IEEE.

关键词： Pixels

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Dynamic Coordination control Strategy of Dual-planetary Power-split Hydraulic Hybrid Vehicle

Dynamic Coordination Control Strategy of Dual-planetary Powe...

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2021中国汽车工程学会年会暨展览会

作者： Zeng Xiaohua Song Meijie Song Dafeng Sun Kehua State Key Laboratory of Automobile Simulation and Control Jilin University

The ride comfort of driving has higher requirements for the double planetary row hybrid hydraulic hybrid system applied in the ***,compared with the electric hybrid system,the vibration problem of the hydraulic hybrid system is particularly prominent due to the different dynamic characteristics of the engine and the hydraulic pump/motor,as well as the structural characteristics of the multi clutch/brake *** the process of driving mode switching and rear planetaiy transmission,the timing of state transition of power and executive part has a great influence on the output of the system torque,which leads to the impact of the whole ***,considering the real-time response state of the power source and the driving demand torque analyzed by the driving operation,the " dynamic transition torque coordination control" function module is added to revise the demand torque for the second time,to solve the total output torque fluctuation caused by the change of control logic and torque distribution mode before and after the driving mode switching,so as to realize the system coordination control during the mode ***,through the dynamic analysis of the rear planetary system,the approximate linear relationship between the system output torque and clutch/brake friction torque,pump/motor output torque is obtained,and the torque control law of pump/motor is *** the same time,the coordination control logic between the power and the actuator in each stage is ***,the joint simulation results of Simulink and AMESim show that the ride comfort of the vehicle is greatly improved during the impact prone multi-mode switching and the upshift/downshift of the rear planetary row.

关键词： hydraulic hybrid hydraulic pump/motor coordinated control

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Distributed Power System simulation and Monitoring Supported by Cloud Technology : A grid optimization scheduling method based on MADRL 4

Distributed Power System Simulation and Monitoring Supported...

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

作者： Luo, Hui Zhang, Jie Hu, Yufeng Zhang, Jingyue Guo, Haiping Huang, Libin Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid 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 National Energy Power Grid Technology R&d Centre Guangzhou China

ISBN: (纸本)9798331518066

This study explores the optimization of Distributed Generation Systems (DGS) within a Multi-Agent Deep Reinforcement Learning (MADRL) framework. The focus is on transforming the overall optimization goal of the system into a global reward function and designing local rewards adapted to heterogeneous agents. Using the IEEE 33 node system as a case study, the impact of power aggregation and load management from photovoltaic systems, energy storage systems, electric vehicle charging facilities, and HVAC systems is analyzed. The results demonstrate that the proposed edge-cloud collaborative framework optimizes resource allocation and scheduling. The cloud platform is capable of integrating data from diverse sources and managing it in a unified manner, thereby coordinating the operations of multiple heterogeneous agents. The scalability and flexibility of cloud technology allow for the dynamic adjustment of computational resources according to demand, ensuring global optimization and the judicious allocation of resources. © 2024 IEEE.

关键词： Cloud platforms

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Molecular ecological networks reveal the spatial-temporal variation of microbial communities in drinking water distribution systems

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Journal of Environmental Sciences 2023年第2期124卷 176-186页

作者： Zibo Jing Zedong Lu Zhinan Zhao Wenfeng Cao Weibo Wang Yanchu Ke Xiaohui Wang Wenjun Sun Beijing Engineering Research Center of Environmental Material for Water Purification College of Chemical EngineeringBeijing University of Chemical TechnologyBeijing 100029China School of Environment Tsinghua UniversityBeijing 100084China Research Institute for Environmental Innovation(Suzhou)Tsinghua Suzhou 215163China State Key Joint Laboratory of Environmental Simulation and Pollution Control College of Environmental Sciences and EngineeringPeking UniversityBeijing 100871China

Microbial activity and regrowth in drinking water distribution systems is a major concern for water service ***,previous studies have focused on the microbial composition and diversity of the drinkingwater distribution systems(DWDSs),with little discussion on microbial molecular ecological networks(MENs)in different water supply *** analysis explores the potentialmicrobial interaction and the impact of environmental stress,to explain the characteristics of microbial community *** this study,the random matrix theory-based network analysis was employed to investigate the impact of seasonal variation including water source switching on the networks of three DWDSs that used different disinfection *** results showed that microbial interaction varied slightly with the seasons but was significantly influenced by different ***,identified as key species,play an important role in the *** UV-chlorine disinfection can effectively reduce the size and complexity of the network compared to chlorine disinfection alone,ignoring seasonal variations,which may affect microbial activity or control microbial regrowth in *** study provides new insights for analyzing the dynamics of microbial interactions in DWDSs.

关键词： Drinking water distribution system Molecular ecological network Water source switch UV-chlorine combined disinfection

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A New Hybrid Battery Thermal Management System: A Numerical Study

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IFAC-PapersOnLine 2024年第29期58卷 13-18页

作者： A. Jiawei Xiao B. Haitao Min C. Rui Jiang C. Weiyi Sun A State Key Laboratory of Automotive Simulation and Control Jilin University Changchun 130022 China General Research and Development Institute China FAW Corporation Limited Changchun 130013 China

Battery Thermal Management System (BTMS) has been investigated to ensure that the battery operates at optimal temperature. This study concentrates on the numerical study of a hybrid thermal management system consisting of liquid cooling and phase change materials (PCM). The performance of the hybrid cooling system at different discharge rates is investigated. The effects of liquid cooling flow velocity and flow direction on the thermal performance of the BTMS system were then studied. The results show that the discharge rate and inlet velocity have a strong influence on the performance of BTMS, and the reverse-flow can significantly decrease the maximum temperature and improve the temperature uniformity.

关键词： Numerical study Hybrid cooling system Battery thermal management systems phase change materials liquid cooling

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Emergency control methods for power systems based on improved deep reinforcement learning 6

Emergency control methods for power systems based on improve...

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2024 6th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2024

作者： Zhang, Jie Zhu, Yihua Liang, Zhuohang Ma, Qinfeng Zhang, Qingqing Liu, Mingshun An, Su Pu, Qingxin Dai, Jiang State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangdong Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangdong Guangzhou510663 China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangdong Guangzhou510663 China Power Dispatching and Control Center of Guizhou Power Grid Co. Ltd. Guizhou Guiyang550000 China

In order to achieve fast and accurate transient stability analysis and emergency control, this paper proposes a transient stability emergency control method based on improved deep reinforcement learning. In order to fully explore the temporal and spatial variation trend of transient response, a multi-dimensional feature containing information such as transient situation energy is constructed, and the deep reinforcement learning model is transformed based on the time-space graph neural network. On this basis, an emergency control model is constructed, and the power grid knowledge is integrated into the emergency control decision-making scheme to reduce the exploration of invalid decision-making and improve the performance of the model. The effectiveness of the proposed method is verified in the IEEE-39 system. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Deep reinforcement learning

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Critical Laplace Pressure and Dewetting Tansition of Aluminum-Based Superhydrophobic Surfaces Textured with a Nanosecond Laser

SSRN

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SSRN 2024年

作者： Wang, Guoyong Xu, Zhengzheng Li, Danqing Jiang, Yue Jiang, Zhonghao Liu, Yan Yang, Chun Cheng Key Laboratory of Automobile Materials Department of Materials Science and Engineering Jilin University Changchun130025 China Key Laboratory of Bionic Engineering Ministry of Education College of Biological and Agricultural Engineering Jilin University Changchun130025 China Key Laboratory of Bionic Engineering Ministry of Education State Key Laboratory of Automotive Simulation and Control Jilin University Changchun130022 China

In critical areas such as aerospace, where the formation of frost can pose a serious threat to safety, delaying and preventing its formation has become extremely important. Although it has been shown that superhydrophobic surfaces (SHs) are capable of delaying ice formation, these surfaces have challenges in maintaining the stability of the Cassie-Baxter (CB) state, especially in high humidity and freezing environments, which limits their application in anti-icing and de-icing. To deal this issue, in this study, a low-cost near-infrared nanosecond laser technique was used instead of the more expensive ultrafast femtosecond laser by inducing the formation of three different micro/nanostructured superhydrophobic surfaces on the aluminum surface. The critical Laplace pressure of these surfaces was tested by evaporation experiments. Further icing/melting cycle experiments observed the ability of these superhydrophobic surfaces to recover from the CB state. The experimental results showed that the surfaces with higher critical Laplace pressures were more likely to recover the CB state under the same conditions, implying that they were better able to maintain their superhydrophobic properties after undergoing the icing/melting process. The results not only deepen our understanding of icing and melting phenomena, but also provide important scientific guidance for the design of superhydrophobic anti-icing surfaces with high CB state stability. These findings are of great practical application value and scientific significance for the development of new anti-icing materials, especially in aerospace and other fields that require high safety. © 2024, The Authors. All rights reserved.

关键词： Recovery

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