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11th China International Conference on Electricity Distribution, CICED 2024

作者： Wang, Yibo Liu, Kaipu Liu, Chen Liu, Yu Du, Zhanhui Wang, Yuan Northeast Electric Power University The Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Jilin China

ISBN: (纸本)9798350368345

Under the background of 'double carbon', the power system is facing green change, and the distribution network is facing the challenge of distributed generation and diversified load. Traditional distribution transformers are unable to cope with local load peaks and sudden load growth. In order to cope with the problem of heavy overload caused by seasonal load, mobile hybrid distribution transformer (MHDT) has gradually attracted attention as an innovative solution. In this paper, the deployment strategy of MHDT is discussed, and an optimization method based on spatial coordinate system mapping is proposed to reduce the amount of calculation and improve the computational efficiency. Through the practical application case of an agricultural irrigation area in Jilin Province, the actual effect of this method in solving the problem of transformer heavy overload is verified. The results show that MHDT can effectively improve flexibility response ability of distribution system. © 2024 IEEE.

关键词： Distribution transformers

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Investigating Black-Box Model for Wind Power Forecasting Using Local Interpretable Model-Agnostic Explanations Algorithm

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CSEE Journal of Power and Energy systems 2025年第1期11卷 227-242页

作者： Mao Yang Chuanyu Xu Yuying Bai Miaomiao Ma Xin Su Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Daqing Power Industry Bureau Daqing 163000China

Wind power forecasting(WPF)is important for safe,stable,and reliable integration of new energy technologies into power *** learning(ML)algorithms have recently attracted increasing attention in the field of ***,opaque decisions and lack of trustworthiness of black-box models for WPF could cause scheduling *** study develops a method for identifying risky models in practical applications and avoiding the ***,a local interpretable model-agnostic explanations algorithm is introduced and improved for WPF model *** that basis,a novel index is presented to quantify the level at which neural networks or other black-box models can trust features involved in ***,by revealing the operational mechanism for local samples,human interpretability of the black-box model is examined under different accuracies,time horizons,and *** interpretability provides a basis for several technical routes for WPF from the viewpoint of the forecasting ***,further improvements in accuracy of WPF are explored by evaluating possibilities of using interpretable ML models that use multi-horizons global trust modeling and multi-seasons interpretable feature selection *** results from a wind farm in China show that error can be robustly reduced.

关键词： Black-box model correlation analysis feature trust index local interpretability local interpretable modelagnostic explanations(LIME) wind power forecasting

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Frame Optimization Design Based on Improved Grey Relational Analysis

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Journal of Shanghai Jiaotong university(Science) 2024年第6期29卷 1071-1080页

作者： WANG Shuang WANG Dengfeng NING Zhanjin HU Zhongjian Department of Emergency Rescue China Fire and Rescue InstituteBeijing 102202China State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China

For effectively improving the overall performance of fire truck frame structure,and solving the complexity of previous methods in the frame optimization design process,the traditional grey relational grade ranking needs to be ***,the first-order modal test was conducted to verify the validity of the initial frame ***,based on this model,a high-strength steel frame was designed to reduce deformation,maximum stress,and frame mass,and increase the fatigue life and the frequencies of the first bending modal and first torsional *** groups of sample points were generated through Hammersley ***,improved grey relational analysis with principal component analysis was proposed to realize the optimal design of the frame ***,the optimal combination of design parameters for the frame was obtained using the proposed ***,the optimized frame structure is found by comparing the models before and after optimization,and the mass is reduced by 14.8%.Moreover,the computational cost can be reduced by 135%when the proposed method is compared with the previous ***,the proposed method can effectively improve the performance of the frame and improve the computational efficiency.

关键词： fire truck frame structure optimization design improved grey relational analysis principal component analysis

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Assessment and Enhancement of FRC of Power systems Considering Thermal Power Dynamic Conditions

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CSEE Journal of Power and Energy systems 2024年第4期10卷 1371-1383页

作者： Feng Hong Yalei Pang Weiming Ji Lu Liang Fang Fang Junhong Hao Jizhen Liu State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources and School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China State Key Laboratory of Alternate Electric Power System with Renewable Energy Sources School of Energy Power and Mechanical EngineeringNorth China Electric Power UniversityBeijing 102206China

Frequency stability and security have been a vital challenge as large-scale renewable energy is integrated into power *** contrast,the proportion of traditional thermal power units decreases during the decarbonization transformation process,resulting in poor frequency *** paper aims to explore the potential of frequency regulation support,dynamic assessment,and capacity promotion of thermal power plants in the transition *** the dynamic characteristics of the main steam working fluid under different working conditions,a nonlinear observer is constructed by extracting the main steam pressure and valve opening degree *** real-time frequency modulation capacity of thermal power units can provide a dynamic state for the power grid.A dynamic adaptive modification for primary frequency control(PFC)of power systems,including wind power and thermal power,is proposed and *** power dynamic allocation factor is adaptively optimized by predicting the speed droop ratio,and the frequency modulation capability of the system is improved by more than 11%under extreme ***,through the Monte Carlo simulation of unit states of the system under various working conditions,the promotion of the frequency regulation capacity with high wind power penetration(WPP)is verified.

关键词： Dynamic evaluation frequency regulation power system predictive modeling wind penetration

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Carbon dioxide reduction through mineral carbonation by steel slag

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Journal of Environmental Sciences 2025年第6期152卷 664-684页

作者： Yongpeng Zhang Yimei Ying Lei Xing Guoxiong Zhan Yanli Deng Zhen Chen Junhua Li School of Environmental and Municipal Engineering North China University of Water Resources and Electric PowerZhengzhou 450046China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Carbon dioxide (CO_(2)) mineralization technology has attracted significant attention, due tothe synergistic terminal treatment of CO_(2) and industrial waste. The combined CO_(2) mineralizationprocess with steel enterprises is a promising route to simultaneously address CO_(2)emissions and SS treatment. Recently, a serial of the relevant work focus on a single type ofsteel slag (SS), and the understanding of CO_(2) absorption by mineralization of various SS isvery ***, it is urgent requirement for systematic summary and discussion onhow to make full use of the mineralized products produced after the mineralization of CO_(2)in SS. This review aims to investigate the progress of CO_(2) mineralization using SS, includingthe potential applications of mineralization products, as well as the environmental impactand risk assessment ofmineralization product applications. Currently, the application of SSmineralization products is primarily focused on their use as construction materials with loweconomic value. With usage of the mineralization products for ecological restoration (*** soil remediation) was treated as an advanced route, but still remaining challenge infunctional materials preparation, and its technical economy and possible hazards need tobe further explored by long-term experimental tests.

关键词： CO_(2)mineralization Steel slag Building materials Soil improvement Environmental risk

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Microbial Electrochemical Wastewater Refining

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Engineering 2025年第3期46卷 245-256页

作者： Na Chu Daping Li Raymond Jianxiong Zeng Yong Jiang Peng Liang Fujian Key Laboratory of Pollution Control and Resource Reuse College of Environmental and Resource SciencesFujian Normal UniversityFuzhou 350117China CAS Key Laboratory of Environmental and Applied Microbiology Environmental Microbiology Key Laboratory of Sichuan ProvinceChengdu Institute of BiologyChinese Academy of SciencesChengdu 610041China Fujian Provincial Key Laboratory of Soil Environmental Health and Regulation College of Resources and EnvironmentFujian Agriculture and Forestry UniversityFuzhou 350002China State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing 100084China

Wastewater treatment significantly contributes to greenhouse gas emissions,which are further exacerbated by the environmental impact of external chemical *** response,microbial electrochemical wastewater refining has gained prominence at the interdisciplinary frontier of wastewater resource recovery and green *** progress has been made in utilizing active electrodes to stimulate CO_(2) fixation rates,applying“binary electron donors”to produce high-value-added chemicals,and developing novel processes and *** review explores various aspects of microbial electrochemical wastewater refining,including microbial electrochemical monitoring of water quality,chemical synthesis from diverse carbon sources,and the deployment of pilot-scale systems for generating electricity,hydrogen,and methane,as well as for in-situ ***,it discusses the challenges and future directions,highlighting the importance of understanding mechanisms,advancing electrocatalyst and microbial engineering,and innovating hybrid *** conclusion,the widespread adoption of microbial electrochemical wastewater refining is emphasized for resource recovery and sustainable chemical production,ultimately reducing environmental impact.

关键词： Microbial electrosynthesis Extracellular electron transfer CO_(2)reduction Wastewater treatment Resources recovery

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An equivalent modeling method for integrated water-wind-solar systems based on sparrow search algorithm

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Energy Informatics 2025年第1期8卷 1-16页

作者： Lu, Yuanhong Zhang, Jie Zhang, Jingyue Huang, Libin Guo, Haiping Hu, Binjiang Guo, Tianyu State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou510663 China National Energy Power Grid Technology R & D Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou510663 China

In the context of extensive integration of renewable energy sources into the electrical grid, the grid's fault transient behaviors have undergone significant changes. However, conventional single-unit equivalent models fail to accurately capture the fault transient responses of combined wind-solar-hydro power stations and often require substantial computational resources, leading to reduced simulation efficiency. This study proposes a cluster-based equivalent modeling approach for hybrid wind-solar-hydro power plants using the Sparrow Search Algorithm. key factors influencing fault characteristics, including the distance to the Point of Common Coupling, DC-side current-limiting measures, irradiance levels, water flow rates, wind speeds, and reactive power at the outlet, are identified and used to construct a transient model. Euclidean distances are computed for these factors, and initial clustering centers for wind turbines are determined using an improved max–min distance technique. These factors and clustering centers serve as the training dataset to establish the clustering equivalent model. simulation results, conducted on the MATLAB2022 platform, demonstrate that the SSA-based model outperforms the single-unit equivalent model by over 150 times in terms of accuracy. Additionally, the SSA-based model achieves a delay time, defined as the time required to compute the system's transient response after a fault, of less than 5 ms, which is less than one-twentieth of the delay time of the single-unit equivalent model. These improvements highlight the model's ability to accurately capture dynamic power responses under various disturbances, making it highly suitable for real-time applications in hybrid renewable energy systems. © The Author(s) 2025.

关键词： MATLAB

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The electromagnetic transient simulation acceleration algorithm based on delay mitigation of dynamic critical paths

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Energy Informatics 2025年第1期8卷 1-12页

作者： Guo, Qi Lu, Yuanhong Zhang, Jie Zhang, Jingyue Huang, Libin Guo, Haiping Guo, Tianyu Tu, Liang State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou510663 China National Energy Power Grid Technology R & D Centre Guangzhou510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou510663 China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou510663 China

The task scheduling problem based on directed acyclic graphs (DAGs) has been proven to be NP-complete in general cases or under certain restrictions. In this paper, building upon existing scheduling algorithms, we introduce a static task scheduling algorithm based on directed acyclic graphs. By incorporating the proportion of task transmission delay as a guiding metric in the optimization process, processors can be prioritized for tasks with high latency, thereby improving computational efficiency. We first validate the theoretical feasibility of the algorithm using a theoretical case study and illustrate the algorithmic effectiveness using two real case studies, direct current (DC) model and alternating current (AC) model respectively. The research indicates that the scheduling algorithm proposed in this paper achieves an average scheduling length improvement of over 1.2% compared to the Heterogeneous Earliest-Finish-Time algorithm (HEFT) in topologies with high latency tasks. Additionally, the experiments show that the HEFT algorithm consumes 39.85us and the EMT-DM algorithm consumes 38.29us during simulation using DC, and the HEFT algorithm consumes 31.23us and the EMT-DM algorithm consumes 26.51us during simulation using AC, both of which are improved compared to the HEFT algorithm. © The Author(s) 2025.

关键词： Flow graphs

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Fault Diagnosis Method of Rolling Bearing Based on MSCNN-LSTM

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Computers, Materials & Continua 2024年第6期79卷 4395-4411页

作者： Chunming Wu Shupeng Zheng Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Ministry of Education Northeast Electric Power UniversityJilin132012China

Deep neural networks have been widely applied to bearing fault diagnosis systems and achieved impressive success *** address the problem that the insufficient fault feature extraction ability of traditional fault diagnosis methods results in poor diagnosis effect under variable load and noise interference scenarios,a rolling bearing fault diagnosis model combining Multi-Scale Convolutional Neural Network(MSCNN)and Long Short-Term Memory(LSTM)fused with attention mechanism is *** adaptively extract the essential spatial feature information of various sizes,the model creates a multi-scale feature extraction module using the convolutional neural network(CNN)learning *** learning capacity of LSTM for time information sequence is then used to extract the vibration signal’s temporal feature *** parallel large and small convolutional kernels teach the system spatial local *** gathers temporal global features to thoroughly and painstakingly mine the vibration signal’s characteristics,thus enhancing model ***,bearing fault diagnosis is accomplished by using the SoftMax *** experiment outcomes demonstrate that the model can derive fault properties entirely from the initial vibration *** can retain good diagnostic accuracy under variable load and noise interference and has strong generalization compared to other fault diagnosis models.

关键词： Bearing fault diagnosis convolutional neural network short-long-term memory network feature fusion

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Synergistic promotion of particulate matter reduction and production performance via adjusting electrochemical reactions in the zinc electrolysis industry

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Frontiers of Environmental Science & Engineering 2024年第1期18卷 23-33页

作者： Zizhen Ma Jingkun Jiang Lei Duan Jianguo Deng Fuyuan Xu Zehui Li Linhua Jiang Ning Duan School of Environmental and Municipal Engineering Qingdao University of TechnologyQingdao 266520China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of the EnvironmentTsinghua UniversityBeijing 100084China State Key Laboratory of Pollution Control and Resources Reuse College of Environmental Science and EngineeringTongji UniversityShanghai 200092China School of Physics Peking UniversityBeijing 100871China

Heavy particulate matter (PM) pollution and high energy consumption are the bottlenecks of hydrometallurgy, especially in the electrolysis process. Therefore, an urgent need is to explore PM reduction methods with production performance co-benefits. This study presents three PM reduction methods based on controlling operating parameters, i.e., lowering electrolyte temperature, H2SO4 concentration, and current density of the cathode. The optimized conditions were also investigated using the response surface methodology to balance the PM reduction effect and Zn production. The results showed that lowering electrolyte temperature is the most efficient, with an 89.0% reduction in the PM generation flux (GFPM). Reducing H2SO4 concentration led to the minimum side effects on the current efficiency of Zn deposition (CEZn) or power consumption (PC). With the premise of non-deteriorating CEZn and PC, GFPM can be reduced by 86.3% at the optimal condition (electrolyte temperature = 295 K, H2SO4 = 110 g/L, current density = 373 A/m^(2)). In addition, the reduction mechanism was elucidated by comprehensively analyzing bubble characteristics, electrochemical reactions, and surface tension. Results showed that lower electrolyte temperature inhibited the oxygen evolution reaction (OER) and compressed gas volume. Lower H2SO4 concentration inhibited the hydrogen evolution reaction (HER) and reduced electrolyte surface tension. Lower current density inhibited both OER and HER by decreasing the reaction current. The inhibited gas evolutions reduced the microbubbles’ number and size, thereby reducing GFPM. These results may provide energy-efficient PM reduction methods and theoretical hints of exploring cleaner PM reduction approaches for industrial electrolysis.

关键词： Zinc electrolysis Particulate matter Energy consumption Operating parameters Bubble characteristic Electrochemical reaction

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