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Joint operation of mobile battery, power system, and transportation system for improving the renewable energy penetration rate

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APPLIED ENERGY 2024年 357卷

作者： Liu, Shan Yan, Jie Yan, Yamin Zhang, Haoran Zhang, Jing Liu, Yongqian Han, Shuang North China Elect Power Univ Sch New Energy State Key Lab Alternate Elect Power Syst Renewable Beijing 102206 Peoples R China Peking Univ Sch Urban Planning & Design Shenzhen 518055 Guangdong Peoples R China State Grid Hubei Elect Power Co Ltd Wuhan 430077 Peoples R China

Future energy system will feature in a high-share of renewable energies (REs), which poses huge challenges to obtain full utilization of renewable power generation. To solve the problem, this paper presents a joint-operation two-stage mixed integer linear programming model to coordinate the power system and train transportation system by optimizing the logistics of mobile batteries and real-time charge/discharge in cities. The full/empty batteries are transported through the train transportation system between the load side and the renewable energy station, which improves renewable energy penetration, economics, and mobilities. The first-stage model deals with the preliminary logistic optimization of batteries including routes, time and capacities of transportation, and the second-stage model optimizes real-time schedule of charge/discharge of batteries. The aim of the proposed model is to minimize the transportation cost, maximize the utilization rate of renewable energy in an energy system and smooth the daily load curve. The proposed model considers technical constraints such as railway transportation capacity, load demand satisfaction and renewable energy consumption in the power system. The optimal logistics plan and real-time charging and discharging plan can be obtained for both full and empty battery transportation. The validity of the method is verified with real data from Northeast China and Northern China, including railway routes, renewable energy output, and load profiles. The results show that the renewable energy penetration rate increases from 84.4% to 95.3% in Northeast China and from 42.7% to 78.2% in Northern China under the 2050 scenario with the proposed method. The peak-to-valley difference in the daily load curve decreases by 84% and 100% in Northeast China and Northern China, respectively. Meanwhile, the case study shows that the costs of battery transportation decrease from 0.398 CNY/kWh and 0.377 CNY/kWh to 0.252 CNY/ kWh and 0.254 CNY/kWh

关键词： Energy storage Mobile battery Logistics and scheduling Joint operation Transportation system Renewable energy

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Influence of glass beads on alkali-activated slag-metakaolin-based novel grouting materials: Physical properties, leaching kinetics and microstructure

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CONSTRUCTION AND BUILDING MATERIALS 2024年 452卷

作者： Luo, Yiping Liu, Yuhao Wang, Defa Li, Yanwei Suo, Nan Liu, Zhao Wang, Qi Xian Univ Technol State Key Lab Ecohydraul Northwest Arid Reg China Xian 710048 Peoples R China Xian Univ Technol Sch Civil Engn & Architecture Xian 710048 Shanxi Peoples R China State Grid Shaanxi Elect Power Construct Co Xian 710048 Peoples R China State Grid Gansu Elect Power Engn Design Consultin Lanzhou 730030 Gansu Peoples R China

Alkali-activated grouting material (AAGM) is widely regarded as a new environmentally friendly material;however, metakaolin (MK) significantly impacts the system's rheology and is typically used as an auxiliary material in most AAGM-related literature. Therefore, this article aims to use MK as the main component and introduces glass microspheres (GB) as admixtures to explore the feasibility of using the GB "ball effect" to improve the overall performance of slag-metakaolin (SL-MK)-based AAGM and systematically studies its influence on the physical properties and microstructure of SL-MK binary mixed grouting materials, to promote the further development of MK in grouting engineering applications;In order to gain a deeper understanding of the reaction behavior of GB as a solid precursor in AAGM, the primary active ions in GB (Si4+, Al3+, and Ca2+) leaching behavior in alkaline solutions. The results indicate that GB demonstrates high reactivity in an alkaline environment. Thanks to GB's particular physical and chemical structure, the overall properties of AAGM are improved. When the GB content is 4 %, the mechanical properties are optimal. Through inductively coupled plasma optical emission spectroscopy (ICP-OES), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA), it was found that the leaching of primary active ions promoted the polymerization reaction of AAGM, and additional gels were generated. Scanning electron microscopy (SEM) and energy dispersion spectroscopy (EDS) analysis further showed that GB also improves the AAGM strength by changing the propagation behavior of cracks in the matrix and the volcanic ash effect. In addition, the enrichment and potential filling effect of C-A-S-H gel contribute to the densification of the entire alkaliactivated material (AAM) system.

关键词： Alkali-activated grouting material Glass beads Metakaolin Leaching kinetics

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An Intrusion Detection Method Based on Attention Mechanism to Improve CNN-BiLSTM Model

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COMPUTER JOURNAL 2023年第5期67卷 1851-1865页

作者： Shou, Dingyu Li, Chao Wang, Zhen Cheng, Song Hu, Xiaobo Zhang, Kai Wen, Mi Wang, Yong Shanghai Univ Elect Power Coll Comp Sci & Technol Shanghai 201306 Peoples R China State Grid Digital Technol Holding Co Ltd Beijing 100053 Peoples R China Beijing Smart Chip Microelect Technol Co Ltd State Grid Key Lab Power Ind Chip Design & Anal T Beijing 100192 Peoples R China

Security of computer information can be improved with the use of a network intrusion detection system. Since the network environment is becoming more complex, more and more new methods of attacking the network have emerged, making the original intrusion detection methods ineffective. Increased network activity also causes intrusion detection systems to identify errors more frequently. We suggest a new intrusion detection technique in this research that combines a Convolutional Neural Network (CNN) model with a Bi-directional Long Short-term Memory Network (BiLSTM) model for adding attention mechanisms. We distinguish our model from existing methods in three ways. First, we use the NCR-SMOTE algorithm to resample the dataset. Secondly, we use recursive feature elimination method based on extreme random tree to select features. Thirdly, we improve the profitability and accuracy of predictions by adding attention mechanism to CNN-BiLSTM. This experiment uses UNSW-UB15 dataset composed of real traffic, and the accuracy rate of multi-classification is 84.5$\%$;the accuracy rate of multi-classification in CSE-IC-IDS2018 dataset reached 98.3$\%$.

关键词： intrusion detection mixed sampling attention mechanism recursive feature elimination convolutional neural network bi-directional long short-term memory network

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A Lightweight Edge Network Intrusion Detection System Based on MobileVit 10th

A Lightweight Edge Network Intrusion Detection System Based ...

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10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024

作者： Yang, Xiaobo Hu, Xiaobo Li, Chao Zhou, Lin Wang, Yong School of Computer Science and Technology Shanghai University of Electric Power Shanghai China State Grid Key Laboratory of Power Industrial Chip Design and Analysis Technology Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing China State Grid Digital Technology Holding Co. Beijing China

ISBN: (纸本)9789819787487

Aiming at the current problems of limited computational and storage resources in edge networks, poor robustness of traditional machine learning algorithms, and the large resource overhead required to deploy deep learning algorithms to edge networks, we proposes a lightweight intrusion detection system based on MobileViT, which can detect cyber-attack traffic in edge networks with little resource consumption. The system uses smote to balance the dataset to make the detection model more sensitive to a small number of samples, and then transforms the network traffic into a custom grey scale graph, which reduces the time of transformation and improves the accuracy of the model, which is then fed into a modified minor-MobileViT network for training, and then tested in a test set. Experimental results with relatively few model parameters show that our proposed method has good detection performance, while the model requires less storage space and has low computational overhead, making it suitable for network traffic detection and classification under edge networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Network intrusion

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Energy Harvesting analysis and Sensing Application of Cantilever Structure Based on Aeolian Vibration and Piezoelectric Effect

Energy Harvesting Analysis and Sensing Application of Cantil...

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2023 IEEE International Conference on Advanced power System Automation and Protection, APAP 2023

作者： Gao, Yisong Fu, Fangda Chen, Lincong Chen, Qinzhu Wang, Zhiming Tan, Zejie Ni, Yang Hainan Power Grid Transmission & Maintenance Branch Corp Production Technology Department China Electric Power Research Institute Hainan Power Grid Co Key Laboratory of Physical and Chemical Analysis for Electric Power of Hainan Province China Digital Grid Research Institute China Southern Power Guangdong Provincial Key Laboratory of Digital Grid Technology China Chongqing University State Key Lab. of Power Transmission and Distribution Equipment and System Safety and New Technology Chongqing China

ISBN: (纸本)9798350306668

Based on aeolian vibration and piezoelectric effect, a cantilever energy harvester is proposed to supply energy to a micro-meteorological online monitoring sensing system for transmission lines. According to the Hamiltonian variational principle and Gauss's law, the distributed parameter coupling model of the piezoelectric cantilever energy harvesting module in the system is established, and the theoretical analytical expression of the output response of the energy harvesting module is derived by the Galerkin decomposition method and the force electrolytic coupling method. The influences of external excitation frequency and external load resistance on the output response of the system energy harvesting module are discussed. The results indicate that the highest output power is obtained when the external excitation frequency is equal to the natural frequency of the structure. Besides, the optimal external load resistance is always exciting with maximum electric power and the smallest vibration displacement. Finally, through indoor tests, the practicability of the self-powered micro-meteorological online monitoring system proposed in this paper is demonstrated. The research results in this paper can provide theoretical and experimental reference for the study of self-energy harvesting of transmission line online monitoring systems, and help for the safe operation and risk warning of transmission lines. © 2023 IEEE.

关键词： Piezoelectricity

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Characteristics of wind load on high-voltage disconnect switch system in substation

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PHYSICS OF FLUIDS 2025年第2期37卷

作者： Li, Jingyao Nie, Shidong Liu, Min Liu, Sikai Wang, Jiaxing Li, Peng Shao, Shuai Chongqing Univ Sch Civil Engn Chongqing 400045 Peoples R China Chongqing Univ Key Lab New Technol Construct Cities Mt Area Minist Educ Chongqing Peoples R China China Power Engn Consulting Grp Northwest Elect Power Design Inst Co Ltd Xian Peoples R China State Grid Elect Power Engn Res Inst Co Ltd Beijing Peoples R China

Ensuring high-voltage disconnect switch system safety is essential for the stable operation of the power system. A method for wind force tests to determine the wind load characteristics of the whole and the segments of the disconnect switch system was developed. Through this method, the distributions of aerodynamic coefficients for both the whole structure and its segments were determined, along with the skewed wind load coefficient relative to wind direction. The two-parameter model for wind load was used to predict wind load distribution along the structure's height. The study also considered the effect of different operating states of the disconnect switch system, namely, the switching-off and switching-on states, on wind force coefficients. Comparisons and analyses were performed to examine how these states influence the mean, fluctuating, and peak wind force coefficients, as well as the skewed wind load coefficient of the structure. The results indicate that the calculations of the two-parameter model are in good agreement with the measurements from the segment models. The most critical wind directions for the drag and skewed wind load coefficients for each segment of the structure were found to be 60 degrees and 120 degrees, respectively. Additionally, the mean wind load on the switch and insulator segments was higher than that on the steel columns. The switching-on state was identified as more detrimental to mean and fluctuating wind loads, with a pronounced effect on crosswind and torsional wind loads, especially on the torsional response of the structure.

关键词： Wind stress

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Super-elastic, hydrophobic composite aerogels for triboelectric nanogenerators

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NANOSCALE 2025年第13期17卷 8047-8056页

作者： Fang, Shize Xu, Xin Wei, Yu Qiu, Fangcheng Huang, Weixin Jiang, Hong Zhang, Ning Song, Yufeng Gao, Meng Liu, Hongbin Liu, Yang Cheng, Bowen Tianjin Univ Sci & Technol State Key Lab Biobased Fiber Mfg Technol Tianjin Key Lab Pulp & Paper Tianjin 300457 Peoples R China Elect Power Res Inst Yunnan Power Grid Co Ltd Kunming 650011 Peoples R China Jiangxi Changshuo Outdoor Leisure Prod Co Tech Res & Dev Dept Jiangxi 335500 Peoples R China Jiangxi Inst Fash Technol Sch Fash Design Nanchang 330201 Jiangxi Peoples R China

Progress toward the advancement of environmentally friendly energy harvesting devices is critical for eco-environmental protection. There is an urgent need for developing energy harvesting devices from biobased materials. However, it is still a challenge to utilize biobased cellulose nanofiber (CNF) aerogels in triboelectric nanogenerators (TENGs) due to their poor mechanical properties, hydrophilicity, and weak polarization capability. Here, we demonstrate a facile strategy to fabricate a super-elastic, hydrophobic CNF/MXene composite aerogel for TENGs through fluorosilane crosslinking and a directional freeze-dried assembled structure. This aerogel can withstand up to 80% compressive strain, rebound to 95.33% of its original height, and exhibit hydrophobicity (water contact angle = 137.65 degrees). In addition, the induction of MXene and the silane coupling agent endows the aerogel with enhanced electronegativity and charge density. These properties enable the CNF/MXene aerogel to harvest energy with an output voltage of 100 V and a short-circuit charge density of similar to 900 nC cm-3, while maintaining stability for 1000 cycles. This aerogel holds great application potential in the field of self-powered sensing and raindrop energy harvesting.

关键词： Aerogels

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analysis of Extreme Precipitation under Nonstationary Conditions in the Yangtze River Basin

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JOURNAL OF HYDROLOGIC ENGINEERING 2025年第1期30卷

作者： Li, Wenyu Zhang, Hairong Xin, Qian Gu, Xuezhi Ma, Haoran Cao, Hui Bao, Zhengfeng Ye, Lei Huai, Xiaowei China Yangtze Power Co Ltd Yichang 443133 Peoples R China Dalian Univ Technol Sch Infrastructure Engn Dalian 116024 Peoples R China China Power Engn Consulting Grp Co Ltd Northeast Elect Power Design Inst Changchun 130021 Peoples R China Hunan Disaster Prevent Technol Co Ltd Changsha 410129 Peoples R China Natl Key Lab Power Grid Disaster Prevent & Reduct Changsha 410129 Peoples R China

As global warming intensifies, both the frequency and magnitude of extreme precipitation events have undergone significant changes, leading to a widespread manifestation of nonstationary characteristics in extreme precipitation sequences. Regarding the current research status in the Yangtze River Basin (YRB), there is a deficiency in comprehensive investigations into the connection between extreme precipitation and climate change. This paper aims to identify the primary climate factors affecting extreme precipitation in the YRB and use them for dynamic assessment of future rainstorm risks. It thoroughly examines the correlation between 11 climate factors and extreme rainfall across different temporal scales to identify potential climate drivers for nonstationary models. Subsequently, ten nonstationary generalized extreme value (GEV) models were constructed, and the optimal covariates for 190 stations were determined within a Bayesian framework. Finally, a complete forecasting process was established, and the extreme rainfall in the YRB under nonstationary conditions was assessed. The results indicate that, on average, 144 stations exhibited nonstationary characteristics across various event scales, accounting for an average of 75.8%. The extreme rainfall in the YRB is influenced by multiple factors, with no single factor demonstrating absolute dominance across different time scales. Neglecting the nonstationarity of extreme precipitation will inevitably lead to misconceptions about extreme rainfall. Furthermore, the spatial distribution of the maximum scenarios of extreme rainfall under nonstationary conditions is significantly different from that under stationary conditions.

关键词： Yangtze River Basin (YRB) Climatic factors Generalized extreme value (GEV) model Nonstationary Extreme precipitation

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Stage-Zero: A Dynamic Ensemble Method for Intrusion Detection in Industrial Control Systems 10th

Stage-Zero: A Dynamic Ensemble Method for Intrusion Detectio...

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10th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2024

作者： Ma, Zhiming Zhou, Lin Hu, Xiaobo Li, Chao Chen, Siyuan Wang, Yong Department of Computer Science and Technology Shanghai University of Electric Power Shanghai China State Grid Key Laboratory of Power Industrial Chip Design and Analysis Technology Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing China State Grid Digital Technology Holding Co. Ltd. Beijing China

ISBN: (纸本)9789819787487

Industrial control systems (ICS) have become increasingly vulnerable to security risks due to the proliferation of network applications. Intrusion detection systems (IDS) are employed to safeguard ICS from hostile attacks. While machine learning-based methods perform well in intrusion detection tasks, combining multiple machine learning classifiers can further increase the detection accuracy. Confidence calibration is a technique developed to enable a machine learning model to produce prediction results along with more accurate proximate correctness likelihood. This study proposes a dynamic ensemble method that utilizes confidence calibration and a zeroth layer neural net classifier to create a semi-stacked ensemble model, while weighted cross-entropy loss is employed to balanced training samples. We tested our method on two real ICS cybersecurity datasets and achieved accuracy that matches traditional aggregating ensembles like voting and stacking while significantly reducing inference computation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Network intrusion

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Fault diagnosis technology overview for lithium-ion battery energy storage station

IET ENERGY SYSTEMS INTEGRATION

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IET ENERGY SYSTEMS INTEGRATION 2024年第S1期6卷 684-701页

作者： Li, Bin Chen, Peiyu Li, Guanzheng Li, Chao Zeng, Kaidi Liu, Bin Li, Xuebin Huo, Qidi Jiao, Kui Wang, Chengshan Tianjin Univ Natl Ind Educ Platform Energy Storage Tianjin Peoples R China State Grid Tianjin Elect Power Co Elect Power Res Inst Tianjin Peoples R China Beijing Sifang Automat Co Ltd Beijing Peoples R China China Energy Engn Grp Tianjin Elect Power Design Inst Tianjin Peoples R China China Elect Power Res Inst State Key Lab Grid Secur & Energy Conservat Beijing Peoples R China

With an increasing number of lithium-ion battery (LIB) energy storage station being built globally, safety accidents occur frequently. Diagnosing faults accurately and quickly can effectively avoid safe accidents. However, few studies have provided a detailed summary of lithium-ion battery energy storage station fault diagnosis methods. In this paper, an overview of topologies, protection equipment, data acquisition and data transmission systems is firstly presented, which is related to the safety of the LIB energy storage power station. Then, existing fault diagnosis technologies are reviewed in detail. Finally, the future developing trends of fault diagnosis technology are discussed.

关键词： battery storage plants fault diagnosis

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