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CAPACITY ALLOCATION METHOD OF BATTERY ENERGY STORAGE SYSTEM CONSIDERING MULTI-SERVICE TARGET LEVEL ASSESSMENT

International Journal of Electrical engineering 2022年第5期29卷 141-153页

作者： Ma, Suliang Wu, Yiwen Jiang, Yuan Li, Yaxin Li, Jianlin School of Electrical and Control Engineering North China University of Technology Shijingshan District Beijing China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Haidian District Beijing China

Rational planning of battery energy storage system is the key technology to solve the problem of high proportion of new energy consumption and the requirements of high performance power supply. Starting from the multiple application dimensions of power supply, power grid, load and battery energy storage system, this paper proposes a method of battery energy storage system capacity allocation based on multi-objective comprehensive evaluation. Firstly, the capacity configuration model of battery energy storage system is established from two aspects of service objectives and operation constraints;Then, under the two-level optimization framework, the capacity allocation scheme of the battery energy storage system is formed by using particle swarm optimization and multi- attribute decision-making methods;Finally, the configuration results of IEEE33 nodes with high proportion of distributed new energy access are analyzed, and the influence of model parameters and target orientation on the capacity of battery energy storage system is discussed. The simulation results show that the proposed method can flexibly and effectively configure the battery energy storage system, complete multiple different target service requirements, and promote the scientific application of the battery energy storage system. © 2022, Chinese Institute of Electrical engineering. All rights reserved.

关键词： Battery storage

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Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

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Journal of Mountain science 2024年第3期21卷 952-972页

作者： GUO Junqi XI Wenfei YANG Zhiquan SHI Zhengtao HUANG Guangcai YANG Zhengrong YANG Dongqing Faculty of Geography Yunnan Normal UniversityKunming 650500China Key Laboratory of Early Rapid Identification Prevention and Control of Geological Diseases in Traffic Corridor of High Intensity Earthquake Mountainous Area of Yunnan ProvinceKunming 650093China Faculty of Public Safety and Emergency Management Kunming University of Science and TechnologyKunming 650093China Key Laboratory of Geological Disaster Risk Prevention and Control and Emergency Disaster Reduction of Ministry of Emergency Management of the People’s Republic of China Kunming University of Science and TechnologyKunming 650093China Guizhou Geological Survey Institute Guiyang 550081China College of Big Data and Intelligent Engineering Southwest Forestry UniversityKunming 650224China

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and *** order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network *** SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and *** Reservoir area is selected as a case study for *** indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard ***,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,***,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation *** area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation ra

关键词： Baihetan SBAS-InSAR SSA-BP Landslide hazard susceptibility evaluation

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Gas Holder Levels Prediction with Multi-Working Conditions Identified by Change Point Detection

Gas Holder Levels Prediction with Multi-Working Conditions I...

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Asian control Conference

作者： Zihe Yang Long Chen Jun Zhao Wei Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The operation of gas holders in steel industry presents complex characteristics due to various factors such as ambient temperature and piston tilt, leading to multiple working conditions. To address this, the paper proposes a gas holder levels prediction method based on time series change point detection, where the real-time data are identified to find the shifts in working conditions and thereby achieves the enhancement of prediction accuracy. To investigate the relationship between the difference of the production and consumption flows and gas holder levels, a deviation series is constructed to capture the deviation between by-product gas production-consumption difference and changes in gas holder levels. Subsequently, the Bayesian method is employed for online detection of the change of the mean in these deviation series. Building upon the outcomes of change point detection, a multi-model switching-based approach employing least squares support vector machine (LSSVM) is designed for online prediction of gas holder levels. Using the actual production data from a steel enterprise for experiments, the proposed method is verified that it can effectively detect the change point across multiple operating conditions, and substantially improve gas holder levels prediction accuracy.

关键词： Employee welfare Training Adaptation models Accuracy Time series analysis Production Switches

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Development of an Automatic Sweet Pepper Harvesting Robot and Experimental Evaluation

Development of an Automatic Sweet Pepper Harvesting Robot an...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Qinghui Pan Dong Wang Jie Lian Yongxiang Dong Chaochao Qiu Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education and the School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The aging population and diminishing working population in agriculture motivate the development of autonomous harvesting robots. Although autonomous harvesting is expanding rapidly, the commercial application of sweet pepper harvesting robots still faces challenges. This paper presents the development of a sweet pepper harvesting robot and reports its experimental verification, which mainly includes end-effector design, visual perception, and grasping pose control. The end-effector adopts electrical control, mainly composed of a servo-electric two-finger parallel clamping module, a swing-cutting module, and a fruit recovery device. Equipped with a tactile sensor array, it can accurately sense the sweet pepper peduncle position and the end-effector state (harvesting failure) to complete the precise cutting. An end-effector grasping pose control algorithm of the manipulator is proposed, which can control the end-effector to grasp along the direction of the fruit peduncle and perpendicular to the tangent direction of the picking point by estimating the pose of the sweet pepper peduncle. Finally, the robot and proposed method were verified in a plant factory. The experimental findings demonstrate that the developed harvesting robot can complete robust detection of fruit peduncles and non-destructive picking of sweet pepper, with an average picking time of about 15 seconds.

关键词： Sociology Tactile sensors Grasping End effectors Production facilities Sensors Statistics

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Event-Triggered Prediction of Blast Furnace Gas Generation Based on a Trend Self-Adaption Scheme

Event-Triggered Prediction of Blast Furnace Gas Generation B...

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Asian control Conference

作者： Guanglin Cong Long Chen Jun Zhao Feng Jin Wei Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The prediction of blast furnace gas (BFG) generation in ironmaking processes is crucial for the BFG scheduling work. Due to frequent switching of working conditions of the ironmaking process, the generation of BFG under each working condition fluctuates greatly. It is difficult to predict accurately during the transition of working conditions. In order to address these problems, this paper proposes a data-driven BFG generation prediction method based on a combination of an event-triggered scheme and a trend self-adaption scheme. In this method, different working conditions are divided by events such as the change of supply of hot air and oxygen. Considering the process characteristics of air reduction and restoration, the decrease and increase trends are predicted by a parameter adaption-based linear logarithmic regression. The model parameters are corrected online to realize trend self-discrimination. Besides, as for the residual sequence after trend fitting, it is modeled by using the long short-term memory (LSTM) network. To validate the effectiveness of the proposed method, actual industrial field data of a steel plant in China are utilized. Simulation experimental results show that the proposed method significantly improves prediction accuracy of the BFG generation flow.

关键词： Employee welfare Adaptation models Atmospheric modeling Time series analysis Switches Predictive models Market research

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A Multi-Task Learning Framework for Load Identification and Signal De-Noising

A Multi-Task Learning Framework for Load Identification and ...

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IEEE International Conference on Robotics and Biomimetics

作者： Chenming Zhang Jiahao Jiang Xiang Li Zhelong Wang Sen Qiu Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of the Ministry of Education and the School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Non-intrusive Load Monitoring (NILM) represents a cost-efficient technological advancement in meticulously monitoring electricity consumption patterns. However, external noise interference in practical load identification poses challenges for accurate monitoring. To address this, a multi-task learning framework is proposed, concurrently tackling load identification and signal de-noising. To extract effective information from load signals, a novel feature representation called variational mode decomposition-instantaneous amplitude (VMD-IA) was introduced. To ensure optimal performance across the different tasks, a multi-gate mixture of expert architecture (MMOE) module is integrated into the proposed model. The proposed approach was evaluated on a self-collected load dataset, as well as public NILM datasets. The experimental results indicate that the proposed model outperforms state-of-the-art methods in all tasks.

关键词： Load monitoring Noise Logic gates Feature extraction Multitasking Robustness Signal denoising Data mining Robots Load modeling

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A generative deep learning framework for airfoil flow field prediction with sparse data

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Chinese Journal of Aeronautics 2022年第1期35卷 470-484页

作者： Haizhou WU Xuejun LIU Wei AN Hongqiang LYU MIIT Key Laboratory of Pattern Analysis and Machine Intelligence College of Computer Science and TechnologyNanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Aerodynamic Noise Control Mianyang 621000China State Key Laboratory of Aerodynamics Mianyang 621000China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 210023China College of Aerospace Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China

Deep learning has been probed for the airfoil performance prediction in recent *** with the expensive CFD simulations and wind tunnel experiments,deep learning models can be leveraged to somewhat mitigate such expenses with proper ***,effective training of the data-driven models in deep learning severely hinges on the data in diversity and *** this paper,we present a novel data augmented Generative Adversarial Network(GAN),daGAN,for rapid and accurate flow filed prediction,allowing the adaption to the task with sparse *** presented approach consists of two modules,pre-training module and fine-tuning *** pre-training module utilizes a conditional GAN(cGAN)to preliminarily estimate the distribution of the training *** the fine-tuning module,we propose a novel adversarial architecture with two generators one of which fulfils a promising data augmentation operation,so that the complement data is adequately incorporated to boost the generalization of the *** use numerical simulation data to verify the generalization of daGAN on airfoils and flow conditions with sparse training *** results show that daGAN is a promising tool for rapid and accurate evaluation of detailed flow field without the requirement for big training data.

关键词： CFD Flow field Generative adversarial networks(GANs) Sparse data Supercritical airfoil

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Effects of hydroxyproline supplementation in low fish meal diets on collagen synthesis,myofiber development and muscular texture of juvenile Pacific white shrimp(Litopenaeus vannamei)

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Animal Nutrition 2024年第2期17卷 428-437页

作者： Menglin Shi Haoming Li Tianyu Chen Bocheng Huang Xiaoyue Li Xiaohui Dong Shuyan Chi Qihui Yang Hongyu Liu Junming Deng Beiping Tan Shuang Zhang Shiwei Xie Laboratory of Aquatic Nutrition and Feed College of FisheriesGuangdong Ocean UniversityZhanjiang 524088China Aquatic Animals Precision Nutrition and High-Efficiency Feed Engineering Research Centre of Guangdong Province Zhanjiang 524088China Key Laboratory of Aquatic Livestock and Poultry Feed Science and Technology in South ChinaMinistry of AgricultureZhanjiang 524088China Guangdong Provincial Key Lab of Aquatic Animals Disease Control and Healthy Culture Zhanjiang 524088China

This experiment aimed to evaluate the impact of dietary hydroxyproline(Hyp)supplementation on the muscle quality of juvenile Pacific white shrimp(Litopenaeus vannamei)fed a low fishmeal *** formulated diets included one high fishmeal(HF;25%fishmeal content)and five low fishmeal diets(10%fishmeal content)with 0%,0.2%,0.4%,0.6%and 0.8%Hyp(LFO,LF2,LF4,LF6 and LF8,respectively).Each diet was assigned to four replicates,and 40 shrimp(0.32±0.00 g)per replicate were fed four times a day for 8 *** Hyp supplementation had little effects on growth performance,but increased the contents of Hyp,prolyl 4-hydroxylases(P4Hs),and *** meat yield,springiness,hardness,chewiness,and cohesiveness of muscle were the highest in the LF4 group among the low fishmeal groups(P<0.05).Cooking loss and freezing loss of muscle were the lowest in the LF4 group(P<0.05).Dietary supplementation with 0.4%Hyp increased the myofiber density and decreased the myofiber diameter of muscle(P<0.05).Supplementation of Hyp in the diet up-regulated the mRNA expression of smyhc5,smyhc15,col1a1,col1a2,igf-1f,tgf-β and tor and down-regulated the mRNA expression of smy hc1,smyhc2,smyhc6a(P<0.05).Supplementation of Hyp in the diet up-regulated the protein expression of P-4E-BP1,P-AKT,AKT and P-AKT/AKT(P<0.05).These results suggested that the addition of 0.4%Hyp to low fishmeal diets improved the muscle quality of ***.

关键词： Hydroxyproline Collagen Muscle quality Litopenaeus vannamei

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Active Fault Diagnosis for Gas-Steam Combined Cycle Power Plant Considering Variable Working Conditions

Active Fault Diagnosis for Gas-Steam Combined Cycle Power Pl...

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Asian control Conference

作者： Yang Han Demin Xu Fan Zhou Ying Liu Jun Zhao Wei Wang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

The gas-steam combined cycle power plant (CCPP) is one of the important energy conversion equipment in iron and steel energy systems., which can utilize the by-product gas to supply power in industrial parks. Due to the complexity of the environment in which the equipment is located., the components of the equipment., including actuators., compressors and combustion chambers., are prone to fault. Especially., the fault information contained in the data is not sufficient when the early fault occurs., it is difficult to fault diagnosis. For this problem., this paper proposes an active fault diagnosis (AFD) method for CCPP considering variable working conditions. Firstly., the system state is estimated by the zonotopic observer., and then the state output set affected by the unknown disturbance is described by the zonotopes. Finally., in order to realize the application of AFD under variable working conditions of the equipment., the auxiliary signal is designed to sperate the state set of the normal model and the fault model under variable working conditions. The experimental results show that the proposed method has good fault diagnosis ability under variable working conditions.

关键词： Employee welfare Fault diagnosis Measurement Energy conversion Observers Iron Compressors

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Universal Trajectory Optimization Framework for Differential-Driven Robot Class

arXiv

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arXiv 2024年

作者： Zhang, Mengke Chen, Nanhe Wang, Hu Qiu, Jianxiong Han, Zhichao Ren, Qiuyu Xu, Chao Gao, Fei Cao, Yanjun The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China

Differential-driven robots are widely used in various scenarios thanks to their straightforward principle, from household service robots to disaster response field robots. There are several different types of deriving mechanisms considering the real-world applications, including two-wheeled, four-wheeled skid-steering, tracked robots, etc. The differences in the driving mechanism usually require specific kinematic modeling when precise controlling is desired. Furthermore, the nonholonomic dynamics and possible lateral slip lead to different degrees of difficulty in getting feasible and high-quality trajectories. Therefore, a comprehensive trajectory optimization framework to compute trajectories efficiently for various kinds of differential-driven robots is highly desirable. In this paper, we propose a universal trajectory optimization framework that can be applied to differential-driven robot class, enabling the generation of high-quality trajectories within a restricted computational time-frame. We introduce a novel trajectory representation based on polynomial parameterization of motion states or their integrals, such as angular and linear velocities, that inherently matching robots’ motion to the control principle for differential-driven robot class. The trajectory optimization problem is formulated to minimize complexity while prioritizing safety and operational efficiency. We then build a full-stack autonomous planning and control system to show the feasibility and robustness. We conduct extensive simulations and real-world testing in crowded environments with three kinds of differential-driven robots to validate the effectiveness of our approach. We will release our method as an open-source package Copyright © 2024, The Authors. All rights reserved.

关键词： Four wheel steering

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