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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Yu, Hong Chen, Xi Zhang, Letian Wei, Lin Yang, Linlin Wang, Zixu State Grid Jinan Power Supply Company Jinan China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Shandong Electric Power Company Jinan China

ISBN: (纸本)9798350346671

The electric energy consumption data of marketoriented customers must be perfectly metered or accurately fitted, that is essential for the construction of electricity spot market. The electricity consumption behavior of market-oriented customers is complex and variable, to address the issue that the patterns of the electricity consumption data are difficult to be accurately characterized, an orthogonal polynomial neural network-based data fitting model of electric energy consumption is established. The model is implemented using Chebyshev orthogonal polynomials, Hermite orthogonal polynomials, Legendre orthogonal polynomials, and Laguerre orthogonal polynomials respectively, while the neural network weight coefficients are trained by gradient descent algorithm. The results show that the fitting effect of the same type of electricity consumption data differs significantly among different implementation methods. The neural network models using Hermite orthogonal polynomials and Laguerre orthogonal polynomials have higher fitting accuracy than other models. It is an effective way to achieve accurate data fitting of customer electricity consumption by selecting the corresponding fitting method according to the type of electricity consumption behavior. © 2023 IEEE.

关键词： Curve fitting

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Power system Load Restoration Based on Data-Driven Constraints Linearization Method

Power System Load Restoration Based on Data-Driven Constrain...

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International Conference on Power and Energy Technology (ICPET)

作者： Xiaoting Lv Hongtao Wang Xuemei Fan Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

In recent years, power outages have occurred frequently around the world, and rapid load recovery after power outages can reduce economic losses caused by power outages. In the restoration model, the power flow calculation is a nonlinear equality constraint. The idea based on mathematical optimization is to linearize the power flow equation based on certain assumptions or perform convex relaxation. Such processing may affect the solution accuracy or speed. Therefore, a data-driven constraints linearization method is proposed, using a large amount of simulation data to linearly fit the power flow through the partial least square method. Then, based on the linear constraints, the load restoration problem is established as a mixed integer linear programming (MILP) problem to reduce the difficulty of solving, improve calculation accuracy and provide dispatchers with optimal recovery decisions. Finally, the validity of the method proposed in this paper is verified in IEEE39 node system.

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River Turbidity Monitoring Based on Semi-supervised Transfer Learning 9th

River Turbidity Monitoring Based on Semi-supervised Transfe...

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9th International Forum on Digital Multimedia Communication, IFTC 2022

作者： Xie, Shuangyi Liao, Xin Bai, Ruxue Zhou, Chengxu Gu, Ke Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Laboratory of Smart Environmental Protection Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China School of Electronic and Information Engineering Liaoning University of Technology Liaoning China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China

ISBN: (纸本)9789819908554

River turbidity is an important index to evaluate the quality of water environment, which is of great significance to environmental monitoring. Most of the existing monitoring methods rely on turbidity labels measured by river water quality monitoring stations. However, due to the limitation of spatial distribution of water quality monitoring stations, those turbidity data outside the monitoring range are difficult to obtain and the correlation of turbidity data between monitoring stations is poor. Using such data directly might weaken the generalization ability that the model has. In this paper, we propose a new river turbidity monitoring model based on semi-supervised transfer learning (RTMM-SSTL) to solve these problems. First, in the pre-training stage, we innovatively propose a semi-supervised training method combined with big data with pseudo labels for river turbidity monitoring to solve the problem of weakened model generalization ability. Then, the model is fine-tuned using GEE hyper spectral data with ground truth to further improve the monitoring capability of the model. Experiments conducted on the river turbidity monitoring task demonstrate that the proposed model is superior to the advanced learning models, and further proves that our semi-supervised transfer learning method performs better than the state-of-the-art supervision models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Rivers

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Multi-Objective Upgrade Planning Strategy for Harnessing Operational Flexibility of Coal-Fired Power Generators

Multi-Objective Upgrade Planning Strategy for Harnessing Ope...

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Power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Zhengxing Ren Xiaodong Chu Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China

The high penetration of renewable energy in power systems leads to significant net load fluctuations. Coal-fired power generators conventionally designed for baseload operations are expected to be flexible with cycling operations. Necessary upgrades received by the power generators to improve their operational flexibility will cause associated costs. An upgrade planning strategy is proposed in this paper for harnessing operational flexibility of coal-fired power generators. First, a multi-objective optimization model of coal-fired power generators is established in which the upgrade cost, operating cost, and the upgraded load following capacity of three stages are comprehensively integrated. Next, an improved multi-objective particle swarm optimization algorithm is used to solve the proposed model. Finally, a multi-criteria decision making method is applied to select the best upgrade plan. The case study results of the IEEE 39-bus system demonstrate the feasibility and effectiveness of the proposed planning strategy.

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The Effect of Phase Locking Error on control of Grid-Connected Inverter in Distribution Network

The Effect of Phase Locking Error on Control of Grid-Connect...

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International Conference on Power system Technology (POWERCON)

作者： Wang Yuanqi Yun Zhihao Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

The phase-locked loop provides a phase reference for the coordinate transformation in grid-connected inverters to ensure synchronous operation and power output. In the distribution network, under the conditions of three-phase unbalance because of the diversity of loads, untransposed line and the complex operating conditions, the phase-locked loop can produce phase locking errors that affect the inverter power output and thus the regulation of the active distribution network. Therefore, by analyzing the inverter control, the influence of phase error of the phase-locked loop on the Park transformation and modulation signal is deduced, and the relationship between phase error, voltage, current, current reference value, and modulation signal is quantified. The simulation results prove the correctness of the analysis.

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10-Hertz squeezed light source generation on the cesium D_(2)line using single photon modulation

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Frontiers of physics 2023年第3期18卷 167-174页

作者： Guan-Hua Zuo Yu-Chi Zhang Gang Li Peng-Fei Zhang Peng-Fei Yang Yan-Qiang Guo Shi-Yao Zhu Tian-Cai Zhang State Key Laboratory of Quantum Optics and Quantum Optics Devices Collaborative Innovation Center of Extreme OpticsInstitute of Opto-ElectronicsShanxi UniversityTaiyuan 030006China College of Physics and Electronic Engineering Shanxi UniversityTaiyuan 030006China Department of Physics Zhejiang UniversityHangzhou 310027China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China

Generation of squeezed light source is a promising technique to overcome the standard quantum limit in precision ***,we demonstrate an experimental generation of quadrature squeezing resonating on the cesium D_(2)line down to 10 Hz for the first *** maximum squeezing in audio frequency band is 5.57 ***,we have presented a singlephoton modulation locking to control the squeezing angle,while effectively suppressing the influence of laser noise on low-frequency *** whole system operates steadily for *** generated low-frequency squeezed light source can be applied in quantum metrology,light–matter interaction investigation and quantum memory in the audio frequency band and even below.

关键词： squeezed state optical parametric amplifier low-frequency squeezing

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Identification of Transient Voltage Stability Weakness in Power systems Based on Grad-CAM 7

Identification of Transient Voltage Stability Weakness in Po...

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7th IEEE International Conference on Power and Renewable Energy, ICPRE 2022

作者： Qin, Changlong Jia, Yujian Li, Zhendong Li, Guang Li, Li Zhu, Yuanzhen State Grid Jinan Power Supply Company Jinan China Shandong University Key Laboratory of Power System Intelligent Dispatch Control of Ministry of Education Jinan China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

With the changes in generation and load characteristics, transient voltage problems have a serious impact on the safe and stable operation of the power system. In this paper, on the basis of constructing a fast evaluation model of transient voltage stability based on convolutional neural network, the key electrical quantities that the model focuses on in the evaluation process are pointed out by Grad-CAM algorithm, and the weakness of system voltage stability are identified. The simulation results show that the proposed method can explore the links that are neglected by traditional methods, and the identified weakness consider both topological and state information, which verifies the superiority of the method in this paper. © 2022 IEEE.

关键词： Convolution

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3D printed-electrospun PCL/hydroxyapatite/MWCNTs scaffolds for the repair of subchondral bone

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Regenerative Biomaterials 2023年第1期10卷 294-305页

作者： Yanyan Cao Lei Sun Zixian Liu Zhizhong Shen Wendan Jia Peiyi Hou Shengbo Sang College of Information Science and Engineering Hebei North UniversityZhangjiakou 075000China Shanxi Key Laboratory of Micro Nano Sensors&Artificial Intelligence Perception College of Information and ComputerTaiyuan University of TechnologyTaiyuan 030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi Research Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China

Osteochondral defect caused by trauma or osteoarthritis exhibits a major challenge in clinical treatment with limited symptomatic effects at *** regeneration and remodeling of subchondral bone play a positive effect on cartilage regeneration and further promotes the repair of osteochondral *** use of the strengths of each preparation method,the combination of 3D printing and electrospinning is a promising method for designing and constructing multi-scale scaffolds that mimic the complexity and hierarchical structure of subchondral bone at the microscale and nanoscale,*** this study,the 3D printed-electrospun poly(ɛ-caprolactone)/nano-hydroxyapatites/multi-walled carbon nanotubes(PCL/nHA/MWCNTs)scaffolds were successfully constructed by the combination of electrospinning and layer-by-layer 3D *** resulting dual-scale scaffold consisted of a dense layer of disordered nanospun fibers and a porous microscale 3D scaffold layer to support and promote the ingrowth of subchondral ***,the biomimetic PCL/nHA/MWCNTs scaffolds enhanced cell seeding efficiency and allowed for higher cell-cell interactions that supported the adhesion,proliferation,activity,morphology and subsequently improved the osteogenic differentiation of bone marrow mesenchymal stem cells in ***,this study elucidates that the construction of 3D printed-electrospun PCL/nHA/MWCNTs scaffolds provides an alternative strategy for the regeneration of subchondral bone and lays a foundation for subsequent in vivo studies.

关键词： additive manufacturing 3D printing electrospinning subchondral bone

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Online Cascading Failure Searching Based on Gradient Boosting decision Tree

Online Cascading Failure Searching Based on Gradient Boostin...

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Power Tech Conference

作者： Tianhao Liu Yutian Liu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

With the penetration of renewable energy sources (RES) increasing rapidly, cascading failures become more complex due to the uncertainty and vulnerability of RES. This paper presents an online cascading failure searching method based on gradient boosting decision tree (GBDT) for the hybrid AC/DC system with high penetration of wind power. First, the cascading failure risk index is established, which considers the impact, probability, and loss of failures. Then, a cascading failure searching based on Monte Carlo tree search and dynamic simulation is performed to acquire the high-risk cascading failures, which are utilized as the training samples. Finally, GBDT is deployed to construct the relationship between operating conditions and failure propagation directions. Online cascading failure searching is realized by combining GBDT failure estimation and dynamic failure simulation. Simulation results of the modified New England 39-bus test system demonstrate that the proposed method can fast and accurately online screen the high-risk cascading failures considering the uncertainty of wind power.

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A novel feature enhancement module for small object detection

A novel feature enhancement module for small object detectio...

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Wang, Ruogu Li, Ning Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (纸本)9781728119489

Generic object detection has made great progress in recent years, yet small object detection is still facing a serious problem of missed detection. The problem is caused by two reasons: low resolution in small targets and feature loss during deep convolution downsampling. Some previous studies used feature pyramid structures and multi-scale training predictions to alleviate this problem, but still cannot efficiently utilise the feature information of small targets. In this paper, firstly we propose a novel and effective feature enhancement module to extract more features;secondly, a filter size design method is presented to extract features of matching objects and incorporate context information;finally, an adaptive fusion method is used to process outputs of our module and improve model robustness. We select YOLOv3 as base model and carry out several experiments on a special Small Object Dataset and the results show that our work can achieve an increase of about seven percentage points (35.73%) compared to 28.78% on baseline. © 2022 IEEE.

关键词： Object detection

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