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2022 2nd International Conference on power Grid systems and Green Energy, PGSGE 2022

作者： Zhang, Tieyan Yang, Junbao Zhao, Tao Li, Min Zhang, Dawei Wang, Yuri Shenyang Ligong University China Shenyang Institute of Engineering China Key Laboratory of Regional Multi-energy System Integration and Control of Liaoning Province China GD Hefeng Wind Power Development Co. Ltd. China Liaoning Shengfang Electric Power Technology Co. Ltd. China Benxi High-Tech Industrial Development Zone Power Supply Branch State Grid Liaoning Electric Power Co. Ltd. China

In order to effectively evaluate the impact of wind power connection on the operation of the colding-heating-electricity interconnection system, a probabilistic energy flow calculation method based on the semi-invariant method and improved K-means is proposed. First, a colding-heating-electricity joint system model was established. Secondly, based on the semi-invariant method, an improved K-means clustering technique was proposed to solve the problems caused by different input random sample types. Finally, the efficiency of the proposed method is verified by simulation. © Published under licence by IOP Publishing Ltd.

关键词： Wind power

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Experimental study of smart buildings providing fast frequency response

Experimental study of smart buildings providing fast frequen...

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Energy, power and Grid (ICEPG), International Conference on

作者： Zhendong Zhao Longjun Wang Zhihui Deng Yiping Chen Shunxin Wei Ziqiang Wang School of Electric Power South China University of Technology Guangzhou China DC building laboratory Shenzhen Building Science Research Institute Co. LTD Shenzhen China Southern Power Grid Southern Power Grid New Power System (Beijing) Research Institute China Beijing China Shien-ming wu school of intelligent engineering South China University of Technology Guangzhou China Power dispatch control center Shenzhen Power Supply Bureau Co. LTD Shenzhen China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

As the penetration of renewable energy increases, the mechanical inertia of the power system decreases, weakening the system’s ability to withstand disturbances, particularly during large frequency events. Smart buildings on the demand side show promise as candidates for providing frequency regulation. This paper presents a fast frequency response test for smart buildings. A series of tests, including frequency step tests, frequency ramp tests, and hybrid tests, were conducted to assess the fast frequency response performance of smart buildings. The results indicate that the building has regulation capabilities comparable to traditional generator units in primary frequency control and demonstrates strong potential for fast frequency response. These findings are now being used to guide the development of standards for demand-side adjustable resources participating in fast frequency response.

关键词： Technical requirements Renewable energy sources Smart buildings Frequency response Regulation Generators Voltage control Protection Frequency control Standards

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Short-Term Multi-Energy Load Forecasting Based on Feature Reconstruction and TCN-Informer

Short-Term Multi-Energy Load Forecasting Based on Feature Re...

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IEEE Student Conference on Electric Machines and systems

作者： Mofan Wei Jiaqi Shi Tieyan Zhang Yan Zhao He Jiang Yutong He School of Electrical Engineering Shenyang University of Technology Shenyang China Key Laboratory of Regional Multi-energy System Integration and Control of Liaoning Province Shenyang China Huadian Electric Power Research Institute CO. LTD. Shenyang China

ISBN: (数字)9798350366945

ISBN: (纸本)9798350366952

With the diversification of user energy and coordinated operation development of the integrated energy system, the coupling relationships between different energies becomes increasingly complex, which brings great challenges to short-term multi-energy load forecasting. Considering inadequate correlation analysis of influence factors and insufficient model learning ability to implicit coupling relationships, a short-term multi-energy load forecasting method is proposed based on feature reconstruction and TCN-informer. Firstly, the day-scale feature is screened and optimal feature sets are reconstructed via correlation analysis between load and influence factor time series in specific date. Secondly, combining TCN and informer network, the multi-energy load forecasting model is built via multi-task learning architecture. The input layer is composed of TCN, which can extract key information and temporal correlation of the input data. The shared layer is composed of Informer network, which can excavate inner relation between different loads effectively. Finally, simulation data sets generate from integrated energy system of the Tempe campus at Arizona State University. Prediction indicator comparison confirms effectiveness and superiority of feature reconstruction and TCN-informer multi-energy load forecasting model.

关键词： Couplings Correlation Load forecasting Time series analysis Neural networks Predictive models Reconstruction algorithms Feature extraction Data mining Load modeling

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Localization Method of Underwater Robot Based on Sonar Image 5

Localization Method of Underwater Robot Based on Sonar Image

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5th International Conference on Information Communication and Signal Processing, ICICSP 2022

作者： Li, Lirong Mei, Bing Chen, Peng Yu, Liang Gong, Pengcheng Hubei University of Technology Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Wuhan China Hubei University of Technology Hubei Engineering Research Center for Safety Monitoring of New Energy and Power Grid Equipment Wuhan China School of Mechanical Engineering Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai China School of Computer Science & Engineering Wuhan Institute of Technology Wuhan China

ISBN: (纸本)9781665485890

In this paper, we propose a positioning algorithm based on sonar images, which is mainly used for the positioning of underwater robots, so that the robots can obtain the position information in real time when operating underwater and avoid colliding with the underwater walls. First, the underwater space was detected with multibeam sonar, and the sonar images of the underwater space wall were found to have line segment characteristics;Composite denoising, threshold segmentation and Canny edge detection are applied to the sonar image to extract the contours of the underwater spatial wall. Then the characteristic line segments of the underwater spatial wall are detected based on the LSD (Line Segment Detector) line segment detection algorithm. In terms of line segment classification, a method is proposed to effectively classify line segments using the origin of the sonar image and the slope of the detected line segment. To further demonstrate the effectiveness of the localization algorithm in this paper, the specific steps of the algorithm are illustrated with the example of underwater rectangular space. © 2022 IEEE.

关键词： Image segmentation

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Adaptive Variable Step Size Photovoltaic MPPT Algorithm Based on Light Intensity Prediction

Adaptive Variable Step Size Photovoltaic MPPT Algorithm Base...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Ba Gui Jingtian Bi Haoqing Xiong Ping Wu Jie Wu Jianping Yu Dispatch Control Center State Grid Tibet Electric Power Company Limited Lhasa Tibet China Power System Research Department China Electric Power Research Institute Beijing China Power System Research Department State Grid Tibet Electric Power Company Limited/State Grid Henan Electric Power Company Lhasa Tibet/Zhengzhou Henan China College of Energy and Electrical Engineering Hohai University Nanjing Jiangsu China

To enhance the efficiency and stability of maximum power point tracking (MPPT) in photovoltaic (PV) power generation systems, and to address the issue of misjudgment in the traditional perturbation and observation method (P&O), an adaptive MPPT control approach based on light intensity prediction is proposed. Firstly, the correlation between the input and output of the system is analyzed to determine the necessary input terms. Secondly, the multi-time series LSTM algorithm is utilized to select pertinent historical PV sequence information according to the correlation analysis results, enabling short-term prediction of PV output. Finally, the Boost circuit is employed as the control object, with the light intensity prediction result serving as the input to adaptively adjust the step size of the P&O. Through the MATLAB/Simulink simulation platform, the results demonstrate that the adaptive variable step size photovoltaic MPPT algorithm based on light intensity prediction can effectively mitigate power oscillation in steady state while exhibiting good tracking speed and accuracy.

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Revealing the Role of Defect in 3D Graphene-Based Photocatalytic Composite for Efficient Elimination of Antibiotic and Heavy Metal Combined Pollution

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Energy & Environmental Materials 2024年第3期7卷 164-174页

作者： Xin Wang Jingzhe Zhang Hui Wang Mengjun Liang Qiang Wang Fuming Chen Research Institute of Frontier Science Southwest Jiaotong UniversityChengdu 610031China Guangdong Provincial Key Laboratory of Quantum Engineering and Quantum Materials School of Electronics and Information EngineeringSouth China Normal UniversityFoshan 528225China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of TechnologyWuhan 430068China MOE Key Laboratory of Thermo-Fluid Science and Engineering School of Energy and Power EngineeringXi'an Jiaotong UniversityXi'an 710049China

Defect engineering can give birth to novel properties for adsorption and photocatalysis in the control of antibiotics and heavy metal combined pollution with photocatalytic ***,the role of defects and the process mechanism are complicated and ***,TiO_(2)/CN/3DC was fabricated and defects were introduced into the tripartite structure with separate O_(2)plasma treatment for the single *** find that defect engineering can improve the photocatalytic activity,attributing to the increase of the contribution from h^(+)and *** contrast to TiO_(2)/CN/3DC with a photocatalytic tetracycline removal rate of 75.2%,the removal rate of TC with D-TiO_(2)/CN/3DC has increased to 88.5%.Moreover,the reactive sites of tetracycline can be increased by adsorbing on the defective *** defect construction on TiO_(2)shows the advantages in tetracycline degradation and Cu^(2+)adsorption,but also suffers significant inhibition for the tetracycline degradation in a tetracycline/Cu^(2+)combined *** contrast,the defect construction on graphene can achieve the cooperative removal of tetracycline and Cu^(2+).These findings can provide new insights into water treatment strategies with defect engineering.

关键词： 3D graphene Cu defect photocatalytic composite tetracycline

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An Advanced control Strategy for Bidirectional Isolated Three Phase AC/DC Dual-Active-Bridge Converter in Hybrid Microgrid 5

An Advanced Control Strategy for Bidirectional Isolated Thre...

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5th IEEE Conference on Energy Internet and Energy system Integration, EI2 2021

作者： Guo, Dongxin Wang, Panbao Kong, Jiansheng Tian, Jinjie Ren, Chunguang Meng, Xiangqi Jia, Yanbing Qin, Yue Wang, Zeqi Shanxi Key Lab. of Power System Operation and Control Taiyuan University of Technology Taiyuan China Department of Electrical Engineering Harbin Institute ofTechnology Harbin China Datong Power Supply Company State Grid Shanxi Electric Power Company Datong China School of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China

ISBN: (纸本)9781665434256

This paper proposes an advanced control strategy consisting of current stress optimization based on triple-phase-shifting (TPS) modulation for front-end DAB converter and 33% PWM method for back-end three-phase full bridge inverter. Compared with the traditional phase shift control, the control strategy proposed for the front-end DAB converter achieves linear control and significantly reduces current stress. In addition, it reduces the DC-Link capacitance, which improves the safety of the equipment. The 33% modulation method adopted by the full bridge inverter at the back-end reduces the switching loss of semiconductor devices. The principle, derivation and realization of the proposed control strategy are described in detail. Simulation results are presented to validate the effectiveness of the proposed strategy. © 2021 IEEE

关键词： Pulse width modulation

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Wide-Area Damping control Enhanced by Non-Invasive Data Verification Against False Data Injection Attacks

SSRN

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SSRN 2024年

作者： Sun, Zhenglong Long, Hao Li, Zewei Gao, Bo Wei, Xiaoqiang Belikov, Juri Levron, Yoash Department of Electrical Engineering Key Laboratory of Modern Power System Simulation and Control & Renewable Energy State Grid Jiashan County Power Supply Company Jiaxing China State Grid Heilongjiang Electric Power Company Limited Heilongjiang China The Andrew and Erna Viterbi Faculty of Electrical Engineering Technion Israel Institute of Technology Haifa Israel Department of Software Science Tallinn University of Technology Tallinn Estonia Northeast Electric Power University China

The increasing interconnectivity of power systems and the integration of renewable energy sources into the grid have exacerbated the low-frequency oscillation problem, which directly impacts the stability of the power grid. The performance of wide-area damping control (WADC), which is an effective oscillation suppression technique , is susceptible to false data injection attacks (FDIA). This study proposes a non-intrusive data verification method using an adaptive variational autoencoder (AVAE) combined with a deep convolutional neural network (DCNN) to enhance WADC’s resistance to FDIA. The method integrates data dimensionality reduction of AVAE and reconstruction capabilities with DCNN’s feature extraction advantages. Itemploys adaptive thresholds to dynamically track grid data fluctuations, accurately distinguishing between normal and abnormal measurements and improving attack detection and performance discrimination. In addition, the study proposes an intelligent repair process based on latent representations for anomalous data in the repair module, using hierarchical clustering and Gaussian mixture models post-Bayesian inference to repair data. AVAE then reconstructs the repaired data, mitigating attack impacts. Simulations on IEEE 39-Bus, 68-Bus, and 118-bus systems demonstrate that this method effectively detects network attacks and restores manipulated signals with minimal reconstruction errors, thus ensuring grid stability and reliability. © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Minimax Regret Robust Co-Planning of Transmission and Energy Storage systems With Mixed Integer Recourse

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IEEE Transactions on Sustainable Energy 2025年

作者： Barkom, Ehsan Saber, Hossein Moeini-Aghtaie, Moein Ehsan, Mehdi Shahidehpour, Mohammad Sharif University of Technology Center of Excellence in Power System Control and Management Department of Electrical Engineering Tehran11365-11155 Iran Sharif University of Technology Department of Energy Engineering Tehran Iran Illinois Institute of Technology Robert W. Galvin Center for Electricity Innovation ChicagoIL60616 United States King Abdulaziz University Jeddah Saudi Arabia

The growing penetration of renewable energy sources, with intermittent and uncertain nature, brings new challenges to the secure and efficient operation of power systems. Expanding transmission networks and utilizing energy storage (ES) have been introduced as effective solutions to address these challenges. This paper presents a minimax regret robust co-planning model with mixed integer recourse for transmission and ES systems, designed from the perspective of a central planner. The model considers a polyhedral uncertainty set for future peak load growth, while uncertainties in wind farm expansion are addressed through internal scenario analysis. This approach will guarantee the robustness of investment decisions and provide the central planner with a clear picture of the maximum regret among all possible scenarios. Furthermore, the proposed minimax regret framework facilitates strategic planning for ES installation after the resolution of long-term uncertainties. In this paper, we reformulate the model into a standard min-max-min problem, in which the maximization level is only over uncertainties. Subsequently, a five-level solution strategy based on a modified nested column and constraint generation decomposition technique is represented to deal with the intractability and complexity of the problem caused by binary variables of transmission lines and ES blocks. The model is finally evaluated through comprehensive simulation studies to verify its tractability, practicality, and effectiveness. © 2010-2012 IEEE.

关键词： Adaptive robust optimization energy storage minimax regret planning studies transmission expansion uncertainties

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Dynamic Security Evaluation Method for power systems Considering Cascading Failures

Dynamic Security Evaluation Method for Power Systems Conside...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Ren Liu Xingye Xu Wei Du Kaishun Xiahou Yihua Zhu Dongxu Chang Hengdao Guo CSG Key Laboratory for Power System Simulation Electric Power Research Institute of China Southern Power Grid Guangzhou China School of Electric power engineering South China University of Technology Guangzhou China State Key Laboratory of HVDC Electric Power Research Institute of China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre China Southern Power Grid Guangzhou China Guangdong Provincial Key Laboratory of China Southern Power Grid Intelligent Operation and Control for New Energy Power System Guangzhou China

With the increasing level of informatization and interconnection in the electric power system, the risk of external attacks on power systems is increasing. In response to the drawbacks of traditional static security assessment methods, this paper establishes two security metrics, which are voltage and power flow amplitude deviation security metric and power flow entropy security metric. Based on these security metrics, a dynamic security evaluation model that considers cascading failure is proposed. Simulation results demonstrate that the proposed security metrics can effectively reflect the security of cascading failure propagation, thereby providing valuable insights for decision-making by power system operators.

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