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检索条件"机构=Key Laboratory of Intelligent Dispatching and Control of Power Grid"

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A Practical Reference Network Planning Model Based on Load Moment and Acceptable Range

A Practical Reference Network Planning Model Based on Load M...

引用

power Science and Technology (ICPST), IEEE International Conference on

作者： Jianjie Li Wentao Zhong Mingliang Mu Jialiang Wang State Grid Shandong Province Power Company Binzhou Power Supply Company Binzhou China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

There is a big gap between theoretical research and practical application of reference network planning. Most of the existing planning models in academic research take cost as the objective function. Although various advanced models and methods are proposed based on this, they are rarely applied in actual power companies. In this paper, a new reference network planning model is proposed according to the actual demand. According to the field investigation, "power supply to the nearest load" is taken as the goal, and the load moment is expressed analytically. In order to meet the increasing demand of renewable energy integrating into the power grid, the concept of acceptable disturbance range is added to the model constraint to improve the system's absorption capacity of renewable energy. Finally, the N-1 security constraint is considered to improve the reliability of the model. The model is transformed into a mixed integer linear programming (MILP)problem by priority objective programming method and can be solved with mature commercial solvers. The validity of the model is verified by IEEE-RTS24 node system. When N-1 safety constraints are taken into account, the advantages of the proposed model become apparent, with a total cost reduction of about 2.5%.

关键词： Renewable energy sources Costs power supplies Biological system modeling Programming Minimization Planning

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Medium and Long Term Scenario Generation Method Based on Autoencoder and Generation Adversarial Network

Medium and Long Term Scenario Generation Method Based on Aut...

引用

Neural Networks, Information and Communication Engineering (NNICE), International Conference on

作者： Boya Peng Zhiyuan Sun Mosi Liu Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electrical Power Research Institute of Guangxi Power Grid Co. Ltd Nanning China

With the proposal of carbon peak and carbon neutrality target, developing renewable energy power generation technology is imperative, accurate simulation for renewable energy power characteristics provides important guarantee for reliable operation of power system. In view of the difficulty in simulating the sequentiality and uncertainty of medium and long-term output scenarios, this paper proposes a medium and long-term scenario generation method based on stacked autoencoder (SAE) and improved conditional generative adversarial networks(CWGAN_GP). Firstly, the ability of automatic feature extraction based on SAE to extract hidden features efficiently, which reduces dimensions for high dimensional series. Secondly, feature weighted K-means clustering method and CWGAN_GP are used to generate typical medium and long term scenarios. Finally, a case is used to verify the effectiveness and serviceability of the proposed method for the simulation that has medium and long-term scenarios with sequentiality and uncertainty.

关键词： Renewable energy sources Uncertainty power system stability Feature extraction Stability analysis Generators power system reliability

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Fast Transient Voltage Stability Assessment for Complex Receiving-End power grid

Fast Transient Voltage Stability Assessment for Complex Rece...

引用

IEEE International Conference on power and Energy Applications (ICPEA)

作者： Xiyang Liu Tianhao Liu Yutian Liu Zhendong Li Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Laiwu Power Supply Company State Grid Shandong Electric Power Company Laiwu China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

The continuous increase of new energy generation and AC-DC interconnection make the transient voltage stability of the receiving-end power grid more and more complicated. In order to realize the rapid assessment of transient voltage stability, a one-dimensional Convolutional Neutral Network (CNN) for transient voltage stability assessment (TVSA) is constructed by selecting the features reasonably on the basis of using the Agglomerative Hierarchical Clustering (AHC) algorithm to partition the receiving-end grid. In order to enhance the assessment work, the Gradient-weighted Class Activation Mapping (Grad-CAM) algorithm is utilized to find out the concerns of the model to features, and the model knowledge of the neural network is analyzed on the basis of surveying on a large number of samples. Based on the transient voltage stability mechanism and the concerns of deep learning model, the factors that cause transient voltage instability are analyzed. The effectiveness of the proposed method is demonstrated by the case study of a provincial grid in eastern China.

关键词： Knowledge engineering Analytical models Voltage power system stability Stability analysis power grids Partitioning algorithms Convolutional neural networks Transient analysis Voltage control

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Low Voltage Distribution Network Reliability Indicator System and Risk Assessment Methodology

Low Voltage Distribution Network Reliability Indicator Syste...

引用

power and Energy (PandaFPE), Panda Forum on

作者： Chenying Yi Yangjun Zhou Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Co. Ltd Nanning China

The development of a suitable low-voltage distribution network reliability evaluation index system is one of the important concerns since the current distribution network reliability indexes cannot effectively reflect the reliability level of customers. The evaluation index system is created in accordance with the low-voltage distribution network's characteristics, and the combination assignment technique is used to carry out the risk assessment of the low-voltage distribution network's reliability. At present, the reliability evaluation index system of low-voltage distribution network is mainly composed of user-side index and system-side index. First, the reliability evaluation index system is built on three tiers: equipment, user, and system, depending on the load characteristics and low-voltage distribution network operation mode. The user-side reliability index and system reliability index reflect the real power consumption of low-voltage users and the reliability of low-voltage distribution network power supply respectively. Then, the combined weighting method of hierarchical analysis-inverse entropy weighting method is used to obtain the comprehensive evaluation value of the evaluation object as the basis for risk judgment. Finally, the validity of the proposed index system and risk evaluation method is verified through case studies.

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Effect Comparison of Rectified and Inverter-fed power control Converters on Sub-synchronous Torsional Stability in Practical ±500kV Lu-Gao-Zhao Three-Terminal DC Project

Effect Comparison of Rectified and Inverter-fed Power Contro...

引用

2021 International Conference on power System Technology, powerCON 2021

作者： Yuan, Hao Hong, Chao Shi, Youjie Zhang, Fan China Southern Power Grid State Key Laboratory of HVDC Electric Power Research Institute Guangzhou China China Southern Power Grid Co. Ltd. Power Dispatching and Control Center Guangzhou China

ISBN: (纸本)9781665407373

Lu-Gao-Zhao three-terminal DC project is the first ±500kV multi-terminal line-commutated converter-based high voltage direct current (LCC-HVDC) transmission project in China. Different with the two-terminal LCC-HVDC situation that only the rectifier can operate in power control mode, Gaopo converter station of the Lu-Gao-Zhao three-terminal DC project can operate in power/dc-current control mode for both the rectified and inverter-fed conditions. Sub-synchronous torsional interactions between thermal power plants and the rectified power control converter have been well researched, but the effects of the inverter-fed power control converter on sub-synchronous torsional stability have seldom been analyzed. Based on the concepts of damping and synchronizing coefficients, this paper presents a small-signal model of the SG connected to HVDC converter system to compare the effects of rectified and inverter-fed power control converters on sub-synchronous torsional stability, and reveals the mechanism of the effect differences. The results have been adopted to the practical Lu-Gao-Zhao three-terminal DC project, and verified by the DPT test and actual operation. © 2021 IEEE.

关键词： power control

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An Optimal Decision-Making Method for Offshore Wind power Considering Multiple Transmission Modes

An Optimal Decision-Making Method for Offshore Wind Power Co...

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Clean Energy Storage and power Engineering (CESPE), International Conference on

作者： Ranran An Yue Yang Xiaobing Liang Sichao Pan Bohan Yang Jiancun Liu Electric Power Research Institute Guangdong Power Grid Co. Ltd Guangdong China Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin China Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin University of Technology Tianjin China

ISBN: (数字)9798331511708

ISBN: (纸本)9798331511715

With the increasing scale of offshore wind farms and the diversification of power transmission technologies, selecting the most suitable transmission scheme requires a comprehensive analysis of technical feasibility, economic efficiency, and grid adaptability. This paper investigates various offshore wind power transmission methods, including highvoltage alternating current (HVAC), high-voltage direct current (HVDC), and hybrid HVAC/HVDC systems. A multi-objective decision-making framework is proposed, incorporating factors such as transmission distance, power capacity, system reliability, reactive power compensation, and overall economic cost. A case study of a deep-sea wind power cluster in China is presented to evaluate five different transmission schemes. The results demonstrate that while each transmission method has unique advantages and limitations, hybrid HVAC/HVDC transmission offers a balanced solution in terms of reliability, technical complexity, and cost-effectiveness. The proposed decisionmaking model provides a valuable reference for optimizing offshore wind power transmission strategies, contributing to the development of low-carbon, intelligent energy systems.

关键词： Reactive power Costs Decision making High-voltage techniques Wind power generation Wind farms Hybrid power systems Reliability Frequency control Optimization

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Small Defect Detection of power Electronic Devices Based on YOLO-DHGC 1st

Small Defect Detection of Power Electronic Devices Based on ...

引用

1st Electrical Artificial Intelligence Conference, EAIC 2024

作者： Chen, Lihua Su, Lumei Li, Tianyou Fan, Yin School of Electrical Engineering and Automation Xiamen University of Technology Xiamen361024 China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361024 China East China Branch of State Grid Corporation Limited Shanghai200120 China

ISBN: (纸本)9789819640621

With the acceleration of industrialization, the demand for high quality and reliability in the manufacturing of power electronic devices has become increasingly prominent. This paper proposes a small object detection algorithm based on YOLO-DHGC, specifically designed for defect detection in such devices. By integrating a high-resolution backbone network, DenseHRNet, with a dual-stream structure based on edge-gated branches, the algorithm captures richer detail information and enhances the network’s ability to perceive the boundaries and shape features of small objects. Additionally, the use of a sub-pixel convolution upsampling module reduces the loss of semantic information during feature propagation, thereby improving the reconstruction and localization accuracy of small objects. Experimental results indicate that the algorithm achieves high detection accuracy, robustness, and generalization capability on the PKU-Market-PCB small object defect dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Defect Detection Dense Connection Dual-Stream Architecture Sub-Pixel Upsampling

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Coordinated Dispatch of Flexible Resources and Thermal Generation Based on Variable Wind power Consumption Region

Coordinated Dispatch of Flexible Resources and Thermal Gener...

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

作者： Wujing Li Zhiwei Wang Xiangqing Hu Wenzhuo Wang Biao Su Qiwen Zhang Power Dispatching Control Center Northwest Branch of State Grid Corporation Xi'an China State Key Laboratory on Electrical Insulation and Power Equipment Xi'an Jiaotong University Xi'an China

With the increasing penetration of renewable energy in recent years, the safety and dispatch of power systems have drawn a lot of attention. A method based on a combination of bi-level programming (BLP) and interval projection algorithm (IPA) is proposed to solve a coordinated dispatch model with an energy storage system (ESS) and pumped storage unit considering the impact of large-scale wind power uncertainty and volatility. Finally, the validity of the model is verified in modified IEEE-RTS 1979, and the influence of flexible resources on wind curtailment, load shedding, and operation cost is analyzed. Results demonstrate that flexible resources could facilitate the ability of renewable energy consumption and the model can strike a balance between the security and economy.

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Reliability Assessment of Medium and Low Voltage Distribution Networks Considering Distributed Energy Sources

Reliability Assessment of Medium and Low Voltage Distributio...

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Energy Engineering and power Systems (EEPS), International Conference on

作者： Wei Zhang Liwen Qin Yangjun Zhou Chenying Yi Shan Li Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Co. Ltd Nanning China

In order to truly evaluate the reliability of low-voltage distribution network, considering the influence of distributed energy uncertainty on the reliability evaluation of low-voltage distribution network, a reliability evaluation method of low-voltage distribution network considering distributed energy is proposed. Firstly, considering the load recovery capability of distributed energy after failure, and then combining with distributed energy, a collaborative assessment method based on sequential Monte Carlo for medium-low voltage distribution network reliability is proposed. Finally, taking IEEE RBTS BUS-2 system as an example, the system reliability levels in different scenarios are compared and analyzed, and the effectiveness of the proposed method is verified.

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A Multi-Model Fusion Approach for Transformer Fault Detection

A Multi-Model Fusion Approach for Transformer Fault Detectio...

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Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Ke Zhou Wei Zhang Ligang Li Shaoming Pan Chengwei Huang Guangxi Power Grid Equipment Monitoring and Diagnosis Technology Innovation Center Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid CO. LTD. Nanning State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences China Power Supply Bureau of Guangxi Hezhou Power Grid Co. Ltd.

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

Addressing the weak generalization capability and suboptimal prediction performance of single mechanistic and data-driven models, this paper proposes a transformer fault detection method based on the fusion of mechanism and data models. Firstly, vibration and current data are collected on-site to train the SVM vibration model and the Adaboost current model. Secondly, current simulation data is obtained using laboratory simulation software. This simulation data, combined with the current data collected under the same conditions on-site, is used as input to train the GBDT error compensation model. Finally, these three models are used as inputs to the GRNN, completing the overall model design. This fusion of mechanistic and data-driven models not only addresses the parameter mismatch issue of the mechanistic model under complex working conditions but also deeply mines time-series data. Experimental results show that The mean squared error of the fusion model is 0.002 lower than that of the data model, and the coefficient of determination is improved by 5.07% compared to the mechanistic model, enhancing the overall predictive accuracy of the model.

关键词： Vibrations Support vector machines Training Accuracy Biological system modeling Fault detection Predictive models Transformers Prediction algorithms Data models

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