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检索条件"机构=State Key Laboratory of Control and Simulation of Power System and Power"

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Short-Term Photovoltaic Prediction Based on Transfer Learning and LSTM

Short-Term Photovoltaic Prediction Based on Transfer Learnin...

引用

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

作者： Tianyu Zhang Kedi Zheng Qixin Chen Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China

With the proposal of carbon peaking and carbon neutrality goals, the proportion of renewable energy generation continues to increase and the number of new photovoltaic power stations is growing rapidly. Accurate photovoltaic power prediction is of great significance for the safe, stable and operation of power system. In order to solve the problem of insufficient historical data of newly constructed PV power plants, this paper proposes a short-term PV power prediction model based on Long Short Term Memory and transfer learning. The model uses meteorological data, numerical weather forecast data and PV power as features. According to the transfer learning theory, the Long Short Term Memory model is pre-trained using the historical data of other previously-built PV power plants, and then a small amount of local operation data is used to fine-adjust the model. Case study based on Hebei open source photovoltaic and meteorological data set proves that the proposed transfer learning model can effectively improve the short-term PV power prediction accuracy, and the MAPE can be improved by up to 15%.

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The HEFT Algorithm Based on Node Merging

The HEFT Algorithm Based on Node Merging

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control Engineering and Advanced Algorithms (IWCEAA), International Workshop on

作者： Ying Huang Yuanhong Lu Jie Zhang Jingyue Zhang Haiping Guo National Energy Power Grid Technology R&D Centre Guangzhou 510663 State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou 510663 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou 510663 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou 510663 Guangzhou China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

The task scheduling problem in power systems is complex, especially when communication costs exceed computation costs. This paper proposes an improved HEFT algorithm with a node merging mechanism, merging nodes through hierarchical traversal to assign high-communication-cost tasks to the same processor, reducing communication overhead. Experiments with 499-dimensional and 1614-dimensional matrices from the power system show that the improved algorithm reduces completion time by 5ms and 2ms, respectively, compared to standard HEFT.

关键词： Costs control engineering Processor scheduling Conferences Merging power systems Standards

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Adaptive Identification of power system Operational states Based on Spatio-Temporal Dynamic Graph Neural Networks

Adaptive Identification of Power System Operational States B...

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Electronic Technology, Communication and Information (ICETCI), IEEE International Conference on

作者： Qingqing Zhang Qinfeng Ma Mingshun Liu Jie Zhang Yihua Zhu Zhuohang Liang Su An Qingxin Pu Jiang Dai Power Dispatching and Control Center of Guizhou Power Grid Co. Ltd. Guizhou China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China

ISBN: (数字)9798350361643

ISBN: (纸本)9798350361650

The state identification of the operational status of power systems plays a crucial role in ensuring the safety, efficiency, and reliable operation of power systems, forming the foundation for the management and control of power system operations. In the practical operation of power systems, the duration of fault states is short, while the system remains in a safe and stable state for a significantly longer period, leading to an imbalance in the training samples available. This imbalance can cause traditional machine learning classification algorithms to favor the majority categories of power system operational states, resulting in inaccurate evaluation metrics and reduced model generalization capability. To address this issue, this paper introduces a spatiotemporal dynamic graph neural network model for the identification of power system operational states. By incorporating class cost coefficients, focal loss, and cross-entropy in a joint loss function, the model adaptively focuses on the less represented operational state categories during training, improving classification accuracy on imbalanced and challenging samples. Moreover, the integration of temporal information and spatial topology information within the graph neural network enhances the model’s robustness and generalization ability in state identification. Experimental results on the standard IEEE 68-bus system demonstrate that, compared to traditional machine learning methods, the proposed joint loss with the spatiotemporal dynamic graph neural network model achieves higher accuracy in the identification of power system operational states, significantly improving classification performance on imbalanced samples with a 4.8% increase in F1-score, reaching a peak F1-score of 98.6%.

关键词： Training Adaptation models Accuracy power system dynamics power system stability Graph neural networks Stability analysis

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MODELING METHOD OF OPLC THERMAL CIRCUIT MODEL BASED ON SUPERPOSITION PRINCIPLE 10

MODELING METHOD OF OPLC THERMAL CIRCUIT MODEL BASED ON SUPER...

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10th Renewable power Generation Conference, RPG 2021

作者： Hu, Bo Wang, He Zhou, Guiping Xu, Xiangsheng State Grid Liaoning Electric Power Co. Ltd. Shenyang China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9781839536069

Optical fiber composite low-voltage cable which combines optical fiber and power cable organically plays an important role in the construction of smart grid and the development of energy internet. The change of temperature impacts the working state of the OPLC and the precision of parameter measurement. Thus, the establishment of the OPLC thermal circuit model has important practical significance. Focusing on the attributes of different kinds and various constructions of the OPLC, this paper proposes an OPLC modeling method based on the superposition principle. Firstly, the asymmetric OPLC is equivalent to several symmetric sub-models, and then each model is superimposed by superposition principle. Secondly, the particle swarm algorithm is utilized to realize the model boundary distinguishing identification, improve the accuracy of the parameters, acquire a precise thermal circuit model, and then realize the accurate calculation of temperature at different positions of OPLC. This paper establishes an OPLC thermal circuit model based on the four-cable core OPLC and proves the effectiveness of the method through simulation analysis and experimental verification. © The Institution of Engineering and Technology.

关键词： Optical fibers

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Distributed Generation Planning for Improving Self-healing Ability of Distribution Network

Distributed Generation Planning for Improving Self-healing A...

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

作者： Haobin Li Huijuan Tan Yueting Lin Zhiwei Chen Ziheng Pan Bo Hu Electric Power Dispatching and Control Center Guangdong Power Grid Co. Ltd. Guangzhou China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing China

ISBN: (数字)9798350375138

ISBN: (纸本)9798350375145

With a large number of Distributed Generation (DG) connected to the distribution network, the distribution network can be reconstructed and isolated island partition for self-healing. In this paper, the two-layer configuration DG operation-planning joint optimization model for improving self-healing ability of distribution network is established to achieve economy and self-healing ability of the system. IEEE 33-node system is used to verify the proposed model. The results show that the two-layer model can effectively coordinate the economy and self-healing ability of distribution network through interactive decision-making of DG allocation scheme.

关键词： Optimization models Decision making Distribution networks Planning Distributed power generation power systems Resource management Optimization

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Cooperative Prediction Approach for the Small-Signal Stability Margin of Renewable power system Based on Vertical Federated Learning

Cooperative Prediction Approach for the Small-Signal Stabili...

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power systems and Electrical Technology (PSET), IEEE International Conference on

作者： Xiang Lai Zhihao Chen Yun Liu Tianchen Dai Haiqing Cai Haohan Gu Wei Chen School of Electric Power Engineering South China University of Technology Guangzhou China State Key Laboratory of HVDC CSG Electric Power Research Institute Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China

ISBN: (数字)9798350353204

ISBN: (纸本)9798350353211

Since sub-synchronous oscillations have been frequently witnessed in large-scale wind farms under weak grid conditions, it is significant to predict the critical stability situations in short term so that timely preventative actions can be taken to avoid potential small-signal stability (SS) risks. To this end, this paper proposes a SS prediction approach based on the grid strength metric of generalized short-circuit ratio (gSCR) under the mechanism of vertical federated learning. Specifically, the improved ridge regression prediction model is employed and its corresponding distributed training and the distributed predicting are derived by utilizing the separable characteristic of gradient vector calculation in the context of federated learning. On this basis, the original largescale predicting problem is decomposed into a large number of small-scale subproblems, and each subproblem is calculated locally by the corresponding wind farm. The feature data information of adjacent wind farms can be effectively used to improve the accuracy of the prediction of the stability margin while ensuring the data privacy and security of all participants. Finally, simulation results illustrate the effectiveness and efficiency of the proposed approach under various scenarios.

关键词： Training Accuracy Federated learning simulation power system stability Wind farms Predictive models Stability analysis Vectors Security

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SiC MOSFET Crosstalk Modelling with Suppression Considering Impacts of dv/dt and di/dt

SiC MOSFET Crosstalk Modelling with Suppression Considering ...

引用

International Conference on power Electronics (ICPE)

作者： Wenhao Xie Shiqi Ji Zhengming Zhao Xin Mo Department of Electrical Engineering State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua University China Tsinghua Sichuan Energy Internet Research Institute China

Compared to Si IGBTs, SiC MOSFETs can reduce switching losses, achieve higher switching frequencies and enable smaller converter size. However, due to the high dv/dt of SiC MOSFETs, certain topologies, such as two SiC MOSFETs in a phase-leg configuration, are highly sensitive to crosstalk, which can slow down switching speed and even reduce gate oxide’s lifetime. In this paper, an accurate model of crosstalk is established by considering the impacts of both dv/dt and di/dt in the power loop. The proposed model can simulate the gate-source voltage on bare die of SiC MOSFETs, allowing for a more accurate evaluation of the impact of crosstalk. Model verification is implemented using a double pulse test (DPT) platform and a gate driver with active miller clamp technology. key parameters of the model are extracted from both 3D simulation models and measurement experiments. The DPT waveform of power loop is used as the excitation source in the simulation, and the simulated gate-source waveform shows good agreement with the experimental waveform. Based on the model, parameter sensitivity analysis is performed, and suggestions for improving crosstalk suppression are proposed.

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A Parameter Design Strategy Based on Operation Mode Analysis Method for LCC Converter Used in High-Voltage DC power Supply

A Parameter Design Strategy Based on Operation Mode Analysis...

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PELS Students and Young Professionals Symposium (SYPS), IEEE

作者： Kai Zhang Hanyu Liu Kai Sun Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China

LCC converter has the characteristics of both series resonance and parallel resonance, which is often used as the front stage of high voltage DC power supply. A three-stage boosting circuit using LCC converter, high-frequency transformer and voltage multiplier circuit is applied to a high-voltage source. In order to realize the design of core resonant cavity parameters, firstly, the working process of LCC converter in continuous current mode (CCM) is solved by using the operation mode analysis method. On this basis, considering the integrated design of stray parameters such as stray capacitance and leakage inductance of high-frequency transformer, the resonant cavity design flow of LCC converter is given. Finally, an experimental platform is built to test the LCC converter and the whole boosting circuit, and the voltage transmission ratio of 20V/10kV is verified.

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A Novel Switching Asynchronous Sampled-Data Scheme: Implementations in Interconnected Feedback systems

A Novel Switching Asynchronous Sampled-Data Scheme: Implemen...

引用

American control Conference (ACC)

作者： Xiaoyu Wang Feng Xiao Qian Feng State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Sampled-data control is continually under research exploration and development to optimally coordinate the limited communication resources in networked control systems. In this paper, a novel switching asynchronous sampleddata framework with double-checking consisting of two distinct sampling schemes is proposed. An established method involves designing the switching sampling scheme with event-triggered and time-triggered mechanisms. We also introduce the concept of switching event-triggered control (SETC), by which a positive minimum sampling interval can be guaranteed effectively. By an integral method and Barbalat's Lemma, sufficient conditions that ensure the stability of interconnected linear systems are derived under the SETC. Numerical examples are presented to demonstrate the effectiveness of the proposed methodology.

关键词： Linear systems Sufficient conditions Networked control systems Delay effects Switches Trajectory Numerical stability

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Optimal Design of Full-Bridge Three-Level LLC Converter Based on Time-Domain Analysis

Optimal Design of Full-Bridge Three-Level LLC Converter Base...

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power Electronics and Application Symposium (PEAS), IEEE International

作者： Zengyang Liu Kai Sun Zheyuan Yi Department of Electrical Engineering State Key Laboratory of Power System Operation and Control Tsinghua University Beijing China

Fully DC wind turbine generator system is a promising substitute for conventional AC one. In the system, the LLC step-up converter plays a key role. Mode analysis and time-domain expressions can provide more accurate estimation of the resonant performance than the conventional First Harmonic Analysis method. The circuit works at different modes as the load rate varies. This paper categorizes these resonant behaviors into four modes, with time-domain expressions of each mode obtained. The variation regular of these modes is given and is applied in the program to realize recognizing the working mode automatically. The simulation and experiment have verified the effectiveness of the proposed method.

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