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4th IEEE International Conference on Electronics Technology, ICET 2021

作者： Yang, Xue Pan, Siyu Hu, Junjie Liu, Baozhu Luo, Kui North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy Storage Systems Beijing China

ISBN: (纸本)9781728176734

With the rapid development of distributed photovoltaic, electric vehicles, energy storage and other technologies, the group of prosumers with dual functions of power production and consumption is growing. Prosumers have high responsiveness, flexible operation characteristics, and huge development potential. However, individual resources are limited and very scattered, and cannot directly participate in the power auxiliary service market. Therefore, virtual power plants are introduced to effectively aggregate and manage the resources of prosumers. Based on the theory of economic mechanism design, a bidding mechanism for prosumers to participate in the auxiliary service market has been established. This mechanism has the characteristics of incentive compatibility, which can effectively encourage Virtual power plants to report true costs, save electricity costs, and achieve effective resource allocation. The rationality and effectiveness of the proposed mechanism are verified through the analysis of a calculation example. © 2021 IEEE.

关键词： Virtual power Plants

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Planning Economy-energy-environment Nexus System: A Case Study of Pearl River Delta, China 2022

Planning Economy-energy-environment Nexus System: A Case Stu...

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11th International Conference on Informatics, Environment, Energy and Applications, IEEA 2022

作者： Lv, Jing Li, Yongping Huang, Guohe Li, Yu Sino-Canada Energy and Environmental Research Center North China Electric Power University China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Beijing Normal University China Institute for Energy Environment and Sustainable Communities University of Regina Canada

ISBN: (纸本)9781450395830

The rapid economic growth has led to resource shortages and environmental degradation, restricting global sustainable development. In this study, an economy-energy-environment nexus (EEEN) optimization model is established, which is capable of coordinating the interests of cities and urban agglomerations and balancing the trade-offs among economic growth, energy consumption and environmental emission. The model is then applied to planning Pearl River Delta (PRD) urban agglomeration's EEEN system during 2021-2035. Three scenarios associated with different GDP growth rates are analyzed. Major findings are: (i) the growth rate of energy consumption and environmental emissions would be lower than that of the economy aggregate, indicating that the economy is gradually decoupled from energy and the environment;(ii) high GDP growth rates would promote the upgrading of industry structure and the share of tertiary industry would increase from 64.61% to 65.86% by 2035;(iii) wholesale and retail transportation and warehousing (WRT) industry would still be the major energy user and VOCs and CO2 emitter, which implicates that WRT has huge potential for energy conservation and emission reduction. © 2022 ACM.

关键词： Energy utilization

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Short-term power Prediction Based on Improved NWP Data Considering Wind Speed Distribution Inner Wind Farm

Short-term Power Prediction Based on Improved NWP Data Consi...

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

作者： Wei Ma Ying Qiao ZongXiang Lu ZhiFeng Liang JiaMing Li YuChen Hao State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments of Electrical Engineering Tsinghua University Beijing China State Grid Corporation of China Beijing China State Grid Jiangsu Power Grid Corporation Nanjing China

The wind farm has only one NWP data point, which cannot accurately reflect the wind resources inside the wind farm. To solve the problem of a poor match between short-term wind power prediction numerical weather forecast and wind farm measured weather. Put forward a kind of based on clustering and temporal characteristics of the modified liters of scale wind power prediction method, first of all, using EOF orthogonal decomposition method to extract the features of each fan, using hierarchical analysis method of the characteristics of the data matrix clustering, and then, each cluster sample selected representative of a fan, using the error transfer characteristic of the NWP data sequence is modified. Finally, The CNN prediction model is used for power prediction, and the weight is determined according to the cluster sample size. A wind farm in northern Hebei, China, is used to verify the effectiveness of the proposed method.

关键词： Fans Wind speed System integration Wind farms Wind power generation Predictive models Feature extraction

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Adaptive Fault Detection Scheme Using an Optimized Self-healing Ensemble Machine Learning Algorithm

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CSEE Journal of power and Energy systems 2022年第4期8卷 1145-1156页

作者： Levent Yavuz Ahmet Soran AhmetÖnen Xiangjun Li S.M.Muyeen Electrical and Computer Engineering Department in Abdullah Gül University Kayseri 38080Turkey Department of Electrical and Computer Engineering College of EngineeringSultan Qaboos UniversityAl-KhoudMuscat123Oman Department of Electrical Engineering Qatar UniversityDoha 2713Qatar State Key Laboratory of Control and Operation of Renewable Energy and Storage Systems China Electric Power Rescarch InstituteBeijing 100192China

This paper proposes a new cost-efficient,adaptive,and self-healing algorithm in real time that detects faults in a short period with high accuracy,even in the situations when it is difficult to *** than using traditional machine learning(ML)algorithms or hybrid signal processing techniques,a new framework based on an optimization enabled weighted ensemble method is developed that combines essential ML *** the proposed method,the system will select and compound appropriate ML algorithms based on Particle Swarm Optimization(PSO)*** this purpose,power system failures are simulated by using the PSCA D-Python *** of the salient features of this study is that the proposed solution works on real-time raw data without using any pre-computational techniques or pre-stored ***,the proposed technique will be able to work on different systems,topologies,or data *** proposed fault detection technique is validated by using PSCAD-Python co-simulation on a modified and standard IEEE-14 and standard IEEE-39 bus considering network faults which are difficult to detect.

关键词： Decision tree(DT) ensemble machine learning algorithm fault detection islanding operation k-Nearest Neighbor(kNN) linear discriminant analysis(LDA) logistic regression(LR) Naive Bayes(NB) self-healing algorithm

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Research on Digital Twin Modeling Method for Combustion Process Based on Model Reduction

SSRN

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SSRN 2024年

作者： Zhang, Yue Li, Jiale Department of Automation North China Electric Power University Hebei Baoding071000 China Hebei Technology Innovation Center of Simulation & Optimized Control for Power Generation North China Electric Power University China Baoding Key Laboratory of State Detection and Optimization Regulation for Integrated Energy System China

In response to the difficulty in obtaining combustion information within coal-fired boiler furnaces, a method is proposed in this study to improve the reduced-order model using clustering segmentation. This approach aims to rapidly predict the combustion temperature field inside the furnace by establishing a twin model of the combustion temperature field. Initially, a finite element method is employed to analyze the combustion system of a 600MW subcritical boiler under various operating conditions. Subsequently, cross-sectional data from burner nozzle positions at each operating condition are extracted. These data are subjected to Proper Orthogonal Decomposition (POD), Spectral Proper Orthogonal Decomposition (SPOD), and Wavelet Transform-POD (WT-POD) for dimensionality reduction to obtain modal data. Comparative analyses are conducted on the modal data obtained from different methods. Furthermore, based on modal data analysis, a Support Vector Machine (SVM) regression model is selected to reconstruct the temperature field. The average absolute error of the reconstructed temperature fields from three methods under different operating conditions is then compared. Finally, the model is refined using clustering segmentation, resulting in an improvement of approximately 0.6% in reconstruction accuracy. This enhancement demonstrates that the clustered POD-SVR-GA model achieves higher accuracy in reconstructing combustion temperature fields after clustering-based improvements. © 2024, The Authors. All rights reserved.

关键词： Support vector machines

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Electromagnetic Performance and Vibration Analysis of a Special-shaped External-rotor Machine 18

Electromagnetic Performance and Vibration Analysis of a Spec...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Dong, Ziwei Yan, Liang Lu, Zhang Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Science and Technology on Aircraft Control Laboratory Beijing100191 China Tianmushan Laboratory Xixi Octagon City Yuhang District Hangzhou310023 China Beihang University Ningbo Institute of Technology Ningbo315800 China Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou China

ISBN: (纸本)9798350312201

Permanent magnet synchronous machines have advantages such as small size, light weight, high efficiency, etc. It is more and more widely used in robots, electromagnetic propulsion, electric vehicles and so on. High power density and high torque density are urgent need for those applications. The electromagnetic design of machines mostly adopt multi-pole magnet patterns to reduce the stator yoke size. It helps to decrease the mass of the machine with the same power and improve the torque density. As the number of poles grows larger, the frequency and the core loss of per unit volume will also increase with the same speed, which can aggravate the heat problem of the machine. It is easy to generate the low-order vibration with high flux density. Therefore, the performance of a special-shaped external-rotor machine and comparisons with the traditional machine are analyzed in this paper. Numerical simulation is conduced to validated that the special-shaped magnet pattern can reduce the torque ripple, improve the torque output and power density. From the two-dimensional Fourier analysis of the radial electromagnetic force, it is found that the low-order amplitude of the special-shaped machine is greatly reduced, so the vibration can be avoided. Subsequently, the vibration simulation is carried out to indicate that the magnet pattern can satisfy low level in vibration and noise of the machine. © 2023 IEEE.

关键词： Vibration analysis

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Location and capacity of distributed photovoltaic generation connected to distribution network based on multi-objective genetic algorithm 5

Location and capacity of distributed photovoltaic generation...

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5th IEEE Advanced Information Management, Communicates, Electronic and Automation control Conference, IMCEC 2022

作者： Qing, Song Xie, Tuo Bai, Qingjun Li, Pai Institute of Water Resources and Hydro-Electric Engineering Xi'An University of Technology Xi'an710048 China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems Beijing102401 China

ISBN: (纸本)9781665479677

In order to further improve the ecological environment in desert areas and actively respond to the development of the 'dual carbon' policy, numerous distributed photovoltaics have been connected to the distribution network in recent years. Network loss caused a greater impact. For the location and capacity planning of distributed photovoltaic access to the distribution network, this paper proposes a distributed photovoltaic location and capacity model that considers investment costs, distribution network losses, voltage stability, and environmental protection costs. The improved multi-objective genetic algorithm is used to solve the optimization model, which is verified by example simulation. After the optimized configuration, the power supply quality and network loss of the distribution network are significantly improved, which verifies the feasibility of the model. This research provides a certain reference and reference for the location and capacity determination of the distribution network with distributed photovoltaics. © 2022 IEEE.

关键词： Genetic algorithms

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The Correlation Mechanism that Micro-Structure Parameters of ZnO Varistor to the Macroscopic Electrical Characteristics

The Correlation Mechanism that Micro-Structure Parameters of...

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International Conference on Electrical Materials and power Equipment (ICEMPE)

作者： Pengfei Meng Jingke Guo Long Zhao Wenhao Lu Zheng Liu Shan Li Kai Zhou Jun Hu College of Electrical Engineering Sichuan University Chengdu China State Grid Linyi power supply company STATE GRID Corporatio of China Linyi China High Voltage Technology Department Extra High Voltage Power Transmission Company of CSG Guangzhou China State Key Laboratory of Intense Pulsed Radiatio Simulation and Effect Northwest Institute of Nuclear Technology Xi’an China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Tsinghua University Beijing China

As the core part of metal oxide arresters, ZnO varistor plays an important part in suppressing the overvoltage of power systems. With the development of UHV technology, the residual voltage and energy capacity of ZnO varistors have put forward higher requirements. The research is carried out from the perspective of material calculation, studied the correlation mechanism between micro-structure parameters and various macroscopic electrical characteristics of ZnO varistor based on Voronoi network. And the microstructure parameters such as grain size and size inhomogeneity were calculated and studied. The study simplified the optimization problem with multiple variates and objectives, into the one with two categories of variates and two categories of objectives. And then proposed specific strategies. The research provides important theoretical basis for improving the performance of ZnO varistors, and witch is of great significance for the design and manufacture of high-performance lightning arresters.

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Short-Term Wind power Forecasting for Multiple Farms with Alternating Temporal and Graph Convolutional Networks

Short-Term Wind Power Forecasting for Multiple Farms with Al...

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Electrical Engineering and Green Energy (CEEGE), International Conference on

作者： Guoqing Li Jianfeng Che Dagui Liu State Grid Xinjiang Electric Power Corporation Urumqi PR China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing PR China

Accurate wind power forecasting (WPF) is very important for stable and reliable power grid integration. Existing WPF approaches make predictions based on numerical weather prediction (NWP) of a single wind farm, where the spatial and temporal correlations among geographically adjacent wind farms are not considered. In this paper, we propose a novel WPF approach for multiple farms by integrating temporal convolution networks (TCN) and graph convolution networks (GCN). Abstracting the set of multiple wind farms into a graph, spatial information is aggregated with GCN on the irregular non-Euclidean mesh defined by the graph. For each farm, temporal information is fused via TCN. With alternating temporal and graph convolution layers, features are extracted from inputs and integrated for forecasting. As demonstrated by experimental results on data from a set of wind farms in Ningxia, China, the proposed WPF for multiple farms performs much better than existing approaches for a single farm.

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Impedance Modeling and Stability Analysis of Grid-forming Converters

Impedance Modeling and Stability Analysis of Grid-forming Co...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Rui Zhao Xiaofeng Yang Ange Wei Jin Zhang State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China School of Electrical Engineering Beijing Jiaotong University Beijing China

ISBN: (数字)9798350317664

ISBN: (纸本)9798350317671

Grid-forming converters can provide inertial and damping support for high-penetration renewable energy grids. However, inadequate tuning of grid parameters may lead to system instability due to variations in grid strength. In this paper, based on harmonic linearization theory, the positive and negative sequence impedance models of grid-forming converters are derived. Then the suitability of grid-forming strategies in weak grids is discussed in conjunction with the Nyquist stability criterion. Additionally, the impact of grid-forming power loop parameters on system stability is revealed, aiming to provide theoretical support for the optimization design of grid-forming converter parameters. Finally, a time-domain simulation model of the grid-forming converter is constructed to validate the theoretical research under typical system parameters.

关键词： Damping Renewable energy sources Analytical models Stability criteria power system stability Harmonic analysis Mathematical models

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