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Achieving an Accurate Random Process Model for PV power Using Cheap Data:Leveraging the SDE and Public Weather Reports

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CSEE Journal of power and Energy systems 2025年第1期11卷 124-135页

作者： Yiwei Qiu Jin Lin Zhipeng Zhou Ningyi Dai Feng Liu Yonghua Song College of Electrical Engineering Sichuan UniversityChengdu610065China State Key Laboratory of the Control and Simulation of Power Systems and Generation Equipment Tsinghua UniversityBeijing 100087China State Key Laboratory of Internet of Things for Smart City University of MacaoMacao999078China Department of Electrical Engineering Tsinghua UniversityBeijing100087China

Stochastic differential equation (SDE)-based random process models of renewable energy sources (RESs) jointly capture evolving probability distribution and temporal correlation in continuous time. It enabled recent studies to remarkably improve performance of power system dynamic uncertainty quantification and optimization. However, considering the non-homogeneous random process nature of PV, there still remains a challenging question: how can a realistic and accurate daily SDE model for PV power be obtained that reflects its weather-dependent and non-Gaussian uncertainty in operation, especially when high-resolution numerical weather prediction (NWP) or sky imager is unavailable for many distributed plants? To fill this gap, this article finds that an accurate SDE model for PV power can be constructed only using the data from low-resolution public weather reports. Specifically, for each day, an hourly parameterized Jacobi diffusion process recreates temporal patterns of PV volatility. Its parameters are mapped from the day's public weather reports to reflect varying weather conditions using a simple learning model. The SDE model jointly captures intraday and intrahour volatility. Statistical examination shows that the proposed approach outperforms a selection of the latest deep learning-based time series models on real-world data collected in Macao.

关键词： Photovoltaic(PV)power random process stochastic differential equation(SDE) stochastic optimization time series modeling uncertainty quantification weather report

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Superhydrophobic ceramic membrane coupled with a biphasic solvent for efficient CO_(2)capture

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Green Energy & Environment 2025年第4期10卷 834-844页

作者： Kaili Xue Zhen Chen Xiaona Wu Heng Zhang Haiping Chen Junhua Li State Key Joint Laboratory of Environment Simulation and Pollution Control School of EnvironmentTsinghua UniversityBeijing100084China Beijing Key Laboratory of Pollutant Monitoring and Control in Thermoelectric Production Process School of EnergyPower and Mechanical EngineeringNorth China Electric Power UniversityBeijing102206China MOE Key Laboratory of Resources and Environmental Systems Optimization College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing102206China

An innovative strategy was proposed by integration of membrane contactor(MC)with biphasic solvent for efficient CO_(2) capture from flue *** accessible fly ash-based ceramic membrane(CM)underwent hydrophobic modification through silane grafting,followed by fluoroalkylsilane decoration,to prepare the superhydrophobic membrane(CSCM).The CSCM significantly improved resistance to wetting by the biphasic solvent,consisting of amine(DETA)and sulfolane(TMS).Morphological characterizations and chemical analysis revealed the notable enhancements in pore structure and hydrophobic chemical groups for the modified *** of wetting/bubbling behavior based on static wetting theory referred the liquid entry pressure(LEP)of CSCM increased by 20 kPa compared to pristine *** with traditional amine solvents,the biphasic solvent presented the expected phase *** experiments demonstrated that the CO_(2) capture efficiency of the biphasic solvent increased by 7%,and the electrical energy required for desorption decreased by 32%.The 60-h continuous testing and supplemental characterization of used membrane confirmed the excellent adaptability and durability of the *** study provides a potential approach for accessing hydrophobic ceramic membranes and biphasic solvents for industrial CO_(2) capture.

关键词： Carbon capture Membrane contactor Hydrophobic modification Membrane wetting Biphasic solvent

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control, Modeling and Stability Analysis of DRU-based Grid-forming Converter

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Chinese Journal of Electrical Engineering 2025年第1期11卷 83-92页

作者： Wencong Wu Minzhi Wang Liang Tu Haiqing Cai Guanglei Yan Xiaohui Qu Haohan Gu Wei Chen State Key Laboratory of HVDC China Southern Power GridGuangzhou 510663China National Energy Power Grid Technology R&D Center Guangzhou 510663China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power Systems China Southern Power GridGuangzhou 510663China CSG Key Laboratory for Power System Simulation China Southern Power GridGuangzhou 510663China School of Electrical Engineering Southeast UniversityNanjing 210096China

Diode rectifier unit(DRU)-based high-voltage direct current(HVDC)transmissionsystems areeffectivein achieving the stableandeconomical operation of offshore *** theuncontrollable characteristicsof DRUs,a grid-forming(GFM)strategy forwind-turbine converters isnecessary to support offshore AC voltageand ***,the active power-synchronization control in traditional GFM converters is unsuitable for DRU-based GFM ***,the stability issue for DRU-based HVDC systems involving DRU-based GFM and grid-following(GFL)converters has not yet been *** solve these issues,this study begins with the characteristics of a DRU-based HVDC system and presents a control scheme for DRU-based GFM converters for power ***,the dq-frame impedance model of the DRU-based GFM converteris proposed for the stability analysis of the entire HVDC ***,a simulation platform is built to verify the model accuracy and system stability.

关键词： Diode rectifier unit offshore wind-powergeneration grid-forming converter impedance model stabilityanalysis

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Study on the Characteristics of Natural Grounding Resistance of Underground Tunnels 11th

Study on the Characteristics of Natural Grounding Resistance...

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11th Frontier Academic Forum of Electrical Engineering, FAFEE 2024

作者： Ma, Pengyu Li, Benliang Zou, Jun State Key Lab of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China State Power Economic Research Institute Beijing102200 China

ISBN: (纸本)9789819787791

With the development of cities, underground tunnels are more and more widely used, and the reinforced concrete in their walls can be used as the natural grounding body of the tunnels. However, underground tunnels have curved structures, multiple cross-sections and deep-buried structures, and the electrical conductivity of the concrete is different from that of the soil, etc., and the traditional analytical method has limitations in calculating the grounding resistance of the tunnels in these cases. In order to satisfy the needs of practical engineering, this paper adopts a numerical method based on the MoM numerical method to analyze the grounding system of underground tunnels with complex geometries and to calculate the grounding resistance of reinforced concrete systems in underground tunnels. In order to assess the difference between the analytical solution and the exact solution, the article introduces a correction factor to measure the ratio between the two. simulations are carried out for real cases, and the results show that the accuracy of the analytical solution can be improved by introducing the correction factor. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： correction factor grounding resistance numerical method Underground tunnels

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A framework of day-ahead wind supply power forecasting by risk scenario perception

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IEEE Transactions on Sustainable Energy 2025年

作者： Yang, Mao Huang, Yutong Wang, Zhao Wang, Bo Su, Xin Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin132012 China China Electric Power Research Institute State Key Laboratory of Operation and Contr Ol of Renewable Energy & Storage Systems Beijing100912 China

Wind power forecasting (WPF) systems are essential to maintain the safe and stable operation of the power system in case of large-scale grid-connected wind farms. However, the current forecasting has the problem of disunity between statistical value and application value, that is, it only pays attention to its forecasting accuracy and ignores the risks caused by it in the power system. In order to solve the above problems, this study proposes a framework of wind supply power forecasting (WSPF) for wind farm cluster, which takes into account the risk scenario perception. First of all, aiming at the predicted risk phenomenon in WPF, TimesNet combined with the fluctuation information of Numerical Weather Prediction (NWP) wind speed is used to identify the corresponding risk scenarios. Secondly, the effective consumption area and power supply risk area evaluation index, as well as the accuracy of WSPF are defined, and the optimal forecasting curve correction scheme is fitted according to the index. Thirdly, taking into account the correction scheme and identification results, a variety of predictors are used to verify the WSPF according to the above framework. Finally, the proposed method is applied to a wind farm cluster in Inner Mongolia Autonomous region of China, the average accuracy of WSPF has increased by 37%, which verifies the effectiveness and universality of this method. © 2010-2012 IEEE.

关键词： Wind forecasting

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Suppression of Phase Current Ripple and Torque Harmonics in Four-Module PMSM with Asymmetric Mutual Inductance

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IEEE Transactions on power Electronics 2025年

作者： Liu, Kaiyuan Li, Chi Zheng, Zedong Li, Yongdong Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Department of Electrical Engineering Beijing100084 China

In N-module motors, uniform carrier phase shifting (UCPS) by 2π/N between modules can effectively suppress torque harmonics caused by high-frequency switching of power devices. In multi-module motors with fractional-slot concentrated winding, the mutual inductance between adjacent windings is higher than that between non-adjacent windings. Although the conventional UCPS can reduce the torque sideband harmonics synthesized by the four modules, this asymmetric mutual inductance (AMI) paradoxically increases phase current ripple in each sub-module, leading to higher system losses. Aiming at this problem, this paper derives the mathematical model of N-module motor with AMI, analyzes the limitations of the traditional UCPS method that increases the phase current ripple. For different optimization objectives, two carrier phaseshifting angle optimized strategies are proposed to achieve integrated suppression of torque sideband harmonics and intramodule phase current ripples, with a genetic algorithm improving optimization speed. A threshold coefficient is introduced to achieve a tradeoff between phase current ripple and q-axis current harmonics, which can be adjusted to prioritize objectives based on user requirements. To enhance algorithm adaptability, the paper further investigates model variations under uneven torque distribution in sub-healthy states and proposes an improved comprehensive optimization algorithm, limiting torque sideband harmonics and current ripple in both healthy and sub-healthy conditions. Finally, the proposed algorithm is validated experimentally by a four-module permanent magnet synchronous motor. © 2025 IEEE.

关键词： Genetic algorithms

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Extraction and application of intrinsic predictable component in day-ahead power prediction for wind farm cluster

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Energy 2025年 328卷

作者： Yang, Mao Jiang, Renxian Yu, Xinnan Wang, Bo Su, Xin Ma, Chenglian The Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing100912 China

With the continuous updating and iteration of artificial intelligence algorithms, prediction models emerge one after another, but the research and utilization of the predictability of wind power is still less. Therefore, this paper proposed a day-ahead power prediction method for Wind Farm Cluster (WFC) based on intrinsic predictable component extraction. Firstly, based on the difference of power distribution between wind farm and WFC, a method of Wind power Curve (WPC) modeling for WFC is proposed, which provides the basis for establishing the Final Set of Wind power Curve (FSWPC). Secondly, the Intrinsic Predictable Component (IPC) of wind power is extracted based on the FSWPC, and the Interference Component (IC) of wind power is separated to eliminate the influence of IC on IPC in the process of prediction. Thirdly, the historical similarity matching method with large threshold is used to predict the IC to make up for the numerical deficiency of the IPC. Finally, the proposed method was applied to a WFC in China to verify its effectiveness. Compared with the traditional prediction strategy, the NRMSE, NMAE and MAPE are reduced by 1.59 %, 1.15 % and 6.42 %, respectively. © 2025 Elsevier Ltd

关键词： Iterative methods

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Semi-empirical equivalent circuit model and evaluation of energy losses for alkaline electrolysis stack in dynamic operations

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International Journal of Hydrogen Energy 2025年 138卷 859-873页

作者： Sha, LianDong Lin, Jin Qi, Ruomei Li, Qinghui Li, Wenying Lin, Ruixiao Gao, Danhui Li, Hang Li, Xiaolong Yang, Chenxi Song, Yonghua State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing 100084 China Tsinghua-Sichuan Energy Internet Research Institute Chengdu 610213 China School of Chemistry and Chemical Engineering Southwest Petroleum University Chengdu 610213 China School of Nuclear Science and Engineering North China Electric Power University Beijing 100084 China State Key Laboratory of Internet of Things for Smart City University of Macau 999078 Macao

In various applications of alkaline water electrolysis (AWE) for hydrogen production, the efficiency of AWE stacks is a critical concern. Emerging applications involve significant dynamic operations, necessitating the evaluation of their impact on stack efficiency. However, a quantitative understanding of the power losses within AWE stacks under dynamic conditions remains limited. A significant research challenge exists in the development of models for AWE stacks that can accommodate dynamic operating conditions, and there is a need for a systematic approach to classify and quantify energy losses within the stack. This paper presents a quantitative assessment method for losses in AWE stacks based on a semi-empirical equivalent circuit model (SECM). The losses within the AWE stack are categorized into four types based on their generation mechanisms: overpotential losses, shunt current losses, non-Faradaic losses, and electrochemical cycling losses (cycling losses for short). Using experimental data from 5 MW and 10 kW AWE stacks, the parameters of the SECM observer are identified through a stepwise data-driven approach, resulting in a mean square error of less than 46.4 mV for 5 MW stack and 80.9 mV for 10 kW stack. The constructed SECM observer is employed to simulate the proportion of various losses under different dynamic operating conditions. This paper focuses on the efficiency and loss behaviors of AWE stacks under multi-stack switching strategies. Case studies demonstrate that the current range, ramp rate, regulation period, and duty cycle significantly influence the four types of losses. Based on the SECM observer, recommended parameters for multi-stack switching are provided. This work contributes to accurate assessment of AWE stack efficiency under dynamic operations and provides a methodology for designing AWE stack operating strategies. © 2025 Hydrogen Energy Publications LLC

关键词： Alkaline water electrolysis stack Dynamic operation Efficiency Electrochemical cycling losses Equivalent circuit model Multi-stack switching strategies

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FDCA-DSTGCN: A Wind Farm Cluster power Day-ahead Prediction Model Based on Frequency Domain Information Gain and Dynamic Trend Sensing

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IEEE Transactions on Sustainable Energy 2025年

作者： Yang, Mao Niu, Jiajun Wang, Bo Huang, Dawei Su, Xin Ma, Chenglian Ministry of Education Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin132012 China China Electric Power Research Institute State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems Beijing100912 China

Accurate wind farm cluster power prediction (WFCPP) is of vital significance for new power systems with large-scale wind power integration. The current WFCPP modeling method ignores the important role of wind direction and frequency domain information, resulting in insufficient use of spatial information and difficult to improve the prediction accuracy. In order to solve the above problems, a day-ahead power prediction model for wind farm cluster power is proposed based on information gain in frequency domain and dynamic trend sensing. Firstly, a cluster division method based on graph theory and progressive fusion of multiple information is proposed, and a virtual information node is set up. Secondly, a method to identify prevailing wind direction under time window is proposed for subsets, and a dynamic weighted directed graph structure is designed based on prevailing wind direction and wind speed. Thirdly, a dynamic spatio-temporal graph convolutional network model with frequency domain gain channel attention mechanism (FDCA-DSTGCN) is proposed to integrate the above information and complete the prediction. Finally, the proposed method is applied to a wind farm cluster in Inner Mongolia of China. Compared with the existing and traditional prediction methods, the normalized root mean square error of the proposed method is reduced by 1.13% -2.15%, which verifies the effectiveness of the proposed method. © 2010-2012 IEEE.

关键词： Mean square error

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Generation of Atmospheric Pressure Plasma by Repetitive Nanosecond Pulses in Air Using Water Electrodes

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Plasma Science and Technology 2011年第6期13卷 735-739页

作者：邵涛于洋章程姜慧严萍周远翔 Institute of Electrical Engineering Chinese Academy of Sciences Key Laboratory of Power Electronics and Electric Drive Chinese Academy of Sciences State Key Laboratory of Control and Simulation of Power Systems and Generating Equipment Electrical Engineering DepartmentTsinghua University

Dielectric barrier discharge （DBD） excitated by pulsed power is a promising method for producing nonthermal plasma at atmospheric pressure. Discharge characteristic in a DBD with salt water as electrodes by a home-made unipolar nanosecond-pulse power source is presented in this paper. The generator is capable of providing repetitive pulses with the voltage up to 30 kV and duration of 70 ns at a 300 Ω resistive load. Applied voltage and discharge current are measured under various experimental conditions. The DBD created between two liquid electrodes shows that the discharge is homogeneous and diffuse in the whole discharge regime, Spectra diagnosis is conducted by an optical emission spectroscopy. The air plasma has strong emission from nitrogen species below 400 nm, notably the nitrogen second positive system.

关键词： non-thermal plasma dielectric barrier discharge pulsed power nanosecondpulse pulse repetition frequency atmospheric pressure air emission spectra.

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