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Torque Limit-based Inertial Control Method Based on Delayed Support for Primary Frequency Control of Wind Turbines

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Journal of Modern power Systems and Clean Energy 2024年第2期12卷 561-570页

作者： Wei Gu Zaiyu Chen Qun Li Minghui Yin Qiang Li Yun Zou School of Automation Nanjing University of Science and TechnologyNanjing 210094China state grid Jiangsu electric power Co. Ltd.Research InstituteNanjing 211103China

To avoid the secondary frequency dip caused by the steep drop of the electrical power of wind turbines(WTs)at the end of frequency support stage,the torque limit-based iner-tial control(TLIC)method sets the power reference as a linear function of rotor speed,rather than the step form for the step-wise inertial ***,the compensation effect on the frequency nadir(FN)caused by the load surge is weakened as the TLIC power is no longer in the step ***,the maximum point of the frequency response component(FRC)contributed by TLIC occurs earlier than the minimum point of FRC corresponding to the load surge,so that the FN cannot be adequately ***,this paper first investigates the relation between the peak and nadir times of FRCs stimulated by the TLIC and load *** this basis,with the compensation principle of matching the peak and nadir times of FRCs,the improved TLIC method based on delayed support is ***,the effectiveness of the proposed method is validated via the experiments on the test bench of wind-integrated power system.

关键词： Wind turbine frequency response component torque limit inertial control delayed support

Multiscale feature learning and attention mechanism for infrared and visible image fusion

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Science China(Technological Sciences) 2024年第2期67卷 408-422页

作者： GAO Li LUO DeLin WANG Song School of Aerospace Engineering Xiamen UniversityXiamen 361102China electric power research institute China Southern Power GridGuangzhou 510063China

Current fusion methods for infrared and visible images tend to extract features at a single scale,which results in insufficient detail and incomplete feature *** address these issues,we propose an infrared and visible image fusion network based on a multiscale feature learning and attention mechanism(MsAFusion).A multiscale dilation convolution framework is employed to capture image features across various scales and broaden the perceptual ***,an attention network is introduced to enhance the focus on salient targets in infrared images and detailed textures in visible *** compensate for information loss during convolution,jump connections are utilized during the image reconstruction *** fusion process utilizes a combined loss function consisting of pixel loss and gradient loss for unsupervised fusion of infrared and visible *** experiments on the dataset of electricity facilities demonstrate that our proposed method outperforms nine state-of-theart methods in terms of visual perception and four objective evaluation metrics.

关键词： infrared and visible images image fusion attention mechanism CNN feature extraction

Optimal Scheduling Strategy of Source-Load-Storage Based onWind power Absorption Benefit

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Energy Engineering 2024年第7期121卷 1823-1846页

作者： Jie Ma Pengcheng Yue Haozheng Yu Yuqing Zhang Youwen Zhang Cuiping Li Junhui Li Wenwen Qin Yong Guo state grid Henan Economic research institute Zhengzhou450000China Zaozhuang power Supply Company State Grid Shandong Electric Power CompanyZaozhuang277000China Key Laboratory of Modern power SystemSimulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China

In recent years,the proportion of installed wind power in the three north regions where wind power bases are concentrated is increasing,but the peak regulation capacity of the power grid in the three north regions of China is limited,resulting in insufficient local wind power consumption ***,this paper proposes a two-layer optimal scheduling strategy based on wind power consumption benefits to improve the power grid’s wind power consumption *** objective of the uppermodel is tominimize the peak-valley difference of the systemload,which ismainly to optimize the system load by using the demand response resources,and to reduce the peak-valley difference of the system load to improve the peak load regulation capacity of the *** lower scheduling model is aimed at maximizing the system operation benefit,and the scheduling model is selected based on the rolling *** load-side schedulingmodel needs to reallocate the absorbed wind power according to the response speed,absorption benefit,and curtailment penalty cost of the two DR dispatching ***,the measured data of a power grid are simulated by MATLAB,and the results show that:the proposed strategy can improve the power grid’s wind power consumption capacity and get a large wind power consumption benefit.

关键词： Wind power consumption two-layer optimal demand response rolling scheduling wind curtailment penalty

Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

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Energy Engineering 2024年第6期121卷 1473-1493页

作者： Lin Ma Liyong Wang Shuang Zeng Yutong Zhao Chang Liu Heng Zhang Qiong Wu Hongbo Ren New Energy Technology Center State Grid Beijing Electric Power Research InstituteBeijing100075China College of Energy and Mechanical Engineering Shanghai University of Electric PowerShanghai200090China

Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.

关键词： Short-term household load forecasting long short-term memory network attention mechanism hybrid deep learning framework

Collaborative robust dispatch of electricity and carbon under carbon allowance trading market

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Global Energy Interconnection 2024年第4期7卷 391-401页

作者： Songyu Wu Xiaoyan Qi Xiang Li Xuanyu Liu Bolin Tong Feiyu Zhang Zhong Zhang electric power research institute of state grid Liaoning electric power Co. Shenyang 110006P.R.China School of electrical Engineering Dalian University of TechnologyDalian 116024P.R.China

The launch of the carbon-allowance trading market has changed the cost structure of the power *** is an asynchronous coupling mechanism between the carbon-allowance-trading market and the day-ahead power-system *** this study,a data-driven model of the uncertainty in the annual carbon price was ***,a collaborative,robust dispatch model was constructed considering the annual uncertainty of the carbon price and the daily uncertainty of renewable-energy *** model is solved using the column-and-constraint generation *** operation and cost model of a carbon-capture power plant(CCPP)that couples the carbon market and the economic operation of the power system is also *** critical,profitable conditions for the economic operation of the CCPP were *** studies demonstrated that the proposed low-carbon,robust dispatch model reduced carbon emissions by 2.67%compared with the traditional,economic,dispatch *** total fuel cost of generation decreases with decreasing,conservative,carbon-price-uncertainty levels,while total carbon emissions continue to *** the carbon-quota coefficient decreases,the system dispatch tends to increase low-carbon unit *** study can provide important guidance for carbon-market design and the low-carbon-dispatch selection strategies.

关键词： Asynchronous coupling mechanism Collaborative robust optimization Carbon price uncertainty Carbon capture power plant Low carbon dispatch

Influence characteristics of water penetration on fibre-reinforced polymer/rigid polyurethane foam interface of the composite cross-arm considering natural ageing

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High Voltage 2024年第1期9卷 81-93页

作者： Jun Xie Zhe Zhou Ziqian Liu Haonan Tian Sigang Zhang Qing Xie Hebei Provincial Key Laboratory of power Transmission Equipment Security Defense North China Electric Power UniversityBaodingChina state grid Gansu electric power Company LanzhouChina

Fibre-reinforced polymer(FRP)/rigid polyurethane foam(RPUF)interface is susceptible to moisture intrusion in addition to natural ageing during *** study investigated the influence of moisture intrusion on the FRP/RPUF interface under natural ageing using experiments and molecular dynamics(MD)*** absorption,shear strength,and leakage current tests were used to clarify the changes in the interface *** degradation mechanism of moisture intrusion at the interface under natural ageing was revealed by MD simulation and *** results show that the natural ageing of interfacial materials will slightly reduce the quality of the interface but will reduce the water resistance of the material and promote the process of water intrusion into the *** addition,water mainly invades the interface through *** water penetration,the interfacial bonding strength and insulation performance significantly *** and hydrolysis of interfacial materials are the main reasons for decreased interfacial *** can cause irreversible damage to the interface,increasing interface defects and water *** vicious cycle of material hydrolysis is the ultimate cause of interfacial *** polar molecules produced by this process and the water absorbed by the interface caused the degradation of the interface insulation performance.

关键词： interface polyurethane interfacial

A New Method for the Aging Evaluation of Oil-Paper Insulation Using η-Butanol and Methanol

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CSEE Journal of power and Energy Systems 2024年第2期10卷 717-726页

作者： Jianyi Wang Yuanxiang Zhou Jun Liu Zhaowei Wang Song Bai Jiayu Lu Department of High Voltage China Electric Power Research InstituteBeijing 100192China state Key Laboratory of power grid Environmental Protection Beijing 100192China electrical Engineering Department Tsinghua UniversityBeijing 100084China Solar Storage Division of state Key Lab of power System and Generation Equipment School of Electrical EngineeringXinjiang UniversityUrumqi 830047China state grid Wuwei electric power Supply Company Wuwei 733000China

To improve the accuracy and efficiency of the aging life prediction and assessment of transformer oil-paper insulation,and to make up for the deficiencies of traditional characterizers,such as 2-furfural,carbon monoxide,and carbon dioxide,a method for the simultaneous determination of methanol,ethanol,n−propanol,and η-butanol in oil with a single injection is established by headspace-gas chromatography-mass *** measured results show that the determination limits of the four alcohol characterizers can be controlled to 10μg/kg *** on this method,the change patterns of the above four alcohols with thermal aging time and degree of polymerization are obtained through thermal aging experimental ***,η-propanol,and η-butanol in oil indicate nearly linear correlations with thermal aging time and degree of polymerization,similar to that of *** analyzing 52 sets of measured data of 500 kV EHV transformers in operation,η-butanol is found to have excellent performance,and a new method to evaluate the aging state of oil-paper insulation employing η-butanol and methanol is proposed along with the aging attention value *** measured data of 500 kV EHV transformers in operation indicate that the combination of η-butanol and methanol as the preferred characterizers can effectively compensate for the shortcoming of traditional characterizers in the early stages of aging,and the feasibility of the method is *** possible pathways for the generation of η-butanol by cellulose cleavage during the aging of oil-paper are proposed from the chemical structure of cellulose.

关键词： Aging characterization determination method methanol η-butanol oil-paper insulation 500 kV transformers

A Situational Awareness Method for Initial Insulation Fault of Distribution Network Based on Multi-Feature Index Comprehensive Evaluation

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Energy Engineering 2024年第8期121卷 2191-2211页

作者： Hao Bai Beiyuan Liu Hongwen Liu Jupeng Zeng Jian Ouyang Yipeng Liu electric power research institute China Southern Power GridGuangzhou510663China state Key Laboratory of Disaster Prevention and Reduction for power grid Changsha University of Science and TechnologyChangsha410114China electric power research institute of Yunnan power grid Co. Ltd.Kunming650032China Qujing power Supply Bureau of Yunnan power grid Co. Ltd.Qujing655099China

Most ground faults in distribution network are caused by insulation deterioration of power *** is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution *** order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is ***,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management ***,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation ***,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was *** optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was ***,the trained multi-class SVM was used to predict 6 kinds of situation level prediction *** results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution an

关键词： Distribution grid insulation degradation initial insulation fault multi-feature indices multi-class SVM situational level situational awareness

The Short-Term Prediction ofWind power Based on the Convolutional Graph Attention Deep Neural Network

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Energy Engineering 2024年第2期121卷 359-376页

作者： Fan Xiao Xiong Ping Yeyang Li Yusen Xu Yiqun Kang Dan Liu Nianming Zhang state grid Hubei electric power research institute Wuhan430077China College of Energy and electrical Engineering Hohai UniversityNanjing210098China

The fluctuation of wind power affects the operating safety and power consumption of the electric power grid and restricts the grid connection of wind power on a large ***,wind power forecasting plays a key role in improving the safety and economic benefits of the power *** paper proposes a wind power predicting method based on a convolutional graph attention deep neural network with multi-wind farm *** on the graph attention network and attention mechanism,the method extracts spatial-temporal characteristics from the data of multiple wind ***,combined with a deep neural network,a convolutional graph attention deep neural network model is ***,the model is trained with the quantile regression loss function to achieve the wind power deterministic and probabilistic prediction based on multi-wind farm spatial-temporal data.A wind power dataset in the *** taken as an example to demonstrate the efficacy of the proposed *** with the selected baseline methods,the proposed model achieves the best prediction *** point prediction errors(i.e.,root mean square error(RMSE)and normalized mean absolute percentage error(NMAPE))are 0.304 MW and 1.177%,*** the comprehensive performance of probabilistic prediction(i.e.,con-tinuously ranked probability score(CRPS))is ***,the significance of multi-wind farm data and spatial-temporal feature extraction module is self-evident.

关键词： Format wind power prediction deep neural network graph attention network attention mechanism quantile regression