2019 IEEE Sustainable Power and Energy Conference (iSPEC)最新文献_第3页

Rule Extraction-based Data Augmentation Method for Transient Instability Identification of Power Systems Using Machine Learning 基于规则提取的电力系统暂态不稳定机器学习数据增强方法

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8975153

Yanzhen Zhou, Jian Guo, Qinglai Guo, Hongbin Sun, Ya-Chu Lu, Xiongfeng Xu

{"title":"Rule Extraction-based Data Augmentation Method for Transient Instability Identification of Power Systems Using Machine Learning","authors":"Yanzhen Zhou, Jian Guo, Qinglai Guo, Hongbin Sun, Ya-Chu Lu, Xiongfeng Xu","doi":"10.1109/iSPEC48194.2019.8975153","DOIUrl":"https://doi.org/10.1109/iSPEC48194.2019.8975153","url":null,"abstract":"Machine learning methods have become a promising method for rapid identification of transient stability and unstable generators of power systems. However, the transient unstable instances are always fewer than stable instances, which brings difficulties of transient instability identification. This paper presents a data augmentation approach to increase the number of unstable instances. Firstly, original data will be generated by time domain simulation considering the randomness and limitations of power systems. Then, the patient rule induction space (Prism) method is used to obtain the unstable rule set from the training data. After that, new instances can be generated by the unstable rules and time domain simulation. Then, the machine learning method is used to generate the transient stability prediction model and unstable generator identification model based these two kinds of instances. All the generated instances can be verified by time domain simulation. Comprehensive studies are conducted on the New England 10-machine 39-bus system to verify the effectiveness of the proposed approach.","PeriodicalId":413554,"journal":{"name":"2019 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129478576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Fault classification of PEM fuel cell systems based on CS-SVM method 基于CS-SVM的PEM燃料电池系统故障分类

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8975285

Jiaxi Yu, Qi Li, Wei-rong Chen, Jiawei Liu, Jincheng Li, Chengpeng Xu

引用次数: 1

Design of Automatic Verification System for Fully Compatible Metering Products Paper 全兼容计量产品自动检定系统设计

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8975181

He Yuhan, Sun Yanling, Zhai Xiaohui, Yu Danwen, Xing Yu, Song Jiale, Guo Liying

引用次数: 0

Flexibility Upgrading of LP Turbine Outage Scheme for Cogeneration Units and its Economic Cost Analysis 热电联产机组低压汽轮机停运方案的灵活性提升及其经济成本分析

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8974967

Haisheng Yang, Wenying Wang, W. Du

{"title":"Flexibility Upgrading of LP Turbine Outage Scheme for Cogeneration Units and its Economic Cost Analysis","authors":"Haisheng Yang, Wenying Wang, W. Du","doi":"10.1109/iSPEC48194.2019.8974967","DOIUrl":"https://doi.org/10.1109/iSPEC48194.2019.8974967","url":null,"abstract":"With the increasing pressure of the strengthening the peak load regulating capability for the cogeneration units in North China, various flexibility upgrading schemes are suggested for the existing cogeneration units. Among these LP Turbine Outage Upgrading Scheme is one of the most attractive schemes. Model-based software is utilized for the performance simulation of the one 300MW subcritical cogeneration unit and its LP Turbine Upgrading Scheme. Based on the models simulation results, the unit peak load regulating capability and the economical cost effect under various heating load conditions is studied. It is shown from the calculation results that under same main steam inlet flow condition, the maximum heating steam supply capacity is increased by around 100t/h and the unit power output is decreased by 14-15MW from the adopted upgrading scheme, therefore LP Turbine Outage operation can significantly increased heating supply capacity of the cogeneration unit. Further analysis indicates that under same heating steam supply conditions, compared with the original cogeneration unit the unit minimum power output can be decreased by around 56MW using the upgrading scheme, and this peaking load capacity improvement stays nearly constant for a wide range of heating load conditions. However, under LP Turbine Outage operation mode the disadvantage of operating as a backpressure generation unit makes the unit impossible to adapt to external power demand fluctuations. In addition, in spite of the performance improvement on heat rate and coal consumption rate per kW.h under same heating steam supply condition, the total economic benefit of the cogeneration unit is less profitable in upgrading scheme operation than in original scheme, which implies some compensation mechanism has to be arranged. The minimum peak load regulating marginal cost for upgrading scheme is calculated for this purpose.","PeriodicalId":413554,"journal":{"name":"2019 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124185807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Adaptive Wavelet Multilevel Soft Threshold Algorithm for Denoising Partial Discharge Signals 局部放电信号去噪的自适应小波多电平软阈值算法

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8975273

Shengya Sun, Yuanyuan Sun, Yahui Li, Shuo Ma, Lina Zhang, Yiru Hu

{"title":"An Adaptive Wavelet Multilevel Soft Threshold Algorithm for Denoising Partial Discharge Signals","authors":"Shengya Sun, Yuanyuan Sun, Yahui Li, Shuo Ma, Lina Zhang, Yiru Hu","doi":"10.1109/iSPEC48194.2019.8975273","DOIUrl":"https://doi.org/10.1109/iSPEC48194.2019.8975273","url":null,"abstract":"For denoising of partial discharge (PD) signals in electrical equipment, the traditional wavelet threshold method is affected by the empirical and subjective selection methods of wavelet base and decomposition layer, which will cause the waveform to be distorted and produce large errors in the process of denoising. In order to reduce the influence of the above factors, this paper proposes a new adaptive wavelet multilevel soft threshold denoising algorithm based on waveform similarity parameters and energy distribution analysis. Firstly, the waveform similarity method is used to determine the optimal wavelet base. Secondly, multi-scale wavelet decomposition is performed on the simulated ideal partial discharge signal and noise, and the signal is processed by the multilevel threshold method. Finally, the energy analysis of the PD signal and the noise signal is performed to determine the optimal number of decomposition layers. The proposed method and the traditional wavelet threshold method are used to denoise the simulated discharge signal, and the denoising effects of the two algorithms are compared quantitatively from four indexes: signal-to-noise ratio, root mean square error, waveform similarity coefficient and ascending trend parameter. After calculation, the index of the new algorithm is improved, which indicates that the new algorithm has certain practicability and provides a new reference for the denoising of PD signals.","PeriodicalId":413554,"journal":{"name":"2019 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121393846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed Gradient Algorithm for Economic Dispatch of Multi-area Power Systems 多区域电力系统经济调度的分布式梯度算法

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8975026

Shibiao Shao, F. Gao, Jiang Wu, Ruitong Liu, Yingxuan Yang, Fangwei Duan

{"title":"Distributed Gradient Algorithm for Economic Dispatch of Multi-area Power Systems","authors":"Shibiao Shao, F. Gao, Jiang Wu, Ruitong Liu, Yingxuan Yang, Fangwei Duan","doi":"10.1109/iSPEC48194.2019.8975026","DOIUrl":"https://doi.org/10.1109/iSPEC48194.2019.8975026","url":null,"abstract":"The economic dispatch of multi-area power systems can be regarded as a new constrained optimization problem in multi-agent network, which comparing to the problems that have been researched includes the global and local decision variables, as well as about their local equality constraints. For solving this problem, a modified distributed gradient algorithm is proposed by combining two existing methods. Firstly, the interaction prediction and balance method is used to solve the global and local decision variables alternately with a coordination center. Secondly, the optimization problem in coordination center is transformed into an existing constrained optimization problem in multi-agent network and solved by using the distributed primal-dual sub-gradient optimization algorithm. As thus, the multi-area economic dispatch problem can be optimized in a fully distributed way without any coordination center. Through the numerical testing of IEEE-24 bus system divided into three interconnected areas, the three areas can converge to the same global optimal solutions, and compared with the calculation results of centralized optimization, the correctness of the algorithm is verified.","PeriodicalId":413554,"journal":{"name":"2019 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114203738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Research on Calculation of Live Line Insulator Replacement Based on Life Cycle Cost 基于全寿命周期成本的带电绝缘子更换计算研究

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8974932

Chen Ran, Zhang Lingle, Yang Dong, Zhou Li, Zhang Yang

引用次数: 0

Short-term wind speed prediction model of VMD-FOAGRNN based on Lorenz disturbance 基于Lorenz扰动的VMD-FOAGRNN短期风速预测模型

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8974883

Guifang Pan, Jingyi Han, Yagang Zhang

{"title":"Short-term wind speed prediction model of VMD-FOAGRNN based on Lorenz disturbance","authors":"Guifang Pan, Jingyi Han, Yagang Zhang","doi":"10.1109/iSPEC48194.2019.8974883","DOIUrl":"https://doi.org/10.1109/iSPEC48194.2019.8974883","url":null,"abstract":"Accurate wind speed prediction is the key to wind energy development and utilization. However, due to the intermittent, random and chaotic nature of wind speed, wind speed prediction has the problem of low accuracy. So a short-term wind speed prediction model of VMD-FOAGRNN based on Lorenz perturbation is proposed in this paper to predict wind speed. Firstly, the actual wind speed sequence is decomposed into multiple components by variational mode decomposition (VMD). After that, the generalized regression neural network (GRNN) model is used for training and prediction for each component, and the GRNN model is optimized by the fruit fly optimization algorithm (FOA) to improve the wind speed prediction accuracy. Next, the predicted values of the respective components are reconstructed to obtain the preliminary prediction values of wind speed. Finally, in consideration of the influence of atmospheric disturbance on wind speed, the Lorenz equation is introduced to correct the preliminary prediction values of wind speed to obtain the final wind speed prediction values. The high prediction accuracy and versatility of the prediction model of this paper are verified by experimenting with the wind speed data of two wind farms.","PeriodicalId":413554,"journal":{"name":"2019 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121625379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Review On Insulation And Reliability Of Dry-type Transformer 干式变压器绝缘与可靠性研究进展

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8975106

Peng Chen, Yangjue Huang, Fanjie Zeng, Yang Jin, Xiaofeng Zhao, Jinfeng Wang

引用次数: 9

Comprehensive Economic Benefit Assessment Method and Example of Energy Storage Based on Power Grid 基于电网的储能综合经济效益评价方法及实例

2019 IEEE Sustainable Power and Energy Conference (iSPEC) Pub Date : 2019-11-01 DOI: 10.1109/iSPEC48194.2019.8975018

J. Ke, Zhang Xinzhen, Su-Chuan Lin, Shi Zinan, Wang Haobo, Yu Guoqiang, Jiang Hua

{"title":"Comprehensive Economic Benefit Assessment Method and Example of Energy Storage Based on Power Grid","authors":"J. Ke, Zhang Xinzhen, Su-Chuan Lin, Shi Zinan, Wang Haobo, Yu Guoqiang, Jiang Hua","doi":"10.1109/iSPEC48194.2019.8975018","DOIUrl":"https://doi.org/10.1109/iSPEC48194.2019.8975018","url":null,"abstract":"With the continuous development of energy storage technology, more and more scenarios of energy storage are applied in user side, generation side and power grid side. However, there is no mature commercial and profit model for grid-side energy storage system, so it is necessary to evaluate the comprehensive economic benefits of grid-side energy storage system. In this paper, a life cycle cost analysis method for energy storage system is proposed. Considering the comprehensive benefits of grid-side energy storage system in delaying grid construction, power supply installation, energy saving and emission reduction, an input-output benefit evaluation model and method for grid-side energy storage system are constructed and verified by typical examples. The results show that with the increase of battery life and the decrease of battery cost, the economic benefits of energy storage on the grid side become more and more obvious, and the comprehensive benefits of energy storage on the grid side will be significantly reduced with the slowdown of load growth rate.","PeriodicalId":413554,"journal":{"name":"2019 IEEE Sustainable Power and Energy Conference (iSPEC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127590519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2