2020 IEEE International Conference on Energy Internet (ICEI)最新文献_第2页

Sensitivity Analysis-based Control Parameters Optimization for MMC-based DC Distribution Systems 基于灵敏度分析的mmc直流配电系统控制参数优化

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00016

Jialing Liu, Wansong Liu, Boyu Qin

引用次数: 1

Steady-state Power Quality Anomaly Recognition Based on Time Series Trend 基于时间序列趋势的稳态电能质量异常识别

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00011

Song Guo, Pengpai Feng, Zhipeng Zhong, Wenqing Li, Chenguan Xu, Meng Yu, Yuantong You, Yongbing Tang, Wenxu Yao

{"title":"Steady-state Power Quality Anomaly Recognition Based on Time Series Trend","authors":"Song Guo, Pengpai Feng, Zhipeng Zhong, Wenqing Li, Chenguan Xu, Meng Yu, Yuantong You, Yongbing Tang, Wenxu Yao","doi":"10.1109/ICEI49372.2020.00011","DOIUrl":"https://doi.org/10.1109/ICEI49372.2020.00011","url":null,"abstract":"In order to improve the quality of power supply to the park and conduct differentiated service and management, the influence of the power quality (PQ) level of the park needs to be considered. At the same time, the traditional steady-power quality anomaly identification method only compares the value with the limit value and does not consider the change trend of the data, which has some limitations. The characteristics of time-series trend changes of steady-state power quality data is focused on this paper and a steady-state power quality anomaly identification method based on time series trend analysis is proposed. Firstly, data preprocessing is carried out through piecewise linearization to filter out data fluctuations and retain the main trend change characteristics of data. Secondly, the trend change of data is represented by the trend pattern, and the similarity between different trend sequences is calculated by the pattern distance. Finally, combined with the amplitude anomaly index, the comprehensive anomaly index of the data to be identified relative to the normal data segment is calculated to identify whether there are anomalies in the steady-state power quality of the corresponding measurement point. Through simulation examples and case analysis, it is proved that the proposed method is accurate, applicable and easy to implement, and can be easily integrated into the existing power quality monitoring system.","PeriodicalId":418017,"journal":{"name":"2020 IEEE International Conference on Energy Internet (ICEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129249497","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

[Title page i] [标题页i]

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/icei49372.2020.00001

引用次数: 0

Distributed Multi-Factor Electricity Transaction Match Mechanism based on Blockchain 基于区块链的分布式多因素电力交易匹配机制

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00030

Songpu Ai, Diankai Hu, Jian Guo, Yunpeng Jiang, Chunming Rong, Junwei Cao

{"title":"Distributed Multi-Factor Electricity Transaction Match Mechanism based on Blockchain","authors":"Songpu Ai, Diankai Hu, Jian Guo, Yunpeng Jiang, Chunming Rong, Junwei Cao","doi":"10.1109/ICEI49372.2020.00030","DOIUrl":"https://doi.org/10.1109/ICEI49372.2020.00030","url":null,"abstract":"With the rapid development of the power generation technology of distributed renewable energy, great quantities of prosumers emerged and joined to regional energy internets (REIs), which could lead to challenges to conventional energy transaction match mechanisms. At the present stage, traditional mechanisms such as double auction are mostly adopted in the process of electricity transaction match, which may lead problems with practical utilization such as the match of clean energy is relatively difficult and the waste of electricity transmission is hard to be indicated, etc. In addition, the conventional centralized match platform could face challenges considering the widely deployment of building and even house level prosumers among regions, as well as the instantaneous variable characteristic of clean energy generation such as photovoltaic and wind. Aiming at the challenges above, a blockchain-based multi-factor electricity transaction match mechanism is proposed in this paper. The suitability of multiple factors such as electricity price, transaction volume, transmission distance, and energy type are calculated and compared based on the calculation formula of dissimilarity degree in the K-prototypes clustering. The most suitable seller and purchaser demands are matched. Moreover, corresponding automatic match, signing match records by private key and settlement of the transactions were designed based on smart contract. The experimental results illustrated that compared with conventional solutions, by adopting the proposed mechanism, the supply proportion of clean energy in the entire REI increased to 80.40%; the actual unit price gap between clean energy and nonclean energy decreased by 63.00%; the total electricity sale volume in the entire REI increased by 83.37%.","PeriodicalId":418017,"journal":{"name":"2020 IEEE International Conference on Energy Internet (ICEI)","volume":"17 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131234657","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: 6

A Blockchain-based Distributed Controllable Electricity Transaction Match System 基于区块链的分布式可控电力交易匹配系统

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00019

Songpu Ai, Diankai Hu, Jian Guo, Yunpeng Jiang, Chunming Rong, Junwei Cao

{"title":"A Blockchain-based Distributed Controllable Electricity Transaction Match System","authors":"Songpu Ai, Diankai Hu, Jian Guo, Yunpeng Jiang, Chunming Rong, Junwei Cao","doi":"10.1109/ICEI49372.2020.00019","DOIUrl":"https://doi.org/10.1109/ICEI49372.2020.00019","url":null,"abstract":"A large number of individual power prosumers are emerging and participating in the regional energy internet (REI) with the rapid development of the power generation technology of distributed renewable energy. The increasing scale of the REI may bring challenges to the traditional centralized electricity trading and match platform in the REI. However, existing researches and realizations on blockchain based distributed electricity transaction platform adopts traditional mechanisms such as double auctions more, which may cause challenges in actual applications such as the match of clean energy is relatively difficult, the waste of electricity transmission is hard to be calculated, and the electricity seller cannot select the purchaser, etc. In this paper, a blockchain-based distributed controllable electricity transaction match system is designed and implemented to propose a feasible system to overcome the existing challenges. The automatic match of single transactions on the blockchain is implemented based on smart contract technology in the system, which avoids the interference of the number of transactions and the matching cycle on the matching speed of single transaction in the matching process. Experimental results indicated that compared with traditional solutions, the supply ratio of clean energy in the entire REI increased from 4.69% to 78.15% by adopting the proposed system, and the electricity transmission loss in the entire REI is reduced by 1.08%.","PeriodicalId":418017,"journal":{"name":"2020 IEEE International Conference on Energy Internet (ICEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131267921","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

Voltage Sag Mitigation Strategy for Industrial Users Based on Process Electrical Characteristics-physical Attribute 基于过程电气特性-物理属性的工业用户电压暂降缓解策略

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00014

Mingwen Zhuang, Jingteng Chen, Minhui Wu, Songyong Xiao, Fang Chen, Weiming Li

{"title":"Voltage Sag Mitigation Strategy for Industrial Users Based on Process Electrical Characteristics-physical Attribute","authors":"Mingwen Zhuang, Jingteng Chen, Minhui Wu, Songyong Xiao, Fang Chen, Weiming Li","doi":"10.1109/ICEI49372.2020.00014","DOIUrl":"https://doi.org/10.1109/ICEI49372.2020.00014","url":null,"abstract":"Voltage sag can cause abnormal interruption of production process of industrial users, resulting in huge economic losses. In view of the single governance angle and poor governance effect of existing voltage sag mitigation schemes, according to the electrical characteristics and physical attributes of industrial processes, this paper proposes electrical means focusing on voltage control and physical means focusing on process quantity maintenance. From the point of view of process parameters, the effects of various mitigation measures are measured in a unified way. A voltage sag mitigation method is proposed, which combines the installation of customized power equipment with the renovation of plant facilities, in order to maintain the process parameters during the period of disturbance and avoid the serious consequences of process interruption. Considering the investment cost and income of various mitigation measures, the allocation of mitigation measures is determined with the goal of maximizing the net present value of the scheme. The mitigation strategy proposed in this paper is applied to a new energy material enterprise. The results show that the proposed method can effectively mitigate the consequences of voltage sag and is more economical than the traditional voltage compensation scheme.","PeriodicalId":418017,"journal":{"name":"2020 IEEE International Conference on Energy Internet (ICEI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127986129","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 the Impact of the Frequency Deviation of the Crystal Oscillator on PMU Measurement in Steady State Condition 稳态条件下晶体振荡器频率偏差对PMU测量的影响研究

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00026

W. Xiong, Shuang Leng, Guoen Wei, Z. Yuan, Quan Xu, Shaofan Zhang, Feiyang Xu, Wenwei Chen, A. Xue

引用次数: 0

Deep Learning Detection Method of Encrypted Malicious Traffic for Power Grid 电网加密恶意流量的深度学习检测方法

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00024

Lin Chen, Yixin Jiang, Xiaoyun Kuang, Aidong Xu

引用次数: 1

Power Grid Risky IP Identification Algorithm Based on Hybrid Genetic Ensemble Learning 基于混合遗传集成学习的电网风险IP识别算法

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00012

Yixin Jiang, Lin Chen, Xiaoyun Kuang, Aidong Xu, Yiwei Yang

引用次数: 1

Digital-twin based Power Supply System Modeling and Analysis for Urban Rail Transportation 基于数字孪生的城市轨道交通供电系统建模与分析

2020 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2020-08-01 DOI: 10.1109/ICEI49372.2020.00022

Jian Guo, Xiaobo Wu, Hong Liang, Junfeng Hu, B. Liu

引用次数: 2