2020 5th International Conference on Power and Renewable Energy (ICPRE)最新文献_第10页

Optimal Design of Multi-energy Complementary Distributed Energy System Considering Load Uncertainty 考虑负荷不确定性的多能互补分布式能源系统优化设计

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233144

Huan Ma, Pengfei Zhang, Zhongyang Chen, Ying Fan, Na Wang, H. Ren

{"title":"Optimal Design of Multi-energy Complementary Distributed Energy System Considering Load Uncertainty","authors":"Huan Ma, Pengfei Zhang, Zhongyang Chen, Ying Fan, Na Wang, H. Ren","doi":"10.1109/ICPRE51194.2020.9233144","DOIUrl":"https://doi.org/10.1109/ICPRE51194.2020.9233144","url":null,"abstract":"With the large-scale penetration of distributed combined cooling, heating and power system, many problems like the poor flexibility and single energy source occur, which poses a big obstacle to its future development. To overcome these issues, the multi-energy complementary distributed energy system is proposed for improving the flexibility and increasing the ratio of renewable energy resources. For such a complex system, how to integrate and operate various equipment in an efficient and environmentally friendly way is of vital importance. Thus, rational system design and optimization is necessary. In this study, on the basis of stochastic programming theory, the optimal equipment configuration of the multi-energy complementary distributed energy system considering uncertain loads is studied. All possible load conditions are simulated by Monte Carlo simulation, then the stochastic optimization is transformed into the deterministic optimization. The results show that when considering the uncertain load, the system configuration is affected obviously and the overall advantage of the multi-energy complementary distributed energy system is declined.","PeriodicalId":394287,"journal":{"name":"2020 5th International Conference on Power and Renewable Energy (ICPRE)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123342951","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

Region-Free Cloud Recognition Based on Center Net 基于中心网的无区域云识别

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233243

Chen Jing, Cui Chenggang, Yan Nan, Xi Peifeng

{"title":"Region-Free Cloud Recognition Based on Center Net","authors":"Chen Jing, Cui Chenggang, Yan Nan, Xi Peifeng","doi":"10.1109/ICPRE51194.2020.9233243","DOIUrl":"https://doi.org/10.1109/ICPRE51194.2020.9233243","url":null,"abstract":"Because of the significant influence produced by different types of cloud on photovoltaic power, accurate cloud identification is developed widely to predict the variation of photovoltaic power generation. Classical cloud-recognition methods generally use texture, structure, and color simultaneously to capture the cloud characteristic. In this paper, a Center Net-based cloud image recognition method is applied to cloud identification for the first time to simplify the operation and enhance the detection speed. The proposed algorithm adopts Hourglass Resdcn18, Resdcn101, and DLA -34 networks respectively to generate heatmap, and picks the heatmap peaks as a center point for target identification. Eight kinds of clouds are selected to verify the detection performance of the proposed algorithm: altocumulus, altostratus, cumulus, cirrus, cirrostratus, cumulonimbus, cumulonimbus, stratocumulus. The effectiveness of identification is compared under the structure of each network. The cloud center location and confidence are visualized under the DLA-34 model with higher confidence. The results showed that the highest confidence level of DLA-34 network is 0.973, which is higher than that of other networks apparently. Compared with Faster R-CNN, the cloud image recognition speed of Center Net is faster and the confidence is higher.","PeriodicalId":394287,"journal":{"name":"2020 5th International Conference on Power and Renewable Energy (ICPRE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116944983","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

Analysis and Realization Method of Selective Leakage Protection Technology of Self-adaptive Full Compensation Domain 自适应全补偿域选择性漏电保护技术分析与实现方法

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233238

Li Rui

引用次数: 1

Data Mining Based Reactive Power and Voltage Operation Assessment in Power Grid 基于数据挖掘的电网无功电压运行评估

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233251

Lufei Xu, Tianhua Chen, Gen Li, Jianhua Chen

引用次数: 0

A Method of Updating Load Characteristic Database of Typical Consumers Based on Machine Algorithm 基于机器算法的典型用户负荷特征库更新方法

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233308

Junying Song, Zhenyu Mao, Xinran Li, Taowen Liu, W. Zhong, Yiwei Cui

{"title":"A Method of Updating Load Characteristic Database of Typical Consumers Based on Machine Algorithm","authors":"Junying Song, Zhenyu Mao, Xinran Li, Taowen Liu, W. Zhong, Yiwei Cui","doi":"10.1109/ICPRE51194.2020.9233308","DOIUrl":"https://doi.org/10.1109/ICPRE51194.2020.9233308","url":null,"abstract":"The daily load curves of the electric power system can reflect the actual electricity consumption characteristics of consumers, so daily load curves of the electric power system is widely used in load modeling. However, due to the complexity of most consumers' power consumption structures. it is difficult to distinguish the typical characteristics. So it is necessary to establish a more accurate load characteristics database of typical consumers to achieve the typical industry classification of different consumers. In order to solve the problem that the current power consumption characteristics are not obvious and it is difficult to select typical consumers, this paper proposes a method of updating typical consumers load characteristics database based on machine algorithm by using the support vector machine algorithm. First of all, read the historical load characteristic database of typical consumers and train the historical daily load curve data. Secondly, comprehensively use the support vector machine algorithm to identify the industry of the new consumers daily load data and determine its typical degree. Finally, eliminate the data with poor characteristics in the database, so as to realize the update of the typical consumers load characteristic database. The results show that the proposed method can improve the cluster quality, realize the database updating and optimization, and truly reflect the power consumption characteristics of consumers in a certain area.","PeriodicalId":394287,"journal":{"name":"2020 5th International Conference on Power and Renewable Energy (ICPRE)","volume":"194 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132479931","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

Design of Mine-Used Combination Switch Gateway Based on EtherNet/IP 基于以太网/IP的矿用组合交换机网关设计

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233221

Ding Junfeng, Rong Xiang, YU Shuohang, Wei Lipeng

引用次数: 1

Power System State Estimation Based on RWUKF Algorithm 基于RWUKF算法的电力系统状态估计

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233184

Chen Yang, Qiang Song, Yongjin Yu, Na Wu, Xingquan Ji

引用次数: 1

Analysis of Material and Temperature Rise Test of 10kV Drop-out Fuse 10kV熔断器材料分析及温升试验

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233209

Liang Xingyu, Wang Feiming, Cheng Hui, Jin Yuanyuan, Li Bing, G. Baohong

{"title":"Analysis of Material and Temperature Rise Test of 10kV Drop-out Fuse","authors":"Liang Xingyu, Wang Feiming, Cheng Hui, Jin Yuanyuan, Li Bing, G. Baohong","doi":"10.1109/ICPRE51194.2020.9233209","DOIUrl":"https://doi.org/10.1109/ICPRE51194.2020.9233209","url":null,"abstract":"In order to effectively control the quality of the 10kV drop fuse, the main reason for the operation of the fuse in the system is given, and the quality improvement method is proposed. The State Grid Corporation conducts the sampling test of the 10kV drop fuse. Through the material analysis and temperature rise test of the fuse, the material temperature of the contact surface of the main circuit conductor of the 10kV drop fuse is tested, and the test standard temperature rise limit is given. Combined with the temperature rise test results, the operating conditions and quality problems of the fuse equipment were analyzed. The test analyzes the root cause of the different operating currents of the fuses and the overheating at different locations. The temperature rise curve and the rising rate of the fuses at different positions are given. The results show that the fuse materials generally have different degrees of defects, the material testing failure rate is 88.9%, and the temperature rise test failure rate is 44.4%. The heat rise point of the fuse temperature rise test is mainly concentrated on the sliding position of the upper conductive piece and the upper contact, the screw connection position of the upper contact nut and the fusion tube, and the fastening position of the fuse and the lower conductor bolt. Therefore, strictly controlling the material quality of the 10kV drop fuse is of great significance for improving the stable operation of the 10kV drop fuse. The research results in this paper provide technical support for the material procurement of State Grid Corporation.","PeriodicalId":394287,"journal":{"name":"2020 5th International Conference on Power and Renewable Energy (ICPRE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131174509","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

Insulation Detection Technology and Its Application of AC-DC Distribution Cables 交直流配电电缆绝缘检测技术及其应用

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233203

Luan Jun, Jiang Xuan, Ji Xiang, Lei Xing, L. Wenzhu, Cai Yanxing

引用次数: 1

Simulation of Fault Detection in Photovoltaic System Based On SSTDR 基于SSTDR的光伏系统故障检测仿真

2020 5th International Conference on Power and Renewable Energy (ICPRE) Pub Date : 2020-09-12 DOI: 10.1109/ICPRE51194.2020.9233125

Zhihua Li, Zhanfei Yang, Chunhua Wu

引用次数: 1