发布求助
文献互助 智能选刊 最新文献

2021 IEEE International Conference on Energy Internet (ICEI)最新文献

筛选
英文 中文
Robust Optimization Strategy for Residential User’s Electricity Price Score Coefficient Considering Response Uncertainty 考虑响应不确定性的住宅用户电价得分系数稳健优化策略
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00022
Yujiang Chen, Kun Yu, Xingying Chen, Lei Gan
{"title":"Robust Optimization Strategy for Residential User’s Electricity Price Score Coefficient Considering Response Uncertainty","authors":"Yujiang Chen, Kun Yu, Xingying Chen, Lei Gan","doi":"10.1109/ICEI52466.2021.00022","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00022","url":null,"abstract":"The current Chinese residential electricity prices are regulated by the government, which cannot well reflect the relationship between supply and demand, and have made it difficult to develop a more flexible price-based demand response mechanism. The proposal of electricity price score mechanism can well solve the problem of price control under such regulated market environment. However, due to the lack of considering users’ response uncertainty in the current design of electricity price score coefficient, the effect of the score mechanism is greatly reduced. Thus, a robust optimization strategy of electricity price score setup is proposed here considering the uncertainty of users’ response. Firstly, based on analyzing the load adjustable potential of residential users, the kernel density estimation method is used to calculate the load adjustable potential of group users, and then the users’ response characteristic model considering uncertainty is established based on the theory of consumer psychology. Secondly, a robust optimization model of electricity price score coefficient is constructed with the goal of minimizing expenditure cost to stimulate demand response program, solved by CPLEX. The numerical analysis verifies that the obtained price coefficient design strategy of the proposed method can mobilize the enthusiasm of residential users to participate in the interaction of the power grid. When the uncertainty of users’ response occurs, the power grid can reduce the peak-valley differential rate at the least cost, which is of great significance to improve the operational efficiency of power system, and alleviate power supply pressure, as well as to contribute to energy conservation and emission reduction in China.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123926802","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
A Flexible SoC Subsystem for Harmonic Measurement and Metering 一个灵活的SoC谐波测量与计量子系统
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00026
Xiaohui Xiao, Chunguang Lu, N. Tan, Jie Cao, Hengzhi Hu, Aijun Wang
{"title":"A Flexible SoC Subsystem for Harmonic Measurement and Metering","authors":"Xiaohui Xiao, Chunguang Lu, N. Tan, Jie Cao, Hengzhi Hu, Aijun Wang","doi":"10.1109/ICEI52466.2021.00026","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00026","url":null,"abstract":"The widespread use of power electronic devices has introduced a lot of harmonics to the power grid. It is increasingly essential that an energy meter in the smart grid is able to measure the harmonics. In this paper, we design a flexible harmonic processing SoC subsystem for the energy meter. The subsystem is composed of a transceiver to receive and transfer data through an SPI automatically, a fast fourier transform (FFT) engine to transform the received time-domain signal to the frequency-domain, and a digital signal processor (DSP) to measure the harmonics from the FFT results. With the flexibility of the design, users can carry out different harmonic processing algorithms without taking up much CPU resources. The design is verified by universal verification methodology (UVM) verification and field programmable gate array (FPGA) prototyping and is currently under fabrication.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116751759","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
Electricity-heat collaborative optimization strategy in microgrid using deep reinforcement learning 基于深度强化学习的微电网热电协同优化策略
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00008
Ma Hanmei, Sun Mingyue, Jian Yanhong, Wang Qian, W. Yirong
{"title":"Electricity-heat collaborative optimization strategy in microgrid using deep reinforcement learning","authors":"Ma Hanmei, Sun Mingyue, Jian Yanhong, Wang Qian, W. Yirong","doi":"10.1109/ICEI52466.2021.00008","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00008","url":null,"abstract":"With the massive penetration of renewable energy, the flexibility of microgrids is rapidly declining, and its optimal operation is facing great challenges. For the microgrid that uses regional centralized heating as the source of heating power, we propose to use local electric heating devices to provide auxiliary heating to reduce the operating cost of the microgrid. We first establish an electricity-heat collaborative optimization framework that considers real-time prices in the electricity market and unit heating power prices in regional centralized heating. Then, in order to minimize the long-term cost of the microgrid, we transformed the optimized operation of the microgrid into a Markov decision process problem, and applied the deep deterministic policy gradient algorithm to solve the problem. Finally, we verify through simulation experiments that the architecture and algorithm proposed in this paper can effectively reduce the operating cost of the microgrid by 27.5%, and the algorithm has good convergence and stability.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127611375","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
Benefits Allocation Method for Demand Response in Smart Distribution Network with High PV Penetration 高光伏渗透率智能配电网需求响应的利益分配方法
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00023
Xiu-Chao Tang, Kun Yu, Xingying Chen, Lei Gan, H. Hua
{"title":"Benefits Allocation Method for Demand Response in Smart Distribution Network with High PV Penetration","authors":"Xiu-Chao Tang, Kun Yu, Xingying Chen, Lei Gan, H. Hua","doi":"10.1109/ICEI52466.2021.00023","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00023","url":null,"abstract":"Under the background of the Chinese government has committed that China will achieve peak carbon dioxide emissions before 2030 and carbon neutrality before 2060, renewable energy and distributed generation (DG) have once again focused people’s attention. However, the access of DG will cause the reverse power flow of the distribution network, which will cause problems such as voltage overruns and voltage fluctuations. To a certain extent, these problems can be solved by demand response (DR). This paper proposes a DR benefit allocating method in smart distribution network (SDN) with high PV penetration, which constructs a user’s demand response contribution (DRC) index system, and uses the TOPSIS ranking method to comprehensively evaluate the user’s DRC. The calculation example proves that the proposed index system can more comprehensively measure the DRC of users, and can provide a fairer apportionment index for the next benefit allocation, compared with the traditional method of benefit allocation based only on the amount of interactive electricity in DR.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"02 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129267343","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: 4
Blockchain-Based Distributed Reputation for a Cap-and-Trade Carbon Emission System 基于区块链的碳排放限额与交易系统的分布式声誉
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00039
Dong Wang, Da Li, Junwei Ma, Zhenhua Yan, Yongliang Li, Tonghe Wang, Songpu Ai, Junwei Cao
{"title":"Blockchain-Based Distributed Reputation for a Cap-and-Trade Carbon Emission System","authors":"Dong Wang, Da Li, Junwei Ma, Zhenhua Yan, Yongliang Li, Tonghe Wang, Songpu Ai, Junwei Cao","doi":"10.1109/ICEI52466.2021.00039","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00039","url":null,"abstract":"Reputation has been widely used in the energy field in recent years. However, their reputation mechanisms are usually centralized even if they are designed for distributed energy systems, which could cause vulnerability to single point failures. This paper explores the design of blockchain-based distributed reputation for a cap-and-trade carbon emission system. The blockchain technology is adopted to achieve distributed management of reputation scores and realize a peer-to-peer carbon trading market. Simulation experiments are carried out to demonstrate the influence of the proposed reputation rules on reputation scores. In addition, a case study shows how reputation affects the results of carbon trading. As far as we know, this paper is one of the few works that incorporate distributed reputation in a carbon emission system.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133014218","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
Classification Method of Voltage Sag Sources in Station Area Based on Edge Computing 基于边缘计算的站区电压暂降源分类方法
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00014
Yonggui Wang, Zhu Liu, Lvchao Huang, Shuai Zhang, Zhi Li, Siyang Deng
{"title":"Classification Method of Voltage Sag Sources in Station Area Based on Edge Computing","authors":"Yonggui Wang, Zhu Liu, Lvchao Huang, Shuai Zhang, Zhi Li, Siyang Deng","doi":"10.1109/ICEI52466.2021.00014","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00014","url":null,"abstract":"Classification of the voltage sag are the keys of power quality improvement and responsibility definition between the power supply and consumption. A method for voltage sag calssification based on edge intelligent terminal is proposed in this paper. Relying on the power distribution Internet of Things system, the training and execution mechanism of the voltage sag source classification model based on cloud-side collaboration is designed. Aiming at five types of sag source faults, including sag source orientation, symmetrical fault, asymmetrical fault, motor startup, and transformer switching, a sag source identification model based on support vector machine (SVM) algorithm is proposed. Test and simulation results demonstrate that the average accuracy of the sag source calssification is higher than 98%, which is better than the LR, ID3, C4.5, KNN methods. Meanwhile, the task processing time, CPU load utilization and memory load utilization for the cloud-edge collaboration strategy are superior to the traditional cloud-architecture.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131171466","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
Short-term Load Forecasting Based on Hierarchical Clustering and ISA-LSSVM Model 基于分层聚类和ISA-LSSVM模型的短期负荷预测
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00019
Bin Yang, Xuesong Shao, Le Zheng
{"title":"Short-term Load Forecasting Based on Hierarchical Clustering and ISA-LSSVM Model","authors":"Bin Yang, Xuesong Shao, Le Zheng","doi":"10.1109/ICEI52466.2021.00019","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00019","url":null,"abstract":"For short-term load forecasting of different types of users, support vector machine and deep learning model are widely used at present. A hybrid model is proposed to solve the problems of the least squares support vector machine (LSSVM) model, such as the difficulty in determining the hyperparameters, the high data quality requirements of the model, and the slow optimization speed and easy to fall into the local optimization of the integrated conventional optimization algorithm. In this model, firstly, the original feature data is clustered by hierarchical clustering (HC) and then the corresponding LSSVM model is established for the same prediction day. Then, the super parameters in LSSVM are heuristic searched by the improved simulated annealing algorithm (ISA). Finally, by comparing the performance of the load forecasting model with that of various load forecasting models, the results show that the proposed model can effectively improve the accuracy of load forecasting and shorten the forecasting time.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"2016 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127430165","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
A new security authentication method for master station and terminal 一种新的主站和终端安全认证方法
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00029
Fan He, Z. Ang, Qingqin Fu, Guanglun Yang, Pingjiang Xu, Jia Liu, Ling Yi, Changsheng Niu, Jiankui Liu, Yuqiang Jiang
{"title":"A new security authentication method for master station and terminal","authors":"Fan He, Z. Ang, Qingqin Fu, Guanglun Yang, Pingjiang Xu, Jia Liu, Ling Yi, Changsheng Niu, Jiankui Liu, Yuqiang Jiang","doi":"10.1109/ICEI52466.2021.00029","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00029","url":null,"abstract":"This paper analyzes the shortcomings of the traditional master station and terminal security authentication method, and proposes a new security authentication method for the master station and the terminal. This method uses a combination of session initialization and recovery, and session negotiation instructions to complete security authentication. The user can optionally execute the corresponding application instruction according to the actual application, thereby improving the security of the authentication and the randomness of the session key of the subsequent business operation.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121034120","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
State Estimation of Energy Internet Using SCADA and PMU Data Based on Graph Convolutional Networks 基于图卷积网络的SCADA和PMU数据能源互联网状态估计
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00024
Xian Wu, Huaying Zhang, Shengru Guo, Junwei Cao
{"title":"State Estimation of Energy Internet Using SCADA and PMU Data Based on Graph Convolutional Networks","authors":"Xian Wu, Huaying Zhang, Shengru Guo, Junwei Cao","doi":"10.1109/ICEI52466.2021.00024","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00024","url":null,"abstract":"The real-time state estimation is crucial to guarantee the stable operation of energy Internet (EI) which has variable loads and distributed power generations. Therefore, this paper proposes a real-time transient state estimation method for EI based on graph convolutional networks (GCN). Using data of SCADA and limited phasor measurement unit (PMU), the GCN in the proposed method fuses the heterogeneous data of EI buses with the adjacency matrix that represents the topology of EI. Then the transient states of EI buses without PMU measurement are estimated by SCADA data and adjacent PMU data through the training of GCN model. The case study on the simulation data of an IEEE 9 bus system that considers fault injection and disturbances verifies the effectiveness of the proposed approach. The result shows that the proposed approach achieves fast and accurate state estimation of all EI buses during the transient process of faults and disturbances.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126857349","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
Research on Insulating Oil Gas Analysis and Fault Prediction Based on the Edge Computing Platform of the Internet of Things 基于物联网边缘计算平台的绝缘油气分析与故障预测研究
2021 IEEE International Conference on Energy Internet (ICEI) Pub Date : 2021-09-01 DOI: 10.1109/ICEI52466.2021.00044
J. Lin, Wenjing Guo, Rundong Liu, Wenjing Li, Zhi Li, X. Liang
{"title":"Research on Insulating Oil Gas Analysis and Fault Prediction Based on the Edge Computing Platform of the Internet of Things","authors":"J. Lin, Wenjing Guo, Rundong Liu, Wenjing Li, Zhi Li, X. Liang","doi":"10.1109/ICEI52466.2021.00044","DOIUrl":"https://doi.org/10.1109/ICEI52466.2021.00044","url":null,"abstract":"The analysis of dissolved gas in insulating oil is essential for judging the abnormality or potential failure of oil-filled electrical equipment such as transformers or high-resistance. Currently, oil chemical analysis experiments mainly rely on manually taking oil samples and sending them to testing laboratories for manual analysis and judgment. This process takes a long time, and the oil samples are prone to oxidization and deterioration during transportation, which significantly reduces the detection efficiency and judgment accuracy. Based on the edge computing platform of the Internet of Things, this paper builds the framework of the online insulating oil gas analysis system. It uses the Least Squares Twin Support Vector Regression machine (LSTSVR) as the calculation model on the edge side and then carries out the accuracy and accuracy test. The test results show that the system can automatically sample and analyze in real-time, shorten the detection delay, and provide accurate data results and fault range prediction.","PeriodicalId":113203,"journal":{"name":"2021 IEEE International Conference on Energy Internet (ICEI)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116124253","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信