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Residential Short Term Load Forecasting Based on Federated Learning 基于联邦学习的住宅短期负荷预测
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998969
Jiuxiang Chen, Tianlu Gao, Ruiqi Si, Yuxin Dai, Yuqi Jiang, Jun Zhang
{"title":"Residential Short Term Load Forecasting Based on Federated Learning","authors":"Jiuxiang Chen, Tianlu Gao, Ruiqi Si, Yuxin Dai, Yuqi Jiang, Jun Zhang","doi":"10.1109/DTPI55838.2022.9998969","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998969","url":null,"abstract":"Load forecasting is an essential task in the power industry as an important means to assist the grid to balance supply demand. A large amount of user data monitored by smart grids can support deep learning models for load prediction, but accurate and fine-grained user data may reveal consumers' electricity consumption behaviors, which brings privacy and security issues. Federated Learning (FL) is a new type of high-efficiency machine learning between multiple participants or multiple computing nodes under the premise of ensuring information security during big data exchange and protecting the privacy of terminal data and personal data. Therefore, this paper explored a short-term residential energy demand forecasting method based on FL. The experimental data comes from the U.S. hourly residential base load. The federal forecast model was built on Pytorch, and we explored model behavior under different experimental conditions.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133924881","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
Architecture of Intelligent Operation Center for Thermal Power Unit 火电机组智能运行中心体系结构研究
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998879
Gao Yaokui, G. Haidong, Wang Lin, Gong Linjuan, Wang Wenyu, Lei Yangxiang, Wu Jianguo, Yu Xinbo, Sun Guangqing
{"title":"Architecture of Intelligent Operation Center for Thermal Power Unit","authors":"Gao Yaokui, G. Haidong, Wang Lin, Gong Linjuan, Wang Wenyu, Lei Yangxiang, Wu Jianguo, Yu Xinbo, Sun Guangqing","doi":"10.1109/DTPI55838.2022.9998879","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998879","url":null,"abstract":"Starting from the practical application requirements, this paper proposes the architecture of the intelligent operation center (IOC) for thermal power unit, involving hardware, network, and functions. In terms of hardware and network, based on the distributed control system, this paper further expands the intelligent controller, high-performance server, intelligent interface, decision-level network, etc., so as to meet the requirements of IOC for intelligent control, complex computing, massive data access, big data analysis, artificial intelligence learning, data visualization, high-speed interaction. In terms of functions, based on the goals, connection relationships and information flow processes of different applications, this paper divides the functions of the IOC into intelligent control, autonomous decision-making, and intelligent interaction, which are of great significance to the construction of smart power plants and the development of smart energy systems.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127732812","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
Path Planning of Mobile Robot Based on an Improved Genetic Algorithm 基于改进遗传算法的移动机器人路径规划
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998894
Zenghua Chen, Gang Xiong, Sheng Liu, Zhen Shen, Yue Li
{"title":"Path Planning of Mobile Robot Based on an Improved Genetic Algorithm","authors":"Zenghua Chen, Gang Xiong, Sheng Liu, Zhen Shen, Yue Li","doi":"10.1109/DTPI55838.2022.9998894","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998894","url":null,"abstract":"In order to solve the problem of premature convergence of the basic genetic algorithm when planning the robot running path, the basic genetic algorithm is improved and optimized. Different population initialization methods are used to initialize multiple populations randomly, so as to improve the diversity of populations; Improve the adaptive strategy and elite strategy of crossover and mutation operators to improve the convergence speed of the algorithm; Add the path tortuosity as the planning index in the fitness function to make the planned path smoother, and add constraints to the model to avoid obstacles; Finally, through the transformation of the coding paradigm of the above improved genetic algorithm, it can run on Flink distributed cluster to obtain faster solution speed, so as to meet the efficiency requirements of path planning in large-scale robot cluster system. The optimized algorithm is compared with the basic genetic algorithm. The simulation results show that the improved algorithm is efficient in robot path planning.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129034412","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
Functional Requirements Enabling Levels of Predictive Maintenance Automation and Autonomy 支持预测性维护自动化和自治级别的功能需求
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.10036152
Katherine A. Flanigan, Sizhe Ma, M. Berges
{"title":"Functional Requirements Enabling Levels of Predictive Maintenance Automation and Autonomy","authors":"Katherine A. Flanigan, Sizhe Ma, M. Berges","doi":"10.1109/DTPI55838.2022.10036152","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.10036152","url":null,"abstract":"Artificial Intelligence (AI) supporting Digital Twins (DTs) has undoubtedly changed the ways predictive maintenance (PMx) is carried out on assets by enabling processes to be increasingly automated. However, without a standard definition for such evolution, this transformation lacks a solid foundation upon which to base its development. Other fields, namely, autonomous vehicles (AVs), use standardized levels of automation to outline coherent, agreed-upon criteria for AI-driven developments supporting autonomy that minimize barriers to interdisciplinary collaboration. In this work, we draw inspiration from the autonomy levels present in AV industry and propose levels of PMx DT automation. These levels define a clear path forward for AI-driven PMx DT developments. Motivated by our understanding that standardized processes for deploying AI-driven DTs (not only for PMx) in practice must have stakeholder buy-in that requires scalability, transferability, and integration into existing processes, we explore the functional requirements that facilitate systematic approaches at each of the proposed automation and autonomy levels.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122254760","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
End to End Autonomous Driving Behavior Prediction Based on Deep Convolution Neural Network 基于深度卷积神经网络的端到端自动驾驶行为预测
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998956
Baicang Guo, Yin-Lin Wang, Ming Gao, Jia Lu, Guang-sheng Han, Li-bin Zhang
{"title":"End to End Autonomous Driving Behavior Prediction Based on Deep Convolution Neural Network","authors":"Baicang Guo, Yin-Lin Wang, Ming Gao, Jia Lu, Guang-sheng Han, Li-bin Zhang","doi":"10.1109/DTPI55838.2022.9998956","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998956","url":null,"abstract":"The end-to-end automatic driving behavior prediction has become an important research direction in the field of automatic driving because of its simplicity and efficiency. Most of the existing end-to-end driving behavior prediction models use simple CNN structure. However, this method is vulnerable and captures less deep information, resulting in poor accuracy. In order to achieve more accurate end-to-end automatic driving behavior prediction, we combined the attention mechanism with the depth network and developed a residual network (ResNet50) model integrating the effective channel attention mechanism (ECANet). First, the residual network is used to extract spatial features from the RGB images collected by the left, middle and right cameras, and the effective channel attention module (ECA) is embedded to weight the attention of each feature channel. Secondly, the steering angle prediction result is output by using the weighted spatial feature information of the full connection layer fusion. Finally, an experiment was conducted using Udacity's public data set, which showed that the accuracy of ECA resnet50 in driving behavior prediction was better than other CNN models. In addition, compared with the model based on other attention mechanisms, its accuracy is also the highest.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133696791","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 parallel control strategy of thermal power plant operating parameters 火电厂运行参数并联控制策略研究
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998955
Junyu Cai, Jian Gao, Baozhu Zhou, Tianyu Wang, Junwei Song, Delei Wang, Chen Zeng, Deheng Ji
{"title":"Research on parallel control strategy of thermal power plant operating parameters","authors":"Junyu Cai, Jian Gao, Baozhu Zhou, Tianyu Wang, Junwei Song, Delei Wang, Chen Zeng, Deheng Ji","doi":"10.1109/DTPI55838.2022.9998955","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998955","url":null,"abstract":"The operation of thermal power plant generating units is complicated, and the operators cannot comprehensively and accurately monitor units' operation. The model is used to determine the upper and lower thresholds of each index under different operating conditions, and the operation of each index is monitored in real-time in the parallel intelligent monitoring system and synchronized to the physical power generation system. The experimental results show that each index's upper and lower thresholds under different working conditions can change dynamically according to the actual business scenarios of the generating units. It effectively reduces the false alarm rate of the system, captures the abnormal moments of the indexes, realizes the continuous optimization of the unit operation process, reduces the operators' workload and improves the units' safety and economy.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133586744","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
Vision-based UAV autonomous landing system 基于视觉的无人机自主着陆系统
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998957
Junjie Yang, Xuan Li
{"title":"Vision-based UAV autonomous landing system","authors":"Junjie Yang, Xuan Li","doi":"10.1109/DTPI55838.2022.9998957","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998957","url":null,"abstract":"Unmanned aerial vehicles (UAVs) have been widely used in suburban traffic planning and guidance, but their short endurance and limited range still affect the application prospect of UAVs. Therefore, the heterogeneous system between UAVs and intelligent vehicles (IVs) can effectively solve this problem. We propose a vision based UAV autonomous landing system and construct a traffic simulation scene based on a complex urban road. This paper uses the gazebo-based simulation platform to test the whole heterogeneous autonomous landing system in different conditions. The quadrotor UAVs are equipped with a monocular camera to detect landmarks. Then, the PID-based controller is used to autonomously land our UAVs. The experiments are conducted using different flight heights. The experimental results indicate that:1) the simulation platform can quantitatively analyze heterogeneous autonomous landing system performance. 2) sufficient adjustment time and higher landmark recognition metrics can effectively improve the landing performance of UAVs.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124796189","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
Leverage Digital Twins Technology for Network Lifecycle Management 利用数字孪生技术进行网络生命周期管理
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998901
Da Wang, Jianchao Guo, Ye Ouyang, Shoufeng Wang, Aidong Yang, Zhidong Ren, Ying Ding, Guo Chen, Cheng Zhou, Danyang Chen
{"title":"Leverage Digital Twins Technology for Network Lifecycle Management","authors":"Da Wang, Jianchao Guo, Ye Ouyang, Shoufeng Wang, Aidong Yang, Zhidong Ren, Ying Ding, Guo Chen, Cheng Zhou, Danyang Chen","doi":"10.1109/DTPI55838.2022.9998901","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998901","url":null,"abstract":"Digital twin is a virtual entity that creates physical entities in a digital way. Based on the historical data, real-time data and algorithm model, the whole lifecycle process of physical entity can be simulated, verified, predicted and controlled by the digital twin entity. There are many uncertain factors in the whole lifcycle of communication networks. Digital twin technology can be well integrated into the network lifecycle management. This paper analyses the various scenarios of network lifecycle management based on digital twin technology. Using digital twin technology, the cost of network lifecycle management can be significantly reduced and network efficiency can be improved.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125000583","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
Parallel Control Strategy for Flexible Operation of Ultra-supercritical Units Under Digital Twin Theory 数字双生理论下超超临界机组柔性运行并联控制策略
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998903
Ting Huang, G. Hou
{"title":"Parallel Control Strategy for Flexible Operation of Ultra-supercritical Units Under Digital Twin Theory","authors":"Ting Huang, G. Hou","doi":"10.1109/DTPI55838.2022.9998903","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998903","url":null,"abstract":"With the rapid development of big data and cloud technology, the coordinate control of thermal power plants is fast changing to a flexible and adaptive intelligent control model. In order to improve the operational flexibility of ultra supercritical (USC) units, a parallel control scheme based on ACP method is constructed in this paper. Firstly, an artificial control system that can reflect the operational conditions of units in real-time is constructed by the digital twin technology. Then, the precise model and active disturbance rejection control method are chosen for artificial system to guide the operation of USC units using computation experiments. Afterwards, the operational stability is ensured by the parallel execution of the artificial control system and actual USC units. Finally, the remarkable control performance of USC units based on the proposed parallel control scheme is successfully confirmed on a 1000MW units.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127258975","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
Pavement Crack Detection on BEV Based on Attention-Unet 基于Attention-Unet的纯电动汽车路面裂缝检测
2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI) Pub Date : 2022-10-24 DOI: 10.1109/DTPI55838.2022.9998932
Jia Zhang, Na Chen, Jiangtao Peng, Fengmei Cui
{"title":"Pavement Crack Detection on BEV Based on Attention-Unet","authors":"Jia Zhang, Na Chen, Jiangtao Peng, Fengmei Cui","doi":"10.1109/DTPI55838.2022.9998932","DOIUrl":"https://doi.org/10.1109/DTPI55838.2022.9998932","url":null,"abstract":"Identifying and detecting pavement cracks quickly and accurately for traffic safety is one of the important problems in the field of automatic driving. This study presents a framework of crack detection on BEV (Bird's Eye View). Firstly, based on the binocular parallax information, the captured road image is transformed from perspective to BEV as the input of the network. The Unet with attention mechanism is used to selectively fuse the deep and shallow features to identify the cracks on the pavement. In addition, further processing is performed according to the results of crack detection. The results help judge the quality of the pavement and provide a basis for the measurement of crack width in the direction of normal vector, laying a foundation for subsequent application. The test shows the method has high detection accuracy and is suitable for complex pavement conditions.","PeriodicalId":409822,"journal":{"name":"2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130483888","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
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