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检索条件"任意字段=3rd IEEE International Conference on e-Science and Grid Computing"

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A Reliability Index Deviation Allocation Method for Distribution System with Distributed Generation 3

A Reliability Index Deviation Allocation Method for Distribu...

引用

3rd international conference on energy and electrical Power Systems (ICeePS)

作者： Zhou, Yangjun Pan, Juntao Zhang, Wei Yi, Chenying Huang, Weixiang Li, Shan Feng, Bin Zhou, Yuanchao Wu, Lifang Guangxi Power Grid Co Ltd Guangxi Key Lab Intelligent Control & Maintenance Elect Power Res Inst Nanning Peoples R China Guangxi Power Grid Co Ltd Nanning Peoples R China Guangxi Power Grid Co Ltd Nanning Power Supply Bur Nanning Peoples R China

ISBN: (纸本)9798350375145;9798350375138

The access of distributed generation will increase the complexity of reliability evaluation, which will affect the accuracy of theoretical reliability evaluation value. Therefore, it is necessary to allocate the deviation between the true value and the theoretical value of the reliability index to the parameters of each component, and to correct the parameters purposefully that are allocated to more deviations. In this paper, firstly, the reliability model of distributed generation is established. Then, the improved proportional allocation method is used to calculate the contribution rate of each parameter to the system index, and the index deviation is allocated based on this. Next, after eliminating the parameters that contribute more to the deviation, the values of these parameters are calculated inversely through establishing the optimization model by using the known system reliability indexes, realizing the correction of the parameters. Finally, a distribution system for RBTS Bus 6 is introduced as standard case to demonstrate the accuracy of the proposed method.

关键词： distributed generation reliability model the improved proportional allocation method parameter correction

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Total Harmonics Distortion Improvement of AC grid using Fuzzy Control based 7-Level MLI Compared with a 5-Level MLI by Reducing the Harmonics 3

Total Harmonics Distortion Improvement of AC Grid using Fuzz...

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3rd international conference on Automation, computing and Renewable Systems, ICACRS 2024

作者： Saikumar, M. Jaanaa, S. Rubavathy Dept of EEE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (纸本)9798331532420

This research presents a novel five-level and seven-level inverter topology for improved power quality in multilevel inverter (MLI) systems. The proposed design employs a bidirectional switch and an H-bridge cell, reducing the number of DC sources and simplifying the overall circuit. A fuzzy logic controller (FLC) is implemented to optimize the switching patterns, minimizing Total Harmonic Distortion (THD) and improving output waveform quality. The performance of the proposed topologies is compared with conventional MLI configurations. Results demonstrate that the novel designs achieve lower THD (4.7757) compared to the conventional method (6.7814), while also achieving higher output voltage and current (500V, 15A) compared to the conventional method (320V, 10A). This research contributes to the advancement of MLI technology by offering simplified and more efficient topologies with improved power quality and reduced harmonic distortion. © 2024 ieee.

关键词： Harmonic distortion

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Online Fine-tuning Method for Power grid Artificial Intelligence Model Based on Cloud-edge Collaboration 3

Online Fine-tuning Method for Power Grid Artificial Intellig...

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3rd international conference on Robotics, Automation and Intelligent Control, ICRAIC 2023

作者： Du, Zexu Zhang, Guoliang Zhang, Yi Wei, Wei Chu, Zongbo State Grid Smart Grid Research Institute Co.ltd State Grid Laboratory of Grid Advanced Computing and Applications Beijing China

ISBN: (纸本)9798350360813

As artificial intelligence methods play an increasingly important role in the digital transformation of power grids, when applied in power grid scenarios, these methods face problems such as the inability of models to adaptively deploy data distribution changes, slow response speed, inability to ensure data security on the side, limited computing power on the side, and uneven distribution of computing resources. This method proposes a novel fine-tuning framework based on cloud-edge collaboration to address these issues. This method utilizes reinforcement learning to segment the model, discarding unreliable samples collected on-site to fine-tune the model's fine-tuning parameters. Finally, validation was conducted on the application scenario of detecting violations in the power grid, and the experimental results show the effectiveness of our method. © 2023 ieee.

关键词： Reinforcement learning

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An Online Monitoring Method for Carbon emissions in a Multi-energy Industrial Park 3

An Online Monitoring Method for Carbon Emissions in a Multi-...

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3rd international conference on energy and electrical Power Systems (ICeePS)

作者： Liu, Cheng Wen, Jiying Xian, Zhongye Wan, Zhongtian Zhang, Jiao Guangdong Power Grid Corp Foshan Power Supply Bur Power Grid Planning Ctr Foshan 440605 Peoples R China

ISBN: (纸本)9798350375145;9798350375138

The conventional online monitoring method of carbon emissions in multi energy complementary industrial parks mainly uses MSHea-enKF multi time scale Kalman filtering algorithm to filter the monitoring data, which is vulnerable to the impact of quantitative cycle changes, resulting in excessive deviation of carbon emissions monitoring cycle components. Therefore, an effective online monitoring method of carbon emissions in multi energy complementary industrial parks is proposed. That is to say, an optical sensor for online monitoring of carbon emissions in the multi energy complementary industrial park was designed, and an online monitoring center for carbon emissions in the multi energy complementary industrial park was generated, which became an online monitoring of carbon emissions. The experimental results show that the cycle component of the designed online carbon emission monitoring method is close to the actual carbon emission component, which proves that the designed online carbon emission monitoring method has good monitoring effect, reliability, and certain application value, and has made certain contributions to the development of sustainable production plans for industrial parks.

关键词： Industrial parks Carbon emissions Online Monitoring Methodology

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Reliability evaluation method of distribution network under extreme disasters based on index reuse 3

Reliability evaluation method of distribution network under ...

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3rd international conference on energy and electrical Power Systems (ICeePS)

作者： Wang, Shusheng Ge, Lukun Li, Hongjun Zhao, Dong Chai, Wei Tianjin Univ Key Lab Smart Grid Minist Educ Tianjin Peoples R China State Grid Econ & Technol Res Inst Co Ltd Distribut Network Planning Ctr Beijing Peoples R China State Grid Shanghai Municipal Elect Power Co Elect Power Res Inst Shanghai Peoples R China

ISBN: (纸本)9798350375145;9798350375138

This paper proposes a reliability assessment method for power distribution networks under extreme disasters using index reuse. Firstly, a planning-oriented reliability index is constructed by considering the occurrence probability of extreme scenarios and the resulting load reduction. Secondly, a rapid calculation approach based on fault state impact increment reuse is introduced. By leveraging the similarity in outage and load reduction between normal and extreme conditions, the method reuses fault state impact increments from normal reliability analysis and combines them with high-order fault elimination, significantly enhancing assessment efficiency. Finally, the method is validated using seismic disaster scenarios. experimental results show that the MC+INDeX ReUSe method performs well in single seismic scenarios, while the IISe+INDeX ReUSe method excels in both accuracy and efficiency for full scenario calculations.

关键词： distribution network reliability assessment index reuse higher-order fault elimination

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Intelligent dynamic monitoring method of industrial park energy consumption based on deep circulation neural network 3

Intelligent dynamic monitoring method of industrial park ene...

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3rd international conference on energy and electrical Power Systems (ICeePS)

作者： Zhang, Jiao Wan, Zhongtian Wen, Jiying Xian, Zhongye Liu, Cheng Foshan Power Supply Bur Guangdong Power Grid Corp Power Grid Planning Ctr Foshan Guangdong Peoples R China

ISBN: (纸本)9798350375145;9798350375138

In order to better realize the energy management optimization and energy saving and emission reduction objectives of industrial parks, an intelligent dynamic monitoring method of energy consumption in industrial parks based on deep circulation neural network is proposed. Pre-processing the information of intelligent dynamic monitoring of energy consumption in industrial parks, constructing a deep circulation neural network structure, analyzing the training principle, and extracting the change characteristics of intelligent dynamic monitoring;Set the constraints of intelligent dynamic monitoring of industrial park energy consumption, construct intelligent dynamic monitoring function, and realize the intelligent dynamic monitoring process of industrial park energy consumption. The experimental results show that this method can realize intelligent dynamic monitoring of industrial park energy consumption, and can also output targeted planning schemes, which shows a higher comprehensive utilization rate and energy saving rate in industrial park energy consumption.

关键词： Deep circulation neural network Industrial park energy consumption Intelligent dynamic monitoring

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Feature extraction to evaluate the Quality of Data Using Machine Learning Technique 3

Feature Extraction to Evaluate the Quality of Data Using Mac...

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3rd ieee international conference on Distributed computing and electrical Circuits and electronics, ICDCeCe 2024

作者： Pratheesh, R. Divya, V. School Of Computing Sciences Vels Institute Of Science Technology & Advanced Studies Chennai India School Of Computing Sciences Vels Institute Of Science Technology & Advanced Studies Department Of Information Technology Chennai India

ISBN: (纸本)9798350318609

Data quality analysis is a crucial step in ensuring the reliability and accuracy of data used in machine learning models. The proposed approach utilized with machine learning algorithms to identify outliers in the data. Outliers can indicate errors are anomalies that might affect the quality of the dataset. Data Profiling is used to identify patterns and distributions. Missing Data Imputation predict the missing values. Data Validation and Cleansing, Data Duplication Detection, Inconsistency Detection are considered as the primary analysis to be done. The feature extraction process read the sample test dataset, pre-process the dataset by cleaning the data for data duplication, inconsistency through dynamic algorithms principal component analysis (PCA), Linear Discriminant Analysis (LDA) and independent component analysis (ICA) is considered here. The proposed feature extraction data is further opted for pattern validation through isolated forest algorithm. The performance of the system is evaluated using accuracy, precision, and Recall. The LDA model outperforms with accuracy of 99% for the given testset. © 2024 ieee.

关键词： Feature extraction

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Research on Intelligent Centralized System Based on Security Architecture of Computer Cloud Security Protection 3

Research on Intelligent Centralized System Based on Security...

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3rd ieee international conference on electronic Technology, Communication and Information, ICeTCI 2023

作者： Dang, Fangfang Yan, Lijing Yang, Yang State Grid Henan Electric Power Company Information and Communication Company Zhengzhou450000 China Co. Ltd Beijing100000 China

ISBN: (纸本)9798350398410

This paper identifies the protection objects, security measures and security capabilities of cloud computing platform/system. Then construct network security level protection 2.0 cloud computing security compliance model. Then this paper proposes an algorithm of autonomous protection against malware attacks in cloud computing environment. Feature extraction and analysis of malware attacks and understanding of the current network state. Then the subspace method is used to detect malware attacks. Finally, the system can realize the monitoring of worms, DDoS attacks and other security events to meet the needs of network security management. © 2023 ieee.

关键词： Network security

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A Collaborative Optimization Method of Power grid economy and environmental Protection based on HSMOPSO Algorithm 3

A Collaborative Optimization Method of Power Grid Economy an...

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3rd international conference on Smart Generation computing, Communication and Networking, SMART GeNCON 2023

作者： Dan, Zhao Songsong, Liu Fan, Yao Guoquan, Wang Chunyan, Jia State Grid Chongqing Electric Power Company Economic and Technology Research Institute Chongqing401120 China

ISBN: (纸本)9798350319125

With the continuous development of society, the power industry occupies an increasingly important position in the national economy. However, the traditional development model of power industry often takes economic benefits as its main goal, ignoring its impact on the environment. In order to achieve sustainable development, the power industry needs to optimize the economic benefits and environmental protection. Particle swarm optimization (PSO) is an intelligent algorithm widely used in optimization problems, while hybrid leapfrog algorithm (FSA) is a new search algorithm. This study combines these two algorithms and proposes a HSMOPSO algorithm, which is applied to the collaborative optimization of power grid economy and environmental protection. © 2023 ieee.

关键词： Collaborative optimization computer technology grid economy and environmental protection HSMOPSO algorithm

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Design of Software engineering Approach's for web learning applications using Cloud computing 3

Design of Software Engineering Approach's for web learning a...

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3rd ieee North Karnataka Subsection Flagship international conference, NKCon 2024

作者： Sreenivasa, N. Naidu, P. Ramesh Naresh, e. Chandrakala, B.M. Nitte Meenakshi Institute of Technology Department of Computer Science and Engineering Karnataka Bengaluru560064 India Manipal Academy of Higher Education Manipal Institute of Technology Bengaluru Department of Information Technology Manipal India Dayanandasagar College of Engineering Department of Information Science and Engineering Kumaraswamy Layout Bengaluru560078 India

ISBN: (纸本)9798350364569

Over the years, Cloud computing has significantly influenced various sectors, including Web learning, as education is considered crucial for individual and national growth. The primary objective is to develop an Application Model that supports Web learning Services, addressing the limitations of existing web learning systems in terms of infrastructure and effectiveness. Cloud technology provides a platform to host web learning applications on a service basis, accessible to end users through the internet via cloud infrastructure. This approach offers cost-effective packages for educational organizations, benefiting both trainers and learners. To achieve this objective, a combination of technologies is required. The paper further emphasizes the importance of Web learning Design features and analyzes the significance of cloud computing. It explores the implementation of a cloudbased application model for web learning systems, focusing on its working methodology, architecture design, development tools, and external interfaces. Additionally, it explores the use of software engineering approaches in this context. The paper highlights the importance of utilizing cloud environments for institutes and learners, emphasizing the potential benefits and opportunities in terms of design. © 2024 ieee.

关键词： Cloud platforms

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