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Solar Irradiance Forecasting Utilizing distributed and Federated Learning 25

Solar Irradiance Forecasting Utilizing Distributed and Feder...

引用

25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Zhang, Hao Yan, Ke College of Information Engineering China Jiliang University Hangzhou China China Jiliang University National University of Singapore Singapore

ISBN: (纸本)9798350330014

Photovoltaic energy generation and prediction are crucial for the integration between solar plants and smart grid. Accurate solar radiation prediction is one of the most important research topics for solar energy generation. Existing deep learning methods require sufficient data for training for achieving the desired results. In traditional deep learning modeling, the data sets required for model training usually come from various data in different regions and organizations, and it is difficult to ensure data security and privacy protection. Federated learning can effectively utilize the data optimization model while ensuring data security and privacy, but there is still the risk of privacy leakage by analyzing the parameters uploaded by the client. To effectively utilize data optimization models while ensuring data security and privacy, we propose a method based on a federated learning framework and N-BEATS to achieve interpretable time series prediction of solar irradiance. the model builds the N-BEATS model on the solar irradiance datasets of multiple institutions in a distributed method, does not share local data to protect institutional data privacy, the concept of differential privacy (DP) is introduced, Gaussian noise is added to the parameters of the client before the server-side aggregation processing, the model parameters of each distributed node are collected through TCP communication for federated average, and the parameters are returned to each distributed node. the experimental results show that compared with other deep learning models, the model has better prediction accuracy under the premise of ensuring data security and privacy. © 2023 ieee.

关键词： Solar radiation

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Adaptive ResNet Architecture for distributed Inference in Resource-Constrained IoT systems 19

Adaptive ResNet Architecture for Distributed Inference in Re...

引用

19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Khan, Fazeela Mazhar Baccour, Emna Erbad, Aiman Hamdi, Mounir Hamad Bin Khalifa Univ Qatar Fdn Coll Sci & Engn Doha Qatar

ISBN: (纸本)9798350333398

As deep neural networks continue to expand and become more complex, most edge devices are unable to handle their extensive processing requirements. therefore, the concept of distributed inference is essential to distribute the neural network among a cluster of nodes. However, distribution may lead to additional energy consumption and dependency among devices that suffer from unstable transmission rates. Unstable transmission rates harm real-time performance of IoT devices causing low latency, high energy usage, and potential failures. Hence, for dynamic systems, it is necessary to have a resilient DNN with an adaptive architecture that can downsize as per the available resources. this paper presents an empirical study that identifies the connections in ResNet that can be dropped without significantly impacting the model's performance to enable distribution in case of resource shortage. Based on the results, a multi-objective optimization problem is formulated to minimize latency and maximize accuracy as per available resources. Our experiments demonstrate that an adaptive ResNet architecture can reduce shared data, energy consumption, and latency throughout the distribution while maintaining high accuracy.

关键词： optimization distributed inference neural networks resilience ResNet

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Application Research of Artificial Intelligence in distributed Energy Management System 6

Application Research of Artificial Intelligence in Distribut...

引用

6th international conference on Energy systems and Electrical Power, ICESEP 2024

作者： Wang, Guanyao Zhao, Zihan Wang, Xu Dou, Yuanqi Dou, Yuanfeng Liu, Zheng Beijing Fibrlink Communications Co. Ltd Beijing China Co. Ltd Beijing China State Grid Mudanjiang Electric Power Supply Company Mudanjiang China Beijing Forestry University Beijing China Beijing University of Chinese Medicine Beijing China

ISBN: (纸本)9798350353563

the reliability and stability of the power system are paramount for societal well-being and economic progress. Anomalous fluctuations in power load often precipitate supply interruptions, system breakdowns, and other severe repercussions. Hence, timely and precise power load forecasting is imperative. the conventional rule- and statistic-based power load forecasting technology exhibits numerous limitations that impede its ability to meet the demands of a complex, real-time power system. this paper will delve into AI-based power load forecasting for the power system. In contrast to traditional methods, AI-driven approaches can markedly enhance predictive performance and contribute to more efficient and stable grid management and operations. © 2024 ieee.

关键词： Artificial intelligence Optimization method Power load forecasting

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An Architecture Modeling Framework for distributed Automation systems Using SysML and Semantic Web Technologies 6

An Architecture Modeling Framework for Distributed Automatio...

引用

6th international conference on Mechatronics, Robotics and Automation (ICMRA)

作者： Wang, Dan Li, Xiaofeng Gu, Bin Cao, Yue Liu, Yusheng Acad Aerosp Prop Technol Innovat Ctr Liquid Rocket Engine Digital Res & De CNSA Xian Peoples R China Beijing Inst Control Engn Beijing Peoples R China Zhejiang Univ Technol Coll Comp Sci & Technol Hangzhou Peoples R China Zhejiang Univ State Key Lab CAD & CG Hangzhou Peoples R China

ISBN: (纸本)9798350307542;9798350307535

the rising interdisciplinarity and complexity of the distributed Automation systems (DASs) require the systems to be modeled in an unambiguous and high-level abstract way for cross-discipline/stage communication and interoperability in the Model-Driven Development (MDD) lifecycle. the concept of the System Architecture Model in systems engineering has been adopted for this challenge. To support the creation and analysis of this model, a modeling framework with a modeling methodology, modeling language, knowledge base, and related toolkit is established based on SysML and Semantic Web Technologies. A modeling methodology which is the core of the framework for modeling the architecture of DASs is formally defined with domain-specificity, comprehensiveness, discipline-neutrality, and platformin-dependency. Based on it, the SysML-DAS modeling language is extended from SysML, and the System Architecture Ontology is built with the help of the Knowledge Extraction Tool. this ontology works as the knowledge base not only to provide a unified and unambiguous view of the system but also to support the automated accomplishment of tasks in the MDD process. As a typical task, the semantic correctness and integrity of the system architecture model can be assessed by the Knowledge Analysis Tool in this framework.

关键词： distributed automation system SysML Semantic Web technologies System Architecture Model

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Research and Implementation of Parallel CART Algorithm Based on distributed Database 6

Research and Implementation of Parallel CART Algorithm Based...

引用

2023 ieee 6th international conference on Information systems and Computer Aided Education, ICISCAE 2023

作者： Wang, Jie The Open University of Guangdong School of Artificial Intelligence Guangzhou China

ISBN: (纸本)9798350313444

this paper presents a parallel CART method for multivariate association query. the amount of communication information is reduced by performing two semi-joins. this method adopts a multi-node parallel method, which greatly speeds up the execution efficiency of the system. the sequence of operations generated by this algorithm has global optimization characteristics. One of its important development trends is to realize effective data query by optimizing the database. the simulation experiment proves that the method has fast processing speed, high node utilization rate and strong practicability. this method is suitable for large data processing. © 2023 ieee.

关键词： distributed database optimization algorithm parallel CART algorithm query processing

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Research on the Calculation Method of Openable Capacity of distributed Photovoltaic System 6

Research on the Calculation Method of Openable Capacity of D...

引用

6th international conference on Energy, Power and Grid, ICEPG 2024

作者： Li, Ran Liu, Zheng Zhang, Xuze Xu, Yiting Cai, Bolun Wen, Jiaxuan Lin, Zhijie Liu, Yunan Beijing Fibrlink Communications Co. Ltd Beijing China

ISBN: (纸本)9798350377798

this paper summarizes the current status of research on calculation methods for the openable capacity of distributed photovoltaic (PV) systems, and discusses the specific content and application of the six main calculation methods. the method based on voltage deviation opportunity constraints is planned by building a probabilistic tidal current calculation model for distribution networks, combining the correlation of PV output and opportunity constraints. the integrated demand response model is by constructing a steady state model of the integrated electric-thermal energy system, combined with price-based, incentive-based and elastic thermal load response. Active management and demand-side management methods use a two-stage robust optimization model to improve PV access capacity under 'source-load' uncertainty by combining multiple active management measures. Hybrid particle swarm algorithms are used to accurately calculate capacity by combining constraints such as voltage deviation and line current carrying capacity. the method of considering reasonable light abandonment is to allow a certain percentage of PV power to be abandoned, combined with control means such as transformer tap regulation;the method based on harmonic constraints is to analyze the harmonic characteristics generated by PV inverters, and consider voltage, capacity and harmonic constraints comprehensively. Each of these methods has its own characteristics, and together they promote the refinement and intelligent development of the calculation of the openable capacity of distributed PV systems. © 2024 ieee.

关键词： Demand response

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An Epigraph Approach for distributed Economic Dispatch in General Dynamic Directed Networks 6

An Epigraph Approach for Distributed Economic Dispatch in Ge...

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6th international conference on Electronic Engineering and Informatics, EEI 2024

作者： Lü, Qingguo Zhou, Qixing Zhang, Keke Wang, Zheng Li, Huaqing College of Computer Science Chongqing University Chongqing China College of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (纸本)9798350353594

the intricate complexities of modern energy systems highlight the cruciality of nimble and trustworthy methodologies for the smooth functioning of intelligent grids. this article delves into the economic dispatch problem (EDP) within smart grids, with the objective of maximizing generator scheduling efficiency to meet total demand while minimizing expenditure. We present a comprehensively decentralized algorithm, tailored specifically for addressing the EDP in directed networks, while accounting for the dynamics of communication environments. this algorithm integrates the epigraphic methodology and relies solely on row-stochastic weighting matrices for its execution. We provide theoretical justifications to ensure the convergence of our proposed algorithm, thereby exhibiting its ability to efficiently dispatch the optimal economic solution. To substantiate the efficacy of our algorithm, we conduct simulations, furnishing empirical proof of its performance. © 2024 ieee.

关键词： Stochastic systems

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Research on Optimization Allocation Technology of Rural Electric Power Use Based on Artificial Intelligence Algorithm 6

Research on Optimization Allocation Technology of Rural Elec...

引用

2023 ieee 6th international conference on Information systems and Computer Aided Education, ICISCAE 2023

作者： Zhang, Yichuan Li, Weiming Linc, Wenyu State Grid Zhejiang Ningbo Yinzhou District Power Supply Co. Ltd Ningbo310015 China

ISBN: (纸本)9798350313444

A new rural distributed power trading model is constructed based on the technical characteristics of distributed storage, point-to-point transmission and multi-centralization of artificial intelligence algorithm. the criterion of equal network loss micro increase rate and the criterion of optimal network loss micro increase rate are derived and simplified. Development of reactive power optimization calculation software package. the results show that the proposed method is effective in improving node voltage and reducing power loss, and has little influence on the operation of rural power network. this method has some practical value for the configuration of reactive power optimization software package in rural power network. © 2023 ieee.

关键词： Artificial Intelligence Algorithm distributed Electric Power Trading System Rural Power Grid

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Querying distributed sensor Streams in the Edge-to-Cloud Continuum 6

Querying Distributed Sensor Streams in the Edge-to-Cloud Con...

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6th ieee international conference on Edge computing and Communications (ieee EDGE)

作者： Karlstetter, Roman Widhopf-Fenk, Robert Schulz, Martin IfTA GmbH Puchheim Germany Tech Univ Munich Garching Germany

ISBN: (数字)9781665481403

ISBN: (纸本)9781665481403

sensor data is of crucial importance in many IoT scenarios. It is used for online monitoring as well as long term data analytics, enabling countless use cases from damage prevention to predictive maintenance. Multivariate sensor time series data is acquired and initially stored close to the sensor, at the edge. It is also beneficial to summarize this data in windowed aggregations at different resolutions. A subset of the resulting aggregation hierarchy is typically sent to a cloud infrastructure, often via intermittent or low bandwidth connections. Consequently, different views on the data exist on different nodes in the edge-to-cloud continuum. However, when querying this data, users are interested in a fast response and a complete, unified view on the data, regardless of which part in the infrastructure continuum they send the query to and where the data is physically stored. In this paper, we present a loosely coupled approach that enables fast range queries on a distributed and hierarchical sensor database. Our system only assumes the possibility of fast local range queries on a hierarchical sensor database. It does not require any shared state between nodes and thus degrades gracefully in case certain parts of the hierarchy are unreachable. We show that our system is suitable for driving interactive data exploration sessions on terabytes of data while unifying the different views on the data. thus, our system can improve the data analysis experience in many geo-distributed scenarios.

关键词： edge cloud multivariate sensor data stream distributed query

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A Comprehensive Performance Evaluation Method of the distributed Common Grounding Electrode 6

A Comprehensive Performance Evaluation Method of the Distrib...

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6th international conference on HVDC, HVDC 2024

作者： Jiang, Yutong Zheng, Zhihui Hu, Shangmao Liu, Gang Wu, Yongcong Cai, Hansheng Lu, Hailiang School of Electrical Engineering and Automation Wuhan University Wuhan China China Southern Power Grid Electric Power Research Institute Guangzhou China

ISBN: (纸本)9798350387759

Aiming to enhance the comprehensive performance of the distributed common grounding DC electrode, reduce the construction cost, and solve the problem of optimizing the topology of distributed common DC grounding electrode, a comprehensive performance evaluation method is proposed. In this paper, three evaluation indexes of the distributed common grounding electrode topology is established. Based on the parameters in Guangdong Province, the weight of each index is calculated by the Criteria Importance through Intercriteria Correlation and the Analytic Hierarchy Process, and the comprehensive performance of the typical topologies are evaluated by the Technique for Order Preference by Similarity to an Ideal Solution. the proposed evaluation method can effectively evaluate the comprehensive performance of the distributed common grounding electrode under different topologies, and the star topology shows better comprehensive performance. this study provides a reference for the selection of distributed common grounding electrode topology. © 2024 ieee.

关键词： comprehensive evaluation model distributed common grounding electrode evaluation index topological structure

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