Big Data Analysis and Simulation of Distributed Marine Green Energy Resources Grid-Connected System

In order to improve the working stability of distributed marine green energy resources grid-connected system, we need the big data information mining and fusion processing of grid-connected system and the information integration and recognition of distributed marine green energy grid-connected syste...

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Main Authors: Tian Jun, Huang Lirong
Format: Article
Language:English
Published: Sciendo 2017-11-01
Series:Polish Maritime Research
Subjects:
Online Access:https://doi.org/10.1515/pomr-2017-0121
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author Tian Jun
Huang Lirong
author_facet Tian Jun
Huang Lirong
author_sort Tian Jun
collection DOAJ
description In order to improve the working stability of distributed marine green energy resources grid-connected system, we need the big data information mining and fusion processing of grid-connected system and the information integration and recognition of distributed marine green energy grid-connected system based on big data analysis method, and improve the output performance of energy grid-connected system. This paper proposed a big data analysis method of distributed marine green energy resources grid-connected system based on closed-loop information fusion and auto correlation characteristic information mining. This method realized the big data closed-loop operation and maintenance management of grid-connected system, and built the big data information collection model of marine green energy resources grid-connected system, and reconstructs the feature space of the collected big data, and constructed the characteristic equation of fuzzy data closed-loop operation and maintenance management in convex spaces, and used the adaptive feature fusion method to achieve the auto correlation characteristics mining of big data operation and maintenance information, and improved the ability of information scheduling and information mining of distributed marine green energy resources grid-connected system. Simulation results show that using this method for the big data analysis of distributed marine green energy resources grid-connected system and using the multidimensional analysis technology of big data can improve the ability of information scheduling and information mining of distributed marine green energy resources grid-connected system, realizing the information optimization scheduling of grid-connected system. The output performance of grid connected system has been improved.
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spelling doaj.art-f8af90d41e1c4293b536a344366d08302022-12-21T21:46:05ZengSciendoPolish Maritime Research2083-74292017-11-0124s318219110.1515/pomr-2017-0121pomr-2017-0121Big Data Analysis and Simulation of Distributed Marine Green Energy Resources Grid-Connected SystemTian Jun0Huang Lirong1Foshan Polytechnic, Foshan 528137, Guangdong, ChinaFoshan Polytechnic, Foshan 528137, Guangdong, ChinaIn order to improve the working stability of distributed marine green energy resources grid-connected system, we need the big data information mining and fusion processing of grid-connected system and the information integration and recognition of distributed marine green energy grid-connected system based on big data analysis method, and improve the output performance of energy grid-connected system. This paper proposed a big data analysis method of distributed marine green energy resources grid-connected system based on closed-loop information fusion and auto correlation characteristic information mining. This method realized the big data closed-loop operation and maintenance management of grid-connected system, and built the big data information collection model of marine green energy resources grid-connected system, and reconstructs the feature space of the collected big data, and constructed the characteristic equation of fuzzy data closed-loop operation and maintenance management in convex spaces, and used the adaptive feature fusion method to achieve the auto correlation characteristics mining of big data operation and maintenance information, and improved the ability of information scheduling and information mining of distributed marine green energy resources grid-connected system. Simulation results show that using this method for the big data analysis of distributed marine green energy resources grid-connected system and using the multidimensional analysis technology of big data can improve the ability of information scheduling and information mining of distributed marine green energy resources grid-connected system, realizing the information optimization scheduling of grid-connected system. The output performance of grid connected system has been improved.https://doi.org/10.1515/pomr-2017-0121distributedoceangreen energy resourcesgrid-connected systembig data analysis
spellingShingle Tian Jun
Huang Lirong
Big Data Analysis and Simulation of Distributed Marine Green Energy Resources Grid-Connected System
Polish Maritime Research
distributed
ocean
green energy resources
grid-connected system
big data analysis
title Big Data Analysis and Simulation of Distributed Marine Green Energy Resources Grid-Connected System
title_full Big Data Analysis and Simulation of Distributed Marine Green Energy Resources Grid-Connected System
title_fullStr Big Data Analysis and Simulation of Distributed Marine Green Energy Resources Grid-Connected System
title_full_unstemmed Big Data Analysis and Simulation of Distributed Marine Green Energy Resources Grid-Connected System
title_short Big Data Analysis and Simulation of Distributed Marine Green Energy Resources Grid-Connected System
title_sort big data analysis and simulation of distributed marine green energy resources grid connected system
topic distributed
ocean
green energy resources
grid-connected system
big data analysis
url https://doi.org/10.1515/pomr-2017-0121
work_keys_str_mv AT tianjun bigdataanalysisandsimulationofdistributedmarinegreenenergyresourcesgridconnectedsystem
AT huanglirong bigdataanalysisandsimulationofdistributedmarinegreenenergyresourcesgridconnectedsystem