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Design of PV operation and maintenance management system based on data cleaning and PostgreSQL

Published: 20 June 2024 Publication History

Abstract

Distributed photovoltaic power stations are small in scale, which can make full use of idle areas such as roofs to generate electricity and improve power output. However, this also brings problems of operation and maintenance management. Each power station is relatively independent, and the total amount of equipment is still large. This paper uses PostgreSQL database and RuoYi-Vue backend framework to design a web client management system to realize data management, fault alarm and data visualization for photovoltaic power stations. In order to optimize data validity, data in the database is cleaned.

References

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National Energy Administration of the People's Republic of China. Statistical data of National Electric Power Industry[R]. 2023-10.
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Yang Honglei. Operation and maintenance management and development trend of distributed photovoltaic power station. Shanghai Energy Saving [J], 2022, No.405(09): 1137-1142.
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RuoYi Management System Construction Web application [EB/OL]. http://doc.ruoyi.vip/
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PostgreSQL-based Timescale documentation [EB/OL]. https://docs.timescale.com/
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Meng Anbo, Xu Xuancong, Chen Jiaming Ultra-short term photovoltaic power prediction based on reinforcement learning and combined deep Learning model. Power Grid Technology [J], 2019,45(12):4721-4728.
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Machine Learning; Researchers from Nanchang University Report Findings in MachineLearning (Prediction of Photovoltaic Power Output Based On Similar Day Analysis, Genetic Algorithm and Extreme Learning Machine) [J]. Journal of Robotics & Machine Learning, 2020.
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Kim Kwang Baek, Song Doo Heon, Park Hyun Jun. Intelligent Automatic Segmentation of Wrist Ganglion Cysts Using DBSCAN and Fuzzy C-Means [J]. Diagnostics, 2021: 11-12.
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LI Fusheng, Lin Dan, Yu Tao, Wang Keying, WU Yufeng, Yang Jiajun. Upfrequency reconstruction of electrical data based on improved generative adversarial network [J]. Automation of Electric Power Systems,2022,46(03):105-112. (in Chinese)
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CMLDS '24: Proceedings of the International Conference on Computing, Machine Learning and Data Science
April 2024
381 pages
ISBN:9798400716393
DOI:10.1145/3661725
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 June 2024

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Author Tags

  1. data cleaning
  2. management system
  3. operation and maintenance
  4. photovoltaic power station

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