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10-06-2022 | Original Paper

A dynamic and combined maintenance strategy for photovoltaic power plants considering the dependencies and availability of components

Authors: Wei Chen, Xubin Li, Qingchun Ji, Xiping Pei, Zhongfei Wang, Feng He

Published in: Electrical Engineering | Issue 6/2022

Abstract

Aiming at the problem that the regular maintenance method of the photovoltaic power generation system cannot comprehensively consider the optimization of maintenance cost, availability and profit during the maintenance period. On the basis of considering the operating state of equipment and the influence of weather, a novelly dynamic and combined maintenance model of photovoltaic power plants based on component correlation and availability is proposed. Firstly, an association set is established from the component correlation. The maintenance decision is made with the association set as the basic unit. Then through the improved Markov state transition process, the state of the equipment and the association set is predicted, and its availability is determined. Finally, the maintenance model is established with the lowest maintenance cost and highest availability as the objective function. The model comprehensively considers the influence of component correlation, availability and weather factors on the maintenance strategy. The simulation of matlab proves that the model can effectively reduce maintenance times and maintenance costs. Taking a photovoltaic power station as an example, by setting different scenarios, comparing the model with the regular maintenance model that does not consider correlation, availability and weather factors, the economy and effectiveness of the maintenance model are verified.

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Title: A dynamic and combined maintenance strategy for photovoltaic power plants considering the dependencies and availability of components
Authors: Wei Chen
Xubin Li
Qingchun Ji
Xiping Pei
Zhongfei Wang
Feng He
Publication date: 10-06-2022
Publisher: Springer Berlin Heidelberg
Published in: Electrical Engineering / Issue 6/2022
Print ISSN: 0948-7921
Electronic ISSN: 1432-0487
DOI: https://doi.org/10.1007/s00202-022-01576-7

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