Maintenance Strategy of Photovoltaic Power Station Based on Component-System Classification Optimization

被引：0

作者：

Zhu X. ^{[1
]}

Liu Y. ^{[2
]}

机构：

[1] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding

[2] Dispatching and Control Center of State Grid Qinhuangdao Electric Power Supply Company, Qinhuangdao

来源：

Zhu, Xiaorong (xiaorongzhu@ncepu.edu.cn) | 2020年 / Automation of Electric Power Systems Press卷 / 44期

关键词：

Classification optimization; Correlation; Failure rate; Maintenance strategy; Photovoltaic power generation; State prediction; Time threshold;

D O I：

10.7500/AEPS20190626009

中图分类号：

学科分类号：

摘要：

In order to maximize the power generation efficiency of photovoltaic power stations and reduce the maintenance costs, a maintenance strategy for photovoltaic power station is proposed based on component-system classification optimization method. Firstly, considering the failure rate of each component in the photovoltaic power station, the state transition matrix for each component is determined and states of each component are predicted by using Markov chain method. Secondly, in the component-level optimization stage, based on the state prediction results of Markov chain method and considering the direct maintenance costs, maintenance downtime cost and fault risk losses, the most optimal maintenance time and sub-optimal maintenance time for each component are determined and a maintenance strategy set for each component is obtained. It provides selection basis for system-level optimization stage. In the system-level optimization stage, the time thresholds for the combination maintenance of components are calculated based on the correlation of maintenance costs and structural dependence between components, and the optimal maintenance strategy of the system is determined according to the time thresholds. Finally, the validity of the proposed method is verified through case studies. Results show that the proposed maintenance strategy can significantly reduce maintenance costs and system downtime losses. © 2020 Automation of Electric Power Systems Press.

引用

页码：92 / 99

页数：7

共 21 条

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