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基于元件-系统分级优化的光伏电站维护策略
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1.新能源电力系统国家重点实验室(华北电力大学),河北省保定市 071003;2.国网秦皇岛供电公司电力调度控制中心,河北省秦皇岛市 066000

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Maintenance Strategy of Photovoltaic Power Station Based on Component-System Classification Optimization
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1.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding 071003, China;2.Dispatching Control Center of State Grid Qinhuangdao Electric Power Supply Company, Qinhuangdao 066000, China

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    摘要:

    为了能够最大限度地提高光伏电站的发电效率、降低维护成本,提出了元件-系统分级优化的光伏电站维护策略。首先在考虑光伏电站中各元件故障率的基础上,确定各个元件的状态转移矩阵,采用马尔可夫链对元件进行状态预测。然后在元件级优化阶段,借助于马尔可夫链状态预测结果,依据元件的直接维修费用、维修停机费用和故障风险损失,确定每个元件最经济的预防性维修时间及次最优维修时间,得到各个元件的维修策略集合,为系统级优化提供选择依据。在系统级优化阶段,依据元件之间的维修费用相关性与结构依赖性计算元件共同维修的时间阈值,从而确定系统最优维修策略。算例分析表明,该维护策略能够大幅节省维修费用,减少系统停机时间,验证了所提方法的有效性。

    Abstract:

    In order to maximize the power generation efficiency of photovoltaic power stations and reduce the maintenance costs, a maintenance strategy 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 using Markov chain method. In the component-level optimization stage, by considering the direct maintenance costs, maintenance downtime losses, and fault risk losses, the most optimal maintenance time and near-optimal maintenance time for each component are determined and a maintenance strategy set for each component is obtained. In the system-level optimization stage, the time thresholds for the combination maintenance of components are calculated based on the economic dependence 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.

    表 1 元件平均故障时间和故障修复时间Table 1 Mean time between failure and mean time to repair of components
    表 6 发电单元最优维修策略Table 6 Optimal maintenance strategy of power generation unit
    表 4 元件H1,I1,H2,I2的最优维护策略Table 4 Optimal maintenance strategy of component H1, I1, H2, I2
    表 5 发电单元最优维修时间及共同维修区间Table 5 Optimal maintenance time and joint maintenance interval of power generation unit
    表 2 元件维修费用Table 2 Maintenance costs of components
    图1 光伏电站电气结构Fig.1 Electrical structure of photovoltaic power station
    图2 时间阈值确定原理Fig.2 Determination principle of time threshold
    图3 光伏阵列可用率Fig.3 Availability of photovoltaic array
    图4 光伏阵列Cm,Ci和Cr随时间变化的趋势Fig.4 Trends of Cm, Ci and Cr versus time
    图5 最优维修时间确定Fig.5 Determination of optimal maintenance time
    图 光伏阵列结构图Fig. Structure of photovoltaic array
    图 光伏阵列状态转移图Fig. State transition diagram of PV array
    图 Cm,Ci和Cr随时间变化趋势示意图Fig. Trends of Cm, Ci and Cr over time
    图 发电单元结构图Fig. Structure of power unit
    表 3 元件H1,I1,H2,I2最优维修时间及共同维修区间Table 3 Optimal maintenance time and joint maintenance interval of component H1, I1, H2, I2
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引用本文

朱晓荣,刘亚维.基于元件-系统分级优化的光伏电站维护策略[J/OL].电力系统自动化,http://doi.org/10.7500/AEPS20190626009.
ZHU Xiaorong,LIU Yawei.Maintenance Strategy of Photovoltaic Power Station Based on Component-System Classification Optimization[J/OL].Automation of Electric Power Systems,http://doi.org/10.7500/AEPS20190626009.

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  • 收稿日期:2019-06-26
  • 最后修改日期:2019-09-24
  • 录用日期:2019-10-21
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