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储能系统技术 储能系统 ★ 4.0

电力变电站设备不完美维护与更换的调度:一种基于风险的优化模型

Scheduling the Imperfect Maintenance and Replacement of Power Substation Equipment: A Risk-Based Optimization Model

作者 Nan Zhou · Lingen Luo · Gehao Sheng · Xiuchen Jiang
期刊 IEEE Transactions on Power Delivery
出版日期 2025年5月
技术分类 储能系统技术
技术标签 储能系统
相关度评分 ★★★★ 4.0 / 5.0
关键词 变电站设备 维护与更换调度 不完全维护 风险优化模型 成本效率
语言:

中文摘要

合理的维护与更换计划有助于恢复电力设备健康状态,提升成本效益并降低电网故障风险。不完美维护虽无法使设备恢复至“如新”状态,但其成本远低于更换。本文提出一种考虑老化设备不完美维护的变电站设备维护与更换风险优化模型。基于历史故障数据趋势分析建立退化过程,引入虚拟年龄模型描述不完美维护的效果,并量化设备故障、维护及更换风险,构建混合整数线性规划(MILP)模型求解最优调度方案。案例分析表明,相较于传统策略,该方法总风险降低34%,成本效率提高12.1%。

English Abstract

A proper and effective maintenance and replacement schedule help to restore power equipment health condition, increase cost efficiency, and reduce the failure risk of the power grid. Imperfect maintenances cannot restore the equipment to a “as good as new” state as replacement did, but the financial cost of maintenance is much lower than that of replacement. The optimal balance and coordination between imperfect maintenances and replacements leads to the optimal substation operational cost. In this paper, a risk-based optimization model for power substation equipment maintenance and replacement scheduling is proposed in the presence of imperfect maintenances for the aging power equipment. The degradation process is firstly established based on historical trending analysis of failure data. Afterwards, a virtual age model is proposed for each equipment and the imperfect maintenance effectiveness is represented by the rejuvenation of this virtual age. Eventually, equipment failure risk, maintenance risk, and replacement risk are obtained, which are then incorporated into a MILP problem to obtain the optimal scheduling results. Case studies are performed on substations with three different bus-bar layout schemes. Results shows that the proposed method achieves a 34% lower total risk and 12.1% higher cost efficiency, compared to the traditional maintenance strategies.
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SunView 深度解读

该基于风险的不完美维护优化模型对阳光电源储能及光伏产品线具有重要应用价值。针对PowerTitan大型储能系统和SG系列逆变器,可将虚拟年龄模型集成至iSolarCloud智能运维平台,实现变流器、功率模块等核心部件的预测性维护调度优化。通过量化SiC/GaN器件老化风险与维护成本,可在完全更换与定期维护间找到最优平衡点,显著降低电站OPEX成本。该MILP优化方法可直接应用于ST系列储能变流器的主动热管理策略,结合历史故障数据建立功率器件退化模型,指导关键部件维护周期制定,提升系统全生命周期可靠性与经济性,支撑阳光电源大型储能项目的智能运维服务能力。