考虑维修时间不确定性的配电网维修预算的混合整数线性规划方法

Hamed Mirsaeedi, Alireza Hassankashi, Mahsa Sajjadi, P. Siano
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引用次数: 0

摘要

作为资产管理策略的一个组成部分,维护管理对于提高配电网的可靠性至关重要。为了提高系统的效率,电力公司投入了大量的精力将资金分配给重要的系统组件。本文提出了一种考虑修复时间不确定性的维修预算的混合整数线性规划方法。该方法为配电网馈线的维护任务找到了最优的预算。目标是降低总成本,其中包括客户的总中断成本$\left(\boldsymbol{T} \boldsymbol{C}_{\boldsymbol{C I C}}\right)$,未提供的总能量${cost}\left(T C_{E N S}\right)$,维修的总材料和人工成本$\left(T C_{R E P}\right)$,以及维护的总成本$\left(T C_{P M}\right)$。为了观察建议维护方法的有效性,还考虑了三种情况:情形1假设系统不进行任何维护操作,情形2平均考虑每个配电馈线的维护预算,情形3根据约束条件,建议公式分配最优维护预算。对罗伊比林顿测试系统的2号母线(RBTS2)进行了可靠性改进,并对改进结果进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Mixed-Integer Linear Programming Approach to Maintenance Budgeting in Electrical Distribution Networks Considering Repair Time Uncertainty
As a component of asset management strategies, maintenance management is essential for improving the reliability of the Electrical Distribution Networks (EDNs). To increase system efficiency, electricity companies invest a significant effort to assign their financial sources to important system components. In this paper, a mixed-integer linear programming approach to maintenance budgeting considering restoration time uncertainty is suggested. The suggested technique finds the optimal budget for doing maintenance tasks in distribution network feeders. The objective is to reduce overall cost, which includes total interruption cost of customer $\left(\boldsymbol{T} \boldsymbol{C}_{\boldsymbol{C I C}}\right)$, total energy not supplied ${cost}\left(T C_{E N S}\right)$, total cost of materials and labor for repair $\left(T C_{R E P}\right)$, and total cost of maintenance $\left(T C_{P M}\right)$. Three cases are also taken into account to observe the effectiveness of the suggested maintenance method: Case I assumes that no maintenance actions are performed in the system, in Case II, maintenance budget for each distribution feeder is taken into consideration equally, in Case III, according to constraints, the suggested formulation allocates the optimal maintenance budget. The Roy Billinton test system’s bus number two (RBTS2) is subjected to the proposed reliability improvement approaches, and the results are discussed.
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