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Optimizing scheduling of post-earthquake electric power restoration tasks

机译：震后电力恢复任务的优化调度

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This paper presents a stochastic integer program developed to determine how to schedule inspection, damage assessment, and repair tasks so as to optimize the post-earthquake restoration of the electric power system. The objective of the optimization is to minimize the average time each customer is without power, and a genetic algorithm is used to solve it. The effectiveness of the schedules recommended by the optimization are evaluated by running a detailed discrete event simulation model of the restoration process with both the optimization-generated schedules and the power company's original schedules, and comparing the resulting restorations according to three measures—average time each customer is without power, time required to restore 90% of customers, and time required to restore 98% of customers. The optimization and simulation models both consider all the earthquakes that could affect the power system and represent the uncertainty surrounding expected restoration times. The models were developed through an application to the Los Angeles Department of Water and Power (LADWP) electric power system, but the general approach is extendable to other electric power systems, other lifelines, and other hazards.
机译：本文提出了一个随机整数程序，用于确定如何安排检查，损坏评估和维修任务的时间，以优化电力系统的震后恢复。优化的目的是最大程度地减少每位客户停电的平均时间，并使用遗传算法对其进行求解。通过运行详细的恢复过程离散事件模拟模型（使用优化生成的时间表和电力公司的原始时间表），并根据三种测量方法（每个平均时间）比较最终的恢复结果，来评估优化建议的计划的有效性。客户没有权力，恢复90％的客户所需的时间和恢复98％的客户所需的时间。优化和仿真模型都考虑了可能影响电力系统的所有地震，并代表了预期恢复时间周围的不确定性。这些模型是通过洛杉矶水电局（LADWP）电力系统的应用程序开发的，但是一般方法可扩展到其他电力系统，其他生命线和其他危害。

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