Abstract Hardening components is an effective way to decrease the load loss risk caused by component outages in power systems. The system hardening against the long-term risk usually faces the computation burden problem brought up by the risk evaluation. This paper proposes a deterministic hardening planning model to minimize the long-term system risk of load curtailment, which eases the computational cost concern. To accomplish this task, a set of system events with load loss and corresponding load curtailments are obtained by an improved Monte Carlo simulation. An analytical function of system risk index with respect to the unavailability of components is derived and can calculate the risk index rapidly. Then, the deterministic model is constructed by applying the analytical function into the stochastic problem of system hardening planning. The greedy algorithm is developed to solve the model. The proposed model and method improve the computation efficiency by avoiding the repeated time-consuming risk evaluations. Case studies are conducted on the RBTS, RTS79, and a modified RTS96 system. Performances of the proposed model and method are compared with that of the conventional reliability optimization method (CROM). Results demonstrate that the model obtains better solution than the existing study on hardening planning for long-term risk, and has higher computation efficiency than CROM.

中文翻译：

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降低长期风险的电力系统加固规划分析模型

摘要 部件加固是降低电力系统因部件停电引起的负荷损失风险的有效途径。针对长期风险的系统加固通常面临风险评估带来的计算负担问题。本文提出了一种确定性强化规划模型，以最大限度地降低长期系统负荷削减的风险，从而缓解计算成本问题。为完成此任务，通过改进的蒙特卡罗模拟获得一组具有负载损失和相应负载缩减的系统事件。推导了系统风险指数对组件不可用性的分析函数，可以快速计算出风险指数。然后，通过将解析函数应用于系统强化规划的随机问题，构建确定性模型。贪心算法被开发来解决模型。所提出的模型和方法通过避免重复耗时的风险评估来提高计算效率。案例研究是在 RBTS、RTS79 和修改后的 RTS96 系统上进行的。将所提出的模型和方法的性能与传统的可靠性优化方法（CROM）进行了比较。结果表明，该模型比现有的针对长期风险的强化规划研究获得了更好的解，并且具有比CROM更高的计算效率。将所提出的模型和方法的性能与传统的可靠性优化方法（CROM）进行了比较。结果表明，该模型比现有的针对长期风险的强化规划研究获得了更好的解，并且具有比CROM更高的计算效率。将所提出的模型和方法的性能与传统的可靠性优化方法（CROM）进行了比较。结果表明，该模型比现有的针对长期风险的强化规划研究获得了更好的解，并且具有比CROM更高的计算效率。