This paper elaborates a novel optimum programming‐based algorithm that embeds the stochastic multiobjective particle swarm optimization (PSO) method and the deterministic interior point method to calculate the maximum wind power penetration level. With the optimization target of promoting the wind generation capacity, the three‐stage optimization strategy is established to contemplate the transient stability constraint (TSC) as well as the uncertainty factors in the high wind penetrated system. To address the uncertainty factors in system, the chance‐constrained optimization approach is practiced to figure out the initial optimal operating point in the first stage. On the ground of which, the TSC is reinforced in the second stage to delineate the dynamic feasible region. Among the obtained security domain, the ultimate operation solution is calculated in the last stage and provides operators with specific operating scheme. The framework is capable of supporting alternative optimal methods and can be extended to more complex system modeling. The feasibility of the algorithm framework has been demonstrated by simulations on two benchmark systems. And it has prosperous application prospects for optimization problems that need to consider system dynamic security and uncertainty simultaneously.

中文翻译：

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考虑系统暂态稳定性的基于多目标优化的最大风力渗透极限计算框架

本文阐述了一种新颖的基于最优规划的算法，该算法嵌入了随机多目标粒子群优化（PSO）方法和确定性内点方法，以计算最大风能穿透水平。以提高风力发电容量为优化目标，建立了三阶段优化策略来考虑高风速渗透系统的暂态稳定约束（TSC）和不确定性因素。为了解决系统中的不确定性因素，实践中采用了机会受限的优化方法来确定第一阶段的初始最佳运行点。基于此，在第二阶段对TSC进行了增强，以描绘出动态可行区域。在获得的安全域中，最终的运营解决方案在最后阶段进行计算，并为运营商提供特定的运营方案。该框架能够支持替代的最佳方法，并且可以扩展到更复杂的系统建模。通过在两个基准系统上进行仿真，证明了算法框架的可行性。对于需要同时考虑系统动态安全性和不确定性的优化问题，它具有广阔的应用前景。