The increasing penetration of highly intermittent wind generation could seriously jeopardize the operation reliability of power systems and increase the risk of electricity outages. To this end, this paper proposes a novel data-driven method for operation risk assessment of wind-integrated power systems. Firstly, a new approach is presented to model the uncertainty of wind power in lead time. The proposed approach employs k-means clustering and mixture models (MMs) to construct time-dependent probability distributions of wind power. The proposed approach can also capture the complicated statistical features of wind power such as multimodality. Then, a non-sequential Monte Carlo simulation (NSMCS) technique is adopted to evaluate the operation risk indices. To improve the computation performance of NSMCS, a cross-entropy based importance sampling (CE-IS) technique is applied. The CE-IS technique is modified to include the proposed model of wind power. The method is validated on a modified IEEE 24-bus reliability test system (RTS) and a modified IEEE 3-area RTS while employing the historical data of wind generation. The simulation results verify the importance of accurate modeling of short-term uncertainty of wind power for operation risk assessment. Further case studies have been performed to analyze the impact of transmission systems on operation risk indices. The computational performance of the framework is also examined.

中文翻译：

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基于混合模型和重要性抽样的风电系统数据驱动型运营风险评估

高间歇性风力发电的普及率不断增加，可能会严重损害电力系统的运行可靠性，并增加停电的风险。为此，本文提出了一种新的数据驱动方法，用于风电系统的运行风险评估。首先，提出了一种新方法来建模提前期中风电的不确定性。所提出的方法采用k均值聚类和混合模型（MM）来构建时间相关的风力发电概率分布。所提出的方法还可以捕获风力发电的复杂统计特征，例如多模式。然后，采用非顺序蒙特卡洛模拟（NSMCS）技术来评估操作风险指标。为了提高NSMCS的计算性能，应用了基于交叉熵的重要性采样（CE-IS）技术。修改了CE-IS技术，以包括拟议的风力发电模型。该方法在修改后的IEEE 24总线可靠性测试系统（RTS）和修改后的IEEE 3区RTS上进行了验证，同时采用了风力发电的历史数据。仿真结果证明了对风电短期不确定性进行准确建模对于操作风险评估的重要性。已经进行了进一步的案例研究，以分析传输系统对操作风险指数的影响。还检查了框架的计算性能。该方法在修改后的IEEE 24总线可靠性测试系统（RTS）和修改后的IEEE 3区RTS上进行了验证，同时采用了风力发电的历史数据。仿真结果证明了对风电短期不确定性进行准确建模对于操作风险评估的重要性。已经进行了进一步的案例研究，以分析传输系统对操作风险指数的影响。还检查了框架的计算性能。该方法在修改后的IEEE 24总线可靠性测试系统（RTS）和修改后的IEEE 3区RTS上进行了验证，同时采用了风力发电的历史数据。仿真结果证明了对风电短期不确定性进行准确建模对于操作风险评估的重要性。已经进行了进一步的案例研究，以分析传输系统对操作风险指数的影响。还检查了框架的计算性能。