The rapid development of economy and society stimulates the increase of power demand. Wind power has received great attention as a typical renewable energy, and the share of wind power is continually increasing in recent years. However, the high integration of wind power brings challenges to the secure and reliable operation of power grid due to the intermittent characteristic of wind power. In order to solve the operation risk caused by wind power uncertainty, this paper proposes to solve the problem of stochastic security-constrained unit commitment (SCUC) by considering the extreme scenarios of wind power output. Firstly, assuming that the probability density distribution of wind power approximately follows a normal distribution, a great number of scenarios are generated by Monte Carlo (MC) simulation method to capture the stochastic nature of wind power output. Then, the clustering by fast search and find of density peaks (CSFDP) is utilized to separate the generated scenarios into three types: extreme, normal and typical scenarios. The extreme scenarios are identified to determine the on/off statuses of generators, while the typical scenarios are used to solve the day-ahead security-constrained economic dispatch (SCED) problem. The advantage of the proposed method is to ensure the robustness of SCUC solution while reducing the conservativeness of the solution as much as possible. The effectiveness of the proposed method is verified by IEEE test systems.

中文翻译：

---

极端风力场景下安全约束的机组承诺

经济和社会的飞速发展刺激了电力需求的增长。作为典型的可再生能源，风能受到了极大的关注，近年来，风能的比重不断增加。然而，由于风力的间歇性，风力的高度集成给电网的安全可靠运行带来了挑战。为了解决风电不确定性带来的运行风险，本文提出了考虑风电输出的极端情况来解决随机安全约束机组承诺（SCUC）的问题。首先，假设风能的概率密度分布近似服从正态分布，蒙特卡洛（MC）仿真方法生成了大量场景，以捕获风能输出的随机性。然后，通过快速搜索和找到密度峰值（CSFDP）进行聚类，将生成的场景分为三种类型：极端，正常和典型场景。确定了极端方案来确定发电机的开/关状态，而典型方案则用于解决日前安全受限的经济调度（SCED）问题。提出的方法的优点是在确保SCUC解决方案的鲁棒性的同时，尽可能地降低了解决方案的保守性。IEEE测试系统验证了该方法的有效性。通过快速搜索和找到密度峰值（CSFDP）进行聚类，可将生成的场景分为三种类型：极端，正常和典型场景。确定了极端方案来确定发电机的开/关状态，而典型方案则用于解决日前安全受限的经济调度（SCED）问题。提出的方法的优点是在确保SCUC解决方案的鲁棒性的同时，尽可能地降低了解决方案的保守性。IEEE测试系统验证了该方法的有效性。通过快速搜索和找到密度峰值（CSFDP）进行聚类，可将生成的场景分为三种类型：极端，正常和典型场景。确定了极端方案以确定发电机的开/关状态，而典型方案则用于解决日前安全受限的经济调度（SCED）问题。提出的方法的优点是在确保SCUC解决方案的鲁棒性的同时，尽可能地降低了解决方案的保守性。IEEE测试系统验证了该方法的有效性。而典型方案则用于解决日趋安全受限的经济调度（SCED）问题。提出的方法的优点是在确保SCUC解决方案的鲁棒性的同时，尽可能地降低了解决方案的保守性。IEEE测试系统验证了该方法的有效性。而典型方案则用于解决日趋安全受限的经济调度（SCED）问题。提出的方法的优点是在确保SCUC解决方案的鲁棒性的同时，尽可能地降低了解决方案的保守性。IEEE测试系统验证了该方法的有效性。