Stochastic Transient Stability Analysis for Structure Preserved Electric Power Systems

电力系统负荷是无数电力需求的函数，这些需求取决于各种因素，包括时间、天气、地理和经济。数千台独立切换的独立设备的聚合行为的结果是电力系统负载本质上是随机的。最近的结果表明，电力系统稳定性(或不稳定性)的确定可能会受到负荷模式的随机行为的不利影响。遗憾的是，由于缺乏合适的算法来分析大规模随机电力系统，阻碍了对这些影响的研究。因此，在这个项目中，我们将开发适当的工具来分析随机电力系统的动态行为。智能优点：这个领域非常及时和相关，因为可再生能源和插电式电动汽车增加了负荷和间歇发电来源的随机性水平。为了提高电力系统的可靠性、恢复力和安全性，更好地了解与系统不确定性负荷模型相关的固有风险是很重要的。该项目将解决影响电力系统暂态稳定的随机因素，并为安全评估和安全裕度的建立提供定量和定性的方法。广泛的影响：该项目将为培养不同的电力系统工程劳动力提供机会。该项目将支持一名女性博士生。PI和她的研究生将建立密切的指导关系，不仅包括电力工程方面的一对一指导，还包括伦理研究实践、沟通技能和国际意识。研究生还将接受课堂教学和学术生涯准备方面的指导。此外，数值方法的发展将被纳入由国际计算方法协会编写的下一版教科书中。

Electrical power system loads are functions of a myriad of power demands that depend on a variety of factors including time, weather, geography, and economics. The result of the aggregate behavior of many thousands of individual devices switching independently is power system loads that are stochastic in nature. Recent results have indicated that the determination of the stability (or instability) of the electric power system may be adversely affected by the random behavior of the loading patterns. Unfortunately, investigating these effects is hindered by the lack of appropriate algorithms with which to analyze large scale stochastic power systems. Therefore, in this project we will develop the appropriate tools to analyze the dynamic behavior of stochastic power systems.Intellectual Merit: This area is extremely timely and pertinent as the level of stochasticity in the loads and intermittent generation sources increase due to renewable energy resources and plug-in electric vehicles. It is important to better understand the inherent risks associated with nondeterministic load models of the system to improve the reliability, resiliancy, and security of the electric power system. This project will address the stochastic factors that impact the transient stability of the electric power system and provide quantitative and qualitative approaches to security assessment and establishing security margins.Broader Impacts: The project will provide an opportunity for educating a diverse engineering workforce in electric power systems. This project will support one women Ph.D. students. The PI and her graduate student will enter into a close mentoring relationship that will include one-on-one instruction not only in power engineering, but also ethical research practices, communication skills, and international awareness. The graduate students will also receive mentorship in classroom instruction and academic career preparation. Furthermore, the numerical methods developments will be incorporated into the next edition of the textbook authored by the PI on computational methods.