Collaborative Research: Computationally Efficient Solvers for Power System Simulation

协作研究：用于电力系统仿真的计算高效求解器

• 批准号: 1665422
• 负责人: Maggie Cheng
• 金额: $ 5.43万
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1665422&HistoricalAwards=false
• 关键词: Collaborative; Research; Computationally; Efficient; Solvers

Collaborative Research: Computationally Efficient Solvers for Power System SimulationMariesa Crow, Electrical Engineering, Missouri University of Science & TechnologyMaggie Cheng, Computer Science, Missouri University of Science & TechnologyShuwang Li, Applied Mathematics, Illinois Institute of TechnologyAbstract: Several recent advances in computational methods in a variety of fields have brought the goal of real-time dynamic simulation within reach. Unfortunately, many power system analysis tools do not use algorithms that implement state-of-the-art solution techniques due to the time lag of results percolating from one field to another. Therefore, there is a need to bring together the best of the mathematicians, computer scientists, and power engineers to solve realistic problems. In this project, computationally efficient solution methods will be synergistically developed and applied to the problem of achieving real-time power system simulation. Specifically, recent advances in computational science and theoretical computer science will be extended to the problem of electric power networks. Intellectual Merit: Real-time simulation has long been considered to be a grand challenge in electric power engineering. A realistically sized electric power network problem can generate hundreds of dynamic state variables and 50,000+ algebraic states. The computational complexity of some power system simulations has kept time domain simulation from being used in on-line decision making. If simulations could run in real-time, then power system operators would have situational awareness and could implement on-line control to avoid cascading failures. This tool will assist the operator with proactive measures to limit the extent of the incident, and can significantly improve power system reliability. This project will exploit the expertise and advances in areas of linear solvers from a variety of physical fields and will adapt them for use in power system simulation.Broader Impact: This project will provide an opportunity for educating a diverse STEM workforce in electric power systems, computer algorithms and applied mathematics. The PIs, the graduate students, and the post-doctoral fellow will enter into a close mentoring relationship that will include one-on-one instruction not only in computational methods, but also ethical research practices, communication skills, and international awareness. The results of this research will be incorporated into multiple graduate classes: Computational Methods for Power Systems andApproximation Algorithms. The PIs will also develop undergraduate course material and pre-college hands-on projects.

合作研究：电力系统仿真的计算高效求解器Mariesa Crow，电气工程，密苏里州科技大学&Maggie Cheng，计算机科学，密苏里州科技大学&Shuwang Li，应用数学，伊利诺伊州理工学院摘要：最近在计算方法在各个领域的一些进展带来了实时动态仿真的目标触手可及。 不幸的是，许多电力系统分析工具不使用实现最先进的解决方案技术的算法，由于从一个领域到另一个领域的结果的时间滞后。 因此，有必要将最好的数学家、计算机科学家和电力工程师聚集在一起，以解决现实问题。 在这个项目中，计算效率高的解决方案的方法将协同发展，并应用于实现实时电力系统仿真的问题。 具体来说，计算科学和理论计算机科学的最新进展将扩展到电力网络的问题。 智力优势：实时仿真一直被认为是电力工程中的一个巨大挑战。 一个现实规模的电力网络问题可以生成数百个动态状态变量和50，000+代数状态。 一些电力系统仿真的计算复杂性使时域仿真不能用于在线决策。如果模拟可以实时运行，那么电力系统运营商将有态势感知，并可以实施在线控制，以避免连锁故障。该工具将帮助运营商采取主动措施来限制事故的范围，并可以显着提高电力系统的可靠性。 该项目将利用各种物理领域的线性求解器领域的专业知识和进步，并将其应用于电力系统仿真。更广泛的影响：该项目将为教育电力系统，计算机算法和应用数学方面的多元化STEM劳动力提供机会。 PI，研究生和博士后研究员将进入一个密切的指导关系，将包括一对一的指令不仅在计算方法，而且道德研究实践，沟通技巧和国际意识。 这项研究的结果将被纳入多个研究生班：电力系统的计算方法和近似算法。PI还将开发本科课程材料和大学预科动手项目。