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.

协作研究：电力系统仿真的计算高效求解器密苏里科技大学电气工程的玛丽萨·克罗密苏里科技大学计算机科学的马吉·程伊利诺伊理工学院应用数学李书旺摘要：在不同领域的计算方法的几个最新进展使实时动态仿真的目标变得容易实现。不幸的是，由于结果从一个领域渗透到另一个领域的时间滞后，许多电力系统分析工具没有使用实现最先进解决方案技术的算法。因此，有必要将最优秀的数学家、计算机科学家和电力工程师聚集在一起来解决现实问题。在本项目中，将协同开发计算高效的求解方法，并将其应用于实现电力系统实时仿真的问题。具体地说，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问题。智能优点：实时仿真一直被认为是电力工程中的一项重大挑战。一个实际规模的电网问题可以产生数百个动态状态变量和50,000多个代数状态。一些电力系统仿真的计算复杂性使其不能用于在线决策。如果仿真能够实时运行，那么电力系统操作员就会有态势感知，并可以实施在线控制，以避免连锁故障。该工具将帮助操作员采取主动措施，限制事故的范围，并可显著提高电力系统的可靠性。这个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，并将它们应用于电力系统仿真。广泛的影响：该项目将为培养电力系统、计算机算法和应用数学方面的不同STEM劳动力提供机会。PI、研究生和博士后研究员将进入密切的指导关系，其中不仅包括计算方法方面的一对一指导，而且还包括伦理研究实践、沟通技能和国际意识。这项研究的结果将被纳入多个研究生课程：电力系统的计算方法和近似算法。PIS还将开发本科课程材料和大学预科实践项目。