Collaborative Research: Scalable Circuit theoretic Framework for Large Grid Simulations and Optimizations: from Combined T&D Planning to Electromagnetic Transients

这个NSF项目旨在开发一个通用的分布式框架，用于解决大规模电网问题，在大多数实际环境中既快速又健壮。该项目将为未来的电网运营和规划带来变革性的变化，这些变化取决于易于处理的大规模时域和稳态模拟以及快速电气化和脱碳的优化。该项目将通过推进非线性规划，物理启发的图形划分和具有子模块类型目标的组合优化的最新技术来实现这种转变。该项目的智力优势包括利用专门的边界块对角结构的网格问题的计算易处理性和物理根源的等效电路表示的网格模型的数值稳定性和算法性能。该项目的更广泛影响包括加速向零碳电网过渡所需的技术，促进公民科学工作，以及促进本科生的研究和教育。零碳电网的运行和设计将需要大型计算的解决方案。这些范围将从系统范围的电磁瞬态模拟由于不断增长的渗透逆变器为基础的资源，以大型多周期优化由于增加资源的不确定性。由于其庞大的规模和复杂性，最先进的通用方法无法在实际环境中鲁棒有效地解决这些大型模拟和优化。我们将利用网格问题的结构和物理行为产生的潜在的专门属性，通过三个项目重点来解决这些差距。Thrust 1将建立一个可扩展的电路理论通用框架，以解决有界块对角可分解的大型非线性模拟（NLS）和优化（NLP）。重点1将利用基本问题的等效电路表示来实现项目目标。推力2将引入一种新的度量，用于分析量化分解机制中各种子问题之间耦合强度的概念，推力3将确定最佳分解策略。该奖项反映了NSF的法定使命，通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This NSF project aims to develop a generalized distributed framework for solving large-scale power grid problems that are both fast and robust in most practical settings. The project will bring transformative change in the future grid operation and planning that depend on tractable large-scale time-domain and steady-state simulations and optimizations for rapid electrification and decarbonization. The project will bring about this transformation by advancing the state-of-the-art in nonlinear programming, physics-inspired graph-partitioning, and combinatorial optimization with submodular type objectives. The intellectual merits of the project include leveraging specialized bordered-block-diagonal structure of grid problems for computational tractability and physics-rooted equivalent-circuit representation of grid models for numerical stability and algorithm performance. The broader impacts of the project include accelerating technologies necessary for the transition to zero-carbon power grids, enabling citizen science efforts, and promoting undergraduate research and education. Zero-carbon electric grid operation and design will require solutions to large computations. These will range from system-wide electromagnetic transient simulations due to the growing penetration of inverter-based resources to large multi-period optimizations due to increasing resource uncertainty. State-of-the-art general methods cannot solve these large simulations and optimizations robustly and efficiently in practical settings due to their sheer size and complexity. We will leverage the underlying specialized properties stemming from the structure and physical behavior of grid problems to address these gaps through three project thrusts. Thrust 1 will build a scalable circuit-theoretic generalized framework to solve bordered-block-diagonal decomposable large nonlinear simulations (NLS) and optimizations (NLPs). Thrust 1 will harness equivalent circuit representations of the underlying problems to achieve project goals. Thrust 2 will introduce a novel metric for analytically quantifying the notion of strength of coupling between various subproblems in a decomposed regime, and Thrust 3 will identify optimal decomposition strategies. The proposed thrusts, while focused on power grids, can revolutionize the solution methodology of large-scale problems in many other domains.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.