NSF Award
2514755
Computer simulation is a widely used but computationally intensive method for predicting the transient stability of power systems following large disturbances. Currently, simulation performance lags behind industry demand for online, real-time applications and research need for data-driven applications, particularly for practically sized systems with high penetration of renewable energy. This NSF project aims to develop a high-performance framework that enables data, task, and job parallelisms for transient stability simulations to scale to the full capacity of contemporary and future parallel computing hardware. The proposed framework will bring transformative changes to the understanding of how power system models should be represented and how computational workflows should be structured to take advantage of modern parallel computers. The intellectual merits of the project include a) accelerating the building and solving phases of differential-algebraic equations (DAE) through the design of parallel-enabled software representations of power system models, and b) the identification and utilization of computational methods and hardware devices based on the characteristics of simulation test cases. The broader impacts of the project include the dissemination of research findings via open-source software and publications, integrated research and education activities, and the potential to enhance the stability of the power grid infrastructure.<br/><br/>Three tasks have been identified to accomplish the goal. Task 1 will create software representations of power models and computational workflows to enable staged data and task parallelisms for the DAE building process on CPUs and Graphics Processing Units (GPUs). It will ensure correct results from concurrent executions by coordinating the updating of equations shared across models while optimizing caches. Task 2 will develop adaptive dispatchers to identify and apply the most efficient hardware and solution algorithms for given power system cases, considering system size, acceleration techniques, and practical constraints. Task 3 will investigate pipelining algorithms for parallelizing multi-scenario jobs on heterogeneous hardware to build and solve DAEs for maximized hardware utilization. Upon successful completion, the project is expected to have established a novel, high-performance framework for modern computing hardware that will markedly accelerate the simulation of power system dynamics.<br/><br/>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.
