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arxiv: 2112.00347 · v1 · pith:2GWEX32Inew · submitted 2021-12-01 · 📡 eess.SY · cs.SY· math.OC

An Open Source Software Stack for Tuning the Dynamical Behavior of Complex Power Systems

classification 📡 eess.SY cs.SYmath.OC
keywords powersoftwarelearningmachinestackalgorithmsautomaticavailable
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BlockSystems.jl and NetworkDynamics.jl are two novel software packages which facilitate highly efficient transient stability simulations of power networks. Users may specify inputs and power system design in a convenient modular and equation-based manner without compromising on speed or model detail. Written in the high-level, high-performance programming language Julia a rich open-source package ecosystem is available, which provides state-of-the-art solvers and machine learning algorithms. Motivated by the recent interest in the Nordic inertia challenge we have implemented the Nordic5 test case and tuned its control parameters by making use of the machine learning and automatic differentiation capabilities of our software stack.

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