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The letter proposes an adaptive model reduction approach based on tensordecomposition to speed up time-domain power system simulation. Taylor seriesexpansion of a power system dynamic model is calculated around multipleequilibria corresponding to different load levels. The terms of Taylorexpansion are converted to the tensor format and reduced into smaller-sizematrices with the help of tensor decomposition. The approach adaptively changesthe complexity of a power system model based on the size of a disturbance tomaintain the compromise between high simulation speed and high accuracy of thereduced model. The proposed approach is compared with a traditional linearmodel reduction approach on the 140-bus 48-machine Northeast Power CoordinatingCouncil system.

Tensor Decomposition based Adaptive Model Reduction for Power System Simulation