Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies

arXiv:2310.00763v3 Announce Type: replace
Abstract: This work presents an efficient data-driven method to construct probabilistic voltage envelopes (PVE) using power flow learning in grids with network contingencies. First, a network-aware Gaussian process (GP) termed Vertex-Degree Kernel (VDK-GP), developed in prior work, is used to estimate voltage-power functions for a few network configurations. The paper introduces a novel multi-task vertex degree kernel (MT-VDK) that amalgamates the learned VDK-GPs to determine power flows for unseen networks, with a significant reduction in the …

abstract arxiv construct cs.lg cs.sy data data-driven eess.sy flow functions kernel network power prior process strategies type vertex work