A new methodology for ultra-fast and accurate statistical EMT analysis in electric power-systems
Year: 2025
Type: article
Abstract: This paper introduces Quadrature Mirror Filter Electromagnetic Transient (QMF-EMT) methodology as a novel, precise, and ultra-fast method for statistical studies (SS) of EMTs in electrical networks. Building on a previously proposed approach for real-time EMT simulation, QMF-EMT incorporates nonlinear elements such as surge arresters, sequential switching operations, and a statistical switching model. The method is highly parallelizable and achieves superior accuracy and computational speed compared to conventional time-domain (TD) and frequency-domain (FD) techniques. The effectiveness of QMF-EMT is demonstrated through its application to the statistical analysis of two test networks. Validation is performed by comparing the results with established techniques, including PSCAD/EMTDC and the Numerical Laplace Transform (NLT) method. The case studies include the integration of surge arresters, controlled switching operations as overvoltage (OV) mitigation measures, and a large-scale network comprising 39 three-phase nodes. Notably, QMF-EMT's high computational speed on conventional CPUs enables efficient determination of the required number of events and integration steps for statistical analyses. This work underscores QMF-EMT's potential as a transformative tool for addressing computational challenges in EMT studies, particularly in large-scale power-systems.
Source: Electric Power Systems Research
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,810
OpenAlex ID: W4415675445