Novel estimation framework for short-circuit current contribution of type IV wind turbines at transient and steady-state of the faults

Abstract

Given the increasing penetration of converter-interfaced resources in power systems, properly estimating the short-circuit current (SCC) contribution in large networks has become a growing challenge and necessity to ensure the security and stability of the systems and assets. This paper presents two novel methods to estimate the SCC contribution of type IV wind turbines at both the transient and steady-state stages of unbalanced and balanced faults: (1) a machine learning-based method trained with electromagnetic transient (EMT) simulations and capable of estimating some of the initial peak and transient current magnitudes; (2) an analytical approach to estimate the steady-state SCC based on the voltage and grid code dependency of the converter during the fault. The methods are coupled into a single framework and compared to field-validated EMT models of a real turbine. The results show that the majority of the estimated currents in the transient stages present errors below 5%. In steady-state, the errors are not greater than 1.21%. Given the complexity of the problem, these margins may be deemed acceptable for short-circuit studies.