Analysis of surge arrester energy withstand in protecting wind turbines based on Monte Carlo simulation

Abstract

This paper presents a procedure for assessing the failure risk of metal oxide (MO) surge arresters intended for the protection of wind turbines (i.e. wind farms), due to the energy that they must be able to absorb during a direct lightning strike to the wind turbine. The calculation procedure is statistical in nature and is based on Monte Carlo simulation, using the well-known EMTP-ATP software package. It takes into account the fact that the lightning current parameters incident to the wind turbine (amplitude, front duration and crest duration) are of a statistical nature, as well as the energy carrying capacity of the metal oxide surge arrester itself. In addition, the proposed procedure also takes into account the fact that the wind turbine, as a free-standing, exposed and very tall object, initiates its own upward lightning strikes (the parameters of which differ significantly from downward lightning strikes). In this regard, the basis for determining the energy stress of the ZnO surge arrester is the analysis of the so-called backsurge that accompanies a direct lightning strike to the wind turbine.

Petar Sarajčev

Full Professor | Department of Power Grids and Substations

Josip Vasilj

Associate Professor | Department of Power Grids and Substations

Researcher and Associate Professor at the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split, where he teaches courses related to engineering economics, power system analysis, power grids and machine learning. His research focus is the application of advanced numerical methods to problems in the analysis and planning of power system operations.

Ranko Goić

Full Professor | Department of Power Grids and Substations

Full professor at the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split exeperienced in transmission and distribution networks, renewable energy sources (RES), power system planing and economics