2026-04-13T06:05:37Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4422882025-09-24T13:07:25Zcom_2072_1033col_2072_452951

Grid strength estimation for offshore wind power plant with back-to-back converters Juaristi Elguea, Mikel Àrees temàtiques de la UPC::Energies::Energia eòlica Wind power Offshore structures Energia eòlica Estructures marines This thesis presents the modeling and control of a grid-forming voltage source converter (VSC) intended for offshore wind power plant applications. The main objective is to develop a control strategy capable of estimating the strength of the grid (commonly referred to as grid impedance or short-circuit ratio) in order to adapt the converter’s behavior accordingly. The system is designed to operate reliably in both weak and strong grid conditions, and to provide functionalities such as voltage and frequency support. The methodology is based on a full simulation model built in MATLAB/Simulink. The model includes a back-to-back converter, offshore transformer, grid models of varying impedance, and control blocks implementing virtual admittance and Q/V droop strategies. Additionally, a method for online grid strength estimation is integrated into the model. Several test scenarios—both under nominal and fault conditions—are evaluated to verify the performance of the converter in grid-forming mode. Results show that the proposed converter control can maintain stable operation and contribute to system support even in weak grid environments. The implementation of the grid strength estimation algorithm enables adaptive behavior, which is crucial for ensuring compliance with national grid codes and improving the robustness of future offshore wind systems. The work concludes that the integration of advanced grid-forming strategies is not only technically feasible but also essential for the evolving power systems landscape. 2025-09-24T13:07:25Z 2025-09-24T13:07:25Z 2025-09-24T13:07:25Z 2025-07 Master thesis http://hdl.handle.net/2117/442288 Open Access Universitat Politècnica de Catalunya