## 1 Introduction
(2) A segmentation method for the fault-crossing process based on statistical modal characteristics is proposed to divide the data interval of the fault stage accurately, and a general structured model framework for fault-crossing segmentation control of doubly fed wind turbines is constructed. (3) A genetic Newtonian hybrid fault traversal parameter optimization algorithm is proposed, which combines global search and local optimization to improve accuracy and robustness significantly. (4) Based on the proposed method and theory, a set of generalized black box new energy unit parameter identification software is developed by combining Matlab App Designer Version: 9.11.0.1769968 (R2021b) and PSD-BPA version 3.1. The proposed method and the developed software are validated using semi-physical hardware-in-the-loop test data from the RTLAB-based doubly fed unit. The results demonstrate that the proposed method is more accurate and robust, achieving a 2.89% reduction in error compared to the traditional method, which is of significant value for engineering applications. Meanwhile, the developed parameter identification software platform automates the entire process of data preprocessing, parameter optimization, and simulation verification, improving modeling efficiency by 40% and addressing the issue of convenience in engineering applications. The structure of this paper is as follows:  
Part I: Based on the new energy scale statistics of the International Renewable Energy Agency (IRENA), we point out the key grid integration technical challenges facing the global new energy development and emphasize that high-precision new energy modeling is the theoretical cornerstone of the security and stability analysis of new power systems. By systematically combing the research progress of wind power, photovoltaic and energy storage modeling, and combining it with the comparative analysis of the optimization performance of various identification algorithms, the current technological bottlenecks and methodological limitations are further clarified, thus laying an important theoretical foundation and research basis for the innovative solutions proposed in this study. Part II: The common fault ride-through segmented control characteristics of new energy units are analyzed according to the high and low ride-through standards of new energy units in various countries, based on which a general structured model of three-segment control of wind turbine fault ride-through is established, and the core control parameters of the control strategies in each phase are analyzed. Part III: The RTLAB hardware in-loop test simulation platform is utilized to conduct in-loop testing of the actual doubly fed wind turbine black box controller and to obtain the output response data of the controller under various operating states. Aiming at the measured data, a method of data segmentation preprocessing using the statistical modal feature segmentation method and a method for fast and accurate identification of structured models using the genetic Newtonian algorithm are proposed. Part IV: According to the control identification method and various optimization algorithms proposed in this paper, a universal parameter identification software simulation platform is developed by combining Matlab App Designer and PSD-BPA. Part V: The actual black box controller of a doubly fed wind turbine model that has been put into operation is selected for the RTLAB semi-physical hardware-in-the-loop test, and combined with the output response data, the parameter identification software platform, and the general structured electromechanical transient model of the doubly fed wind turbine, the parameter identification for the fault ride-through control of this doubly fed turbine's black box controller is completed, and the simulation results of the different identification algorithms are compared in a variety of operating conditions. Which proves the validity and accuracy of the proposed parameter identification method and the developed software.