## 1 Introduction  
In recent years, the global energy sector has continued to grow rapidly. According to the statistics of the International Renewable Energy Agency (IRENA), as of the end of 2023, the total global installed capacity of renewable energy has reached 337 million kilowatts, accounting for 30% of the total global installed power generation capacity, with a compound annual growth rate of 9.3% over the past 10 years. It is expected that the total installed capacity of the world will exceed 1.1 billion kilowatts by 2030 [1]. However, the large-scale grid integration of new energy sources has also brought a series of technical challenges to the power system: its volatility and intermittency have led to frequent grid frequency and voltage stability problems, the increasingly severe phenomenon of low-voltage or high-voltage off-grid, and the coupling of power electronic equipment with synchronous systems has triggered broadband oscillation problems [2; 3; 4; 5; 6]. These problems have triggered major grid accidents several times around the world. For example, a localized grid collapse triggered by a large-scale wind power off-grid in Northwest China in 2019 resulted in a power outage of several hours [7], and wind and photovoltaic (PV) power crises were exacerbated by a large-scale off-grid due to insufficient low-voltage ride-through capability during a winter storm in Texas, USA, in 2021 [8]. To address these technical challenges, accurate simulation analysis is necessary, and valid conclusions from simulation analysis rely on accurate modeling of new energy sources. For example, inaccurate LVRT modeling can affect the validation of relay protection algorithms, potentially leading to the misoperation of actual protection devices and triggering chain failures [9; 10; 11]. Therefore, to address the accurate modeling problems of the new energy \"black box\" controller fault ride-through control, this paper conducts related research, aiming to improve the accuracy and applicability of the new energy model, thereby providing theoretical support for the safe and stable operation of the new power system. For a long time, scholars around the world have conducted numerous studies on wind power, photovoltaics, and energy storage power generation system models, gaining a deeper understanding of their related model structures and operational principles. For example, [PERSON] et al. [12] and [PERSON] et al. [13] ignored the current control process and modeled the amplitude-phase dynamics of the DFIG wind power system under DC voltage and rotor speed time scales, respectively. [PERSON] et al. [14] established the equivalent impedance model of the DFIG wind power system and grid based on the impedance analysis method, which is used to analyze the interaction between the wind power grid-connected system and the grid. [PERSON] et al. [15] proposed a reduced-order model of a PV power system for small-signal stability assessment and estimated the maximum penetration level of the PV system. This study emphasized the importance of simplified models in power system stability analysis. [PERSON] et al. [16] developed a Norton equivalent model for PV power systems and analyzed the effects of grid-connected capacity and grid strength on system resonance. [PERSON] et al. [17] developed a detailed and averaged model of a large-scale PV power system for electromagnetic transient simulation under grid faults. The model can accurately reflect the dynamic behavior of the PV system, but it has high computational complexity. [PERSON] et al. [18] proposes a composite demand-side simplified model structure containing loads, distributed PV generation, and energy storage systems and proposes a model parameter identification method based on environmental signals and fault data. The model structure is capable of recognizing the dynamic characteristics of PV generation and energy storage systems at the high-voltage bus by simplifying these systems. [PERSON] et al.