## 1 Introduction
In [24], the control strategy combining a crowbar and dynamic demagnetizing is presented for a doubly-fed variable speed pumped storage. The hybrid protection method and the traditional crowbar method are compared in terms of reactive power absorption and electromagnetic torque oscillation aspects. In [25], the static VAR compensator (SVC) and on-load tap changer (OLTC), based on a deep neural network (DNN), are designed for PV smart inverters. A DNN is trained as a local controller to determine the optimal setting points of the SVC and smart inverters. The PV energy penetration is maximized, and the voltage variation is minimized simultaneously using a mixed-integer linear optimization. In [26], the SVC configurations and OLTC tap positions are analyzed in PV hosting capacity (PVHC). In addition, the sensitivity of range-valued PVHC to the number of Monte Carlo simulations and the width of the PV installation capacity range is examined. In [27], the static synchronous compensator (STATCOM) is implemented for the LVRT requirement of the PV system. In [28], the distribution STATCOM (D-STATCOM) is intended for low-voltage distribution networks with high PV penetration. The D-STATCOM technique increases the ability to store the energy of the inductor, prolonging service life. In [29], PV is supplemented with a battery system to improve low voltage ride-through. Bi-directional DC-DC converters for battery energy storage reduce the fluctuation of the DC-link voltage. In [30], the battery energy stored quasi-Z source inverter (BES-qZSI) is implemented for the PV power system. BES-qZSI is employed in a phase-locked loop with a PR regulator to control the PV current. In [31],the super capacitor (SC) and distribution static compensator are applied to a two-stage grid-connected PV. SC features are utilized to enhance the frequency responsiveness of a two-stage grid-connected PV system. In [32], a solid-state transformer (SST) is implemented to analyze the mechanism of active power backflow of the PV system during LVRT. In [33], an SST is utilized to investigate the mechanism of active power backflow of the PV system during interphase short-circuit fault conditions. Crowbar circuit and braking chopper generally offer temporary solutions due to their limited effectiveness, though they are cheap. SVC and STATCOM have limitations in application areas such as LVRT due to their high cost and complex structure, although they have advanced features. Battery storage and SCs have limitations regarding energy density and cost, but they are useful in terms of renewable energy integration and providing fast energy support. The SST is not yet suitable for large-scale applications due to its excessively high cost and complexity, though it offers an innovative solution for modern power systems. In this study, the proposed DC chopper and CBFCL, based on the ML system, provide a more cost-effective and compact solution than other presented device approaches for improving LVRT in the literature. Also, the proposed system both increases energy efficiency and significantly improves the sustaining ability of the LVRT with its ability to limit short-circuit current. In addition, the proposed system provides high performance, sustainability, and long-term durability for power energy systems. This study aims to present a hybrid protection system combining a DC chopper and CBFCL to increase and regulate the LVRT capability of a grid-connected PVPP system. This study proposes an architecture that integrates a DC chopper and a CBFCL using an ML control system to achieve this. An ML approach is applied to the control method of the hybrid protection system. The main contributions of this study can be summarized as follows:  
1. The hybrid protection method limits the excessive fault currents that the traditional method alone usually cannot achieve, and ensures that a PVPP system remains connected to the electrical power grid. 2.