Fault-Tolerant Operation of Photovoltaic Systems Using Quasi-Z-Source Boost Converters: A Hardware-in-the-Loop Validation with Typhoon HIL

Abstract

Photovoltaic (PV) systems are prone to different types of faults, primarily electrical faults such as line-to-ground (L-G) and line-to-line (L-L) faults, which can significantly reduce system performance, efficiency, and lead to increased power losses. Moreover, mechanical damage caused by environmental stressors (such as wind, hail, or temperature variations), aging, or improper installation also contribute to system degradation. This study specifically focuses on electrical faults and proposes a method that not only enables the isolation of faulty modules but also ensures the uninterrupted operation of the remaining healthy modules and also assists in the localization of faults. Unlike benchmarked techniques-based boost converters, the Quasi-Z-Source Boost Converter (QZBC) topology offers improved voltage boosting with high gain values, reduced component stress, and enhanced reliability when the PV system is undergoing fault identification and localization algorithms. A 600-watt PV system connected with a Quasi-Z-Source Boost Converter was implemented and tested under different fault conditions using a hardware-in-the-loop (HIL) setup with Typhoon HIL. All the component values of the QZBC were calculated based on the system requirements rather than assumed, ensuring both practical feasibility and design accuracy. The experimental results show that the converter achieved an efficiency of over 96% under electrical-fault conditions, confirming the effectiveness of the quasi-Z-source boost converter in maintaining a stable power output when the PV system is undergoing fault identification and localization algorithms. The study further highlights the benefits of HIL-based testing for evaluating PV-system resilience and fault-handling capabilities in real-time conditions using a Typhoon HIL 404 environment.

1. Introduction

Electricity consumption has been shifted towards renewable-energy sources, which has shown a significant increase in the deployment of grid-connected photovoltaic systems. Among renewable-energy sources, photovoltaic (PV) systems have seen remarkable growth and a significant penetration in many applications such as solar-battery charging stations, space systems, telecommunication, residences, electric vehicles, and commercial installations, as well as parts of hybrid power systems [1,2].

However, the increased deployment of PV systems, especially in distributed and mobile environments such as EVs, introduces new challenges related to fault detection and system protection. These include an increased risk of line-to-ground and line-to-line faults due to variable environmental conditions, bidirectional power flow, and complex load behaviors.

Therefore, understanding and mitigating these faults is critical for the safe and efficient operation of modern PV-integrated power systems. PV systems convert solar energy into electrical power, offering a sustainable alternative to fossil fuels. However, the reliability and efficiency of grid-connected photovoltaic systems are often faced with various faults such as electrical, mechanical, and environmental faults [3,4,5,6,7]. This study focuses exclusively on electrical and environmental faults such as line-to-ground (L-G) and line-to-line (L-L) faults, abrupt changes in irradiance, and partial shading in PV strings where more than one module is connected in series [8]. These faults can lead to substantial power losses, short circuiting the system, and system instability. To address these challenges, researchers have been investigating advanced converter topologies and fault-tolerant control strategies to improve the resilience of photovoltaic (PV) systems under fault conditions [9,10,11,12,13,14].

1.1. Quasi-Z-Source Boost Converter (QZBC) in PV Systems

The quasi-Z-source boost converter plays a very important role in improving the efficiency of the converter of the photovoltaic systems by identifying the limitations of benchmarked power conversion methods. Unlike benchmarked DC-DC boost converters, the quasi-Z-source topology integrates voltage boosting and conditioning within a single stage, eliminating the need for multiple conversion steps. This not only improves overall converter efficiency but also enhances reliability by reducing component size and associated losses [15,16]. Additionally, its unique impedance network provides better voltage gain, an improved transient response, and enhanced fault tolerance, making it a highly effective solution for stabilizing and optimizing the power output of photovoltaic systems [17,18].

The quasi-Z-source boost converter (QZBC) offers significant benefits in renewable-energy applications. Its ability to handle wide input voltage variations, due to either short circuits or partial shading, makes it particularly suitable for photovoltaic systems, where the output voltage can fluctuate due to L-G, L-L faults in string, or changing environmental conditions such as irradiance and temperature [16,19,20,21,22].

In addition to employing GaN-based switches, this implementation distinguishes itself from prior QZBC-based PV systems through its focus on real-time fault-tolerant operation at high switching frequencies (1 MHz), which has not been explored extensively in the existing literature. Most previous studies utilizing QZBC topologies operate below 1 MHz and do not address system behavior during electrical faults in a modular PV setup [16,19,20,21,22,23,24,25].

1.2. Fault-Tolerant Strategies in PV Systems

Researchers have explored the fact that different types of faults may occur in photovoltaic (PV) systems, including mechanical, electrical, and environmental faults. This study focuses on electrical faults in photovoltaic systems, such as line-to-ground (L-G) and line-to-line (L-L) faults, which can severely impact performance and pose safety risks. Implementing fault-tolerant strategies is essential to ensuring continuous operation and maintaining the power quality of the PV system. Various approaches have been suggested to improve the fault tolerance of PV systems [26,27].

In [28] proposed a real-time hardware-in-the-loop (HIL) based open-circuit fault diagnosis method using artificial neural networks (ANNs) for cascaded H-bridge multilevel inverters. The proposed model achieved a 96% classification accuracy between various fault conditions, demonstrating its effectiveness in maintaining system performance during faults.

Another approach focuses on enhancing the converter topology itself to improve fault tolerance; the active-switched boost quasi-Z-source inverter (ASB-qZSI) has been proposed to enhance the efficiency of PV systems. The ASB-qZSI demonstrated improved performance under partial-shading conditions, which are analogous to certain fault scenarios, highlighting its potential in fault-tolerant PV applications [18,21,29].

1.3. Hardware-in-the-Loop Simulation for PV Systems

Accurately assessing the performance of photovoltaic (PV) systems under fault conditions demands precise and dependable testing methods. In the literature, real-time simulation platforms, such as FPGA-based hardware-in-the-loop (HIL) systems, have been widely used due to their high-speed processing and low latency. However, FPGA platforms typically require complex hardware description language (HDL) programming and longer development times, making them less accessible and harder to adapt for rapid prototyping. In contrast, Typhoon HIL offers a user-friendly, software-driven environment specifically designed for power electronics, enabling fast model development, seamless integration with control hardware, and real-time testing capabilities [30,31,32,33].

Importantly, repeatedly testing fault conditions on a physical PV system can lead to the degradation or failure of critical components, which are often costly and time-consuming to replace. Typhoon HIL overcomes this limitation by allowing exhaustive testing of a wide range of fault scenarios in a safe, repeatable, and non-destructive virtual environment. Therefore, HIL setup was used to validate the results, employing a Typhoon HIL 404 device (Typhoon HIL Inc., Somerville, MA, USA) interfaced with an F28379D microcontroller (Texas Instruments Inc., Dallas, TX, USA). The control algorithms were executed on the microcontroller, while the HIL platform facilitated real-time system emulation under various fault scenarios. This setup provided a safe and cost-effective means to assess system behavior under uncertain PV-production conditions [34].

1.4. Scope of the Study

Building on advancements in quasi-Z-source inverter (qZSI) technology and fault-tolerant strategies, this study explores the use of a quasi-Z-source boost converter (QZBC) to improve the fault tolerance of photovoltaic (PV) systems. A major challenge in photovoltaic (PV) systems is ensuring that healthy modules within a faulty string can continue delivering power efficiently, even when electrical faults such as line-to-line or line-to-ground faults occur. Traditional approaches often require complete string isolation, resulting in significant energy loss. To address this, our study investigates the integration of a high-frequency (1 MHz) quasi-Z-source boost (QZSB) converter, which allows for fault-tolerant operation by enabling power extraction from healthy modules during electrical fault conditions. A 600-watt PV system integrated with a QZBC was evaluated using a hardware-in-the-loop simulation setup with Typhoon HIL. All component values in the system were meticulously calculated based on system requirements to ensure accuracy and reliability. The objectives of this study are

• To design and implement a QZBC for a 600-watt PV system, ensuring optimal performance under normal and electrical fault conditions of the PV system.
• To validate the fault-tolerant capabilities of the QZBC using HIL 404 simulation, specifically assessing the system’s ability to maintain continuous power delivery during L-G, L-L faults, and partial shading conditions.
• To evaluate the efficiency of the PV system integrated with the QZBC under various operating conditions, aiming to achieve high efficiency of the operational PV system even in the presence of different electrical faults.

By addressing these objectives, the study aims to contribute to the development of more resilient and efficient PV systems capable of maintaining performance in the face of common electrical faults.

2. Methodology

This section includes the design, parameter calculation, and real-time validation of a 600 W photovoltaic (PV) system integrated with a quasi-Z-source boost converter (QZBC). The methodology follows an analytical approach using Kirchhoff’s Voltage Law (KVL), volt-second balance principles, and real-time implementation using a Typhoon Hardware-in-the-Loop (HIL) system as shown in Figure 1. The converter is designed to provide a stable 400 V DC output under varying input voltages from 30–100 V, ensuring operation under worst-case conditions.

2.1. Operation of Quasi-Z-Source Boost Converter (QZBC)

The QZBC topology consists of an impedance network composed of two inductors (L1 and L2) and two capacitors (C1, C2). In this paper, All the equations of the QZBC have been derived based on Figure 2 and Figure 3. The steady-state waveforms of the quasi-Z-source boost converter during normal operation have been shown in Figure 4. The first waveform in Figure 4 illustrates the switching signal, indicating the timing when the main switch is turned ON, which controls energy flow within the converter. The second waveform depicts the current through Inductor 1, which increases during the switch ON interval as energy is stored in the magnetic field. The third waveform shows the voltage across Capacitor 1, which decreases slightly as it discharges energy to the load and other circuit components. The fourth waveform presents the current through Inductor 2, reflecting the energy transfer from the source through the impedance network to the output. Finally, the fifth waveform represents the voltage across Capacitor 2. Together, these waveforms verify the proper energy storage and transfer mechanisms of the converter in a steady state, demonstrating the boost operation and efficient energy management within the impedance network. The converter operates in two main states:

Shoot-Through Mode (Switch ON): Energy is stored in the inductors, while the diode is reverse-biased;

Non-Shoot-Through Mode (Switch OFF): The stored energy is released to the output, supplying the load.

2.2. KVL Analysis for Different Switching States

Case 1: Switch ON (Shoot-Through Mode)

When the switch is ON, the diode is reverse-biased, and the inductors charge. Applying Kirchhoff’s Voltage Law (KVL) in this mode gives

$$-V_{in}+V_{L1}-V_{C2}=0$$

(1)

$$V_{L2}+V_{c1}=0$$

(2)

Case 2: Switch OFF (Non-Shoot-Through Mode)

When the switch is OFF, energy is transferred to the load. Applying KVL gives

$$-V_{C2}+V_{L2}=0$$

(3)

$$-V_{in}-V_{L1}+V_{C1}=0$$

(4)

$$-V_{C1}-V_{L2}+V_O=0$$

(5)

$$-V_{in}-V_{L1}-V_{L2}+V_O=0$$

(6)

2.3. Volt-Second Balance and Boost Factor Calculation

By applying the volt-second balance principle to Equations (1) and (6), we derived the output voltage equation for QZBC:

$$\begin{array}{l}(V_{in}+V_{C2})T_{ON}=(V_O-V_{in}-V_{L2})T_{OFF}\\ (V_{in}+V_{C2})(T_{ON}+T_{OFF})=V_O\ast T_{OFF}\\ V_O=(V_{in}+V_{C2})\ast {\displaystyle \frac{T}{T_{OFF}}}\end{array}$$

$$V_O=(V_{in}+V_{C2})\ast {\displaystyle \frac{1}{1-D}}$$

(7)

By applying the volt-second balance principle to Equations (2) and (3), we derived the output voltage equation for QZBC:

$$V_{C1}\ast T_{ON}=V_{C2}\ast T_{OFF}$$

(8)

$$V_{C1}=V_{C2}\ast {\displaystyle \frac{T_{OFF}}{T_{ON}}}$$

$$V_O={\displaystyle \frac{1}{1-D}}\ast V_{C2}\ast {\displaystyle \frac{T_{OFF}}{T_{ON}}}$$

(9)

By comparing Equations (7) and (9), the V_C2 voltage was derived in terms of input voltage.

$${\displaystyle \frac{1}{1-D}}\ast V_{C2}\ast {\displaystyle \frac{T_{OFF}}{T_{ON}}}=(V_{in}+V_{C2})\ast {\displaystyle \frac{1}{1-D}}$$

$$V_{C2}=V_{in}\ast ({\displaystyle \frac{D}{1-2D}})$$

(10)

Putting V_C2 in Equations (8) and (9) allows the V_C1 and V_o equations in terms of V_in and the duty cycle to be obtained as follows:

$$V_{C1}=V_{in}\ast ({\displaystyle \frac{D}{1-2D}})\ast {\displaystyle \frac{T_{OFF}}{T_{ON}}}$$

$$V_{C1}=V_{in}\ast ({\displaystyle \frac{1-D}{1-2D}})$$

(11)

Using Equations (9) and (10), the output and input voltage relationship was obtained:

$$V_O={\displaystyle \frac{1}{1-D}}\ast {\displaystyle \frac{T_{OFF}}{T_{ON}}}\ast V_{in}\ast ({\displaystyle \frac{D}{1-2D}})$$

$$V_O={\displaystyle \frac{V_{in}}{(1-2D)}}$$

(12)

For the inductor, Equation (2) was used:

$$L_2{\displaystyle \frac{d{i}_2}{dt}}=V_{C1}$$

$$L_1=L_2=V_{C1}{\displaystyle \frac{D{T}_S}{\mathrm{\Delta }{I}_2}}$$

(13)

For the capacitor calculation, during Shoot-Through Mode, the following equations have been used:

$$I_{C2}=I_{L1}=I_{in}$$

$$C_2={\displaystyle \frac{I_{in}D{T}_S}{\mathrm{\Delta }{V}_{C2}}}$$

(14)

$$C_1={\displaystyle \frac{I_{L2}D{T}_S}{\mathrm{\Delta }{V}_{C1}}}$$

(15)

To find the output, the power balanced formula was used:

$$P_{in}=P_o$$

(16)

$$I_0=I_{in}(1-2D)$$

(17)

2.4. PV System Configuration

The photovoltaic (PV) system in this study was modeled and implemented in the Typhoon HIL real-time simulation platform for the proposed model as shown in Figure 5, and for the benchmarked model as shown in Figure 6.

A modified PV model was used, designed to deliver a rated power output of 200 W at 30 V and 6.7 A under standard test conditions. This custom configuration was developed in Typhoon HIL using a waveform generator (see Figure 7) to reflect practical operating conditions while maintaining compatibility with the simulated power converter and load. The model was based on the general characteristics of commercial monocrystalline panels, such as the JKM200M-72 produced by Jinko Solar (Jinko Solar Co., Ltd., Shanghai, China) [35]. The modified PV module is available within the SCADA interface of the Typhoon HIL, enabling direct control and monitoring of its parameters during simulation.

The PV system consists of three series-connected modules forming a 3 × 1 configuration. Each module has a power rating of 200 W, with a maximum power point voltage of 30 V and a current of 6.7 A. The total power generated is 600 W, with string voltage varying between 30 V, 60 V, and 90 V based on line-to-ground and line-to-line faults and irradiance conditions as shown in

Table 1. Specification of the 3 × 1 PV system and QZSB converter’s components.

Parameters	Specification
Each module maximum power (Pm)	200 W
Open circuit voltage (Voc)	36.5 V
Voltage at maximum power (Vmax)	30 V
Short circuit current (Isc)	7.22 A
Current at maximum power (Imax)	6.7 A
No. of cells per module	70
Ideality factor	1.300
Irradiance	1000 W/m2
Temperature	25 °C
L1	2.8 mH
L2	2.8 mH
C1	5.0 µF
C2	5.0 µF
C3	5.0 µF
Ro	320 Ω

.

3. Hardware-in-the-Loop (HIL) Setup and Validation

The system was implemented using Typhoon HIL 404 for real-time validation. The setup consisted of

(a)

A simulated PV array providing variable input voltages of 30 V, 60 V, and 90 V;

(b)

A digital control unit implementing a pulse-width modulation (PWM) scheme at 1 MHz to regulate QZBC switching;

(c)

A resistive load consuming 600 W at a 400 V output;

(d)

Measurement and monitoring tools to record real-time voltage, current, and efficiency.

A Texas Instruments F28379D microcontroller served as the interface between the Typhoon HIL schematic and the HIL 404 hardware device, enabling accurate signal exchange. The voltage and current signals were conditioned and limited to a range of 0–3 V to ensure compatibility with the microcontroller’s analog input limits and to maintain signal integrity during interfacing, as shown in Figure 8.

The converter performance was evaluated under normal and fault conditions, including line-to-ground (L-G) and line-to-line (L-L) faults. The converter achieved a peak efficiency of 98%, confirming the effectiveness of the QZBC in maintaining stable power delivery under varying input conditions.

4. Results and Discussion

The quasi-Z-source boost converter was simulated in a photovoltaic (PV) system to evaluate its performance under normal and faulty conditions. The simulation results demonstrate that the converter effectively maintained stable voltage-boosting capabilities while handling fluctuations in input power from the PV array.

The simulated PV system consisted of three modules; each rated at 200 W and connected in series to form a 600 W string with a total voltage of 90 V. The performance of the quasi-Z-source boost converter was analyzed under normal and fault conditions to evaluate its efficiency and fault tolerance. For the line-to-ground (L-G) fault scenario, the last module was short-circuited to the ground as shown in Figure 9, causing a temporary drop in output voltage.

However, the system quickly recovered, demonstrating the converter’s capability to suppress transients and maintain stable operation. Similarly, under the line-to-line (L-L) fault condition, where the second module was shorted within the string as shown in Figure 10, the system experienced more significant voltage fluctuations and transient oscillations. Despite the disturbance, the QZBC effectively mitigated voltage instability, allowing the system to recover swiftly as shown in Figure 11. The results highlight the converter’s enhanced fault resilience and improved voltage regulation, making it a robust solution for photovoltaic applications. As shown in Figure 11, from the results, it is noticeable that at 0.5 s, one of the modules experienced a short circuit, causing the input voltage to drop to 70. However, the output voltage remained stable at 400, with some oscillations. This clearly demonstrates that during a line-to-ground fault in this string, the QZBC ensures continuous power delivery from the healthy modules to the system to keep efficiency high.

In large-scale PV systems, a common issue during faults is that the entire string gets disconnected due to its voltage dropping below the operational threshold compared to other strings. This leads to significant power loss and reduced converter efficiency. However, using the quasi-Z-source boost converter (QZBC) with an integrated fault-detection mechanism allows the healthy modules within the string to continue delivering power even under faulty conditions, rather than disconnecting the string completely from the system. This ensures that the system retains a substantial portion of its output, enhancing overall energy utilization. Once the fault is cleared, the converter seamlessly restores the string to its full power delivery without requiring a complete shutdown. This adaptive capability improves fault resilience, minimizes downtime, and optimizes power-generation efficiency in photovoltaic applications.

The data, summarized in

Table 2. Comparison of QZSB converter with benchmarked boost converters connected with 3 × 1 PV system [36,37].

Condition	Vin	Vo	Gain	QZSB Converter			Benchmarked Converters
-	-	-	-	D	MPPT Compatibility	Efficiency	D	MPPT Compatibility	Efficiency
Normal	90 V	400 V	4.44	0.38	Yes	98%	0.77	Yes	96%
One module faulty	60 V	400 V	6.6	0.41	Yes	89%	0.82	Limited	67%
Two modules faulty	30 V	400 V	13.3	0.46	Yes	77%	0.93	Limited	67%

, were collected under standard test conditions (1000 W/m² irradiance and 25 °C temperature) during normal operation, one module failure, and two module failures, to provide a fair and comprehensive comparison between the two techniques.

Figure 11 shows the results when one module is faulty, while Figure 12 illustrates the case when two modules in the same string are faulty. From Figure 11, it is noticeable that at 0.2 s, one of the modules experienced a short circuit, causing the input voltage to drop to 70. However, the output voltage remained stable at 400 with some oscillations. This clearly demonstrates that during a line-to-ground fault in this string, the QZBC enables the system to continue delivering power from the healthy modules with 400 watts output power and 67% efficiency of its rated power output due to the reduced available input. However, based on the input power that remains available, the converter continues to operate at an efficiency of approximately 98%, as shown in Figure 13, indicating that the power conversion and control remain highly effective under faulty conditions, whereas in the case of benchmarked converters, the entire string is often disconnected if the voltage falls below the minimum threshold, leading to complete power loss from that string. In the proposed method, the required gain during the fault is 0.42 instead of 0.39, which is easy to achieve, whereas in benchmarked cases, a much higher gain of 0.9 is needed. Additionally, if two modules are short-circuited, the input voltage drops to 40, as shown in Figure 12, requiring a gain of 0.47 to maintain 400 V output, to deliver the healthy module 200 watts of power with 33% efficiency of the string, while in benchmarked cases, achieving a 400 V output is almost impossible, as shown in the Table 2.

The methodology involves analytical modeling, worst-case component sizing, and real-time testing using Typhoon HIL. The QZBC successfully boosted the PV voltage to 400 V across a wide range of input conditions. The efficiency of 98% validates the proposed design’s robustness, making it suitable for fault-resilient PV power applications.

Moreover, this paper suggests using GaN FET to enable operation at 1 MHz frequency, which helps in significantly reducing the size of the system while maintaining efficient power delivery. The choice of semiconductor technology significantly affects power density, efficiency, weight, and volume. GaN FET, SiC, and Silicon converters operate at different switching frequencies (1 MHz, 100 kHz, 50 kHz, and 10 kHz), influencing their performance, see

Table 3. Qualitative Comparison of GaN FET, Silicon Carbide, and Silicon Converters for PV systems [23,24,25,38,39,40,41,42].

Parameter	GaN FET (1 MHz)	SiC (100 kHz)	SiC (50 kHz)	Silicon (10 kHz)
Switching Frequency	1 MHz	100 kHz	50 kHz	10 kHz
Power Density	Highest	Higher	Medium	Lowest
Efficiency	~98%	~96%	~92%	~92%
Losses	Lowest	Medium	higher	Highest
Weight	Lightest	Moderate	Higher	Heaviest
Volume	Smallest	Medium	Medium+	Largest
Thermal Management	Least required	Moderate	Critical	Most required
Cost	High	Medium	Medium+	Low

. Higher switching frequencies reduce passive component sizes, increasing power density, while wide bandgap materials (GaN and SiC) achieve lower losses and higher efficiency compared to Silicon. GaN FET offers the highest efficiency (~98%), lowest losses, and smallest volume, making it ideal for compact applications, though it comes at a higher cost. SiC provides a balance of efficiency (~96% at 100 kHz and ~92% at 50 kHz) and cost, with moderate weight and volume, whereas Silicon, despite being cost-effective, has the highest losses, lowest efficiency (~92%), and largest volume. Table 2 below summarizes the key comparisons:

GaN FET converters are ideal for space-constrained PV applications due to their superior power density and efficiency, while SiC offers a cost-efficient compromise. Traditional Silicon technology, although cheaper, suffers from a larger size and lower efficiency, making it less suitable for high-performance applications.

Although employing a GaN-based QZSB converter operating at 1 MHz offers clear benefits in terms of compactness, a fast dynamic response, and improved efficiency, it also introduces several limitations that must be carefully considered when implementing fault-detection algorithms in PV systems. At such high switching frequencies, distinguishing fault-related transients becomes more challenging due to the increased presence of high-frequency noise, which can obscure critical fault signatures in voltage and current waveforms. This necessitates the use of high-speed, high-resolution sensors and fast analog-to-digital converters, thereby increasing both the hardware cost and the computational demands on the control system. The higher operating frequency also requires more sophisticated gate drivers and more precise control algorithms capable of real-time processing, which further increases the system complexity.

Additionally, the design of the printed circuit board (PCB) becomes significantly more sensitive to parasitic inductance and capacitance at 1 MHz, requiring careful layout techniques, additional EMI filtering, and often the use of multilayer boards.

5. Conclusions

This paper demonstrates the design and validation of a quasi-Z-source boost converter (QZBC) for a 600 W photovoltaic (PV) system. The converter successfully stepped-up input voltages of 90 V, 60 V, and 30 V to a stable 400 V DC output, ensuring reliable power conversion under varying input conditions. The system was modeled and analyzed based on worst-case scenarios, and all component values were calculated to meet the system’s performance requirements.

The system was validated using Typhoon HIL, and the results showed that the converter achieved a high efficiency of 98%. The converter effectively maintained stable output even under fault conditions, such as line-to-ground (L-G) and line-to-line (L-L) faults, demonstrating its ability to ensure continuous power delivery from healthy PV panels when part of the array is affected by faults.

This study highlights the potential of the fault-detection mechanism to not significantly disrupt the energy-conversion process, making the overall system suitable for practical deployment in PV applications where both efficiency and fault resilience are critical.

Future research will focus on refining the control strategies to further optimize system performance and conducting real-world testing to validate the proposed design’s practical feasibility in actual PV installations.