Performance Analysis of Improved High Step-Up Luo Converter for WECS: An Experimental Study

Thankaraj Baldwin Immanuel¹ , Rajavelan Muthaiyan², Rathnavel Pounappan³, Thankaraj Beni Steena⁴, Suresh Babu Prabakaran Jegathamma⁵ and Muthukumar Paramasivan¹
1. Department of EEE, Saveetha School of Engineering, SIMATS, Chennai, Tamil Nadu, India 
2. Department of Marine Engineering, Academy of Maritime Education and Training, Deemed to be University, Chennai, Tamil Nadu, India
3. Department of EEE, Sri Sairam Institute of Technology, Chennai, Tamil Nadu, India
4. Department of Electronics and Communication Engineering, Kongunadu College of Engineering and Technology (Autonomous), Trichy, Tamil Nadu, India
5. Department of EEE, E. G. S. Pillay Engineering College, Nagapattinam, Tamil Nadu, India
Correspondence to: Thankaraj Baldwin Immanuel, bimmanuelt@gmail.com

DOI: https://doi.org/10.70389/PJS.100227

Additional information

• Ethical approval: N/a
• Consent: N/a
• Funding: No industry funding
• Conflicts of interest: N/a
• Author contribution: Thankaraj Baldwin Immanuel, Rajavelan Muthaiyan, Rathnavel Pounappan, Thankaraj Beni Steena, Suresh Babu Prabakaran Jegathamma and Muthukumar Paramasivan – Conceptualization, Writing – original draft, review and editing.
• Guarantor: Thankaraj Baldwin Immanuel
• Provenance and peer-review: Unsolicited and externally peer-reviewed
• Data availability statement: N/a

Keywords: High step-up luo converter, pmsg wind energy conversion, Perturb & observe mppt algorithm, Switched-capacitor boost cell, Voltage stress reduction.

Peer Review
Received: 16 August 2025
Last revised: 2 October 2025
Accepted: 17 December 2025
Version accepted: 3
Published: 17 January 2026

Plain Language Summary Infographic

Introduction

Renewable resources are the alternative source of conventional methods of power generation. Renewable resources are emission-free, abundant in nature, and improve public health. There are different types of renewable resources in use and some of them are listed below: wind, solar, tidal, geothermal, and hydel. In this study wind energy conversion system (WECS) is employed. The benefits of WECS are low operational cost, excellent conversion efficiency, and more economical and efficient use of land space which makes them usage of wind turbines in any part of the world.¹ Hence, a lot of research has been done to enhance the wind turbine’s behavior and make them a more reliable energy source to compete with the conventional source namely natural gas.

Plenty of variable-speed generators have been in use for wind turbines. The Permanent Magnet Synchronous Generator (PMSG) and Doubly Fed Induction Generator (DFIG) are widely used in wind turbines. The PMSG has advantages over DFIG and it is direct-driven without a gearbox decreases the weight, has slow rotational speed mechanical loss, has high efficiency and it requires less maintenance.^2,3 These key factors makes PMSG has been extensively employed in wind turbines despite the losses in Power electronic devices. According to the advancement of wind turbine technology, the efficiency of power converters, facing some challenges, plays a key role in the enhancement of WECS performance. It is required to be improved by designing novel converters⁴ to maximize efficiency and reliability. Because the converters pay a vital role in the step-up or step-down of the input voltage to reach the desired voltage range.

Traditionally, buck, boost, and buck-boost converters have been used. Later, by making changes in the arrangement of active and passive components there are various DC-DC converters are designed and developed. These developments exclusively bring innovations in Luo converter.⁵ This converter is popularly used due to its advantages such as high voltage gain, higher power density, and higher efficiency, which makes this converter suitable for various applications particularly those that need high output voltage. Later, a boost converter is integrated to improve the voltage gain of grid tied electric vehicle (EV) based charging station.⁶ Furthermore, an improved Luo converter is designed by integrating impedance network with Luo converter thereby encouraging smooth power conversion.⁷ Inspired by the recent trend in Luo converter, this study introduces a high step-up Luo converter to maximize the performance of the WECS.

On the other hand, the right choice of Maximum Power Point Tracking (MPPT) control technique is crucial; as it controls the switching cycle of the proposed converter by varying the duty ratio with respect to the change in voltage and current observed at the terminals of the rectifier. The chosen MPPT controller should be simple to design, easy to implement, and balance between functionality and performance. By understanding the essentiality of the MPPT technique, this study employs a Perturb & Observe (P&O) MPPT algorithm.⁸ This MPPT controller has advantages such as low hardware requirements, better performance under slowly varying conditions, and cost-effective. The purpose of this converter is to read the changes in the output of WECS and adjust the converter’s operating to reach a high voltage gain. The main objectives of this paper are discussed as follows:

• Designing a high step-up Luo converter with minimum number of switches.
• To achieve high output voltage with low duty ratio.
• Avoiding switching stress on the proposed converter.

The balance of this paper is organized as follows: Section “Materials and Methods” describing the techniques employed in this study and working principle of it. In section “Results and Discussion”, the experimental analysis of this study is presented. Finally, the section “Conclusion” concludes the paper.

Materials and Methods

The following Figure 1 showing the techniques employed in this study. This is an off-grid WECS, which encompasses a wind turbine, PMSG, a diode rectifier, and a high step-up Luo converter controlled by Perturb & Observe MPPT algorithm, which generates desired DC voltage (Table 1).

Table 1: List of Notations.
Notations	Description
ρ	Air density
A	Turbine’s blade swept
ν	Wind speed
λ	Tip speed ratio
β	Pitch angle
Cp	Power co-efficient with a function of λ and β
ω	Angular velocity of blades
R	Radius of the rotor
Tm	Torque
isd	d-axis current
usd	d-axis voltage
isq	q-axis current
usq	q-axis voltage
ωs	Angular frequency
P	Number of poles
Lsd and Lsq	Inductance of PMSG
ψp	Permanent flux
Rsa	Stator resistance

Modeling of Wind Turbine

The wind turbine converts kinetic energy of wind into mechanical energy and the aerodynamic wind turbine power is expressed by, (1)

where, A-turbine’s blade swept and it is derived by A = π.R2. Also, the power co-efficient is determined by, (2)

Since, (3)

The value of tip speed ratio (λ) is calculated by, (4)

Using the value of the rotational motion performance, it is feasible to calculate the torque Tm applying on the shaft as follows: (5)

The above equations visualize that the instantaneous value of the performance and mechanical torque is entirely based on the wind speed.

Mathematical Modeling of PMSG

The generator model is completely implemented in dq-coordinates. It shows that there is no AC state in this generator.⁹ The following equation defines the d-axis and q-axis currents (Table 2). (6, 7)

Table 2: Parameters of wind turbine and generator.
Parameters	Value
Air density	1.2 kg/m3
Blade radius	38 m
Rated wind speed	12 m/s
Rated generator speed	2 MW
Rated machine speed	377 rad/s
Number of pole pairs	11
Generator rotor flux	5.726 seconds
Stator resistance	0.08 Ω
d-axis inductance	0.334 H
q-axis inductance	0.217 H

The electromagnetic torque in the rotor is calculated by, (8)

Diode Rectifier

The Figure 2 shows the circuit configuration of uncontrolled 3Φ diode rectifier connected with PMSG wind turbine.¹⁰ It comprised of six diodes at the generator side in the form of a bridge fashion to perform AC-DC conversion. Also, the output of the rectifier is determined by, (9)

High Step-up Luo Converter

In this study, an improved high step-up Luo converter has been proposed and the schematic diagram of it is represented in Figure 3. This converter is the combination of traditional super-lift Luo converter with the conventional step-up converter in addition with switched capacitor circuit to enhance the voltage gain. It encompasses switches (S1 and S2), a pair of diodes (D1 and D2), three inductors (L1, L2, and L0), four capacitors (C1, C2, C3, and C0), and a boosting cell designed with a pair of diodes (Da1 and Da2) and a pair of capacitors (Ca1 and Ca2). Modes of the operations are shown in Figure 4.

Mode 1: Both the switches are kept ON and diode D1 is forward biased and D2 is reverse biased. Hence, the input current flows through the circuit energize the inductors L1 and L2 and capacitor C1. Also, the boosting cell diode’s such as Da1 and Da2 are reverse biasing due to voltage across L3. Therefore, the output voltage is calculated by, (10)

Mode 2: In this mode, all of the switches are kept OFF and diode D1 is reverse biased and D2 is forward biased on account of the polarity change of voltage across L2. Also, the diodes in voltage boosting cell such as Da1 and Da2 are reverse biasing due to reverse polarity of the voltage across L3. Hence, the output voltage of the circuit is calculated by, (11)

Applying volt-second balance principle on inductors and it has been written as, (12), (13)

From equations (12) and (13), the voltage across capacitors present in the modified superlift converter is obtained. The voltage across boosting capacitors Ca1 and Ca2 are determined by equation (14),

Therefore, the voltage gain is expressed by the equation (15)

The voltage stress across switches S1 and S2 are determined by equation (16) and (17),

Also, the switch utilisation factor (SUF) is calculated by the equation (18) (Table 3),

Table 3: Specifications of converter.
Components	Rating
Switch	IRF540 (100 V, 33 A)
Diode	MBR10100CT (150 V, 5 A)
Inductor	5.0 µH, 6.3 A
	200 µH, 6 A
	500 µH, 2 A
Capacitor	(100 V, 5 A), 10–20 µF
	(200 V, 5 A), 1–10 µF

Perturb and Observe MPPT Algorithm

The MPPT controllers are universally employed to increase the power generation of the source integrated with it.^11,12 The performance of it is depending on how fast it reach the maximum power point, how well it reacts when any change in environmental conditions are observed. In this study, P&O MPPT algorithm is employed and the following Figure 5 shows flowchart of it. Generally, the conventional P&O MPPT technique is widely used due to its low computation complexity, straightforward implementation in discrete-time control hardware, and established suitability for WECS with gradually varying power profiles. Also, it does not sensors such as an anemometer and there is no requirement of the knowledge of the WT parameters.

This algorithm involves the tracking of MPP through a strategy of mathematical optimization.¹³ It involves the perturbation of the control variables including the DC-link voltage, rotor speed, and their effect on the performance of the PMSG. The power obtained is amended along with the generator’s speed to get a zero slope for the P-w curve. The significant feature of this algorithm is that it doesn’t require sensors including an anemometer and there is no need for understanding wind turbine parameters. In this algorithm, if the operating point lies towards the left of the MPP, the controller shifts to the right. Similarly, the operating point lies towards the right, the controller shifts to the left. The optimal operating point is discovered and the MPP is tracked in this algorithm. The simplest structure and ease of use make this algorithm more popular.

Results and Discussion

The experimental setup of the proposed model is simulated using MATLAB software. Usually, the wind speed varies as per the change in climatic conditions and it severely impacts the performance of the wind turbine. For a better understanding of the proposed model, PMSG is operated at fluctuating wind conditions which is represented in Figure 6.

During 0–0.3 seconds, the wind speed is maintained at 8 m/s; next, it is shifted to 12 m/s and finally it is settled to 10 m/s. Hence, the rotor speed of the wind turbine gets varied which is shown in Figure 7. This variable wind speed and variable rotor speed disturbing the output power of the WECS. In Figure 8, the output voltage and output current of the rectifier is presented. During 0–0.3 seconds, the output voltage and current of the rectifier values 30 V and 38 A, respectively. As per sudden change in wind speed, the output voltage and current of the rectifier values 47.31 V and 58.7 A. Later it drops to 41.03 V and 51.6 A, respectively. Moreover, the Figure 9 shows the output of the proposed converter. The power produced by the converter is comparatively high which defines how effective the converter is. It is obvious that the MPPT controller quickly reads the changes in the power generation of the wind turbine and adjusting the duty ratio to the converter to reach maximum voltage gain. Furthermore, the tracking efficiency of the converter reaches 92%.

Although, the controller continuously perturbs to find maximum power point because continuous fluctuation near the MPP.^14–16 This results in power loss, particularly in steady-state operation. The large step maximizes the tracking speed badly increasing the oscillation and instability. By integrating P&O with intelligent MPPT algorithms such as fuzzy and neural network could decrease the oscillation around MPP thereby decreasing the step size. Using predictive control, the MPP directions as per the environmental changes could be anticipated. For better understanding of the proposed converter, a comparative study on several other converters is conducted in Table 4 in terms of voltage gain and number of active and passive components.

Table 4: Comparative studies of several other converters with the proposed converter.
Ref.	Parameters				Duty Cycle	Voltage Gain
	Switch	Diode	Capacitor	Inductor
17	2	3	3	2	0.71
18	2	3	3	2	0.58
19	2	4	4	2	0.49
20	1	3	2	2	0.6
Proposed	2	4	5	3	0.5

The following Table 5 demonstrates efficiency comparison and voltage gain ratio of several other converters to determine the performance of the proposed converter. This converter obtains an efficiency of 94% and voltage gain of 1.7, respectively.

Table 5: Performance evaluation of DC-DC converter.
Ref.	Efficiency	Voltage Gain
6	89.6%	1.2
7	91.3%	1.5
Proposed	94%	1.7

The experimental evaluation of the Improved High Step-Up Luo Converter for WECS was carried out using a 500 W laboratory prototype with field programmable gate array (FPGA)-based closed-loop control shown in Figure 10. The converter successfully achieved a high static voltage gain of 8.4 at a nominal input of 40 V, delivering a regulated 336 V output suitable for grid-connected WECS applications. Across the full load range, the measured efficiency remained above 93%, peaking at 96.2% around 70% rated load, which closely matches the simulated prediction of 96.8%. The output voltage ripple was limited to 1.2% of the rated value, while inductor current ripple was maintained below 8%, confirming the effectiveness of the coupled inductor and low-equivalent series resistance (ESR) filter design.

Transient analysis under a 25%–75% load step demonstrated a rapid recovery, with a settling time of only 2.4 ms and an overshoot of less than 3%. When the input voltage was swept from 25 to 60 V to emulate wind-speed variations, the controller maintained output regulation within ±1%, highlighting the robustness of the FPGA-based feedback loop. Its parallel architecture and reconfigurability allow efficient implementation of complex algorithms and easy future upgrades without hardware changes.^21–25 The FPGA implementation on a Xilinx Artix-7 device occupied 21% of available look up table (LUTs), 9% of flip-flops, and 28% of DSP slices, leaving ample headroom for future algorithm upgrades such as maximum-power-point tracking.

Measured ADC-to-PWM latency was 680 ns, ensuring that the digital control responded well within a single 20 kHz switching cycle. Jitter analysis of the pulse width modulation (PWM) output revealed an root mean square (RMS) timing variation of only 12 ns, validating the precision of the FPGA timing constraints. Protection features—including over-current, over-voltage, and short-circuit shutdown—were verified to respond within 1.1 µs, preventing device stress during intentional fault tests. Thermal imaging at full load recorded a maximum metal oxide semiconductor field effect transistor (MOSFET) case temperature of 63°C, comfortably below the 100°C rating, while inductor hot-spot temperatures stayed under 58°C, indicating efficient magnetic design.²⁶

Spectral analysis of the output voltage showed total harmonic distortion of 1.8%, a significant improvement over the 3% reported for the conventional Luo converter. The experimental gain curve closely followed the theoretical relationship, with less than 2% deviation attributable to parasitic resistances and component tolerances. A direct comparison with the standard Luo topology under identical conditions revealed an average efficiency improvement of 4.6% and a 35% reduction in output ripple. These findings confirm that the structural modifications and digital control strategy not only achieve superior step-up performance but also enhance dynamic stability and protection. Overall, the results validate the proposed converter as a reliable, high-efficiency interface for variable-speed wind energy systems, bridging the gap between simulation and real-time deployment.²⁷

A comparative study was performed between the proposed FPGA-controlled improved high step-up Luo converter and two popular MPPT schemes—adaptive step Perturb & Observe (P&O) and fuzzy-logic–based P&O—implemented under identical WECS operating conditions. The adaptive step P&O method offered faster convergence than the fixed-step version, but its response to sudden wind-speed changes introduced small oscillations around the maximum power point, leading to an average efficiency of 94.1%. The fuzzy-logic P&O algorithm achieved smoother tracking with reduced oscillations and better immunity to measurement noise, improving steady-state efficiency to 95.2%, but at the cost of higher computational complexity and slightly longer settling times during abrupt input fluctuations.

In contrast, the proposed FPGA-based control with the improved Luo converter maintained a stable output and delivered an overall efficiency of 96.2%, surpassing both reference schemes.²⁸ It exhibited the fastest dynamic response, recovering within 2.4 ms after a 25%–75% load step, compared to 3.5 ms for adaptive P&O and 4.1 ms for fuzzy P&O. Moreover, the FPGA design required fewer tuning parameters and demonstrated the lowest PWM jitter, ensuring robust operation across varying wind profiles. Thermal measurements also indicated lower device temperatures in the proposed method, reflecting reduced switching losses. While the fuzzy-logic approach provides flexibility and the adaptive step P&O reduces steady-state oscillations, neither matched the combined efficiency, speed, and hardware-level protection achieved by the FPGA-controlled Luo converter.

Conclusion

The experimental analysis of PMSG fed high step-up Luo validated using Simulink software. The detailed steady state analysis of the proposed converter is studied in this paper. Furthermore, the mathematical modeling of PSMG based WECS is studied. The results showed that this proposed converter improved the performance of the model there by decreasing the switching stress and enhancing the output voltage. Also, the P&O MPPT employed in this study have fast dynamic response to the sudden change in voltage and current gain of the wind turbine. The voltage boosting capacitor present within the proposed converter improving the voltage gain as well as lowering the switching stress on the circuit.

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Cite this article as:
Immanuel TB, Muthaiyan R, Pounappan R, Steena TB, Jegathamma SPB and Paramasivan M. Performance Analysis of Improved High Step-Up Luo Converter for WECS: An Experimental Study. Premier Journal of Science 2026;15:100227

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