Optimized Energy Management System for Wind Lens-Enhanced PMSG Utilizing Zeta Converter and Advanced MPPT Control Strategies

Abstract

This paper presents the design and analysis of an efficient energy management system for a wind lens integrated with a permanent magnet synchronous generator (PMSG) and a zeta converter. The wind lens, a ring-shaped structure encircling the rotor, enhances the turbine’s capability to capture wind energy by increasing the wind influx through the turbine. In the contemporary wind energy sector, PMSGs are extensively employed due to their superior performance characteristics. This study integrates a 1 kW PMSG system with a wind lens to optimize power extraction from the wind energy conversion system (WECS) under varying wind speeds. A comparative analysis of different control strategies for maximum power point tracking (MPPT) is conducted, including the incremental conductance (INC) method and the perturb and observe (P&O) method. The performance of the MPPT controller integrated with the wind lens-based PMSG system is assessed based on output DC voltage and power delivered to the load. To evaluate the overall effectiveness of these control strategies, both steady-state voltage and dynamic response under diverse wind conditions are examined. The system is modeled and simulated using the MATLAB R2023a/Simulink 9.1 software, and the simulation results are validated to demonstrate the efficacy of the proposed energy management system.

1. Introduction

An optimized energy management system (EMS) for a wind lens-enhanced permanent magnet synchronous generator (PMSG) represents a significant advancement in renewable energy technology. This system integrates advanced algorithms and control strategies to maximize the efficiency and output of wind energy systems that utilize wind lens technology and PMSGs [1]. The wind lens is an augmentation device that enhances the performance of wind turbines by focusing and accelerating wind flow onto the turbine blades. This technology increases the wind speed at the rotor, thereby boosting the energy output without the need for larger turbines [2]. The wind lens can significantly increase the power output of a wind turbine by concentrating wind flow, The wind lens can help reduce aerodynamic noise, making wind turbines quieter and more suitable for various environments. The design can also improve safety by stabilizing the turbine in high-wind conditions [3]. PMSGs are known for their high efficiency, reliability, and compact size, making them ideal for wind energy applications [4]. PMSGs operate without the need for external excitation, reducing energy losses and improving overall efficiency. The high power density of PMSGs allows for smaller and lighter generator designs [5]. With fewer moving parts and no brushes, PMSGs require less maintenance compared to traditional generators [6]. PMSGs are highly efficient even at low wind speeds and have a better performance compared to traditional induction generators, especially in variable wind conditions [7]. The EMS for wind lens-enhanced PMSGs aims to optimize the performance and energy output of the wind turbine system through advanced control algorithms and real-time data analysis.

The EMS utilizes MPPT algorithms to ensure the wind turbine operates at its optimal power output regardless of wind conditions. Sensors and data analytics enable continuous monitoring and control of the turbine system, allowing for dynamic adjustments to maximize efficiency [8]. The EMS can integrate with energy storage systems to manage fluctuations in power generation and ensure a stable energy supply. By analyzing operational data, the EMS can predict maintenance needs, reducing downtime and extending the lifespan of the equipment. The EMS ensures that the generated power is compatible with the grid, managing voltage, frequency, and phase to meet grid requirements [9].

The increasing demand for sustainable and renewable energy sources has propelled the development of advanced wind energy systems [10,11]. One such promising advancement is the use of wind lens technology, which enhances the efficiency and power output of wind turbines by concentrating wind flow towards the rotor [12]. Coupled with permanent magnet synchronous generators (PMSGs), which offer high efficiency and reliability, these systems are poised to significantly contribute to the global energy mix [13].

To optimize the performance of wind lens-enhanced PMSGs, integrating sophisticated power electronic converters and advanced maximum power point tracking (MPPT) strategies is essential [14]. The zeta converter, known for its capability to operate in both buck and boost modes with high efficiency, presents a viable solution for managing the variable nature of wind energy [15,16]. This converter, in conjunction with advanced MPPT algorithms, ensures that the maximum possible energy is harnessed from the wind under varying conditions [17,18]. Recent studies have focused extensively on the optimization of energy management systems for wind turbines. For instance, Kabalci et al., in [19], explored the use of intelligent control methods for energy conversion in wind systems, highlighting the importance of adaptive MPPT techniques for improving efficiency [20]. Similarly, Kumar et al. [21] demonstrated the advantages of using zeta converters in renewable energy applications, emphasizing their role in achieving stable and efficient power conversion.

Advanced MPPT strategies such as perturb and observe (P&O), incremental conductance (INC), and machine learning-based methods have shown significant improvements in tracking the optimal power point under dynamic wind conditions [22,23]. Research by Jena et al. [24] compared these methods, concluding that hybrid approaches combining traditional and intelligent algorithms yield superior performance and effectiveness of wind lens technology in enhancing the aerodynamic efficiency of wind turbines. These enhancements lead to increased power output and more stable operation, which are critical for the overall reliability of wind energy systems [25,26]. Incorporating these advanced technologies and control strategies into a cohesive energy management system can significantly improve the performance and reliability of wind energy systems [27,28].

The combination of wind lens technology, permanent magnet synchronous generators (PMSGs), and advanced energy management systems (EMSs) marks a paradigm shift in wind energy generation. These systems may maximize energy output, improve operational efficiency, and guarantee stable and reliable power supply even under fluctuating wind conditions by utilizing sophisticated MPPT algorithms, zeta converters, and intelligent control techniques. The combination of these technologies improves wind turbine performance as well as advancing sustainable and renewable energy solutions, opening the way for a more resilient and efficient global energy infrastructure This paper aims to present an optimized energy management system for wind lens-enhanced PMSGs, utilizing zeta converters and advanced MPPT control strategies, thereby contributing to the sustainable development of renewable energy infrastructure.

The objective of this work is to design and develop a stand-alone system for a wind lens integrated with a wind energy–battery-based renewable energy system. An energy management system is proposed to maintain the balanced power flow between the load and battery for different environmental conditions. The proposed system can be evaluated in the Simulink platform under various different control techniques. The remainder of this paper is organized as follows: Section 2 demonstrates the system’s structure and architecture. Section 3 discusses wind lens-enhanced WECSs with MPPT; Section 4 discusses the experimental results for the proposed systems. Finally, this study concludes with conclusions and discussion in Section 5.

2. Enhanced Wind Energy Optimization Architecture

2.1. Wind Lens—Introduction

Wind lenses, often called shrouded or ducted turbines, work by encircling the turbine with a flanged diffuser to boost wind speed and enhance wind turbine efficiency. The fundamental idea of a wind lens is to produce a pressure differential that speeds up the wind flow through the turbine, increasing the power output of the device. The performance of a wind energy system is greatly improved by the addition of a wind lens [29], which is a shrouded structure that surrounds the wind turbine. Wind lenses efficiently raise the wind speed at the rotor by generating a pressure differential [30] that quickens the airflow through the turbine. This improvement yields a significant increase in power production, which is frequently more than double that with traditional open rotor designs [31]. By concentrating and enhancing the available wind resource, the wind lens also helps to reduce noise and raises the turbine’s overall efficiency. The effectiveness of wind lenses in a variety of environmental settings has been proven by experimental research and numerical simulations, indicating that they have the potential to completely transform wind energy technology [32,33].

2.2. Power Output Equation with a Wind Lens

The power output of a wind turbine can be expressed as

$$\begin{array}{c}\hfill P_{lens}={\displaystyle \frac{1}{2}}\rho A{\omega }^3{C}_p\end{array}$$

(1)

For a wind lens, the effective wind speed ${\omega }_{eff}$ is enhanced due to the lens effect, which can be represented as

$$\begin{array}{c}\hfill {\omega }_{eff}=k\times \omega \end{array}$$

(2)

where k is the wind speed enhancement factor due to the wind lens. Thus, the power output equation for a wind turbine with a wind lens becomes

$$\begin{array}{c}\hfill P_{lens}={\displaystyle \frac{1}{2}}\rho A\left(k{\omega }^3\right)C_p\end{array}$$

(3)

where k is the wind speed enhancement factor due to the wind lens. This demonstrates the significant impact of the wind lens in increasing the effective wind speed, and consequently, the power output.

2.3. Wind Lens-Enhanced Wind Energy Conversion System

The three primary sections of the proposed system are represented by Figure 1: (i) a wind lens with an added wind turbine; (ii) a wind energy conversion system that also makes use of a zeta converter and battery storage; and (iii) a battery management system. MPPT (maximum power point tracking) technology is used in the wind programs. The MPPT is turned off, putting the controller and wind energy systems in an off state, when the electricity generated exceeds the load requirement. Next, the battery’s stored energy powers the load. The MPPT [34] reactivates to bring the battery back up to full capacity and give power to the load whenever the battery’s state of charge (SOC) drops. In order to guarantee that the load is continuously supplied, an energy management system supervises the regulation of electricity under diverse conditions.

3. Wind Lens-Enhanced WECS with MPPT

As seen in Figure 2, the wind energy conversion system is composed of a variable-speed wind turbine, a 1 KW PMSG, a zeta converter, and an MPPT controller. The low cost and minimal maintenance of PMSG is the basis for its selection [35,36]. PMSG power is rectified using three-phase uncontrolled rectifiers, and uncontrolled DC-DC voltage is managed by zeta converters with MPPT controllers. Based on the battery’s charge state, MPPT regulates the zeta converter [37]. In the proposed method, the perturbing variable is the DC current. The DC-link voltage slope is used by the program to indirectly identify abrupt variations in wind speed.

Additionally, the voltage slope is used to increase the tracking speed of the algorithm and prevent the generator from failing during a sudden fall in wind speed. A WECS with wind speed fluctuation settings uses three MPPT approaches. Every MPPT technique has benefits and drawbacks of its own, and the particulars of the application may influence which technique is best. Two MPTT techniques are adopted to analyze the performance of the proposed system, namely, the incremental conductance (INC) method and the perturb and observe (P&O) method. These MPPT methods are able to gauge the maximum power point effectively and reliably when used in conjunction with a zeta converter, improving the overall performance of renewable energy systems. The performance parameters are calculated based on time-domain analysis. The MPPT Algorithm 1 continuously adjusts the duty cycle to ensure that the WECSs operate at their maximum power point, optimizing the energy harvested from the speeds. This is achieved by integrating a zeta converter with an incremental conductance (INC) maximum power point tracking (MPPT) algorithm. The zeta converter’s versatility in handling varying input voltages makes it well suited for WECS applications where the speed fluctuates. The INC MPPT Algorithm 1 ensures that the WECS operate at their maximum power point (MPP), maximizing the energy harvested. The INC MPPT algorithm is used to find and maintain the maximum power point of the speed, as shown in Figure 3. It is based on the principle that the derivative of power with respect to voltage is zero at the MPP. The INC method compares the instantaneous conductance (I/V) to the incremental conductance ($\Delta I$/$\Delta V$) to determine the direction in which to adjust the operating point.

Algorithm 1 INC MPPT algorithm.

Step 1: Measure Instantaneous Voltage (V) and Current (I) from rectifier output. Step 2: Calculate Instantaneous Power $\left(P\right):P=V\times I$ Step 3: Calculate Derivatives:     Instantaneous Conductance: $G=I/V$     Incremental Conductance: $\Delta G=\Delta I/\Delta V$ Step 4: Determine Operating Point:     if $\Delta G=-G$ then        The system is at MPP.     else if $\Delta G>-G$ then        Increase the voltage (decrease duty cycle).     else if $\Delta G<-G$ then        Decrease the voltage (increase duty cycle).     end if Step 5: Adjust Duty Cycle: Based on the comparison, adjust the PWM signal controlling the Zeta converter to move the operating point towards the MPP.

The DC-link voltage across the battery and capacitor reflects the acceleration data from the generator. The zeta converter is a flexible and efficient part in optimizing energy harvest from changeable renewable sources since it can perform both step-up and step-down voltage conversion. The suggested approach is evaluated using a 1 kW prototype configuration and shows enhanced stability and fast tracking capability in both high- and low-rate-of-change wind speed scenarios.

4. Experimental Results

Figure 4 illustrates the comparison results of a wind lens enhanced with wind concentration and energy storage (WCES) technology and its position. The enhanced wind lens demonstrates improved efficiency and energy capture compared to a standard setup. This enhancement is visualized in terms of performance metrics such as increased power output or improved aerodynamic efficiency.

Figure 5 illustrates the response of a permanent magnet synchronous generator (PMSG) to varying wind speeds over a period of 1.2 s, showing the wind speed, mechanical power, and PMSG output power. The PMSG MPPT system might find it difficult to generate any appreciable amount of power and the turbine blades may rotate more slowly; therefore, the wind lens increases the amount of wind speed in terms of rad/s with respect to the movement of the actuator. The outcomes of a comparison between incremental conductance (INC)-based MPPT (second set) and P&O-based MPPT (first set) in a wind energy conversion system with wind lens. The P&O approach is shown by the first diagram, which has smoother transitions but is less sensitive to variations in wind speed, leading to extremely high output and mechanical power. While there are noticeable drops in mechanical power, the second diagram, which shows the INC technique, is more responsive to variations in wind speed and maintains a greater and more stable PMSG output power. This suggests that the INC method is the preferable MPPT methodology for this wind lens-augmented wind energy system because it achieves higher efficiency and power output stability.

Initial phase (0–0.2 s): All three parameters rise sharply, with wind speed driving the increase in mechanical and output power. From 0 to 0.2 s, the wind speed rises steeply, reaching approximately 12 rad/s. Corresponding to the initial wind speed increase, mechanical power rises to approximately 1300 W by 0.2 s. The output power increases alongside the wind speed, reaching around 1100 W by 0.2 s.

Stabilization phase (0.2–0.4 s): Wind speed and mechanical power stabilize with minor fluctuations. The PMSG output power stabilizes too but with higher fluctuations, reflecting dynamic control and load interactions. Between 0.2 and 0.4 s, the wind speed remains relatively stable around 12 rad/s. It stabilizes around this value with minor fluctuations until 0.4 s. Between 0.2 and 0.4 s, the output power remains relatively stable but shows more fluctuations compared to mechanical power, indicating the generator’s response to load changes.

Dip phase (0.4–0.6 s): A slight decrease in wind speed causes corresponding minor decreases in mechanical and output power, with output power showing higher fluctuation sensitivity. From 0.4 to 0.6 s, there is a slight dip to around 11 rad/s before stabilizing again. During the wind speed dip from 0.4 to 0.6 s, mechanical power decreases slightly but remains relatively stable. From 0.4 to 0.6 s, output power reflects the slight dip in wind speed with increased fluctuations.

Stable phase (0.6–1.0 s): Wind speed, mechanical power, and output power stabilize again. Mechanical power remains smoother, while output power continues to fluctuate. After 0.6 s, the wind speed maintains a level slightly above 11 rad/s until about 1.0 s. From 0.6 to 1.0 s, mechanical power continues to reflect the stable wind speed, remaining at around 1100 W. Between 0.6 and 1.0 s, output power stabilizes again but with noticeable oscillations around 1000 W.

Final phase (1.0–1.2 s): The sharp drop in wind speed leads to rapid decreases in both mechanical and output power, with all parameters approaching zero by the end. Finally, from 1.0 to 1.2 s, the wind speed drops sharply to about 2 rad/s. As the wind speed drops sharply after 1.0 s, mechanical power also decreases dramatically, approaching zero by 1.2 s. Following the sharp wind speed decrease after 1.0 s, output power declines rapidly, nearing zero by 1.2 s.

Figure 5 illustrates the performance of the rectifier over 1.2 s. Initially, the wind speed rises sharply to 12 rad/s, stabilizes, dips slightly, and then, drops sharply at the end. Mechanical power follows this trend, rising to 1600 W, stabilizing with minor fluctuations, and then, decreasing sharply. The PMSG output power mirrors mechanical power but with more pronounced fluctuations, indicating dynamic control responses. In the rectifier plots, Vdc rises to 62 V, stabilizes, and drops sharply after 1.0 s. Idc follows a similar pattern, rising to 13.8 A, stabilizing with minor dips, and then, dropping. Rectifier power also follows these trends, peaking at 1000 W and stabilizing before sharply decreasing. The comparison shows how changes in wind speed directly affect mechanical and electrical outputs, with the rectifier parameters ($V_{dc}$, $I_{dc}$, rectifier power) closely following the PMSG output power, highlighting the interconnected dynamics of the system.

The waveform in Figure 6 illustrates the battery’s charging and discharging behavior in response to wind speed changes. As shown, when the wind speed drops around the 1 s point, the battery discharges maximum energy to the load, as indicated by the sharp rise in battery power output. The firing pulses to the switching devices and the instantaneous load voltages are illustrated in Figure 7 and Figure 8.

As seen in Figure 9, the load voltage is kept constant in all scenarios. Combining battery storage systems with charge controllers and back-to-back converters allows for this. The system dynamically adjusts to balance supply and demand when the wind source fluctuates owing to variations in wind speed for turbines. Batteries are used to store extra energy during times when wind energy production is at its peak. The stored energy is released to maintain a constant load voltage during periods of low production. Despite the unpredictability of wind sources, this steady voltage is essential for the stand-alone system’s dependable functioning, protecting it from harm and guaranteeing its effectiveness.

Table 1. Parameters of the experimental prototype.

Equipment	Parameter	Value
PMSG	Nominal power	1000 W
	Nominal voltage	66 V
	Nominal current	15 A
	Rated speed	120 rps
	Stator resistance	0.56 $\mathrm{\Omega }$
	Stator inductance ($L_d,L_q$)	0.0045 mH
	Pole pair (P)	4
	Moment of inertia (J)	2.08 × 10−3 kg·m2
	Coefficient of friction (K)	3.90 × 10−3 N·m·s/rad

summarizes the key parameters of the experimental prototype for the permanent magnet synchronous generator (PMSG), highlighting its electrical and mechanical characteristics. These parameters are crucial for analyzing performance and implementing advanced control strategies.

5. Conclusions

The optimized energy management system (EMS) for wind lens-enhanced permanent magnet synchronous generators (PMSGs) demonstrates significant advancements in wind energy technology, as evidenced by a data-driven model. The integration of wind lens technology with PMSGs, supported by advanced optimization algorithms and control strategies, leads to notable improvements in the efficiency and reliability of wind energy systems. The computational modeling shows a significant increase in power output due to the enhanced wind capture capabilities of the wind lens. The wind lens effectively concentrates the wind flow, resulting in higher energy conversion rates by the PMSG. The EMS, using sophisticated algorithms like maximum power point tracking (MPPT), ensures that the wind turbine operates at its optimal performance point. Simulation studies indicate a marked improvement in operational efficiency across various wind speeds. The control strategies implemented in the EMS enhance the stability and reliability of the wind energy system. The computational experimental results highlight the system’s ability to maintain stable power output even in fluctuating wind conditions, reducing the likelihood of operational disruptions. The integration of real-time monitoring and adaptive control reduces the wear and tear on the system components. The framework confirms that the optimized operational parameters lead to lower maintenance requirements and a longer system lifespan.

The significant improvements in power output and efficiency contribute to a more effective utilization of wind energy, supporting the transition to renewable energy sources. Increased efficiency and reduced maintenance costs make wind energy more cost-competitive with traditional energy sources, promoting wider adoption. The system’s ability to scale and adapt to different environments and turbine sizes makes it a versatile solution for diverse applications. The data modeling outputs validate the effectiveness of the optimized EMS for wind lens-enhanced PMSGs, demonstrating clear improvements in power output, efficiency, stability, and cost-effectiveness. This innovative system exemplifies the potential of combining cutting-edge technology with intelligent management strategies to harness the full potential of wind energy, paving the way for a sustainable and renewable-energy future.