Conversion System Research Articles

New design of robust controller based on fuzzy 12 linguistic variables for wind power conversion system

New design of robust controller based on fuzzy 12 linguistic variables for wind power conversion system

Functionalization of ionic liquids for heterogeneous catalysis in CO2 conversion: Cycloaddition of epoxides and hydrogenation

The mitigation of environmental impacts caused by greenhouse gas emissions has become increasingly urgent, and the use of CO2 as a primary carbon source is an alternative in chemical transformations, including the synthesis of organic carbonates, formic acid, or methanol. This work aims to synthesize ionic liquids from the imidazolium cation family to be used in the cycloaddition of CO2 with ILs anchored in SiO2-clay heterostructure, MCM-41 and KIT-6 mesoporous materials, as well as the hydrogenation of CO2 with ILs added to ruthenium complexes, i.e., two catalytic systems. The most satisfactory result for CO2 cycloaddition (TON PC = 226) was obtained using the IL (MeO)3Sipmim.Cl anchored in SiO2-clay heterostructure (0.16 mol%) as the catalyst and ZnBr2 (0.04 mol%) as the co-catalyst. The hydrogenation was conducted with the IL (edaO)3Sipmim.Cl and the ruthenium complex Ru-PNN were not successful, but with co-catalyst PEHA, formic acid/formamide was produced (TON Form = 552). The unique catalytic system that showed activity for forming methanol was the commercial Ru-MACHO, Ru-C29H30ClNOP2, (TON MeOH = 3.3). These results highlight the potential of ruthenium-based complexes and supported ionic liquids as active systems in CO2 conversion.

Effect of moisture content on pyrolysis product yield from lignite and lignite-peanut shell mixtures using slow pyrolysis

ABSTRACT The conversion of biomass-coal mixtures into energy using thermal conversion systems offers a more environmentally sustainable alternative to conventional coal consumption. A reactor with an internal compartment is proposed to improve the pyrolysis performance of lignite coal and mixtures of lignite coal with peanut shells. The study investigates lignite coal with varying moisture contents and peanut shell proportions (0%, 10%, 25%, and 50%) at a temperature of 500°C, using a heating rate of 0.1°C/s. The results indicated that dry mixtures demonstrated higher overall productivity compared to wet mixtures, particularly in terms of charcoal production. The weight of charcoal increased by 4.83%, 4.71%, 4.02%, and 2.61% across the mixtures. The total conversion rates for dry mixtures were 24.59%, 29.27%, 34.36%, and 40.44%, while for wet mixtures, the conversion rates were 29.42%, 33.98%, 38.38%, and 43.05%, respectively. The results revealed that moisture content during pyrolysis significantly influenced the productivity of lignite and lignite-peanut shell mixtures. The conversion rates in dry mixtures were lower compared to those in wet mixtures. The novelty of this work lies in its pioneering investigation of the impact of moisture on the slow pyrolysis of Turkish lignite mixed with peanut shells. It offers novel insights into optimizing the thermal conversion process for these materials by uniquely examining the effects of moisture on productivity and conversion rates.

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

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.

Significant statistical model of heat transfer rate in radiative Carreau tri-hybrid nanofluid with entropy analysis using response surface methodology used in solar aircraft

The recent advancement of technologies focuses on the use of solar-based heat radiation and nanotechnology. The primary source of heat is solar energy, which is obtained by absorbing sunlight. In addition, solar thermal planes, photovoltaic cells, and sun-based hybrid nanofluids all help to harness solar energy. Therefore, main concern of the study is to explored the two-dimensional Engine oil-based Carreau tri-hybrid nanofluid (SiO2 (silica dioxide), MOS2 (Molybdenum disulfide), Fe3O4(black iron oxide)) flow via a stretching sheet within solar wings. The flow phenomena of the non-Newtonian fluid enrich for the effects of radiant energy and the external heat source. By adopting similarity transfiguration, the dimensional partial main flow equations are changed into nonlinear dimensionless ordinary differential equations. The most effective and powerful tool of the semi-analytical method ADM (Adomain Decomposition Method) is utilized to solve the nanofluid flow problem. The uniqueness of the proposed study arises due to the analysis of entropy generation obtained by various irreversibility processes. The graphical illustration of outcome of various governing parameters on velocity, temperature, entropy terms and engineering quantities have been presented and theoretically analyzed. The findings reveal that The Carreau ternary hybrid nanofluids enhance the system's thermal conductivity for optimal temperature regulation in solar aircraft and better heat dissipation. The use of Carreau ternary hybrid nanofluids significantly reduces entropy generation, which implies a more reversible process, enhancing the overall efficiency of the energy conversion systems in solar aircraft. The heat flow of the system is accurately reflected by the chosen variables and their interactions, as demonstrated by the constructed model's strong statistical significance. For real-world applications, this improves the model's predictability and dependability.

Thermodynamic analysis of supercritical CO2 power generation system for waste heat recovery with impurities in CO2

Waste heat recovery from gas turbines is an effective method for meeting the demand for a more efficient and cleaner energy system with decreased CO2 emissions and lower environmental pollution. The supercritical CO2 Brayton cycle is a promising power conversion system for waste heat recovery. The advantage of the supercritical CO2 Brayton cycle can be attained based on its physical characteristics. However, when another fluid is mixed as an impurity in a system using pure CO2, physical characteristics of working fluid was changed and operation at the design point can be challenging. Therefore, it is important to verify the purity of CO2 and understand the effect of impurities in CO2 in advance. This study examined the effects of impurities in the working fluid of a supercritical CO2 power generation system for actual demonstration facilities. The effect of impurity, a CO2-based mixture, in a supercritical CO2 power generation system on waste heat recovery from an LM500 gas turbine was investigated. A purity test of industrial grade CO2, which was noted as 99.9 % pure by the supplier, was conducted to verify the composition of the working fluid. The results of the purity test showed that the supplied CO2 consisted of 99.076 % CO2 along with nitrogen, argon, oxygen, water, and methane. Based on the results of the purity test, sensitivity analyses of the CO2-based binary mixtures and industrial mixtures were performed. A design point analysis was conducted for the CO2-based industrial mixture in comparison with pure CO2, which has cycle efficiency of 16.15 %, gross power of 510.03 kW, mass flow rate of 12.55 kg/s, and waste heat recovery of 2119.06 kW. In the case of fixed waste heat with mass flow rate of 14.417 kg/s, the cycle efficiency decreased by 0.39 % and gross power increased by 66.14 kW. In the case of fixed mass flow rate with 1844.598 kW waste heat, the cycle efficiency decreased by 0.32 % and gross power decreased by 9.84 kW. In addition, the influence of the performance of the major components on the system performance was investigated.

Loofah-based self-powered triboelectric nanogenerator-supercapacitor for an integrated self-charging energy system

New urbanization is ushering in a surge in construction and amplifying a substantial demand for urban road development, simultaneously spurring innovation and development of environmentally sustainable power sources. Triboelectric nanogenerator (TENG), a revolutionary technology of energy conversion, efficiently capturing high-entropy energy from the environment and offering the advantages of self-powered and immediacy. Recognizing the critical need to store the energy harvested by TENGs, we present an integrated energy conversion and storage system that combines a loofah-based self-powered rotating TENG (LS-TENG) with a supercapacitor. The maximum instantaneous output power and the corresponding instantaneous power density of the LS-TENG are 0.75mW and 202.69mW/m2 at 30rpm. The supercapacitor, featuring carbon nanotube (CNT) interdigitated electrodes created through microelectronic printing technology, utilizes polyacrylamide (PAM)-lithium chloride (LiCl) as a gel electrolyte (adhesion strength of 16.69 kPa). The supercapacitor is seamlessly integrated onto the back of the LS-TENG’s stator, which effectively simplified the energy conversion and storage system. At a current density of 0.01mA/cm2, the supercapacitor achieves a high volumetric capacitance of 341.47 mF/cm3, an energy density of 17.07mWh/cm3, and a power density of 257.07 mW/cm3, with a remarkable capacitance retention rate of 99.12% after 30000 cycles at a current density of 0.02mA/cm2. Furthermore, a concept demonstration of an integrated self-charging energy system is implemented, in which the supercapacitor can be charged at wind speed rate of 3.0m/s. The proposed integrated energy storage and conversion system makes it ideal for converting and storing wind energy.

Quasi Z source direct matrix converter based K- to three-phase wind energy conversion system using maximum constant boost current control modulation technique

The conversion system for wind energy has no restriction on the number of output phases. K numbers of output phases can be converted into standard grid-connected three-phase supply using a quasi-Z source direct matrix converter (QZSDMC). The obtained input supply may be five phases from the wind energy conversion system with continuously variable frequency as well as variable terminal voltages. Using the proposed QZSDMC converter with maximum constant boost current control modulation technique constant three-phase voltages as well as frequency can be maintained at the grid side. Additionally, the energy conversion system has high output voltage gain. The proposed converter as well as the modulation technique produces the maximum voltage transfer ratio of 1.05. The output voltage gain reached nearly 1.99 compared with the traditional power converters. The voltage THD and current THD are maintained within the acceptable limit of 5.3 and 3.6 respectively. The power factor have been maintained nearly unity throughout the all mode of operations. To stabilize the grid frequencies and grid voltages additional control blocks are used. This research article presents simulation results for the proposed QZSDMC converter with a maximum constant boost current control modulation technique. Also, the proposed scheme has been validated with suitable experimental results.

Wind energy and hydrogen production: a new approach for green and sustainable greenhouse agriculture in Morocco

In response to the critical current energy demands and the imperative transition to green and sustainable agriculture, this study introduces an innovative approach by integrating wind energy into greenhouse agriculture. The sites of Dakhla, Agadir, Essaouira, and Kenitra, known for their intensive agricultural activities, were selected for a comprehensive evaluation. Utilising the Weibull distribution, a detailed wind potential analysis was conducted. The study's novelty lies in its combined technico-economic and environmental analysis, applied to four commercial wind turbines ranging from 1 kW to 10 kW. The findings reveal that Dakhla and Essaouira possess significant wind potential, sufficient to meet the electricity demands of agricultural greenhouses either partially or entirely. Specifically, the power densities recorded were 150.03 W/m2 and 62.29 W/m2 for Dakhla and Essaouira, respectively. The areas covered were 2 919.59 m2 and 1 120.26 m2, with a payback period of 1 year for Dakhla and 4.66 years for Essaouira using the T4 turbine. Additionally, the study explores the potential of integrating a wind/hydrogen conversion system, tested on a 100 kW turbine, which produced 6 648 kg of hydrogen in Dakhla and 4 443 kg in Essaouira. This approach allows for varied hydrogen uses, supporting sustainable agriculture.

Multi-stage control design for oscillating water column-based ocean wave energy conversion system

Despite the enormous global potential of ocean wave energy, it has yet to achieve a level of maturity and economic competitiveness that would result in a substantial impact. Challenges include direct integration into weak or isolated microgrids, a high proportion of uncertain marine environments, nonlinear dynamics, oscillating water column (OWC) device limitations, slower response times, unplanned power outages, power fluctuations, high capital and operational costs in ocean wave energy conversion (OWEC) systems. To this end, a new independent multi-stage design approach is proposed for the performance enhancement of an OWC-based OWEC system. Firstly, an airflow and rotational speed optimal control stage enhances power capture in the Wells turbine-based OWC plant. Secondly, compared to conventional control, the proposed permanent magnet synchronous generator control incorporates an adaptive nonlinear back-stepping control algorithm based on Lyapunov stability theory. Thirdly, introducing reconfigurable control into the conventional six-leg power converter ensures the uninterrupted operation of an OWEC system. Lastly, a model-predictive control-based energy management system is integrated with a bidirectional DC-DC converter that delivers steady power from the grid-connected OWC OWEC system. Hence, MATLAB simulations ensure the overall performance enhancement and feasibility of the OWEC system application and verify that the proposed multi-stage solution is efficient, robust, and reliable.

Direct torque control of a dual star induction generator based on a modified space vector PWM under fault conditions

Recent studies have shown that electrical systems in wind power conversion are subject to a 67 % failure rate, and conventional three-phase generators are considered to be the most sensitive to these faults. Induction generator current harmonics are a major source of torque ripples causing acoustic noise and vibrations. These ripples can progressively increase under faulty operating conditions. In six-phase machines, there is appearance of high harmonic currents in the air gap as space harmonics. Power electronic converters are also subject to faults, the most common being Short-Circuit (SC) and Open-Circuit (OC) faults. SC faults cause large peaks in the line currents, which trigger the protection devices, resulting in a complete shutdown of the production system. OC faults, on the other hand, cause imbalances in the phases, but the system remains in operation.Direct Torque Control (DTC) based on Space Vector Modulation (SVM) at constant switching frequency is an effective solution to tackle induction generator current harmonics. This paper proposes a DTC combined with a Proportional Integral Fuzzy Logic Controller (PIFLC) optimized by Particle Swarm Optimization (PSO) in order to overcome the problems of torque ripples. Furthermore, using Vector Space Decomposition (VSD) and the Modified Space Vector Pulse Width Modulation (MSVPWM) strategy, a significant reduction of harmonics in the air-gap can be achieved.Simulations were carried out under MATLAB/Simulink, and the results obtained demonstrate the superiority of the proposed DTC-PIFLC-PSO controller in terms of robustness against wind speed variations and under faulty switch conditions in the power converter of the Dual Star Induction Generator (DSIG) generator. In addition, a comparative study with the classical PI controller is presented to show the effectiveness of the DTC-PIFLC-PSO controller against faults with a significant reduction in the Total Harmonic Distortion (THD) during both faulty and non-faulty conditions.

Streamlined fractionation for recovery of high-yield xylo-oligosaccharides, pure lignin and ethanol from poplar using short-chain organic acid/pentanol biphasic system

Biphasic pretreatment offers a sustainable method by integrating the fractionation of hemicellulose, lignin, and cellulose into a single process, thereby enhancing biomass resource utilization while reducing environmental impact. However, this process faces the challenge of diverse hemicellulose products with low added value. This study employed organic acid-catalyzed water/pentanol biphasic pretreatment to selectively convert hemicellulose into xylooligosaccharides (XOS), while simultaneously separating lignin and cellulose. Both the organic acids and pentanol used are biodegradable and compatible. The lactic acid (LA)/pentanol biphasic system was particularly effective for XOS production and lignin removal, attributed to the high acidity of LA and its relatively low partition coefficients in the water/pentanol system, crucial factors influencing hemicellulose and lignin separation efficiency. The XOS yields reached 46.9 %, while the lignin removal rate was 74.6 %. Additionally, LA/pentanol pretreatment significantly enhanced cellulose digestibility, demonstrated by an ethanol production of 54.1 g/L during simultaneous saccharification fermentation at 15 % solids loading. The recovered lignin from the organic phase retained the structural characteristics of native lignin. It also had a low molecular weight and abundant phenolic hydroxyl groups, indicating its suitability for further valorization. Pentanol maintained its performance after four cycles of reuse, demonstrating the stability and reusability of the solvent system. This study highlighted the potential of the LA/pentanol biphasic system for simultaneous hemicellulose conversion and lignin isolation, offering a simplified and sustainable one-step valorization route for biomass.

A control strategy of DC transmission system for offshore wind power based on hybrid converters

Abstract As the DC transmission system of modular multilevel converters for offshore wind power suffers problems like large volume, heavy weight, difficulty in platform transportation, and high cost, a DC transmission scheme for offshore wind power based on diode rectifier units and modular multilevel converters is put forth in the present work; Meanwhile, the features of active-power coordination, the DC harmonic current, and the AC harmonic current of the hybrid converter in this proposed scheme are analyzed to propose control strategies for active power coordination control, DC harmonic current suppression, and AC harmonic current suppression of the hybrid converter, respectively. The performance and feasibility of the proposed strategies are verified by testing the hardware in the loop real-time simulation system for transmission of offshore wind power through hybrid converters based on RTDS. It is found that the proposed strategies could improve the stability, flexibility, and reliability of the system.

Reducing neural network complexity via optimization algorithms for fault diagnosis in renewable energy systems

This article discusses the challenges involved in diagnosing faults in renewable energy systems. A significant challenge is the high computational demands of the artificial intelligence algorithms needed for grid-connected photovoltaic (GCPV) and wind energy conversion (WEC) systems in fault diagnosis. To address this issue, several methods are proposed to reduce computation time, minimize memory requirements, and improve efficiency. First, optimization algorithms such as the Salp Swarm Algorithm (SSA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), combined with machine learning classifiers for feature selection, are suggested to reduce computational time and memory space requirements. This approach notably decreases computation time but has a limited impact on memory space. Secondly, further reduction in memory space requirements is recommended by using the variogram method for data reduction. This method can leverage the outputs of preceding algorithms to optimize renewable energy systems, making their operations cost-effective and efficient. Finally, the outputs of the variogram are used to train neural network (NN), recurrent neural network (RNN), and long short-term memory (LSTM) classifiers to differentiate between various modes of operation in GCPV and WEC systems. Experimental results demonstrate the effectiveness and robustness of the proposed methods, showing that memory space can be reduced by 1.3 to 5.6 times and CPU time by 1.1 to 11 times while maintaining accuracy and improving efficiency compared to conventional algorithms.

Performance assessment of a Triple Coaxial-Cylinder Wave-Energy Converter (TCWEC)

We propose a novel Triple Coaxial-cylinder Wave-Energy Converter (TCWEC) system, as an evolution of the commonly deployed dual-coaxial cylinder WEC (DCWEC). TCWEC consists of one inner cylinder and two concentric outer cylinders, characterized by two coupled resonant frequencies, improving wave power absorption. A semi-analytical model, based on potential flow theory and matched eigenfunction expansions, is developed to analyze the 3-Degrees of Freedom (DOF) system. The viscous drag coefficients are determined by Computational Fluid Dynamics (CFD) simulations and employed as equivalent linear damping. Analysis of impact of the viscous flow-separation factor fvis on the capture width indicates that the higher energy-absorption capability of TCWEC is not merely attributed to a smaller fvis value, but rather a planned split of the outer cylinder in DCWEC design into two cylinders in TCWEC, so as to produce an effectively broader resonance property. Under identical sea conditions, it is found that, compared to DCWEC, the optimal capture width of TCWEC is increased by as much as 77% in regular waves. In irregular waves, the optimal capture width is increased up to 40% across the entire frequency range. These findings suggest that the energy absorption efficiency of TCWEC is promising and its potential for real-world applications.

Fault Diagnosis of Wind Turbine Blades with Continuous Wavelet Transform based Deep Learning Model Using Vibration Signal

Wind Turbines are the most crucial devices in wind energy conversion systems to increase energy generation efficiency from wind sources. Blade failure in wind turbines is due to the induced vibrations of change in ecological variables. It is necessary to periodically inspect the state of the wind turbine blades to enhance safety by decreasing downtime, lessening the likelihood of unplanned failures requiring extensive repair, and progressively increasing power generation with reduced logistical costs. The primary goal of the proposed research is to adopt a hybrid strategy that combines convolutional neural network models and continuous wavelet transform. The bump wavelet-based continuous wavelet transform with a convolutional neural network model is employed to classify the faulty wind turbine blades based on the extracted vibration signals of turbine blades. This approach distinguishes between different states of blade faults affecting wind turbine blades during operational phases. The research considers blade faults in the horizontal axis wind turbine, including blade bending, erosion, and the connection looseness between the hub and blade. The cross-validation and hold-out methods are used to validate the classification accuracy and are compared with other existing popular methods. The hold-out method has a better classification accuracy of 97.916%.

Organic Rankine Cycle System Design by Utilizing The Waste Heat of Internal Combustion Engine Based on Numerical Simulation

Abstract Most of the energy supply for today’s human activities still comes from fossil energy. Energy based on fossil fuels can cause an increase in greenhouse gas (GHG) emissions. Therefore, increasing the efficiency of energy conversion systems based on fossil fuels is necessary to mitigate pollutant emissions. The internal combustion engine (ICE) is one energy conversion machine that still consumes fossil energy to work in the transportation sector. Losses during internal combustion engine operation result in reduced engine thermal efficiency. Exhaust gas heat loss is one of the relatively significant losses. It leads to the waste of heat, which could be utilized and converted into valuable energy in the form of electrical energy that the engine can use, resulting in a considerable amount of primary fuel that could be saved. An organic Rankine cycle (ORC) system is considered in this analysis as a heat recovery unit from the Diesel ICE. The Aspen Plus simulation software was chosen to design the system consisting of an ORC unit integrated with a Diesel ICE unit. The working fluid for ORC used in this analysis is R-141B, R-123, and R-245fa. The simulation results show that the heat the ORC unit receives from the ICE via turbocharger is around 366 °C. Thus, the system has a thermal efficiency of 11.11% when using R-141B as the working fluid, 8.41% if R-123 as the working fluid, and 6.63% when using R-245fa as the working fluid. This study also obtained a condenser design as part of the ORC unit. The condenser can be considered a plate heat exchanger, with 53 plates needed to support the process.

Exploring The Potentials and Drawbacks of Hysteresis Current Controller For SRM: A Case Study Of Wind Energy Conversion System

Switched Reluctance Machines (SRMs) have drawn interest in renewable energy systems because of their special qualities and applicability. This study examines the idea of hysteresis current regulation in a wind energy conversion system with a Switched Reluctance Generator (SRG). The system is modeled in MATLAB/SIMULINK. The model is simulated and analyzed to ascertain the system’s benefits and shortcomings, focusing on reducing torque ripples in SRG. Considering most classical controllers are complicated to construct, the hysteresis current control is straightforward and effective. However, this controller's two primary shortcomings are that it produces a variable switching frequency and increases current ripples at a steady state, both enhancing acoustic noise in SRM. Lastly, the report suggests that improving controller performance should be the primary emphasis of future research in this field.

Study on the dynamic characteristics and control strategies of the coupled system of the FHR and SCO2 cycle

The supercritical carbon dioxide (SCO2) Brayton cycle has high efficiency, compactness, and rapid response. Furthermore, the fluoride-salt-cooled high-temperature reactor (FHR), as a Generation IV nuclear reactor, is characterized by compactness, high temperature, and inherent safety. Therefore, the SCO2 cycle as the energy conversion system of the FHR can meet the requirements of modularity and compactness. However, the interaction characteristics between the FHR and SCO2 cycle are unknown, and the system control strategies that can guarantee the safety and flexibility of the coupled system need to be explored. In this study, a dynamic simulation model of the coupled system of the FHR and SCO2 cycle is established. Considering the complexity of the system, the dynamic characteristics of the FHR and SCO2 cycle are investigated separately. Then, the FHR and SCO2 cycle is coupled, and the interaction characteristics between the FHR and SCO2 cycle are further analyzed. It is shown that the coupled system is more flexible under SCO2 mass flow rate disturbance than under FHR reactivity disturbance. Based on that, various SCO2 mass flow rate control strategies are designed and investigated. Among them, the turbine bypass control strategy is the fastest, and system parameters are the most stable.

A New Stochastic Controller for Efficient Power Extraction from Small-Scale Wind Energy Conversion Systems under Random Load Consumption

This paper presents an innovative scheme to enhance the efficiency of power extraction from wind energy conversion systems (WECSs) under random loads. The study investigates how stochastic load consumption, modeled and predicted using a Markov chain process, impacts WECS efficiency. The suggested approach regulates the rectifier voltage rather than the rotor speed, making it a sensorless and reliable method for small-scale WECSs. Nonlinear WECS dynamics are represented using Takagi–Sugeno (TS) fuzzy modeling. Furthermore, the closed-loop system’s stochastic stability and recursive feasibility are guaranteed regardless of random load changes. The performance of the suggested controller is compared with the traditional perturb-and-observe (P&O) algorithm under varying wind speeds and random load variations. Simulation results show that the proposed approach outperforms the traditional P&O algorithm, demonstrating higher tracking efficiency, rapid convergence to the maximum power point (MPP), reduced steady-state oscillations, and lower error indices. Enhancing WECS efficiency under unpredictable load conditions is the primary contribution, with simulation results indicating that the tracking efficiency increases to 99.93%.