Variable Wind Research Articles

Control of a Doubly Fed Induction Generator for Variable Speed Wind Energy Conversion Systems using Fuzzy Controllers optimized with a Genetic Algorithm

This paper presents a comprehensive study of a wind turbine system operating under variable wind conditions, utilizing a Doubly Fed Induction Generator (DFIG) connected to the grid. The DFIG is controlled via a rotor-side transducer, allowing for independent regulation of the conductors to manage both active and reactive power flows effectively. The control strategy focuses on generating reference voltages for the rotor to ensure that active and reactive power align with the desired targets, optimizing the tracking of the maximum power point to maximize electrical output. The research analyzes the system's dynamic performance under fluctuating wind conditions, emphasizing control strategies for managing active and reactive energy. A notable innovation is the integration of fuzzy logic and genetic algorithm into the control strategy for the wind turbine's switching mechanism, which enhances system performance and efficiency. Simulation results demonstrate that this approach provides higher efficiency, improved performance, and greater stability compared to the traditional Proportional-Integral (PI) controllers. Advanced artificial intelligence methods, such as fuzzy genetic algorithm control, were employed and the proposed system's effectiveness was validated with Matlab/Simulink simulations.

Changes in Equatorial Kelvin Wave Activity in the Upper Troposphere and Lower Stratosphere Associated with Interannual Variability of the Upper-Tropospheric Equatorial Zonal Wind

Abstract We investigate the influence of the background wind regime on interannual variability in equatorial Kelvin waves (including both freely propagating ones and convectively coupled ones) in the upper troposphere and lower stratosphere using the ERA5 reanalysis data. We focus on variability in the number of Kelvin wave cases as a function of the background westerly wind that controls wave propagation, given by the zonal wind index (ZWI) in the equatorial eastern Pacific that is a measure of the strength of the upper branch of the Walker circulation in the Western Hemisphere. The ZWI correlates well with sea surface temperature in the Niño-3.4 region, though one-third of the peaks of negative ZWI (weak westerly) cases occur during seasons other than December–February which is the typical El Niño season. In the positive ZWI (stronger westerly) cases, both the convective activity over the western Pacific and the extratropical Rossby wave activity over the central and eastern Pacific are enhanced. Kelvin waves over the Western Hemisphere appear frequently at 200 hPa but barely reach 100 hPa due to the strong westerly wind below this level that prohibits upward wave propagation. In the negative ZWI period, the number of Kelvin wave cases at 200 hPa decreases due to weaker convection; Kelvin waves reach 100 hPa and propagate even further upward into the stratosphere. The increasing (decreasing) tendency of Kelvin waves already starts 6 months before the weakest (strongest) westerly wind month in the Western Hemisphere (i.e., the ENSO peak seasons). Significance Statement Equatorial Kelvin waves play a critical role in the upward transport of momentum driving the equatorial stratospheric circulation. Our results reveal that background winds in the upper troposphere and the lower stratosphere act as a filter for equatorial Kelvin waves, regulating the number of their packets propagating upward. An investigation of the role of Kelvin wave dissipation in the westerly duct region, i.e., in the upper troposphere over the equatorial eastern Pacific, is needed.

Techno-economic dataset for energy market and capacity payment co-optimization in the Dominican Republic's power market.

The electric power industry has an impact on fossil fuel consumption, which must be considered in decarbonization strategies. Energy systems optimization modelling can be applied to evaluate policy scenarios in the power sector to accelerate energy transitions. These modelling tools need data to simulate different scenarios in the power system to clarify the design of energy policies. For this reason, collecting and processing technical and economic data is needed to guarantee quality input for the modelling tools. This article presents a dataset for an optimization model of the generation mix and the energy demand in the power system of the Dominican Republic to determine the capacity value of variable renewable energy (VRE), i.e., wind and solar, that can serve as an incentive for these technologies. While the data corresponds to the Dominican Republic's power system, the method of collecting and processing data can be implemented in other countries. The data collected is an open-access database of the independent system operator, the power sector regulator, and utilities, as well as websites and databases of international organizations.

Maximizing Wind Turbine Power Generation Through Adaptive Fuzzy Logic Control for Optimal Efficiency and Performance

Wind power output fluctuations, driven by variable wind speeds, create significant challenges for grid stability and the efficient use of wind turbines, particularly in high-wind-penetration areas. This study proposes a combined approach utilizing an ultra-capacitor energy storage system and fuzzy-control-based pitch angle adjustment to address these challenges. The fuzzy control system dynamically responds to wind speed variations, optimizing energy capture while minimizing mechanical stress on turbine components, and the ultra-capacitor provides instantaneous buffering of power surpluses and deficits. Simulations conducted on a 50 kW DFIG wind turbine powering a 23 kW load demonstrated a substantial reduction in power fluctuations by a factor of 3.747, decreasing the power fluctuation reduction scale from 13.04% to 3.48%. These results highlight the effectiveness of the proposed system in improving the stability, reliability, and quality of wind energy, thereby advancing the broader adoption of renewable energy and contributing to sustainable energy solutions.

Climatology of waterspouts in Mexico and numerical modeling of a particular case

Abstract Numerous waterspout events occur practically in all Mexican waters. The principal aim was to carry out a climatology of these events. A data compilation allowed the identification of 103 cases from 2010-2022. A Szilagyi waterspout nomogram was constructed to explain the formation mechanism using the ERA5 reanalysis data. The nomogram classified waterspout events according to their origin using thermodynamic parameters. The results revealed that the thermodynamics of some waterspouts in Mexico do not fit the current definition of the Szilagyi nomogram. Most waterspouts are thunderstorm-related and fit the nomogram. A minority that arises from land breezes and upper-low conditions also fit. A relevant case, which occurred in an area with a recurrent incidence of waterspouts, allowed observation of relevant dynamic properties, such as its strength, occurred on August 8, 2019, in Coatzacoalcos, Veracruz. The documented waterspout trajectory revealed that it moved through the sea and city. The Weather Research and Forecasting (WRF) model was used for modeling this event at a resolution of 250 m. The results showed the instability, a cyclonic disturbance (misocyclone) that caused the waterspout. The analysis showed the behavior of meteorological variables, such as temperature, humidity, wind, vorticity, and unstable atmospheric variables during the storm.

Self‐Powered System by an Aerodynamic‐Complementary Triboelectric‐Electromagnetic Hybridized Generator with Triple‐Mode Switching Power Management Topology for Wide‐Range Wind Energy Collection and Climate Monitoring

AbstractRotary wind energy harvester has always been the focus of attention in the field of self‐power technology. However, a conflict between start‐up and saturation rotation speed of wind energy harvester hinders the adaptive energy collection from low to strong wind speeds in different wind speed ranges. Herein, a self‐powered system by an aerodynamic‐complementary triboelectric‐electromagnetic hybridized generator (AC‐TEHG) equipped with a triple‐mode switching power management topology (TmSPMT) is proposed to achieve self‐adaptive power supply mode switching in response to different wind speed ranges. Specifically, AC‐TEHG integrates Savonius and wind cup miniaturized turbine to achieve layered energy collection over wide‐range wind speed regions (1.4–16.3 m s−1), where the triboelectric nanogenerator (TENG) and electromagnetic generator (EMG) units have the excellent electrical output with Voc, Isc, and instantaneous peak power reaching 664 V/10.83 V, 35.96 µA/19.84 mA and 8.01 mW/62.45 mW, respectively. AC‐TEHG equipped with TmSPMT can effectively respond to different wind speed ranges of windlessness, low, medium, and high wind speeds for steadily powering commercial electronics. Finally, a wireless self‐powered climate monitoring system is developed to indicate that AC‐TEHG equipped with TmSPMT is a sustainable solution to efficiently power Internet of Things sensors in regions with variable wind speeds.

Mathematical modeling for detecting variable gear tooth cracks in a windturbine gearbox operating under a ramp-up wind speed

Abstract Wind is natural and possess renewable energy. This energy is an opportunity when fossil fuel is shrinking very fast and creating heavy ecological imbalance. Wind energy (WE) is an input to wind turbine (WT) system that produces electricity. Therefore, knowledge of wind is a prerequisite for the dynamic modelling of wind turbine drivetrain system (WTDS) in case of defective gear drives. Wind speed is not certain and its ramp-up component can be very detrimental in poor occasions. Input torque to drivetrain system is modelled based on ramp-up wind speed for the diagnosis under healthy and defective WTDS. Lumped parameter model simplifies the mathematical model of gearbox and the Lagrange’s formulation gives insights to derive the equation of motion of the system. Time varying mesh stiffness (TVMS) computed at mean speed is interpolated in MatLab to get the same at ramp-up condition. The interpolated stiffness is incorporated in the mathematical formulation for both healthy and defective system. Numerical discretization of differential equation is done in MatLab using Houbolt method to produce the dynamic responses of WTDS with gear defects under ramp-up speed. Here, time frequency (TF) domain analysis is explored to perform dynamic analysis. Hence, short time Fourier transforms (STFT) is applied to low pass filtered signal; wavelet packet transform is helpful in filtering process. The signal processing technique is proposed to investigate the defective WTDS under variable wind speed. This can be helpful in future investigations in WT under more real situations.

Pumped hydro energy storage to support 100% renewable energy

Abstract The rapidly growing scale of solar photovoltaics and wind energy coupled with electrification of transport, heating and industry offers an affordable pathway for achieving deep decarbonization. Massive integration of variable solar photovoltaics and wind energy requires large-scale adoption of short (seconds-hours) and long (hours-days) duration energy storage. Currently, long-duration pumped hydro energy storage (PHES) accounts for about 95% of global energy storage for the electricity sector. This paper discusses the Global PHES Atlases developed by the Australian National University which identify 0.8 million off-river (closed-loop) PHES sites with a combined 86 million Gigawatt-hours of storage potential, which is about 3 years of current global electricity production. These Atlases show that most global jurisdictions have vast potential for low-cost PHES with small water and land requirements, and that do not require new dams on rivers. The low capital cost of premium PHES systems ($ per kilowatt-hour) is pointed out. Methods for creating shortlists of promising PHES sites from the Atlases for detailed investigation are developed.

Revealing an unexpectedly low electron injection threshold via reinforced shock acceleration

Collisionless shock waves, found in supernova remnants, interstellar, stellar, and planetary environments, and laboratories, are one of nature’s most powerful particle accelerators. This study combines in situ satellite measurements with recent theoretical developments to establish a reinforced shock acceleration model for relativistic electrons. Our model incorporates transient structures, wave-particle interactions, and variable stellar wind conditions, operating collectively in a multiscale set of processes. We show that the electron injection threshold is on the order of suprathermal range, obtainable through multiple different phenomena abundant in various plasma environments. Our analysis demonstrates that a typical shock can consistently accelerate electrons into very high (relativistic) energy ranges, refining our comprehension of shock acceleration while providing insight on the origin of electron cosmic rays.

The JAGUAR-DAS whole neutral atmosphere reanalysis: JAWARA

Using the Japanese Atmospheric General circulation model for the Upper Atmosphere Research-Data Assimilation System (JAGUAR-DAS), a whole neutral atmosphere reanalysis dataset (JAWARA) over about 19 years from September 2004 to December 2023 is produced. JAWARA is the first long-period reanalysis covering the height region from the surface to the lower thermosphere (~ 110 km). This wide height coverage is a notable advantage over other operational reanalysis datasets, which cover up to the middle mesosphere. Key dynamical characteristics are compared between JAWARA and two satellite observations and three other operational reanalysis datasets in their covered height regions. The seasonal variations of zonal mean temperature and zonal wind are similar between JAWARA and the datasets used for comparison. The climatologies of zonal mean temperature, zonal wind, residual-mean circulation, and E-P flux in the meridional cross section are also broadly consistent with other reanalysis datasets. The analyzed residual-mean vertical flow in the northern high latitudes in the middle atmosphere exhibits the well-known patterns of upwelling in summer and downwelling in winter. JAWARA also shows a prominent feature of strong downward propagating anomalies from the lower thermosphere to the upper stratosphere after sudden stratospheric warmings. This analysis takes full advantage of the JAWARA data, which cannot be made using satellite observations and other reanalysis datasets. This reanalysis product is expected to contribute broadly to future research on the characteristics of observed mesospheric phenomena, thermosphere–ionosphere coupling, space weather, and improvement of middle atmospheric meteorological systems, including their interannual and decadal scale variability.

Comparing Two Samples of Circular Data Using Watson's Test

The investigation focuses on the spatial differences in wind directions: a comparison of circular wind data from two locations over a period of 30 days. Utilizing Watson's U² test, this non-parametric approach to circular data, questions whether directional variations occur between the two sites in a significant way. Initial exploratory data visualization with polar plots does suggest distinct wind patterns at each site: the first location is marked with a broad distribution of wind directions, whereas the second location exhibits clustering within certain angular ranges. Visual differences on these plots point to unique directional characteristics between sites, thus warranting further rigorous statistical analysis. The U² test statistic is then computed and compared with critical values to determine significance. This approach provides much more solid justification than simply observing spatial differences in wind pattern by eye alone. Results From the results, it is seen that there exists significant spatial variation in wind directionality between the two locations, hence a practical extension. Hazard assessment in meteorology stands to benefit from this result in adding value to existing weather forecast models. For environmental planning, especially in areas where wind direction affects dispersion, having accurate wind data will improve the accuracy in such planning. Understanding the details of localized wind patterns can also add benefit to the wind power industry because knowledge of such information informs about the best placement of turbines, site selection, and energy-capture strategies. The methodology used in this research study will allow the identification and analysis of spatial wind variations through Watson's U² test on circular data, thereby contributing to better decision-making in environmental, meteorological, and energy-related areas.

Spatiotemporal Variability of Saturn's Zonal Winds Observed by Cassini

AbstractThe strong zonal winds on giant planets are among the most interesting phenomena in our solar system. Observations recorded by the Composite Infrared Spectrometer (CIRS), the Imaging Science Subsystem (ISS), and the Visual and Infrared Mapping Spectrometer (VIMS) on the Cassini spacecraft are utilized to investigate spatiotemporal variations in Saturn's zonal winds. A general thermal wind equation works for investigating the vertical structure of zonal winds at all latitudes, but it has integration gaps near the equator caused by the cylindrical integration path. Here, we develop an algorithm to address this limitation, which is validated by the observed zonal winds. The algorithm is combined with the CIRS‐retrieved temperature and the ISS‐measured winds to generate a complete picture of the vertical structure of Saturn's zonal winds for the upper troposphere (i.e., 50–500 mbar), which suggests that the equatorial zonal winds have complicated vertical structures. The zonal winds from 10°S to 10°N initially decrease with altitude and then increase. Additionally, the intense narrow equatorial jet between 3°S and 3°N widens with altitude. The zonal winds are further used to examine the atmospheric stability, which implies some unstable regions. Finally, the analysis of Cassini multi‐instrument observations reveals different temporal behaviors of zonal winds in the vertical direction, which suggests that seasonally varying solar flux is one of the drivers of temporal variations in zonal winds.

On the potential role of flexible Norwegian hydropower in managing challenging renewable energy variability events in Europe

Abstract Previous research has identified flexible Norwegian hydropower as one potential key resource for managing variations in wind and solar power in Northern Europe. There is, however, a need for further detailed examination of this potential role of Norwegian hydropower based on updated future scenarios and using the latest data and model tools available. We analyze potential power system impacts of expanding Norwegian hydropower flexibility and Norway-Europe transmission, considering renewable energy variability based on a simulation for the historical weather years 1991-2020. The simulations are performed using FanSi, a stochastic optimization model for analyzing large-scale power systems with significant shares of hydropower combined with high shares of wind/solar power. A year 2050 scenario for Europe from the integrated energy system model SCOPE SD is used as framework for our analysis with FanSi. Our results highlight how expanded hydropower and transmission can potentially reduce price spikes during periods of low wind/solar output, reduce wind/solar energy curtailment during periods of high wind/solar output; and reduce price differences between interconnected areas during periods of either low or high wind/solar output. We demonstrate that these effects are attributable to more dynamic operation and expanded operational ranges of hydropower and transmission in the simulations assuming expanded hydropower and transmission capacities. We acknowledge high fundamental uncertainty in modelling a future system for the year 2050.

Low Cloud–SST Variability over the Summertime Subtropical Northeast Pacific: Role of Extratropical Atmospheric Modes

Abstract Over the subtropical Northeast Pacific (NEP), highly reflective low clouds interact with underlying sea surface temperature (SST) to constitute a local positive feedback. Recent modeling studies showed that, together with wind–evaporation–SST (WES) feedback, the summertime low cloud–SST feedback promotes nonlocal trade wind variations, modulating subsequent evolution of El Niño–Southern Oscillation (ENSO). This study aims to identify drivers of summertime low-cloud variations, using satellite observations and global atmosphere model simulations forced with observed SST. A transbasin teleconnection is identified, where the north tropical Atlantic (NTA) warming induced by the North Atlantic Oscillation (NAO) increases precipitation, exciting warm Rossby waves that extend into the NEP. The resultant enhancement of static stability promotes summertime low cloud–SST variability. By regressing out the effects of the preceding ENSO and NTA SST, atmospheric internal variability over the extratropical North Pacific, including the North Pacific Oscillation (NPO), is found to drive the NEP cooling by latent heat loss and subsequent summer low cloud–SST variability. With the help of the background trade winds and WES feedback, the SST anomalies extend southwestward from the low-cloud region, accompanied by ENSO in the following winter. This suggests the nonlocal effects of low clouds identified by recent studies. Analysis of a 500-yr climate model simulation corroborates the NTA and NPO forcing of NEP low cloud–SST variability and subsequent ENSO.

Wind‐Driven Variability in the Prereversal Enhancement of the Equatorial Vertical Plasma Drift: Climatologies Observed by ICON

AbstractThe prereversal enhancement (PRE) is a brief surge in upward plasma velocity in the evening equatorial ionosphere and a driver of equatorial spread‐F. This study reports the first PRE climatology from Ionospheric Connection Explorer (ICON) data, exhibiting seasonal and longitudinal variability that is qualitatively consistent with results from two previous satellite missions. Previous missions, however, lacked the neutral wind observations to characterize their impact on the PRE. To quantitatively assess wind impacts, numerical experiments are performed with a standalone dynamo solver using winds from the TIEGCM‐ICON, which is driven from below by observed tides. To quantify the impact of solar/magnetic geometry, such as the alignment between the solar terminator and the magnetic meridian, the model was first driven with seasonally and longitudinally averaged winds (which includes seasonally averaged zonal‐mean winds and migrating tides). This reproduces the observed PRE variability with a correlation of 0.44. Incorporating longitudinally and seasonally varying wind patterns improves the correlation to 0.68. This suggests that climatological wind variability is an important driver of PRE variability, but future work is needed to account for the missing variability. Potential missing drivers include conductivity variability near the terminator and mesoscale wind features such as the solar terminator wave.

The Observed and Simulated Evolution of a Microburst Using X‐Band Phased‐Array Radar Data Assimilation With EnKF

AbstractA microburst is a severe small‐scale meteorological event that develops rapidly, producing intense downdrafts that result in catastrophic divergent winds near the ground. The fine‐scale structure and evolution of real‐case microbursts are rarely analyzed due to the limitation of regular observational platforms and the computational capacity for numerical simulations. On 12 September 2020, a microburst was effectively captured by China's S‐band operational weather radar network and an X‐band polarimetric phased‐array radar (XPAR). XPAR observations can identify precursor signatures of the rapidly evolving microburst before the occurrence of surface wind disasters, demonstrating superior spatiotemporal resolution in monitoring compared to the S‐band radars. To disclose the evolution of small‐scale structure and the underlying physical processes, this study utilizes the Weather Research and Forecasting (WRF) model and the ensemble Kalman filter (EnKF) system to assimilate XPAR data. The simulation successfully reproduces the fine‐scale structure and evolution of the microburst with a misocyclone. The analysis indicates that the microburst's downdraft is primarily triggered by the middle‐level hydrometeor loading. The misocyclone generates a downward‐directed perturbation pressure gradient then accelerates the microburst's downdraft toward the surface. This study is the first observation and simulation of a real‐case microburst using the WRF‐EnKF system assimilating XPAR data. The investigation of the impact of misocyclone on the microburst enhances our understanding of microbursts' forcing mechanism.

Spatiotemporal dynamics of the oropharyngeal microbiome in a cohort of Ivorian school children

The respiratory tract harbours microorganisms of the normal host microbiota which are also capable of causing invasive disease. Among these, Neisseria meningitidis a commensal bacterium of the oropharynx can cause meningitis, a disease with epidemic potential. The oral microbiome plays a crucial role in maintaining respiratory health. An imbalance in its composition is associated with increased risk of invasive disease. The main objective of this study was to evaluate changes in the spatio-temporal dynamics of the oropharyngeal microbiota considering meningococcal carriage in a cohort of 8–12-year-old school children within (Korhogo) and outside (Abidjan) of the meningitis belt of Côte d’Ivoire. A significant geographic difference in the oropharyngeal microbiome was identified between the two study sites in terms of bacterial abundance and diversity (p < 0.001), with greater diversity in children in Abidjan than in Korhogo. Meningococcal carriage was low in the cohort with eight Neisseria carriers identified in Korhogo (3.64%) including one Neisseria meningitidis (0.45%). No Neisseria were detected in Abidjan indicating geographical differences in carriage (p = 0.006). Negative correlations were also found between Neisseria abundance and humidity. Meningococcal carriage was very low during the study; however, Neisseria carriage differed between the two study areas, with a higher frequency in children in Korhogo. Analysis of the oropharyngeal microbiome showed significant differences between children followed in Abidjan and Korhogo with higher microbial diversity in Abidjan, which is generally associated with better health status. Significant correlations between Neisseria or other pathogens carriage and climatic variables (Temperature, Relative humidity, and Wind speed) were also demonstrated, indicating an important role of climate in the carriage of these bacteria; an important element to note in the current context of climate change.

Fractional order control of Wind Energy Conversion System based on DFIG

The paper deals with the elaboration of a robust and efficient decoupled active and reactive powers control algorithm of double-fed induction generator (DFIG) using fractional order control based on proportional and integral controllers. First, the models of wind turbine and electrical generator are established, as well as a decoupled active and reactive powers control of DFIG. Second, the used fractional order controllers are designed using an analytical design method based on frequency domain specifications, namely phase margin, robustness to gain variations and gain limitation at the crossover frequency. Third, to evaluate the fractional order controller control performances, simulation results are presented and discussed for all the operating region of the WECS. Then, simulation results are presented and interpreted considering a variable wind speed in order to reach all the operating regions of the WECS. Finally, a conclusion is given in the light of the obtained results.

Observations of Estuarine Salt Intrusion Dynamics During a Prolonged Drought Event in the Rhine‐Meuse Delta

AbstractSalt intrusion poses a global threat to estuaries and deltas, exacerbated by climate change, drought, and sea level rise. This observational study investigates the impact of river discharge, wind, and tidal variations on salt intrusion in a branching river delta during drought. The complexity and spatial extent of deltas make comprehensive measurements challenging and rare. In this paper, we present a 17‐week data set of a historic drought in the Rhine‐Meuse Delta, capturing dynamics in a multiple‐channel system in a wide range of conditions. Key characteristics of this low‐lying delta are its branching channel network and complicated, human‐controlled discharge. Despite the system's complexity, we found that the subtidal salt intrusion length, defined by the 2 PSU isohaline , follows a power law relationship with Rhine River discharge . Subtidal water level variations contribute to short‐term variations in intrusion length, shifting the limit of salt intrusion upstream and downstream with a distance similar to the tidal excursion length. This can be attributed to the up‐estuary transport of seawater, caused by the estuary adjusting to variations in water levels at its mouth. However, spring‐neap variation in the tidal range does not alter the subtidal salt intrusion length. Side branches exhibit distinct dynamics from the main river, and their most important control is the downstream salinity. We show that treating the side branches separately is crucial to incorporate the highly variable downstream boundary condition, and may apply in other deltas or complex estuaries.

Simulation of Doubly Fed Induction generator (DFIG) for Steady state analysis when connected to a wind farm for power system stability

In this paper, a 2MW variable speed, pitch-regulated Doubly-fed Induction Generator (DFIG) with a speed range of 800-2000 rpm was studied for steady-state analysis. The DFIG was modelled in the Matlab/Simulink environment. The rotor-side converter utilized closed-loop stator flux-oriented vector control for managing the DFIG model. This method allows for rapid control and experimenting of grid-connected, variable speed DFIG wind turbines to examine their steady-state and energetic characteristics beneath ordinary and disturbed wind conditions when connected to a wind farm. The steady-state behavior of the wind turbine generator was derived at two different magnetizing levels: one with the reactive power of the stator equal to zero (Qs = 0), and the other with the direct current of the rotor equal to zero (Idr = 0). Simulation results show that the machine has higher efficiency when magnetized through the stator as compared with magnetization of the machine through the rotor. To come out with the DFIG transitory stability simulation results traditional controllers' for active and reactive power were compared with an adaptive adaptive tracking, self-tuned feedforward proportional integral regulating model for peak performance. Additionally, stability and instability were studied by solving the Swing equation using the Runge-Kutta method of order four. In a steady-state condition for the generator, the acceleration torque (Ta) reaches zero, which signifies that the mechanical torque (Tm) matches the electrical torque (Te). In the stability investigation, Tm is assumed to be constant. The findings provide valuable insights into the control strategies required for enhancing the reliability and efficiency of wind turbines in variable wind conditions.