Wind Model Research Articles

Stochastic economic sizing and placement of renewable integrated energy system with combined hydrogen and power technology in the active distribution network.

The current study concentrates on the planning (sitting and sizing) of a renewable integrated energy system that incorporates power-to-hydrogen (P2H) and hydrogen-to-power (H2P) technologies within an active distribution network. This is expressed in the form of an optimization model, in which the objective function is to reduce the annual costs of construction and maintenance of integrated energy systems. The model takes into account the planning and operation model of wind, solar, and bio-waste resources, as well as hydrogen storage (a combination of P2H, H2P, and hydrogen tank), and the optimal power flow constraints of the distribution network. Electrical and hydrogen energy are administered in an integrated energy system. The modeling of the uncertainties regarding the quantity of load and renewable resources is achieved through stochastic optimization using the Unscented Transformation method. The novelties of the scheme include the sizing and placement of a combined hydrogen and power-based renewable integrated energy system, the consideration of the impacts of bio-waste units, P2H, and H2P systems on the planning of the integrated energy system and the operation of the active distribution network, and the modeling of uncertainties using the Unscented Transformation method to reduce the calculation time. The study's results demonstrate the scheme's ability to improve the technical conditions of the distribution network by considering the optimal planning of integrated energy systems. In comparison to the network power flow, the operation status of the network has been improved by approximately 23-45% through the optimal siting, sizing, and energy management of hydrogen storage equipment, as well as renewable resources in the form of integrated energy systems. In other words, optimal energy management and planning of the integrated energy systems in the distribution network has been able to reduce energy losses and voltage drop by 44.5% and 42.4% compared to the load flow studies. In this situation, peak load carrying capability has increased by about 23.7%. In addition, compared to the case of the network with renewable resources, the overvoltage has decreased by about 43.5%. Also, Unscented Transformation method has a lower calculation time than scenario-based stochastic optimization.

Investigation of morphodynamic response to the storm-induced currents and waves in the Bay of Bengal

Storm surges, driven by Tropical Cyclones (TCs), pose a threat to the coastal areas of the Bay of Bengal (BoB), causing sediment transport and beach erosion. This study introduces a coupled hydrodynamic (TELEMAC-2D) -wave (TOMAWAC) -morphodynamic (GAIA) model to investigate morphodynamic changes during storm surges. The cyclonic wind is crucial for precisely predicting storm surges, wind waves, and morphodynamic bed evolution. Thus, this study introduced a modified parametric wind model to enhance wind field representation near and far from the cyclone center. The simulated storm surges and wind waves were validated against in-situ observations for TC Hudhud (2014) and TC Varadah (2016), and the simulated morphodynamic bed evolution was validated with field-measured data collected for TC Nivar (2020). Further, this study evaluates the performance of different bed load transport formulations for predicting morphodynamic bed evolution during TC Nivar (2020) under storm-induced currents and waves. Results indicate that the Engelund-Hansen model is most effective for currents alone, while the Bijker model excels for combined currents and waves along the open coast of BoB. The results also indicate that the incorporation of the effect of waves along with currents has enhanced the predictive capability of the coupled model framework.

Modelling of wind and solar power output uncertainty in power systems based on historical data: A characterisation through deterministic parameters

Modelling of wind and solar power output uncertainty in power systems based on historical data: A characterisation through deterministic parameters

New Rankine Vortex Models Developed Based on SMAP Measurements

Abstract The L-band passive microwave radiometer on board the NASA Soil Moisture Active Passive (SMAP) satellite can measure brightness temperature to retrieve sea surface wind speed under tropical cyclone (TC) conditions without being affected by rainfall or signal saturation caused by high wind speeds. Based on this advantage, this paper used the SMAP wind products for parameterizing the key decay exponent α of the Rankine vortex model (a traditional parametric model of the TC wind field) and finally developed new Rankine models. The SMAP dataset included 67 TC cases. Through data statistics, we examined the relationship between α and the maximum wind speed Um, the relationship between α and the radius of maximum wind speed (Rm), and the relationship between Rm and the averaged radius of 17 m s−1 (R17). Results showed that the three relationships were both positive correlations, indicating that α can be parameterized in three empirical ways. The first way is to calculate solely with Um. The second way is to calculate solely with Rm. The third way is to calculate Um and Rm together. The three ways correspond to three new models: the SMAP Rankine Model-1 (SRM-1), the SMAP Rankine Model-2 (SRM-2), and the SMAP Rankine Model-3 (SRM-3). Finally, comparisons were made between the new models and three existing Rankine models, according to the model simulations and the Advanced Microwave Scanning Radiometer 2 measurements of 49 TC cases. Results showed that the SRM-3 performed best overall. Significance Statement Ocean surface wind fields are important driving factors for numerical models to guide evolution forecasting and risk assessment of tropical cyclones. The purpose of this study is to utilize the SMAP products to modify the traditional Rankine vortex model for tropical cyclone surface wind field estimation. Rankine decay exponent was found between 0.3 and 0.9 and positively dependent upon maximum wind speed and its radius. Based on these characteristics, the proposed new Rankine models could calculate the decay exponent and further the TC surface wind field symmetrically with high accuracy, simply using maximum wind and its radius. This paper shows a practical use of SMAP measurements on TC wind field monitoring, analyzing, and modeling.

Generalized, Three-Dimensional Wind Tunnel Wall Correction Using Nonlinear Least-Squares Optimization

A novel three-dimensional technique for correcting wind tunnel measurements for wall interference has been developed. The flow around the test body and its wake is approximated as a series of inviscid singularities, while the wind tunnel walls and model support are approximated using a panel method. A nonlinear least-squares approach with trust-region reflective optimization is then used to obtain the strength and locations of singularities together with the domain boundary panel strengths by fitting to measured wall pressures. The technique is demonstrated using computational fluid dynamics for the test case of a well-documented slender delta wing body with high blockage and validated against both experiments and legacy data. The nonlinear least-squares wall correction method is shown to demonstrate a significant improvement in wall corrections compared to the classical two-variable technique.

Magnetized Winds of M-type Stars and Star–Planet Magnetic Interactions: Uncertainties and Modeling Strategy

M-type stars are the most common stars in the Universe. They are ideal hosts for the search of exoplanets in the habitable zone (HZ), as their small size and low temperature make the HZ much closer-in than their solar twins. Harboring very deep convective layers, they also usually exhibit very intense magnetic fields. Understanding their environment, in particular their coronal and wind properties, is thus very important, as they might be very different from what is observed in the solar system. The mass-loss rate of M-type stars is poorly known observationally, and recent attempts to estimate it for some of them (e.g., TRAPPIST-1 and Proxima Centauri) can vary by an order of magnitude. In this work, we revisit the stellar wind properties of M dwarfs in the light of the latest estimates of Ṁ through Lyα absorption at the astropause and slingshot prominences. We outline a modeling strategy to estimate the mass-loss rate, radiative loss, and wind speed, with uncertainties, based on an Alfvén-wave-driven stellar wind model. We find that it is very likely that several TRAPPIST-1 planets lie within the Alfvén surface, which implies that these planets experience star–planet magnetic interactions (SPMIs). We also find that SPMIs between Proxima Cen b and its host star could be the reason for recently observed radio emissions.

Reinforcement Learning for EV Fleet Smart Charging with On-Site Renewable Energy Sources

In 2020, the transportation sector was the second largest source of carbon emissions in the UK and in Newcastle upon Tyne, responsible for about 33% of total emissions. To support the UK’s target of reaching net zero emissions by 2050, electric vehicles (EVs) are pivotal in advancing carbon-neutral road transportation. Optimal EV charging requires a better understanding of the unpredictable output from on-site renewable energy sources (ORES). This paper proposes an integrated EV fleet charging schedule with a proximal policy optimization method based on a framework for deep reinforcement learning. For the design of the reinforcement learning environment, mathematical models of wind and solar power generation are created. In addition, the multivariate Gaussian distributions derived from historical weather and EV fleet charging data are utilized to simulate weather and charging demand uncertainty in order to create large datasets for training the model. The optimization problem is expressed as a Markov decision process (MDP) with operational constraints. For training artificial neural networks (ANNs) through successive transition simulations, a proximal policy optimization (PPO) approach is devised. The optimization approach is deployed and evaluated on a real-world scenario comprised of council EV fleet charging data from Leicester, UK. The results show that due to the design of the rewards function and system limitations, the charging action is biased towards the time of day when renewable energy output is maximum (midday). The charging decision by reinforcement learning improves the utilization of renewable energy by 2–4% compared to the random charging policy and the priority charging policy. This study contributes to the reduction in battery charging and discharging, electricity sold to the grid to create benefits and the reduction in carbon emissions.

Evidence for a Fast Soft X-Ray Wind in M82 from XMM-RGS

Starburst wind models predict that metals and energy are primarily carried out of the disk by hot gas (T > 106 K), but the low energy resolution of X-ray CCD observations results in large uncertainties on the mass and energy loading. Here, we present evidence for a fast soft X-ray wind from the prototypical starburst galaxy M82 using deep archival observations from the Reflection Grating Spectrometer on XMM-Newton. After characterizing the complex line-spread function for the spatially extended outflow ( ≈4′ ), we perform emission-line fitting to measure the velocity dispersion, σ v , from O viii (0.65, 0.77 keV), Ne x (1.02 keV), and Mg xii (1.47 keV). For the T ≈ 3 × 106 K gas, O viii yields a velocity dispersion of σv=1160−90+100 km s−1, implying a wind speed that is significantly above the escape velocity (v esc ≲ 450 km s−1). Ne x ( σv=550−150+130 km s−1) and Mg xii (σ v < 370 km s−1) show less velocity broadening than O viii, hinting at a lower wind speed or smaller opening angle on the more compact spatial scales traced by the T ≈ (0.6−1) × 107 K gas. Alternatively, these higher energy emission lines may be dominated by shock-heated gas in the interstellar medium. Future synthesis of these measurements with performance verification observations of the E = 2−12 keV wind in M82 from the Resolve microcalorimeter on the X-ray Imaging and Spectroscopy Mission will inform the phase structure and energy budget of the hot starburst wind.

Testing the flux tube expansion factor

Context. The properties of the solar wind measured in situ in the heliosphere are largely controlled by energy deposition in the solar corona, which is in turn closely related to the properties of the coronal magnetic field. Previous studies have shown that long-duration and large-scale magnetic structures show an inverse relation between the solar wind velocity measured in situ near 1 au and the expansion factor of the magnetic flux tubes in the solar atmosphere. Aims. The advent of the Solar Orbiter mission offers a new opportunity to analyse the relation between solar wind properties measured in situ in the inner heliosphere and the coronal magnetic field. We exploit this new data in conjunction with models of the coronal magnetic field and the solar wind to evaluate the flux expansion factor and speed relation. Methods. We use a Parker-like solar wind model, the “isopoly” model presented in previous works, to describe the motion of the solar wind plasma in the radial direction and model the tangential plasma motion due to solar rotation with the Weber and Davis equations. Both radial and tangential velocities are used to compute the plasma trajectory and streamline from Solar Orbiter location sunward to the solar ‘source surface’ at rss. We then employed a potential field source surface (PFSS) model to reconstruct the coronal magnetic field below rss to connect wind parcels mapped back to the photosphere. Results. We found a statistically weak anti-correlation between the in situ bulk velocity and the coronal expansion factor, for about 1.5 years of solar data. Classification of the data by source latitude reveals different levels of anticorrelation, which is typically higher when Solar Orbiter magnetically connects to high latitude structures than when it connects to low latitude structures. We show the existence of a fast solar wind that originates in strong magnetic field regions at low latitudes and undergoes large expansion factor. We provide evidence that such winds become supersonic during the super-radial expansion (below rss) and are theoretically governed by a positive v–f correlation. We find that faster winds exhibit, on average, a flux tube expansion at a larger radius than slower winds. Conclusions. An anticorrelation between solar wind speed and expansion factor is present for solar winds originating in high latitude structures in solar minimum activity, typically associated with coronal hole-like structures, but this cannot be generalized to lower latitude sources. We have found extended time intervals of fast solar wind associated with both large expansion factors and strong photospheric magnetic fields. Therefore, the value of the expansion factor alone cannot be used to predict the solar wind speed. Other parameters, such as the height at which the expansion gradient is the strongest, must also be taken into account.

LiDAR-Based Unmanned Aerial Vehicle Offshore Wind Blade Inspection and Modeling

The deployment of offshore wind turbines (WTs) has emerged as a pivotal strategy in the transition to renewable energy, offering significant potential for clean electricity generation. However, these structures’ operation and maintenance (O&amp;M) present unique challenges due to their remote locations and harsh marine environments. For these reasons, it is fundamental to promote the development of autonomous solutions to monitor the health condition of the construction parts, preventing structural damage and accidents. This paper explores the application of Unmanned Aerial Vehicles (UAVs) in the inspection and maintenance of offshore wind turbines, introducing a new strategy for autonomous wind turbine inspection and a simulation environment for testing and training autonomous inspection techniques under a more realistic offshore scenario. Instead of relying on visual information to detect the WT parts during the inspection, this method proposes a three-dimensional (3D) light detection and ranging (LiDAR) method that estimates the wind turbine pose (position, orientation, and blade configuration) and autonomously controls the UAV for a close inspection maneuver. The first tests were carried out mainly in a simulation framework, combining different WT poses, including different orientations, blade positions, and wind turbine movements, and finally, a mixed reality test, where a real vehicle performed a full inspection of a virtual wind turbine.

Evolution of Tidal Disruption Event Disks with Magnetically Driven Winds

We present a time-dependent, one-dimensional, magnetically driven disk wind model based on magnetohydrodynamic (MHD) equations, in the context of tidal disruption events (TDEs). We assume that the disk is geometrically thin, is gas pressure dominated, and explicitly accounts for magnetic braking and turbulent viscosity through an extended α-viscosity prescription. We find a particular wind solution for a set of basic equations that satisfies the necessary and sufficient conditions for vertically unbound MHD flows. The solution shows that the disk evolves with mass loss due to wind and accretion from the initial Gaussian density distribution. We confirm that the mass accretion rate follows the power law of time t −19/16 at late times in the absence of wind, which matches the classical solution of J. K. Cannizzo et al. We find that the mass accretion rate is steeper than the t −19/16 curve when the wind is present. Mass accretion is also induced by magnetic braking, known as the wind-driven accretion mechanism, which results in a faster decay with time of both the mass accretion and mass-loss rates. In the disk emission, the ultraviolet (UV) luminosity is the highest among the optical, UV, and X-ray luminosities. While the optical and X-ray emission is observationally insignificant without magnetic braking, the X-ray emission is brighter at late times, especially in the presence of magnetic braking. This provides a possible explanation for observed delayed X-ray flares. Our model predicts that late-time bolometric light curves steeper than t −19/16 in UV-bright TDEs are potentially compelling indicators of magnetically driven winds.

Bayesian finite element model inversion of offshore wind turbine structures for joint parameter-load estimation

Operating in harsh and unsteady marine environment, offshore wind turbine (OWT) structures are exposed to unpredictable wind and wave loads. Identifying the structural loads and their effects on the OWTs allow for predicting the remaining fatigue life of these structures and improving the structural design procedure. In this paper, a finite element (FE) model inversion method is presented to estimate the unknown loads and model parameters of OWTs using sparse measurement data. A realistic FE model of an OWT structure with jacket substructure is created in the open-source simulation platform, OpenSees. A Bayesian inference framework is presented to integrate the measured data with the FE model to estimate unknown wind loads and mass of rotor-nacelle assembly. To evaluate the performance of this data assimilation framework, the effect of sensor type, number of sensors, and modeling errors on the estimation accuracy of wind loads and model parameters are investigated through different case studies where synthetic data are used as measurements. The results of this study are important to guide instrumentation of new OWT structures, and to understand the potential limitations and sources of error in the real-world application of this data assimilation framework for joint model parameter and input load estimation.

Studying the X-ray absorption characteristics of Centaurus X-3 using nearly 14 years of MAXI/GSC data

Centaurus X-3 is a persistent high-mass X-ray binary with the long-term light curve from the source exhibiting orbit-to-orbit intensity variations with no apparent superorbital periodicity. We used sim 13.5 years of MAXI /GSC data to study the long-term behaviour of X-ray absorption caused by the stellar wind from the companion star and any absorbing structures present in the binary. We used orbital-phase-resolved spectroscopy to study the variation in the photoelectric absorption along the line of sight of the source for both the intensity-averaged data and intensity-resolved data after dividing all the data binned with orbital period into three intensity levels. We find an asymmetric variation in the photoelectric absorption along the line of sight across an orbit of the source. The orbital-phase-resolved spectra show a clear increase in photoelectric absorption after $ orb 0.5, which deviates from a spherically symmetric stellar wind model. The flux of Cen X-3 shows significant variation between consecutive orbits. An intensity-resolved spectral analysis of the source was performed, followed by an intensity-resolved and orbital-phase-resolved spectral analysis, which showed that at the medium and high intensity levels, the orbital-phase-resolved photoelectric absorption is slightly asymmetric with respect to mid-phase ($ orb =$ 0.5). The asymmetry is very pronounced at the lowest intensity level and cannot be explained by a spherically symmetric wind from the companion star. The differences in the orbital phase-dependence of absorption for different intensity levels suggest that the presence of an accretion wake, photoionization wake, or tidal stream is more prominent at a lower intensity level for Centaurus X-3 than at a higher intensity level.

CHANG-ES. XXXIII. A 20 kpc radio bubble in the halo of the star-forming galaxy NGC 4217

Cosmic rays may be dynamically very important in driving large-scale galactic winds. Edge-on galaxies give us an outsider's view of radio haloes, and of their extra-planar cosmic-ray electrons and magnetic fields. We present a new radio continuum imaging study of the nearby edge-on galaxy NGC\,4217. We examine the distribution of extra-planar cosmic rays and magnetic fields. We observed it with both the Jansky Very Large Array (JVLA) in the $S$ band (2--4\,GHz) and the LOw Frequency ARray (LOFAR) at 144\,MHz. We measured vertical intensity profiles and exponential scale heights. We re-imaged both the JVLA and LOFAR data at matched angular resolution in order to measure radio spectral indices between 144\,MHz and 3\,GHz. Confusing point-like sources were subtracted prior to imaging. We then fitted intensity profiles with cosmic-ray electron advection models, using an isothermal wind model that is driven by a combination of pressure from the hot gas and cosmic rays. We discover a large-scale radio halo on the north-western side of the galactic disc. The morphology is reminiscent of a bubble extending up to 20\,kpc from the disc. We find spectral ageing in the bubble, which allowed us to measure the advection speeds of the cosmic-ray electrons, which accelerate from 300 to $600\ $. Assuming energy equipartition between the cosmic rays and the magnetic field, we estimate the bubble may have been inflated by a modest 10\,&lt;!PCT!&gt; of the kinetic energy injected by supernovae over its dynamical timescale of 35\,Myr. While no active galactic nucleus (AGN) has been detected, such activity in the recent past cannot be ruled out. Non-thermal bubbles with sizes of tens of kiloparsecs may be a ubiquitous feature of star-forming galaxies, and if so this would demonstrate the influence of feedback. Determining possible contributions by AGN feedback will require deeper observations.

The Galactic population of canonical pulsar. II. Taking into account several evolutionary paths: Interstellar medium interaction, Galactic potential, and a death valley

Pulsars are highly magnetised rotating neutron stars, emitting in a broad electromagnetic energy range. These objects were discovered more than 55 years ago and are astrophysical laboratories for studying physics at extreme conditions. Reproducing the observed pulsar population helps refine our understanding of their formation and evolution scenarios, as well as their radiation processes and geometry. In this paper, we improve our previous population synthesis by focusing on both the radio and gamma -ray pulsar populations, investigating the impact of the Galactic gravitational potential and of the radio emission death line. To elucidate the necessity of a death line, we implemented our refined initial distributions of the spin period and spacial position at birth. This approach allowed us to elevate the sophistication of our simulations to the most recent state-of-the-art approaches. The motion of each individual pulsar was tracked in the Galactic potential by a fourth-order symplectic integration scheme. Our pulsar population synthesis took into account the secular evolution of the force-free magnetosphere and magnetic field decay simultaneously and self-consistently. Each pulsar was evolved from birth to the present time. The radio and gamma -ray emission locations were modelled by the polar cap geometry and striped wind model, respectively. By simulating ten million pulsars, we found that including a death line allows us to better reproduce the observational trend. However, when simulating one million pulsars, we obtained an even more realistic $P- P $ diagram, whether or not a death line was included. This suggests that the ages of the detected pulsars might be overestimated and so, it sets the need for a death line in pulsar population studies into question. Kolmogorov-Smirnov tests confirm the statistical similarity between the observed and simulated $P- P $ diagram. Additionally, simulations with increased gamma -ray telescope sensitivities hint at a significant contribution coming from the gamma -ray pulsars to the GeV excess in the Galactic centre.

A 45-year updating wind and wave hindcast over the Oman Sea and the Arabian Sea

This study focuses on developing a comprehensive and reliable wind and wave hindcast for the Oman Sea and Arabian Sea, spanning a significant 45-year period (1979–2024). The objective is to capture the intricate wind and wave climate of the region, characterized by distinct monsoon cycles and occasional tropical cyclones. The availability of extensive wave data over four decades would be an irreplaceable tool for researchers and engineers, enabling improved accuracy in extreme value analysis, sediment transport studies, and wave-induced current simulations. Despite limited field observations, all available measured data within the region were collected, analyzed for configuration of the models and utilized for model calibration and validation. The hindcast data was generated using the Weather Research and Forecasting (WRF) model for winds and WAVEWATCH III (WW3) model for waves, and evaluated against observational and measured wind and wave parameters. A comprehensive statistical analysis of the hindcast model's performance reveals adequate agreement with measured data, as evidenced by root mean square errors (RMSEs) of 1.23 m/s for wind speeds and 0.37 m for significant wave heights in average. These results underscore the model's reliability for research and engineering applications, particularly in the Arabian Sea, with a focus on the northern coastlines of the Oman Sea. The specific model configuration employed in this study holds significant potential for future investigations in the northern Indian Ocean, offering a valuable tool for understanding and predicting climatical conditions in this region.

Modeling of Solar Radiation Pressure for BDS-3 MEO Satellites with Inter-Satellite Link Measurements

As the largest non-gravitational force, solar radiation pressure (SRP) causes significant errors in precise orbit determination (POD) of the BeiDou global navigation satellite system (BDS-3) medium Earth orbit (MEO) satellite. This is mainly due to the imperfect modeling of the satellite’s cuboid body. Since the BDS-3’s inter-satellite link (ISL) can enhance the orbit estimation of BDS-3 satellites, the aim of this study is to establish an a priori SRP model for the satellite body using 281-day ISL observations to reduce the systematic errors in the final orbits. The adjustable box wind (ABW) model is employed to refine the optical parameters for the satellite buses. The self-shadow effect caused by the search and rescue (SAR) antenna is considered. Satellite laser ranging (SLR), day-boundary discontinuity (DBD), and overlapping Allan deviation (OADEV) are utilized as indicators to assess the performance of the a priori model. With the a priori model developed by both ISL and ground observation, the slopes of SLR residual for the China Academy of Space Technology (CAST) and Shanghai Engineering Center for Microsatellites (SECM) satellites decrease from −0.097 cm/deg and 0.067 cm/deg to −0.004 cm/deg and −0.009 cm/deg, respectively. The standard deviation decreased by 21.8% and 26.6%, respectively. There are slight enhancements in the average values of DBD and OADEV, and a reduced β-dependent variation is observed in the OADEV of the corresponding clock offset. We also found that considering the SAR antenna only slightly improves the orbit accuracy. These results demonstrate that an a priori model established for the BDS-3 MEO satellite body can reduce the systematic errors in orbits, and the parameters estimated using both ISL and ground observation are superior to those estimated using only ground observation.

UAV Trajectory Tracking Using Proportional-Integral-Derivative-Type-2 Fuzzy Logic Controller with Genetic Algorithm Parameter Tuning.

Unmanned Aerial Vehicle (UAV)-type Quadrotors are highly nonlinear systems that are difficult to control and stabilize outdoors, especially in a windy environment. Many algorithms have been proposed to solve the problem of trajectory tracking using UAVs. However, current control systems face significant hurdles, such as parameter uncertainties, modeling errors, and challenges in windy environments. Sensitivity to parameter variations may lead to performance degradation or instability. Modeling errors arise from simplifications, causing disparities between assumed and actual behavior. Classical controls may lack adaptability to dynamic changes, necessitating adaptive strategies. Limited robustness in handling uncertainties can result in suboptimal performance. Windy environments introduce disturbances, impacting system dynamics and precision. The complexity of wind modeling demands advanced estimation and compensation strategies. Tuning challenges may necessitate frequent adjustments, posing practical limitations. Researchers have explored advanced control paradigms, including robust, adaptive, and predictive control, aiming to enhance system performance amidst uncertainties in a scientifically rigorous manner. Our approach does not require knowledge of UAVs and noise models. Furthermore, the use of the Type-2 controller makes our approach robust in the face of uncertainties. The effectiveness of the proposed approach is clear from the obtained results. In this paper, robust and optimal controllers are proposed, validated, and compared on a quadrotor navigating an outdoor environment. First, a Type-2 Fuzzy Logic Controller (FLC) combined with a PID is compared to a Type-1 FLC and Backstepping controller. Second, a Genetic Algorithm (GA) is proposed to provide the optimal PID-Type-2 FLC tuning. The Backstepping, PID-Type-1 FLC, and PID-Type-2 FLC with GA optimization are validated and evaluated with real scenarios in a windy environment. Deep robustness analysis, including error modeling, parameter uncertainties, and actuator faults, is considered. The obtained results clearly show the robustness of the optimal PID-Type-2 FLC compared to the Backstepping and PID-Type-1 FLC controllers. These results are confirmed by the numerical index of each controller compared to the PID-type-2 FLC, with 12% for the Backstepping controller and 51% for the PID-Type-1 FLC.

A method for configuring hybrid electrolyzers based on joint wind and photovoltaic power generation modeling using copula functions

Considering the specific wind and photovoltaic power characteristics of a certain region, this study investigates the optimal ratio of Alkaline Electrolysis Cells (AEL) to Proton Exchange Membrane (PEM) electrolyzers in a hybrid electrolysis system for hydrogen production. A flexible model for configuring the hybrid electrolysis system is proposed, based on a copula function for joint wind and solar power modeling. This model generates wind and photovoltaic power generation scenarios using the copula function, incorporating a selection mechanism to ensure that the output scenarios are more representative of the actual data characteristics of wind and photovoltaic power output. Consequently, considering both the fluctuation and amplitude, the wind and photovoltaic power data are decomposed using the Ensemble empirical mode decomposition method. The decomposed components are then allocated to the two types of electrolyzers. Furthermore, the optimal configuration of the hybrid electrolysis system is determined by minimizing the costs associated with wasted power, electricity purchases, and other expenses. Finally, a case study of a 100 MW wind farm and a 50 MW photovoltaic power station in Northwest China is presented, concluding that the optimal configuration ratio of AEL to PEM electrolyzers is 2:1. In a Matlab/Simulink platform, the performance metrics of the hybrid electrolysis system were validated. It was found that the hydrogen production rate of the hybrid electrolyzer is comparable to that of the PEM electrolyzer, but with a lower required cost. Additionally, the hydrogen production rate and volume of the optimal configuration for the hybrid electrolyzer determined by the model proposed in this paper are higher than those obtained through the optimization algorithm's optimal configuration.

Radiative acceleration calculation methods and abundance anomalies in Am stars

Atomic diffusion with radiative levitation is a major transport process to consider to explain abundance anomalies in Am stars. Radiative accelerations vary from one species to another, yielding different abundance anomalies at the stellar surface. Radiative accelerations can be computed using different methods: some evolution codes use an analytical approximation, while others calculate them from monochromatic opacities. We compared the abundance evolutions predicted using these various methods. Our models were computed with the Toulouse-Geneva evolution code, in which both an analytical approximation (the single-valued parameter method) and detailed calculations from Opacity Project (OP) atomic data are implemented for the calculation of radiative accelerations. The time evolutions of the surface abundances were computed using macroscopic transport processes that are able to reproduce observed Am star surface abundances in presence of atomic diffusion, namely an ad hoc turbulent model or a global mass loss. The radiative accelerations obtained with the various methods are globally in agreement for all the models below the helium convective zone, but can be much greater between the bottom of the hydrogen convective zone and that of helium. The time evolutions of the surface abundances mostly agree within the observational error, but the abundance of some elements can exceed this error for the least massive mass-loss model. The gain in computing time from using analytical approximations is significant compared to sequential calculations from monochromatic opacities for the turbulence models and for the least massive wind model; the gain is small otherwise. Test calculations of turbulence models with the tabulated OPAL opacities yield quite similar abundances as OP for most elements but in a much shorter time, meaning that determining Am star parameters can be done using a two-step method.