Maximum Power Extraction Research Articles

Design and performance analysis of hybrid MPPT controllers for fuel cell fed DC-DC converter systems

Fuel cell-based power generation is the most utilized renewable energy source in the automotive industry because of its features clean energy, and less environmental pollution. The fuel cell output power is mainly depending on the operating temperature of the fuel cell. The fuel cell gives nonlinear voltage versus current characteristics. As a result, the extraction of maximum power from the fuel stack is very difficult. In order to extract the peak power from the fuel cell, a Maximum Power Point Tracking (MPPT) controller is used at various working temperature conditions of the fuel cell. The main contribution of this study is the introduction and comparative performance analysis of different hybrid MPPT controllers for selecting the optimum duty cycle for the fuel cell-fed boost converter system. The studied MPPT controllers are Adaptive Adjustable Step-based Perturb and Observe (AAS-P&O) controllers, Variable Step Value-Radial Basis Function Controller (VSV-RBFC), Adaptive Step Hill Climb (ASHC) based fuzzy technique, Variable P&O with Particle Swarm Optimization (VP&O-PSO), and Variable Step Grey Wolf Algorithm (VSGWA) based fuzzy logic controller. These hybrid MPPT controllers’ comparative performance analysis has been done in terms of tracking speed of MPP, oscillations across MPP, design complexity of controller, ability to handle fast changes of temperature values, and accuracy of MPP tracking. From the simulative performance results, it is identified that the VSGWA-based fuzzy controller gives superior performance when compared to the other controllers.

Modular battery-integrated bidirectional single-stage DC–DC converter for solar PV based DC Nano-grid application

Attributed to the growing focus on energy savings and eco-friendliness, the solar PV-based DC Nano-grids for residential and commercial buildings are becoming more popular. On the other hand, solar photovoltaic systems (SPV) are intermittent and unreliable due to their dependency on external factors such as solar irradiance, ambient temperature, and unpredictable shadows. In addition, the power degradation occurs in SPV systems due to module mismatch losses caused by various factors like partial shading (PS), dissimilar aging effect, different power ratings, etc. The conventional PV system cannot handle all these issues, so it is essential to address them. This paper proposes a bidirectional modular PV battery system (BMPBS) that uses non-isolated buck and boost converter combinations. This system is capable of self-sustained generation, storage, and bidirectional power flow within the Nano-grid. The proposed BMPBS can handle losses due to module mismatch and intermittency in SPV with the help of battery storage system (BSS), making the overall SPV system reliable. It requires single-stage power conversion to extract maximum power from each PV module and BSS charging and discharging. Its modular design allows it to function across various voltage, power, and BSS choices. This paper discusses the operation, steady-state analysis, and dynamic analysis of the proposed BMPBS. The performance of the proposed BMPBS is validated using a state-of-the-art experimental setup with two PV modules, each having a rating of 90WP.

Cone-shaped resonator-based highly efficient broadband metamaterial absorber

We propose a highly efficient, low-cost metamaterial absorber of nickel (Ni) metal-based cone-shaped resonators with a silicon dioxide dielectric layer (SiO2). The proposed absorber exhibits an average absorption of 97% for the transverse magnetic and transverse electric modes over the visible region simulated by CST software. The nickel-metal impedance coincides with the impedance of free space and makes the proposed design an effective broadband absorber in the visible region. The average absorption with different incidence angles obtains over 90%, showing the polarization angles’ independence. The average absorption spectra are also examined for the absorber with different noble metals. In addition, short-circuit current densities (Jsc) are calculated at different incidence angles for both modes under a global air mass of 1.5 (AM1.5). We have also plotted the J–V curve to obtain the values of the open-circuit voltage (Voc), Fill Factor, and conversion efficiency (η), whose values are 0.563 V, 81.86, and 11.68%, respectively. The proposed metamaterial absorber can be utilized to develop more reliable, highly efficient, cost-effective, and maximum-power extraction photovoltaic systems.

Nonlinear optimal control with effective wind speed estimation for maximum power extraction based on adaptive fuzzy logic controller and extended Kalman Filter

Nonlinear optimal control with effective wind speed estimation for maximum power extraction based on adaptive fuzzy logic controller and extended Kalman Filter

Hardware implementation of a novel hybrid MPPT technique for fast tracking of GMPP in solar PV system under PSCs

PurposeTo generate electricity, solar photovoltaic (PV) systems are among the best, most eco-friendly and most cost-effective solutions available. Extraction of maximum possible electricity from the solar PV system is complicated by a number of factors brought on by the ever-changing weather conditions under which it must operate. Many conventional and evolutionary algorithm-based maximum power point tracking (MPPT) techniques have the limitation of not being able to extract maximum power under partial shade and rapidly varying irradiance. Hence, the purpose of this paper is to propose a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid bridge link-honey comb (BL-HC) configured PV system to enhance the better maximum power during dynamic and steady state operations within less time.Design/methodology/approachIn this method, a hybridization of two algorithms is proposed to track the true with faster convergence under PSCs. Initially, the slime mould optimization (SMO) algorithm is initiated for exploration of optimum duty cycles and later P&O algorithm is initiated for exploitation of global duty cycle for the DC–DC converter to operate at GMPP and for fast convergence.FindingsThe effectiveness of the proposed HSMO MPPT is compared with adaptive coefficient particle swarm optimization (ACPSO), flower pollination algorithm and SMO MPPT techniques in terms of tracked GMPP, convergence time/tracking speed and efficacy under six complex partial shading conditions. From the results, it is noticed that the proposed algorithm tracks the true GMPP under most of the shading conditions with less tracking time when compared to other MPPT techniques.Originality/valueThis paper proposes a novel hybrid slime mould assisted with perturb and observe (P&O) global MPPT technique (HSMO) for the hybrid BL-HC configured PV system enhance the better maximum power under partial shading conditions (PSCs). This method operated in two stages as SMO for exploration and P&O for exploitation for faster convergence and to track true GMPP under PSCs. The proposed approach largely improves the performance of the MPP tracking of the PV systems. Initially, the proposed MPPT technique is simulated in MATLAB/Simulink environment. Furthermore, an experimental setup has been designed and implemented. Simulation results obtained are validated through experimental results which prove the viability of the proposed technique for an efficient green energy solution.

Experimental Implementation of Cascaded H-Bridge Multilevel Inverter with an Improved Reliability for Solar PV Applications

This study presents the boost converter-based cascaded H-bridge (CHB) multilevel inverter with improved reliability for solar PV (photovoltaic) applications. The solar PV is associated with the boost converter to enhance DC link voltage by using the maximum power point tracking-perturb and observe (MPPT-P & O) technique. The proposed configuration is aimed toward the performance analysis of the boost converter-based CHB MLI by reducing the number of components, low total harmonic distortion (THD), reduced power, less cost function, low total standing voltage (TSV), improved reliability, and switching losses for solar PV application. In this study, a CHB multilevel inverter is used to obtain stepped pure sinusoidal AC from the solar PV array. The proposed boost converter extracts maximum power and enhances higher DC link voltage which provides high efficiency. The boost converter is integrated with a 27-level CHB multilevel inverter to generate near-sinusoidal output voltage with lower THD. The inverter is tested with linear and nonlinear loads for robustness, and during dynamic loads, inverter is stable and well suited to grid-connected applications. A detailed comparison is presented on the component count and reliability aspects with existing MLIs and 27-level MLIs. The simulation outcomes of the implemented arrangement are presented with the help of MATLAB/Simulink, an experimental prototype is developed using a dSPACE RTI1104 controller and also tested in the research laboratory for checking the possibility of the implemented arrangement.

Design and investigation of PV string/central architecture for bayesian fusion technique using grey wolf optimization and flower pollination optimized algorithm

One of the most essential factors in the current study is effectively harvesting the Maximum Power Extraction (MPE) from the Photovoltaic (PV) panel. The primary difficulties in extracting solar power is occurrence of partial shading which causes the panel to significantly increases power loss. These will mainly occur due to when partially shaded solar PV array kept under certain critical conditions for obtaining maximum output power. Many researcher have suggested by connecting bypass diodes in anti-parallel to the PV modules hotspots in the modules can be avoided. Out of all techniques, the proposed Bayesian Fusion Technique (BFT) is a hybrid optimization algorithm that combines the Grey Wolf Optimization (GWO) and Flower Pollination Algorithm (FPA) techniques to optimize the performance of solar panels in photovoltaic (PV) systems. The combination of GWO and FPA forms an ideal combination that is beneficial for optimizing the performance of PV systems is determined in this work. In this study real 6*6 PV array string and irregular PV array configuration such as central and parallel-series PV string combination of various partial shading pattern is compared and found to be effective for reducing the hotspots problems. The performance of these configuration under different shading patterns have been compared and analyzed with the different parameters like output power, conversion efficiency and tracking efficiency. This article state about the influence of partial darkening and the crucial point that reduce the sensitivity to shading heaviness. For better understanding for reader the MATLAB/Simulink software is used to validate the simulation result with real time data. Overall, this article states the BFT is an efficient and reliable approach to improve the efficiency of PV systems, by combining two optimization techniques like GWO and FPA hybrid algorithm. This article gives clear insight to the researchers for choosing BFT-GWO algorithm in order to decrease the cost and wastage of energy for achieving better solar panel performance.

Design and Analysis of Input Capacitor in DC–DC Boost Converter for Photovoltaic-Based Systems

Photovoltaic (P.V.) systems have become an emerging field for power generation by using renewable energy (RE) sources to overcome the usage of conventional combustible fuels and the massive release of dangerous gases. The efficient operation of the PV system is vital to extracting the maximum power from the PV source. For this, a maximum power point tracking (MPPT) algorithm works with a DC–DC converter to extract maximum power from the P.V. system. Two main issues may arise with the involvement of a converter: (1) to locate M.P.P and (2) the performance of the PV model in varying weather conditions. Therefore, designing any converter gain has the utmost significance; thus, the proposed work is on non-isolated boost converters. To calculate the values of specific parameters such as input capacitor, output capacitor, and inductor, the averaging state-space modeling typically uses governing equations. In this research, the formula of the input capacitor is derived through the average state-space modeling of the boost converter, which signifies the relation between input and output capacitors. From the results, it has been proven that the input capacitor efficiently performs when the input capacitor is half of the output capacitor. At an irradiance level of 1000 W/m2, the system shows stable behavior with a fast convergence speed of 0.00745 s until the irradiance falls to a value of 400 W/m2. The system is less stable during the morning and the evening when irradiance falls are very low.

A novel robust maximum power extraction framework for sustainable PV system using incremental conductance based MRAC technique

AbstractThis study proposes a maximum power point tracking (MPPT) approach with two components: an Incremental Conductance (INC) MPPT for reference voltage regulation and a Model Reference Adaptive Controller (MRAC) for adjusting the duty cycle of the DC‐DC converter switch. A robustness test is performed on the system considering real‐world situations that involve an abrupt change in atmospheric conditions with load uncertainties. The probabilistic load distribution analysis is accomplished through levels of uncertainty (i.e., Probabilistic DOWN and UP) to guarantee the operation of the proposed INC‐MRAC controller while generating unexpected disturbances in the system. Using MATLAB/Simulink, the performances of the novel INC‐MRAC MPPT are comparatively analyzed with PO, INC, VSSPO, and ANN under realistic case studies in seven states. After comparative analysis, it is evident that the proposed MPPT offers less tracking time, i.e., 3.8 ms, to track maximum power point (MPP) with negligible steady‐state oscillation and ripples. It is about 3, 7, 9, and 10 times faster than ANN, VSSPO, INC and PO, respectively. Moreover, the tracking efficiency of the proposed controller is up to 99.63% as well as overall efficiency of the system is more than 98%. The tracking power loss and error rate in finding MPP for the proposed controller is the lowest among all state‐of‐the‐art MPPT approaches. Finally, the effectiveness of the proposed INC‐MRAC approach is experimentally validated by employing a real‐time simulator OPAL‐RT (OP4510). The study helps in environmental protection and participation in sustainable development.

A Self-Adaptive-Step-Size Incremental-Resistance-MPPT Technique for Reverse-Electrodialysis System

Salinity gradient power (SGP) is a kind of promising renewable energy source with huge potential, which can be derived through reverse electrodialysis (RED). Generally, RED stacks operate at either continuous mode or recycle mode, both of which possess respective advantages in different application scenes. Since SGP technology is still at an infant stage, there is a few research focusing on maximum-power-point-tracking (MPPT) techniques of RED stacks, which are crucial for the effective energy utilization of SGP. In this article, based on the generalized hybrid RED model, a self-adaptive-step-size incremental-resistance MPPT technique is proposed to extract maximum power from RED stacks. Not only is it simple and easy to implement but also it realizes self-adjustment of the step size to strike a balance between fast dynamic responses and small oscillations at a steady state. Moreover, according to the unique intrinsic features of RED stacks, the systematic design principles of the sampling interval and scaling factor are detailed, which help facilitate a fast and stable system. Various tests with the proposed technique under different parameter settings, as well as tests with other conventional MPPT techniques, are conducted on a RED stack prototype to validate the effectiveness of the proposed MPPT.

Maximum Power Extraction in Partial Shaded Grid-Connected PV System Using Hybrid Fuzzy Logic/Neural Network-Based Variable Step Size MPPT

The photovoltaic (PV) system’s output power varies owing to solar radiation’s irregularity, which confines their usage for various applications. Implementation of maximum power tracking (MPT) algorithms increases the efficiency and power generated from solar cells. When the array is partially obscured by clouds or structures, several local maximum power peaks (LMPPs) appear in the solar cell characteristics. Traditional MPPT algorithms, rather than following the global peak power point (GPPP), are preferable to following the local peak power point. If partial shading causes numerous LPPPs, it is necessary to look into how the MPPT technique can keep track of GPPP. Employing soft computing approaches such as the hybrid neural network/fuzzy method with variable step size perturb and observing MPPT, it is possible to trace the GPPP and also augment solar energy extraction. The present research paper focuses on hybrid fuzzy/neural network MPPT integrated with a high-step-up DC-DC converter to harvest the utmost power from the solar PV array. The voltage transients are reduced by controlling the DC link voltage along with solar radiation and temperature variations. The proposed MPPT technique is shown to be effective under both uniform and partial shade conditions in a series of simulations. From the test results, the efficiency of the overall system has increased from 91 to 98% for partial shading and uniform operating conditions.

Impact of demand side management approaches for the enhancement of voltage stability loadability and customer satisfaction index

This research work presents the tri-level optimization framework for the optimal scheduling of grid-connected and autonomous microgrids to diminish power losses and maximize loadability. Since the network's voltage profile depends on the loading level, the flexible load shaping-based demand-side management strategy is incorporated to investigate its impact on microgrid loadability. With the consideration of uncertain parameters related to renewable power generation, load demand, and power loss, voltage limit constraints, the resultant problem is formulated as a stochastic mixed-integer non-linear problem to enhance microgrid loadability and optimize daily operating costs. The interdependency of demand side management program and microgrid loadability is investigated. The seasonal load profiles covering the weekend and weekday loads in winter, summer, and spring/fall seasons are examined in this research work. The enhanced versions of the distribution networks IEEE-33 and IEEE-69 based microgrid test systems are chosen to evaluate the proposed framework in both off-grid and autonomous modes of operation. Simultaneously, the overall customer satisfaction index is evaluated and improved according to the seasonal load profiles winter weekday, winter-weekend, summer-weekday, summer-weekend, spring-weekday, and spring-weekend by 8.68%, 7.97%, 16.7%, 19.62%, 17.14%, 20.50% respectively. The recently reported Whale Optimization Algorithm is adopted to solve the proposed optimization problem, and the obtained simulation results are validated by comparing them with popular metaheuristic algorithms. The computational burden on the utility is reduced for optimal scheduling of grid-integrated microgrid to extract maximum power by maintaining network voltage profile.

Design, analysis, and adaptive maximum power point tracking control of small‐scale wind turbine system

SummaryDue to the stochastic and unpredictable nature of wind speed, extraction of maximum power from the wind turbine system becomes an attractive control objective. Therefore, to capture more wind power, various conventional maximum power point tracking (MPPT) schemes are developed for standalone small‐scale variable speed wind power generation system (VSWPGS). This manuscript proposes novel adaptive step size (ASS) and drift‐free ASS (DF‐ASS) MPPT methods for a permanent magnet synchronous generator (PMSG)‐based VSWPGS. The control schemes achieve maximum power point (MPP) without using mechanical sensors like speed encoder and anemometer. The proposed MPPT controllers are implemented on a laboratory‐scale DC motor‐PMSG‐based wind power generation system (WPGS) using OPAL‐RT real‐time digital platform. The ASS and DF‐ASS methods capture more power, reduce the steady‐state power oscillation around MPP, and improve the tracking speed. Also, the proposed DF‐ASS control scheme avoids drift phenomenon during wind speed increase condition. The comparative experimental results of proposed ASS and DF‐ASS methods with respect to the fixed step size MPPT schemes show better dynamic and steady‐state performance, making it pertinent for small‐scale WPGS.

Analysis of total harmonic distortion in single-phase single-stage grid-connected photovoltaic system

<p>This study presents the power quality issue mainly focus the effect of total harmonic distortion (THD) on a grid-connected PV system. Firstly, a grid-connected PV system with a single-phase single-stage has been developed to monitor the output values of voltage and current and also its harmonic distortion behaviours. Maximum power point tracking (MPPT) was implemented since it is proven as the first step for THD reduction because MPPT will extract maximum output power, voltage, and current of the PV system without fluctuation which leads to a low THD level. Furthermore, the employment of a good filter also reduces the THD level in a PV system. Thus, this study will focus on the THD analysis to resolve the power quality problems in the grid-connected PV system. The result shows that the THD value for current, <em>I<sub>THD</sub></em> analysis is more significant than the THD value for voltage, <em>V<sub>THD</sub></em> analysis in the case of grid-connected PV systems operating under different solar irradiances. In a conclusion, the increase in solar irradiance will increase the rated values of generated power and current thus, increasing the performance of THD values.</p>

Energy management system for AC/DC HMGS integrated with interconnected renewable sources and interlinking converter

AC/DC hybrid micro grid system (HMGS) is designed with renewable energy sources (RES) and battery energy storage system (BESS) with unique control schemes, interfaced with multi terminal interlinking converters (ILCs). This ILC operates on droop control scheme to guarantee bidirectional power sharing to AC/DC sub grids. The power sources in AC/DC sub grids like PV, Fuel cell, BESS are controlled by advance control methods for maximum power extraction with power quality. A three-level control structure is designed for optimal energy management system (EMS). The first level confirms the power balance in AC/DC sub grid with autonomous bidirectional power transfer via ILC in islanded mode. The second level tracks the batteries state of charge (SoC), based on the minimum and maximum SoC the battery operates for charging and discharging. The third level gives the power redundant capability for critical loads connected in AC/DC sub grid for DC system and single-phase system.

Mathematical Modeling and Validation of Saturating and Clampable Cascaded Magnetics for Magnetic Energy Harvesting

Electromagnetic energy harvesting extracts energy from magnetic fields and can provide power to sensors, monitoring nodes, cyber-physical systems and control elements without additional battery and external power source and wiring. This article presents a novel ac-driven electromagnetic energy harvester based on periodically saturating, cascaded magnetics, consisting of a clampable magnetic core and an ungapped high permeability core. The high permeability core guarantees the maximum energy extraction, whereas the clampable core enables the nonintrusive installation of the energy harvester for more pervasive applications. This article first builds a comprehensive mathematical model based on this saturating cascaded magnetic structure, considering the reachability of an individual saturation flux density of the two magnetic cores. This model resolves the new challenges introduced by the cascaded magnetics with respect to a traditional single-core case, providing the accurate calculation of the lengths of the relevant time windows for harvesting and the amount of the harvested power. Our mathematical model is verified against simulation and experiment, showing excellent agreement among them with the maximum discrepancy of less than 6%. This article also reveals that the maximum power extraction occurs when the ungapped core operates in its slightly saturated state and that the harvested power increases with a higher primary current as well as a higher line frequency.

Certainty equivalence-based robust sliding mode control strategy and its application to uncertain PMSG-WECS.

This work focuses on maximum power extraction via certainty equivalence-based robust sliding mode control protocols for an uncertain Permanent Magnet Synchronous Generator-based Wind Energy Conversion System (PMSG-WECS). The considered system is subjected to both structured and unstructured disturbances, which may occur through the input channel. Initially, the PMSG-WECS system is transformed into a Bronwsky form, i.e., controllable canonical form, which is composed of both internal and visible dynamics. The internal dynamics are proved stable, i.e., the system is in the minimum phase. However, the control of visible dynamics, to track the desired trajectory, is the main concern. To carry out this task, the certainty equivalence-based control strategies, i.e., conventional sliding mode control, terminal sliding mode control and integral sliding mode control are designed. Consequently, a chattering phenomenon is suppressed by the employment of equivalent estimated disturbances, which also enhance the robustness of the proposed control strategies. Eventually, a comprehensive stability analysis of the proposed control techniques is presented. All the theoretical claims are verified via computer simulations, which are performed in MATLAB/Simulink.

Novel Double Tied Cross Link with Reduced Cross Cables for Maximum Power Extraction under Uniform and Non-Uniform Shading Conditions

Partially shaded panels lead to the creation of troughs in the power generation PV curve, from its optimal potential. Researchers have focally went through for findings in the optimal Photo Voltaic (PV) configuration namely Series (S), Parallel (P), Series–Parallel (SP), Bridge Link (BL), Honey Comb (HC), Total Cross Tie (TCT), Triple Tied Cross Link (TTCL), and Hybrid Configurations. In this paper, a Novel Double Tied Cross Link (DTCL)-based PV panel configuration is proposed. The superiority of the proposed DTCL configuration is that the number of local maximum power points (LMPP) is reduced in certain partial shaded conditions and optimized cost also possible, as the number of cross-links has been reduced, compared to conventional configurations. The maximum power generation superiority of TCT and TTCL has been realized with the proposed novel configuration of Double Tied Cross Link. Using MATLAB/Simulink, different patterns of possible shadings have been created as a replica of real-time partial shadings. Analysis of the proposed DTCL configuration has been implemented along with the conventional configurations in MATLAB simulation. The technical parameters, such as open circuit voltage, short circuit current, maximum voltage, maximum current, fill factor, mismatch losses, and efficiency, are considered for analyzing the proposed DTCL photo voltaic configuration. Besides, this article also presents a novel DTCL PV configuration which reveals cross-cable savings, maximum power attainment, and economically feasible, as usage of cross cables is less, without much compromising on power generation.

Low-Voltage Photovoltaic System Based on a Continuous Input/Output Current Converter

Low-voltage photovoltaic systems are being widely used around the world, including their introduction into the power grid. The development of these systems requires the adaptation of several power converters, their static and dynamic modeling, the design of passive elements, and the design of the controller parameters, among other actions. Today, power converters are key elements in the development of photovoltaic systems, and classical power converters such as buck converters produce discontinuous input and output currents, requiring a high input capacitance and impacting the output power quality of these systems. This paper presents a proposal for a low-voltage photovoltaic system that uses a continuous input/output current buck converter, which enhances the operation of the classical buck converter in photovoltaic systems. The methodology describes the proposed photovoltaic system, including the power converter, its detailed operation, and the analysis of its waveforms. Moreover, the methodology includes a mathematical model of the photovoltaic system’s dynamic behavior and the design of a sliding-mode controller for maximum power extraction and perturbation rejection. The photovoltaic system is validated in two ways: first, a comparison with the classical buck converter highlighting the advantages of continuous input/output currents is presented; then, an application example using commercial devices is described in detail. The application example uses a flowchart to design the power converter and the sliding-mode controller, and a circuit simulation confirms the advantages of the continuous input/output current buck converter with its controller. In the circuit simulation, the control strategy is formed by a perturb and observe algorithm that generates the voltage reference for the sliding-mode controller, which guarantees the system stability, tracks the maximum power point, and rejects the double-frequency oscillations generated by an intended microinverter.

Adaptive Maximum Power Point Tracking Control Algorithm for Wind Energy Conversion Systems

For small-scale wind energy conversion systems (WECSs), an adaptive maximum power point tracking (MPPT) algorithm is presented in this paper to increase wind energy harvesting. For its adaptability across a wide range of WECSs and quick tracking of maximum power point, the proposed algorithm combines the computational behavior of hill climb search, tip speed ratio, and power signal feedback control algorithms. Using buck–boost-featured single-ended primary inductor converters, the proposed MPPT algorithm is implemented in this paper to extract maximum power from the entire wind velocity profile. A laboratory-scaled dc motor drive-based WECS emulator is used to test the proposed algorithm. The in-lab experimental setup's control schemes are carried out with the help of a 32-bit floating point digital signal controller called TMS320F28335. The experimental results demonstrate that the proposed algorithm's tracking capability is effective and efficient in both sudden and gradual wind conditions.