Electric Wind Research Articles

Optimal Circle-to-Ellipse Orbit Transfer for Sun-Facing E-Sail

The transfer between two coplanar Keplerian orbits of a spacecraft with a continuous-thrust propulsion system is a classical problem of astrodynamics, in which a numerical procedure is usually employed to find the transfer trajectory that optimizes (i.e., maximizes or minimizes) a given performance index such as, for example, the delivered payload mass, the propellant mass, the total flight time, or a suitable combination of them. In the last decade, this class of problem has been thoroughly analyzed in the context of heliocentric mission scenarios of a spacecraft equipped with an Electric Solar Wind Sail as primary propulsion system. The aim of this paper is to further extend the existing related literature by analyzing the optimal transfer of an Electric Solar Wind Sail-based spacecraft with a Sun-facing attitude, a particular configuration in which the sail nominal plane is perpendicular to the Sun-spacecraft (i.e., radial) direction, so that the propulsion system is able to produce its maximum propulsive acceleration magnitude. The problem consists in transferring the spacecraft, which initially traces a heliocentric circular orbit, into an elliptic coplanar orbit of given eccentricity with a minimum-time trajectory. Using a classical indirect approach for trajectory optimization, the paper shows that a simplified version of the optimal control problem can be obtained by enforcing the typical transfer constraints. The numerical simulations show that the proposed approach is able to quantify the transfer performance in a parametric and general form, with a simple and efficient algorithm.

Environmental and health-related research on application and production of rare earth elements under scrutiny

BackgroundUnlike most other commodities, rare earth elements (REEs) are part of a wide range of applications needed for daily life all over the world. These applications range from cell phones to electric vehicles to wind turbines. They are often declared as part of “green technology” and, therefore, often called “green elements”. However, their production and use are not only useful but also risky to the environment and human health, as many studies have shown. Consequently, the range of global research efforts is broad and highly variable, and therefore difficult to capture and assess. Hence, this study aims to assess the global parameters of global research on REE in the context of environment and health (REEeh). In addition to established bibliometric parameters, advanced analyses using market driver and scientific infrastructure values were carried out to provide deep insight into incentives, necessities, and barriers to international research.ResultsThe focus of REE research is in line with national aspirations, especially from the major global players, China and the USA. Whereas globally, regional research interests are related to market interests, as evidenced by the inclusion of drivers such as electric vehicles, wind turbines, and permanent magnets. The topics receiving the most attention are related to gadolinium used for magnetic resonance imaging and the use of ceria nanoparticles. Since both are used for medical purposes, the medical research areas are equally profiled and mainly addressed in high-income countries. Nevertheless, environmental issues are increasingly in focus.ConclusionsThere is still a need for research that is independent and open-ended. For this, market-independent technologies, substitutes and recycling of REEs need to be addressed scientifically. The results of this study are relevant for all stakeholders, from individual scientists to planners to funders, to improve future research strategies in line with these research mandates.Graphical

Energy and exergy analysis of wind power plant: A case study of Gharo, Pakistan

Sustainable, inexhaustible, economical, and clean energy has become a vital prerequisite to replace fossil fuel sources for power production. In such a context, countries like Pakistan, which are heavily skewed towards fossil fuel-fired plants, are diverting attention to install more and more indigenous renewable energy sources projects such as solar-photovoltaic and wind turbine power plants. In order to harness the maximum energy of wind turbines, it is crucial to factually and precisely assess system performance, which is traditionally inferred by energy analysis (first law analysis). Nevertheless, this analysis only computes the nominal power generation output and ignores the effect of meteorological variables that can lead to some serious errors during the energy planning phase. Consequently, this case study presents both the energy and exergy analysis of a wind farm located in Gharo town of Thatta District along the coastline of the Indus Delta. Energy analysis is carried out to quantify energy efficiency, while exergy analysis computes exergy efficiency by taking into account the effect of pressure, temperature, and wind speed. Comparisons of both efficiencies are provided, and the result substantiates that exergy efficiency turns out to be lower than energy efficiency. However, exergy is a more viable index due to the inclusion of exergy destruction, and in comparison to the energy indicator, it presents the actual performance of a thermodynamic system. The monthly energy and exergy efficiency of the general electric wind turbines are maximum in July having values of 0.5 and 0.41, respectively.

Technical, economic, and environmental assessment of the distribution power system with the application of renewable energy technologies

Renewable energy technologies (RETs) have been universally accepted as the prospective choice to increase the reliability of the power system and reduce the effects of emission cost (EC), fuel cost (FC), maintenance cost (MC), power loss (PL), total annual cost (TAC) and voltage deviation (VD). The performance indicators are used in the study to assess the effects of diesel generator (DG), electric storage system (ESS), photovoltaic (PV) and wind turbine generator (WTG) on the environmental, economic, and technical performance of a microgrid system with modified Roy Billiton Test System (RBTS) bus 4 distribution network. The proposed model is utilized to achieve the goals of the study by minimizing the costs that are identified with the power outages, TAC, MC, EC, FC, PL, and VD of the system with the application of an intelligent optimal control method based on the fmincon solver. The outcomes of the study can be used as benchmarks to assess the cost-effectiveness of increasing the capacity of universal power supply and resolve the universal power crisis owing to the depletion of fossil fuels. The study provides vital information to enhance the efficiency of the power system and the guidelines to promote the development of sustainable energy.

Adaptive Controller with PID, FOPID, and NPID Compensators for Tracking Control of Electric – Wind Vehicle

This paper presents a new combination between the Model Reference Adaptive Control (MRAC) with several types of PID’s controllers (PID, Fractional order PID (FOPID), and Nonlinear PID (NPID)) optimized using a new Covid-19 algorithm. The proposed control techniques had been applied on a new model for an electric-wind vehicle, which can catch the wind that blows in the opposite direction of a moving vehicle to receive wind; a wind turbine is installed on the vehicle’s front. The generator converts wind energy into electricity and stores it into a backup battery to switch it when the primary battery is empty. The simulation results prove that the new model of electric–wind vehicles will save power and allow the vehicle to continue moving while the other battery charges. In addition, a comparative study between different types of control algorithms had been developed and investigated to improve the vehicle dynamic response. The comparison shows that the MRAC with the NPID compensator can absorb the nonlinearity (air resistance and wheel friction) where it has a minimum overshoot, rise time, and settling time (35 seconds) among other control techniques compensators (PID and FOPID).

Wind-assisted, electric, and pure wind propulsion – the path towards zero-emission RoRo ships

ABSTRACT Electrical and wind propulsion, together with energy stored in batteries and renewable energies harnessed onboard, can lead the way towards zero-emission ships. This study compares wind propulsion solutions and battery storage possibilities for a RoRo ship operating in the Baltic Sea. The ship energy systems simulation model ShipCLEAN is used to predict the performance of the zero-emission ship in real-life operating conditions. The study showcases how ships can be transferred from a conventional, diesel-powered to a zero-emission ship. For the zero-emission ship, all energy needed for auxiliaries and propulsion is taken from renewable sources onboard or from batteries. Challenges and opportunities, as well as necessary adaptions of the route and logistics, are discussed. Results of the study present which wind propulsion technology is the most suitable for the example RoRo ship, and how the installation of suitably sized battery packs for zero-emission operation affects the cargo capacity of the ship.

Discussion of Wind Turbine Performance Based on SCADA Data and Multiple Test Case Analysis

This work is devoted to the formulation of innovative SCADA-based methods for wind turbine performance analysis and interpretation. The work is organized as an academia–industry collaboration: three test cases are analyzed, two with hydraulic pitch control (Vestas V90 and V100) and one with electric pitch control (Senvion MM92). The investigation is based on the method of bins, on a polynomial regression applied to operation curves that have never been analyzed in detail in the literature before, and on correlation and causality analysis. A key point is the analysis of measurement channels related to the blade pitch control and to the rotor: pitch manifold pressure, pitch piston traveled distance and tower vibrations for the hydraulic pitch wind turbines, and blade pitch current for the electric pitch wind turbines. The main result of this study is that cases of noticeable under-performance are observed for the hydraulic pitch wind turbines, which are associated with pitch pressure decrease in time for one case and to suspected rotor unbalance for another case. On the other way round, the behavior of the rotational speed and blade pitch curves is homogeneous and stable for the wind turbines electrically controlled. Summarizing, the evidence collected in this work identifies the hydraulic pitch as a sensible component of the wind turbine that should be monitored cautiously because it is likely associated with performance decline with age.

Lynas wins US contract for rare earths

The US Department of Defense has awarded Lynas Rare Earths a $120 million contract to build a separation facility for heavy rare earth metals such as gadolinium, dysprosium, and ytterbium. The award follows the DOD’s $30 million grant to Lynas to build a light rare earths facility. Both projects will be on the same site in Hondo, Texas. DOD and Lynas say the materials will make the US a major supplier of rare earths, which are critical in electric vehicles, wind turbines, and electronics.

A Review: Machine Learning for Combinatorial Optimization Problems in Energy Areas

Combinatorial optimization problems (COPs) are a class of NP-hard problems with great practical significance. Traditional approaches for COPs suffer from high computational time and reliance on expert knowledge, and machine learning (ML) methods, as powerful tools have been used to overcome these problems. In this review, the COPs in energy areas with a series of modern ML approaches, i.e., the interdisciplinary areas of COPs, ML and energy areas, are mainly investigated. Recent works on solving COPs using ML are sorted out firstly by methods which include supervised learning (SL), deep learning (DL), reinforcement learning (RL) and recently proposed game theoretic methods, and then problems where the timeline of the improvements for some fundamental COPs is the layout. Practical applications of ML methods in the energy areas, including the petroleum supply chain, steel-making, electric power system and wind power, are summarized for the first time, and challenges in this field are analyzed.

A semi-analytical, numerical and experimental study on performance characteristics of a novel hybrid-rotor CVT magnetic gearbox

With the development of hybrid electric vehicles and wind turbines, the demand for improved efficiency, increased maintenance life, increased reliability, reduced noise, and environmental considerations has increased. Meanwhile, magnetic gearboxes, in particular the technology of continuous variable transmission (CVT) systems, provide an opportunity to meet these needs. In this paper, while presenting four topologies of a novel coaxial hybrid-rotor CVT magnetic gearbox with a consequent-pole high-speed rotor, a simple precise semi-analytical model is presented based on the subdomain method for calculating the magnetic performance characteristics of the gearboxes. Magnetic equations have been rewritten in a pseudo-Cartesian coordinate system, and by applying the appropriate boundary conditions and interface conditions, the general solution and their coefficients have been extracted using the separation of the variables method. The performance characteristics of four studied gearboxes were compared semi-analytically and numerically. A prototype coaxial consequent-pole magnetic gearbox has been fabricated and the results of semi-analytical modeling have been compared with the results of numerical simulations and the experimental tests. The maximum error percentage of the results of numerical simulations and experimental tests is about three, which shows that the proposed semi-analytical model has a high accuracy. A comparison of magnetic torque, torque ripple and induced voltage is carried out between the investigated designs.

One Step Forward to Electrically Assisted Forming Mechanisms and Computer Simulation: A Review

The electrically assisted forming (EAF) is a hybrid manufacturing process that utilizes electric current energy to improve the productivity and efficiency of the forming process. Many studies have been accomplished to investigate the effect of process parameters on its forming abilities, including pulse current effect, grain size, and current duration. There is currently a lack of agreement on the underlying mechanisms of the electroplastic effect to the formability of metallic materials through EAF, specifically on the Joule heating and electric wind's contributions. One promising solution to this dilemma is the application of computer simulation techniques for a better understanding of the physics of EAF. Therefore, this paper provides a brief review of the previous research studying the modeling of EAF and offers new solutions aiming to further the understanding of the underlying physics of this process through computer simulation approaches.

Adaptive composite frequency control of power systems using reinforcement learning

With the incorporation of renewable energy, load frequency control (LFC) becomes more challenging due to uncertain power generation and changeable load demands. The electric vehicle (EV) has been a popular transportation and can also provide flexible options to play a role in frequency regulation. In this paper, a novel adaptive composite controller is designed to solve the LFC problem for the interconnected power system with electric vehicles and wind turbine. EVs are used as regulation resources to effectively compensate the power mismatch. First, the sliding mode controller is developed to reduce the random influences caused by the wind turbine generation system. Second, an auxiliary controller with reinforcement learning is proposed to produce adaptive control signals, which will be attached to the primary proportion-integration-differentiation control signal in a real-time manner. Finally, by considering random wind power, load disturbances and output constraints, the proposed scheme is verified on a two-area power system under four different cases. Simulation results demonstrate that the proposed adaptive composite frequency control scheme has a competitive performance with regard to dynamic performance.

A game theory-based price bidding strategy for electric vehicle aggregators in the presence of wind power producers

A game theory-based approach was proposed for energy exchange between the electric vehicles (EV) load and wind power producers (WPP) active in the regulation, balancing, and day-ahead markets. An optimal Bidding strategy was developed to reduce risks arising from the wind energy–EV imbalance in the energy markets where EV aggregators (EVAs) Bid price packages to WPPs for charging or not charging EVs to compensate for energy deviations. Generally, the WPP collects price Bids by aggregators to determine the share of each aggregator in energy exchange contracts by maximizing its profit function. On the other hand, there is competition between EV aggregators to sell their services to WPPs for compensating losses of EV owners. A non-cooperative game was to serve as a model for the competition among EV aggregators due to insufficient information. The Nash equilibrium was employed to solve this non-cooperative game.

Deep learning-based nonlinear model predictive control of the attitude manoeuvre of a barbell electric sail through voltage regulation

An electric solar wind sail (electric sail or E-sail) is a new type of propulsion system that does not require propellant. This paper proposes a nonlinear model predictive control law based on deep learning to control the attitude of a barbell electric sail. A barbell E-sail is composed of two tip satellites connected via long conductive tethers to a central insulated confluence point. The two tethers are insulated from each other at the confluence point such that the voltages of the two tethers can be independently controlled. The attitude dynamics of the system is modelled using a nonsingular description of tether orientation. To reduce online computation loads, the proposed control scheme has a two-stage design, namely, an offline stage and an online stage. In the offline stage, a large amount of data is generated using the nonlinear model predictive control law and then taken as a dataset to train a deep neural network. In the online stage, feedback control of the system attitude is achieved with extremely low computational cost by performing real-time mapping from the system state to the control output using the trained deep neural network. Finally, the efficacy and performance of the proposed deep learning-based control law are demonstrated via numerical case studies.

Changes of electric field, aerosol, and wind covariance in different blowing dust days in West Texas

• Dust events influence the atmospheric vertical electric field ( E z ). • Not all dust events generate similar E z value, with similar relationship to PM 2.5 . • . E z associated with a reduction of visibility and an increase wind speed and gust. • Opposite pattern between winds and E z were observed at higher frequencies. Blowing dust events are common meteorological phenomena that can influence the atmospheric vertical electric field ( E z ). In this work we examine different local blowing dust days in Lubbock, Texas in order to understand their impact on the local vertical electric field, and the relationships of the vertical E z to horizontal wind speeds, visibility, relative humidity, temperature and PM 2.5 (particles with aerodynamic diameter <2.5 μm). All blowing dust days had an increase in E z , but they did not generate similar E z patterns. Several of the blowing dust days had an expected increase in E z with a reduction of visibility and an increase in PM 2.5 , wind speed, or wind gusts. But others were more complex without a direct relationship between E z and PM 2.5 . Variability of E z at different time scales was examined, including correlation tests with wind speed, visibility, PM 2.5 , temperature, or relative humidity for each blowing dust event and overall. The complexity found, including a decorrelation time scale between wind speeds and E z at relatively high frequencies, emphasizes the sensitivity of the dust events in this region and the dependence on the analysis interval used in this study.

Longitudinal Variability of the Vertical Drift Velocity Inferred from Ground-Based Magnetometers and C/NOFS Observations in Africa

This study aims at discussing longitudinal effects on the variability of the vertical E × B drift velocity at low latitudes, specifically over African sector. To this effect, observations from ground-based magnetometers and the Ion Velocity Meter experiment onboard C/NOFS satellite are analyzed in conjunction with equatorial electric field and neutral wind model estimates under geomagnetically quiet conditions in the years 2012-2013. Notwithstanding the limitation in data over Africa, the combination of ground-based and in-situ observations confirmed the existence of longitudinal differences in the E × B between the Atlantic, Western and Eastern African sectors. This was well reproduced by the equatorial electric field model (EEFM) which showed that during noon, the peak of the equatorial electric field (EEF) was the lowest in the Atlantic sector, with an increasing trend towards the Eastern longitude. The Horizontal Wind Model 14 (HWM14) showed that the eastward zonal (poleward meridional) wind velocity was the lowest (highest) in the Eastern sector. Furthermore, the zonal (meridional) wind increased (decreased) from the Eastern to the Atlantic sector. These results highlight the contribution of the neutral wind velocity in driving the longitudinal difference in the vertical drift velocity over Africa.

Novel Three-Layer Discontinuous PWM Method for Mitigating Resonant Current and Zero-Crossing Distortion in Vienna Rectifier With an LCL Filter

Vienna rectifier is widely employed in the electric vehicle charging system and wind turbine system due to its higher efficiency and lower total harmonic distortion. However, the Vienna rectifier with the LCL filter has the challenge of resonant current mitigation, current zero-crossing distortion elimination, neutral point (NP) voltage balance and switching loss reduction. Moreover, these problems are mutually coupled. To overcome these issues, the causes of resonant current with the conventional discontinuous pulsewidth modulation (PWM) (DPWM) method is analyzed, which reveals that the abrupt change of reference voltage has a wide range harmonics band and easily induces the resonant current at resonant frequency. Then, based on the analysis, a novel three-layer DPWM method with three offset voltages injection is proposed. In the first layer, the NP voltage balance is realized by injecting the first offset voltage. In the second layer, the second offset voltage, which makes the discontinuous reference voltages smooth is presented to reduce the losses and suppress the resonant current. In the third layer, the third offset voltage is elaborated to eliminate current zero-crossing distortion caused by different power factor and the LCL filter. Based on the proposed method, resonant current mitigation, current zero-crossing distortion elimination, NP voltage balance are realized simultaneously with reduced switching losses. The effectiveness and performance of the proposed method are verified by simulation and experiment.

The Application of Small-Scale and Large-Scale Wind Turbines in Kerman, Iran; A Case Study

Wind data collected of the three synoptic sites for the period of Jul 2006 to Jun 2008 at the height of 40 m has been used to study the wind characteristics, monthly and annual wind energy potential for three agricultural districts in Kerman ( 30°15/N, 56°58/E ), Iran. Two statistical methods (Meteorological and Weibull) have been applied to determine the wind characteristics. Wind energy density, mean wind speeds and wind speed directions have been investigated. A technical assessment has been done and the electricity generation from five different wind turbines having capacity of (26 kW, 100 kW, 300 kW, 600 kW and 660 kW) has been calculated. The results show that all the locations studied are not suitable for electric wind application in a large-scale.

Observing electric field and neutral wind with EISCAT 3D

Abstract. Measurements of height-dependent electric field (E) and neutral wind (u) are important governing parameters of the Earth's upper atmosphere, which can be used to study, for example, how auroral currents close or how energy flows between the ionized and neutral constituents. The new EISCAT 3D (E3D) incoherent scatter radar will be able to measure a three-dimensional ion velocity vector (v) at each measurement point, which will allow less stringent prior assumptions about E and u to be made when estimating them from radar measurements. This study investigates the feasibility of estimating the three-dimensional electric field and neutral wind vectors along a magnetic field-aligned profile from E3D measurements, using the ion momentum equation and Maxwell's equations. The uncertainty of ion drift measurements is estimated for a time and height resolution of 5 s and 2 km. With the most favourable ionospheric conditions, the ion wind at E region peak can be measured with an accuracy of less than 1 m/s. In the worst case, during a geomagnetically quiet night, the uncertainty increases by a factor of around 10. The uncertainty of neutral wind and electric field estimates is found to be strongly dependent on the prior constraints imposed on them. In the lower E region, neutral wind estimates have a lower standard deviation than 10 m/s in the most favourable conditions. In such conditions, also the F region electric field can be estimated with uncertainty of about 1 mV/m. Simulated measurements of v are used to demonstrate the ability to resolve the field-aligned profile of E and u. However, they can only be determined well at the heights where they dominate the ion drift, that is above 125 km for E and below 115 km for u. At the other heights, the results are strongly dependent on the prior assumptions of smoothness.

Research Trends and Future Research Directions of Permanent Magnetic Materials

Permanent magnetic materials are essential for converting mechanical and electric energy, and are needed in electric vehicles, electronics, wind turbines, and etc. However, high performance rare-earth element based magnets have many limitations, including critical materials problems and the degradation of magnetic properties at elevated temperatures. There has been increasing international demand to solve these problems, and to develop new magnets with reduced rare earth materials, or free magnets based on metallic alloys. This paper describes current research trends, and state of art and future research directions for next generation permanent magnetic materials, to accelerate their research and rapid industrialization.