Floating Offshore Wind Turbine (FOWT) is an innovative technology with little industry guidance for its hull design. Various FOWT floaters with different hull shapes claim to support the same turbines. Structural integrity and material expense analyses of different pontoon shapes were conducted, and it was found that some configurations, such as those with every two columns connected by both pontoon and bracing, have advantages over others. However, it is important to note that the choice of pontoon shape should be based on the wave loading conditions the floater will be exposed to. While a T-shaped pontoon provides a cost-effective solution under certain wave loading scenarios, it may not be the best option for all conditions. Specifically, ring pontoon designs with full bracing were found to be necessary for withstanding certain wave loads. Therefore, it is important to consider different Dominant Load Parameters (DLP) and ensure that a FOWT floater can withstand all applicable DLPs. An uneven hexahedral column shape, which combines the best attributes of square and round shapes, is proposed as a better alternative to cylindrical columns. It offers ease of manufacture and reasonably low drag. Bracing is found to be necessary for withstanding the wind turbine’s incurred moment and forces. The conclusion is that platform design should prioritize manufacturing costs and strength over maximizing hydrodynamic performance.

In the context of energy decarbonization, wind farms with type IV wind turbines from various manufacturers are being massively put into operation. These wind turbines comply with the requirements of the grid codes of the countries where they are designed and/or manufactured, but do not factor in the specific features of the distribution networks of other countries to which they are connected. The study at issue involves a comparative analysis of the requirements of grid codes of different countries for the stable operation of wind turbines under standard disturbances. The Low Voltage Ride Through (LVRT) characteristic implemented in type IV wind turbine inverters makes it possible to prevent wind turbine shutdowns in case of short-term voltage dips of a given depth and duration. The calculations of transient processes indicate that wind turbines may not meet the requirements of the grid code of a particular country for their stable operation. As a result, standard disturbances will block the reactive current injection and the wind turbine will be switched off. This is often caused by the relay protection devices with a time delay of 1-2 s, which are used in distribution networks and implement the functions of long-range redundancy. Excessive shutdowns of wind turbines lead to emergency rise in the load for the generating units of conventional power plants, aggravating the post-accident conditions and disconnecting consumers of electricity. The paper presents a method for checking the LVRT characteristic settings for compliance with the technical requirements for wind turbines. To prevent wind turbine outages, one should either change the configuration of the LVRT characteristic, or upgrade the relay protection devices in the distribution network adjacent to the wind farm, or implement group or individual technical solutions at the wind farm. The performance of the proposed technical solutions is confirmed by the calculations of transient processes.

Purpose – Extend the Blade Element Momentum Theory (BEMT) such that rotors with pronounced cone and axis angle (tilt or yaw) can be calculated. Derive an equation for the speed ratio (lambda) as a function of Tip Speed Ratio (TSR), radius, blade, cone and axis angle. This converts the BEMT into an Unsteady BEMT or UBEMT. Present the Wagner rotor as one such rotor geometry. --- Methodology – Literature review and calculations. --- Findings – The UBEMT can be used to calculate highly unconventional rotor geometries. --- Research Limitations – Although the aerodynamic coefficients used in the UBEMT are from measurements in steady flow conditions, they can be used with success. --- Practical Implications – Also conventional Horizontal Axis Wind Turbines (HAWT) with noticeable cone and axis angle should be calculated with the UBEMT. The accuracy of power calculations of these HAWTs can be slightly improved. --- Originality – Analytic equations for rotors with cone and axis angle have barely been discussed.

Full-scale/model test comparison studies to validate the traditional ABL wind tunnel simulation technique are reviewed. According to the literature review, notable discrepancies between full-scale measurement results and model test results were observed by most performed comparison studies, but the causes of the observed discrepancies were not revealed in a scientific way by those studies. In this regard, a new research scheme for future full-scale/model test comparison studies is proposed in this article, which utilizes the multiple-fan actively controlled wind tunnel simulation technique. With the new research scheme, future full-scale/model test comparison studies are expected to reasonably disclose the main problems with the traditional ABL wind tunnel simulation technique, and the technique can be improved correspondingly.

The energy transition to wind and solar opens opportunities for green hydrogen as the wind and solar generation tends to bring electricity prices down to very low levels. This paper evaluates whether green hydrogen can integrate well with wind and solar PV to help with improved management of the South Australian electricity grid. Green hydrogen can use membrane electrolysis plants during surplus renewable energy periods. This hydrogen can then be electrified or used in industry. The green hydrogen system was analysed to understand the financial viability and technical impact of integrating green hydrogen. We also used systems engineering techniques to understand the system holistically, including the technical, social, environmental, and economic impacts. The results show opportunities for the system to provide seasonal storage, grid firming, and reliability services. Financially, it would need changes to electricity rules to be viable, but without those changes, our modelling suggested it would be financially viable within this decade

In the present work, a methodology for wind field reconstruction based on the Meteo Particle Model (MPM) from Numerical Weather Prediction (NWP) data is presented. The development of specific wind forecast services is a challenging research topic, in particular for what concerns the availability of accurate local weather forecasts in highly populated areas. Currently, even if NWP Limited Area Models (LAMs) are run at spatial resolution of about 1 km, this level of information is not sufficient for many applications, for example to support drone operation in urban contexts. The coupling of MPM with the NWP Limited Area Model COSMO has been implemented in such a way that the MPM reads the NWP output over a selected area and provides wind values in the generical point considered for the investigation. The numerical results obtained reveal a good behavior of the method in reproducing the general trend of wind speed, as confirmed also by the power spectra analysis. The MPM is able to step over the intrinsic limitations of the NWP model in terms of spatial and temporal resolution even if the MPM inherits the bias that inevitably affects the COSMO output.

This paper performs a comprehensive analysis of the wind energy potential of onshore regions in Greece with emphasis on quantifying the volume risk and the spatial covariance structure. Optimization techniques are employed to derive efficient wind capacity allocation plans (also known as generation portfolios) incorporating different yield aspirations. The generation profile of minimum variance and other optimal portfolios along the efficient frontier are subject to rigorous evaluation using a fusion of descriptive and statistical methods. In particular, principal component analysis is employed to estimate factor models and investigate the spatiotemporal properties of wind power generation, providing valuable insights into the persistence of volume risk. The overarching goal of the study is to employ a set of statistical and mathematical programming tools guiding investors, aggregators and policy makers in their selection of wind energy generating assets. The findings of this research challenge the effectiveness of current policies and industry practices, offering a new perspective on wind energy harvesting with a focus on the management of volume risk.

Extensive surface and upper air measurements of a typhoon over the northern part of the South China Sea, namely, Typhoon Talim in July 2023, are documented and analyzed in this paper. A number of features have been observed from the upper air measurements. First, the log law and the power law are found to be appropriate in fitting the wind profiles of the typhoon in the first 1000 m or so above the sea surface. A low level jet is observed in the lower troposphere from the observations of the radar wind profilers. The paper is also novel from the perspectives that the vertical wind profile from a Doppler LIDAR on an offshore platform over the northern part of the South China sea, and that ocean radar data are used to analyze the surface wind observations of a typhoon in the region. The results of this paper would be useful in understanding the structure of tropical cyclones, e.g. in wind engineering applications.

Currently, there are different types of technology for the production of electricity that use various energy sources, this causes the establishment of generation centers that provide from a small amount to tens of megawatts of electrical energy. These centers are built to supply electricity to nearby loads through networks integrated into a large electrical system or in isolation with their electrical system. The technological evolution, the different energy sources, and the generation centers close to the consumers entail what has been called a distributed generation (DG), the DG carries with it aspects that need to be analyzed. In this paper, the impact of wind generation on the medium voltage energy distribution network is studied, it was determined that the addition to the distribution network of power by wind turbines less than the transmission center does not produce an impact on the network. Simulated results obtained using SIMULINK and DIgSILENT are presented and discussed.

This work compared the performance of three methods for constructing a regional ensemble prediction system (EPS) for wind speed forecasts: dynamical downscaling, breeding of growth modes (BGM), and blending method. The Weather Research and Forecasting (WRF) model was used to downscale the European Centre for Medium-range Weather Forecast (ECMWF) EPS. In addition, as the BGM method needs observation data for generating scaling factors, an alternative method for generating scaling factors was proposed to eliminate dependence on observation data. One-month tests between October 1st and October 30th, 2020, were implemented to evaluate the performance of three methods in the Gansu province of China. The results demonstrate that the blending method outperforms the other two methods. Furthermore, the difference in performance is evident mainly in early forecast lead time and becomes negligible as forecast time increases.

SStatistical characteristics of the wind speed in Samaria region of Israel have been analyzed by processing 11 years of wind data provided by the Israeli Meteorological Service, recorded at 10 m height above the ground. The cumulative mean wind speed at measurement height was shown to be 4.53 m/s with standard deviation of 2.32 m/s. Prevailing wind direction is shown to be char-acterized by cumulative mean azimuth of 226° with standard deviation of 79.76°. The results were extrapolated to 70-meter height in order to estimate wind characteristics at hub height of a me-dium-scale wind turbine. Moreover, Weibull distribution parameters were calculated annually, monthly and seasonally, demonstrating a good match with histogram-based statistical repre-sentations. Shape parameter of the Weibull distribution was shown to reside within a narrow range of 1.93 to 2.15, allowing us to assume a Rayleigh distribution, thus simplifying wind tur-bines energy yield calculations. The novelty of the current paper is related to gathering wind statistics for a certain area (Samaria) we are not aware of any published statistics regarding wind velocity and direction in this area. The data may be interesting for potential regional wind energy development in which the obtained Weibull distribution can be used in calculations of expected power generation of particular turbines with known power dependence on velocity. We also point out that the fact that realistic wind velocity statistics is well described by an analytic formula (Weibull distribution) is not trivial, and in fact the fit may have been poor.

This study examines the effect of surface currents on the bulk algorithm calculation of wind stress estimated using the scatterometer data during 2007-2020 in the Indian Ocean. In the study region as a whole the wind stress decreased by 5.4% by including currents into the wind stress equation. The most significant reduction in the wind stress is found along the most energetic regions with strong currents such as Somali Current, Equatorial Jets and Aghulhas retroflection. A highest reduction of 11.5% is observed along the equator where the Equatorial Jets prevail. A sensitivity analysis has been carried out for the study region and for different seasons to assess the relative impact of winds and currents in the estimation of wind stress by changing the winds while keeping the currents constants and vice versa. The inclusion of currents decreased the wind stress and this decrease is prominent when the currents are stronger. This study showed that equatorial Indian Ocean is the most sensitive region where the current can impact on wind stress estimation. The results showed that uncertainties in the wind stress estimations are quite large at regional levels and hence better representation of wind stress incorporating ocean currents should be considered in the ocean/climatic models for accurate air-sea interaction studies.

The limitedness of the nonrenewable local energy resources in Israel, even in background of the later gas fields’ findings, continues to force the state to devote various efforts for the ‘green’ energy development. These efforts include installations both in the solar and in the wind energy, with a purpose to improve the diversity of energy sources. While the standard discounted cash flow (DCF) method using the net present value (NPV) criterion is extensively adopted to evaluate investments, the standard DCF method is inappropriate for the rapidly changing investment climate and for the managerial flexibility in investment decisions. In recent years, the real options analysis (ROA) technique is widely applied in many studies for valuation of renewable energy investment projects. Hence, we apply in this study the real options analysis approach for the valuation of wind energy turbines and apply it to the analysis of wind energy economic potential in Israel.

Integration of wind energy into the grid faces a great challenge regarding power quality. The International Electrotechnical Commission (IEC)~61400-21 standard defines the electrical characteristics that need to be assessed in a Wind Turbine (WT), as well as the procedure to measure the disturbances produced by the WT. One of the parameters to be assessed are voltage fluctuations or flicker. To estimate the flicker emission of a Wind Power Plant (WPP), the standard establishes that a quadratic exponent should be used in the summation of the flicker emission of each WT. This exponent was selected based on studies carried out in WPPs with type I and II WTs. Advances in wind turbines technology have reduced their flicker emission, mainly thaks to the implementation of power electronics for the partial or total management of the power injected into the grid. This work is based on measurements from a WPP with 16 type III WTs. The flicker emission of a single WT and of the WPP were calculated. Low flicker emission values at the Point of Common Coupling (PCC) of the WPP were obtained. The flicker estimation at the PCC, based on the measurement from a single WT, was analyzed using different exponents. The results show that a cubic summation performs better than the quadratic one in the estimation of the flicker emission of a WPP with type III WTs.

The paper deals with the problem of choosing the best O&M strategy for wind power plants. Current maintenance theory considers just production opportunities and minimizes the maintenance costs, but with the liberalization of the electricity market also the electricity price has become an important variable to take into account in the O&M scheduling. Another important variables that is often neglected by the existing maintenance theory is the weather condition. This paper proposes a new strategy that takes into account the electricity price and weather conditions, improves the expected profit of the systems, and reduce the overall maintenance and logistic costs. The maintenance schedule is formalized as an optimization problem where the discounted cumulative profit of a wind generation portfolio in a fixed-time horizon (e.g. two years ahead), subject to the technologically-derived maintenance time constraints is optimized. Both the theoretical and computational aspects of the proposed O&M strategy are discussed. Results show that taking into account market and weather opportunities in the design of the maintenance strategy, it is possible to achieve a more complete scheduling for a given set of wind power plants.

This article presents a study conducted within a wind tunnel to enhance understanding of the excitation mechanism of stay cable vibration under arid conditions. Numerous wind tunnel tests were meticulously analyzed. Initially, the vibration of the stay cable was measured under steady flow conditions at a flow angle of 45 degrees and an inclination of 25 degrees, while varying wind velocities were applied. Additionally, an investigation into the flow field surrounding the stay cable was conducted in both vertical and horizontal directions. By utilizing two hot wire anemometers in the cable wake, an extensive database of flow field measurements was obtained. The experimental results revealed that the vibration characteristics of the stay cable under the arid conditions considered in this study aligned with findings reported in existing literature. Notably, a deeper comprehension of the excitation mechanism of a stay cable in a dry state was attained. This mechanism is closely associated with the inhibition of Karman vortices and the development of low-frequency vortices. At low wind speeds, Karman vortices predominated, resulting in small-amplitude vibrations. However, as the wind speed increased, the influence of Karman vortices diminished progressively, while the low-frequency vortices grew stronger. These low-frequency vortices exhibited high energy and a significant correlation with shedding along the stay cable, thereby inducing cable vibration in a dry environment.

The survey findings reveal that rivers worldwide carry an annual sediment load of 15 billion tons into the sea, and the Yellow River basin alone contributes 1.6 billion tons of sand. Therefore, understanding the science of wind and sand in the Yellow River is crucial to ensuring the safe development of similar basins across China and the world. This study examines the midstream wind and sand area of the Xiliugou tributary, a part of the upper Yellow River. The researchers used a stepped sand collector combined with an anemometer to measure the sand transport flux at 0-50 cm height on various underlying surfaces of the basin. Then, they estimated the amount of wind and sand entering the Yellow River using a function model based on the measured factors. Furthermore, the team analyzed the particle size composition of wind-eroded sand to better understand the principles of wind and sand erosion and accumulation in the basin. The results of the study show that the sand transport flux per unit area varies significantly across different underlying surfaces. Moreover, the contribution of moving sandy land, semi-fixed sand, and fixed sand to wind and sand deposition in the Yellow River basin was 77.08%, 15.30%, and 7.62%, respectively. The vertical change of sand transport rate on the basin's surface demonstrates that the total sand transport rate is an exponential function of wind speed. Based on this relationship, the researchers estimated that the total annual average wind and sand entering the Yellow River basin via the Xiliugou tributary is approximately 8.09×105t. Due to the basin's unique geography and sand source, the particle size composition of wind-eroded sand differs between the east and west sides of the river channel. On the west side, desert sand, mainly fine sand, and very fine sand constitutes the sand source. Conversely, on the east side, sand collected in the riverbed by secondary wind erosion is the primary sand source. Furthermore, human activities have disturbed the grain composition, mainly comprising powder and clay particles. This phenomenon, known as "wind-blown mud and water-washed sand," is evident in this geographical unit. In conclusion, the Yellow River basin still faces significant ecological security hazards. Understanding the coupling relationship between desert-basin-sand and wind is the foundation for effectively controlling wind and sand flow into the Yellow River basin.

With the rapid development of global offshore wind power, the demand for offshore wind power operation and maintenance is also increasing. Wisdomization of offshore wind farms is a practical need to improve the operation level and benefit of offshore wind farms. This paper first introduces the current development situation and characteristics of global offshore wind power, and expounds the current situation and main challenges of offshore wind power operation and maintenance market. Therefore, our paper discusses the innovation of offshore wind power operation and maintenance from the aspects of operation and maintenance management of offshore wind power, monitoring and analysis technology of units, far-reaching wind field monitoring and operation and maintenance risks. Then, combined with information technology and lean management concept, a smart operation and maintenance management platform for wind farms in far-reaching sea areas is built to explore centralized and intelligent operation and maintenance management mode, improve operation and maintenance efficiency of wind farms in far-reaching sea areas, and minimize operation and maintenance costs. Finally, through the research on the characteristics of 5G technology, combined with the practical experience of operation and maintenance, and in view of the characteristics of offshore wind farms, we analyze and propose several typical application scenarios of 5G technology in the intelligent operation and maintenance of offshore wind farms, which provides a new solution for the efficient operation and maintenance of offshore wind farms.

In this paper, dual-rotor counter-rotating (CR) configurations of vertical axis wind turbines (VAWT) are briefly inspected and divided into three types. This investigation was focused on one of these types – the CR-VAWT with co-axial rotors, in which two equal rotors are placed on the same shaft, displaced from each other along it and rotate in opposite directions. For this CR-VAWT with three-blade H-Darrieus rotors, the properties of the design in terms of aerodynamics, mechanical transmission and electric generator, as well as control system are analyzed. A new direct-driven dual-rotor (DR) permanent magnet synchronous generator (PMSG) was proposed, in which two built-in low-power PM electric machines have been added. They perform two functions – start-up and overclocking of the rotors to the angular velocity at which the lifting force of the blades is generated and stabilizing the CR-VAWT work as wind gusts act on the two rotors. Detailed in this paper is the evaluation of aerodynamic performance of the CR-VAWT via 3D computational fluid dynamics (CFD) simulations. The evaluation was conducted using the CONVERGE CFD software with the inclusion of the actuator line model for the rotor aerodynamics, which significantly reduces the computational effort. Obtained results show that both rotors, while they rotate in opposite directions, had a positive impact on each other: the power coefficients of the upper and lower rotors in the CR-VAWT increased by 5.5% and 13.3% respectively compared to the single-rotor VAWT at the optimal distance between the rotors of 0.3 from a rotor height.

The prediction of wind power output is part of the basic work of power grid dispatching and energy distribution. At present, the output power prediction is mainly obtained by fitting and regressing the historical data. The medium- and long-term power prediction results exhibit large deviations due to the uncertainty of wind power generation. In order to meet the demand for accessing large-scale wind power into the electricity grid and to further improve the accuracy of short-term wind power prediction, it is necessary to develop models for accurate and precise short-term wind power prediction based on advanced algorithms for studying the output power of a wind power generation system. This paper summarizes the contribution of the current advanced wind power forecasting technology and delineates the key advantages and disadvantages of various wind power forecasting models. These models have different forecasting capabilities, update the weights of each model in real time, improve the comprehensive forecasting capability of the model, and have good application prospects in wind power generation forecasting. Furthermore, the case studies and examples in the literature for accurately predicting ultra-short-term and short-term wind power generation with uncertainty and randomness are reviewed and analyzed. Finally, we present prospects for future studies that can serve as useful directions for other researchers planning to conduct similar experiments and investigations.

Sudden variation of aerodynamic loads is the potential source of safety accidents of high-speed train (HST). As a follow-up investigation on the aerodynamic response of a HST that enters a tunnel under crosswind environment, this paper focuses on the transient response of a HST’s safety indices based on the train–track coupling interaction model. Firstly, a wind–train–track coupling dynamic model is proposed by introducing transient aerodynamic loads into the vehicle–track system. Secondly, the temporal evolution of safety coefficients indicates that the train’s safety risk increases during tunnel entry with crosswind. Results show that the derailment coefficients and wheel load reduction rate during tunnel entry are not only larger than those in open air but also those inside the tunnel due to the sudden disappearance of wind excitation at the tunnel entrance. In addition, the characteristic wind curve, which is the wind velocity against the train speed, is presented for application based on the current specification of the safety criteria threshold. The investigation will be useful in assessing the safety risk of a running train subjected to other aerodynamic attacks, such as the coupling effect of infrastructure scenario and crosswind in windy area.

Presently, Jordan confronts a double substantial challenge of enhancing energy security and mitigating greenhouse gas emissions. One of the most encouraging avenues to attain the objectives of sustainable development, energy security, and environmental conservation is to enhance the integration of renewable energy into the generation of electricity. In pursuit of this goal, the Jordanian government intends to expand investments in the green energy sector, with solar and wind energy poised to play a key role in satisfying energy demands and cultivating an environmental sustainability. This paper aims to examine the distinctive dynamics, challenges, obstacles, and potential solutions corresponding to the establishment of community solar and wind farms in Jordan suburban areas. It aims to highlight the opportunities and barriers influencing the track of sustainable energy adoption in the country. Through a comprehensive analysis of the Jordanian context, the goal is to extract insights that can guide policies and practices. Additionally, the findings may serve as a valuable benchmark for other regions confronting similar challenges on their pursuit for a sustainable energy future.

Climate research shows that extreme weather events and their effects are increasing in frequency, severity, and impact. Extreme wind events can cause massive societal and economic damage. High wind occurrences and their causes must be identified because they are hard to define and understand. Extreme wind modeling affects wind power plant planning, installation, and building modeling. This applies to city, vegetation, and vegetational area modeling. The scientific literature utilizes statistical, dynamic (Weather Research and Forecasting-WRF), and machine learning methods to identify extreme wind speeds. This study explores the relationship between lower-level extreme wind speeds and upper-level parameters like Z500, and T850 based on cluster analysis. The aim is to explore the correlation between upper-level atmospheric dynamics and lower-level wind behavior. K-Means cluster analysis method was employed to classify Turkish regions with similar severe wind episodes. WRF model simulation findings from NEWA (New European Wind Atlas) project (2019) were used for that purpose. The NEWA project's wind speed data at 100m a.g.l. was used for cluster analysis. We simplify the process by grid point reduction and applying the top 2% percentile as threshold value. Self-Organized Maps (SOM) clustering was also applied using the upper-level variables.

The maritime sector, grapples with environmental challenges, but the adoption of "cold ironing" emerges as a promising solution, signifying a shift toward sustainability by providing energy to ships at port, reducing reliance on fossil fuels, and significantly lowering emissions, contributing to global climate change efforts. This transition towards renewable energy is especially crucial for islands like Lesvos, addressing challenges of high energy costs and environmental degradation resulting from reliance on imported fossil fuels, highlighting the potential for positive economic and environmental impacts. The existing literature highlights a research gap in the development of Renewable Energy Sources (RES) to support cold ironing operations, specifically due to the absence of specific data for the power demand needed in such operations and the lack of monitoring data for accurate calculations. This study's primary objective is to utilize real monitoring data from the port of Lesvos to evaluate the power demand for a potential cold ironing application. Additionally, the study aims to analyze the implementation of a wind power park to meet the energy needs of an electric port and evaluate the potential reduction in CO2 emissions. The database of Marine Traffic S.A. was utilized, while the determination of the energy used in-port per ship depended on factors such as the number of arrivals, the duration of hoteling, and the type of engine used by the ships. In addition, the software RETSCREEN was used for the energy analysis of a simulated 20 MW wind park that can support the in-port operations. The combined monthly energy demand for both main and auxiliary engines of shipping vessels at Mytilini port was assessed to be 6118 MWh and averaging a power demand equaled to 8.2 MW. The simulation analysis indicates that the annual electricity delivered to the port can be72080 MWh, with a significant portion remaining unused and exported to the grid, amounting to 14956 MWh annually. Due to demand fluctuations, in-port activities require an additional 924 MWh from the main electrical grid, which highlights the importance of additional measures like energy storage and demand-response practices for the gradual transition to 100% Renewable Energy Sources (RES) operations.

This paper is devoted to the analysis of fluctuations in the solar wind plasma and interplanetary magnetic field parameters observed by Solar Orbiter and WIND spacecraft at different scales, ranging from ~10^3 to 10^7 km. We investigated two long observation intervals when the spacecraft were near the Sun-Earth line, during which the distance between the spacecraft was 0.1 and 0.5 AU respectively. It is analyzed how the fluctuation properties in different types of SW, associated with quasi-stationary and transient solar phenomena, transform on the way from the Sun to the Earth. It is shown that the time series behavior of the bulk speed subject to the least change even at the large distance between the observation points, while the time series of the IMF magnitude, components and proton density were significantly transformed even at the relatively short distance. Regardless of the assumed change in the absolute value of the parameters, the conducted statistical analysis shows that the characteristics of their fluctuations (including the level of intermittency) remains near constant regardless of the distance between the observation points and depends mostly on the type of the solar wind.

Renewable energy research becomes increasingly necessary as it grows in importance. Wind turbines are an excellent method of harnessing wind energy, which is one of the most important renewable energy sources. In light of the importance of studying wind turbine performance, this study describes the background and principles of wind turbine operation. Computational fluid dynamics (CFD) was used to evaluate the hydrodynamic performance of two types of offshore and onshore wind turbines. Mechanical power and thrust force are calculated using the CFD model for both types of turbines in a steady state based on the number of blades and rotors. The results of three-dimensional simulations are compared with those of experimental testing. Based on the method and assumptions used, the offshore turbine's mechanical torque showed an average deviation of about 4%. Increased wind speed increased mechanical power and thrust, while turbulence caused irregular pressure distributions on surfaces as a result of turbulence intensity. Furthermore, as the free wind speed increases, the blade tip and hub speed will also increase, expanding the vortices created by that flow.

The close proximity of different buildings heights can cause disturbances in the working of the smoke and ventilation ducts of lower buildings, threatening the health and even the lives of residents. To define the influence of high-rise building on the work of the ducts of the neighbouring double-storied building, experimental investigations in the wind tunnel were conducted. On this basis, empirical equations and graphs were developed leading to determining the aerodynamic coefficients considering different wind directions and the height of ducts. The direction of the wind reveals a greater influence than the height of the ducts. Properly using deflectors or increasing the height of the duct ensures maintaining static rarefaction in the area of smoke and ventilation ducts. The creation of rarefaction ensures the reliability of the natural ventilation system and the safety of the health of residents.

The overcrowding of high-rise buildings in the city adversely affects the wind environment by changing the air currents in the surrounding areas. In particular, extreme climate phenomena caused by climate change are stronger and more frequent, causing social damages in cities. To comprehensively better understand the wind properties around high-rise buildings, actual filed measurement is necessary to determine the environment assessment of wind effect. We performed the on-site measurement on LCT residential complex regions (411.6m tall) with highly concentrated high-rise buildings in coastal city Busan, South Korea under extreme weather conditions such as typhoon invasions to determine wind fluid characteristics. In the field monitoring, five anemometers were installed to analyze the wind environment around high-rise buildings when typhoon 'Hinnamnor' invaded. Compared to the nearby weather station operated by KMA(Korea Meteorological Administration), the gust was 3.7 times stronger and the max 1 min-mean wind speed was 3.1 times stronger, and the characteristics of the downward wind and the canyon wind were shown depending on the location characteristics of the point. Turbulence intensity decreased as the wind speed increased and converged to a certain value. Likewise, the gust factor also decreased as the wind speed increased and converged to 2.0, which is considered to be the parameter that best represents the intensity of the instantaneous gust caused by the skyscraper wind effect.

Sea surface wind forecasts in the Adriatic Sea often suffer for unadequate modelling, especially for the wind speed. This has detrimental effects on the accuracy of sea level and storm surge predictions. We present a numerical method to reduce the bias between the sea surface wind observed by the scatterometers and that supplied by the European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric model, for storm surge forecasting applications. The method, called “wind bias mitigation”, relies on scatterometer observations to determine a multiplicative factor ∆ws which modulates the standard model wind in order to decrease the bias between scatterometer and model. We compare four different mathematical approaches to this method, for a total of eight different formulations of the multiplicative factor ∆ws. Four datasets are used for the assessment of the eight different bias mitigation methods: a collection of 29 Storm Surge Events (SEVs) cases in the years 2004-2014, a collection of 48 SEVs in the years 2013-2016, a collection of 364 cases of random sea level conditions in the same period, and a collection of the seven SEVs in 2012-2016 that were worst predicted by the Centro Previsioni e Segnalazioni Maree, Comune di Venezia (Tide Forecast and Early Warning Centre of the Venice Municipality - CPSM). The statistical analysis shows that the bias mitigation procedures supplies a mean wind speed more accurate than the standard forecast, when compared with scatterometer observations, in more than 70% of the analyzed cases.

In this paper we present AWEbox, a Python toolbox for modeling and optimal control of multi-aircraft systems for airborne wind energy (AWE). AWEbox provides an implementation of optimization-friendly multi-aircraft AWE dynamics for a wide range of system architectures and modeling options. It automatically formulates typical AWE optimal control problems based on these models, and finds a numerical solution in a reliable and efficient fashion. To obtain a high level of reliability and efficiency, the toolbox implements different homotopy methods for initial guess refinement. The first type of methods produces a feasible initial guess from an analytic initial guess based on user-provided parameters. The second type implements a warmstart procedure for parametric sweeps. We investigate the software performance in two different case studies. In the first case study we solve a single-aircraft reference problem for a large number of different initial guesses. The homotopy methods reduce the expected computation time by a factor of 1.7 and and the peak computation time by a factor of 8, compared to when no homotopy is applied. Overall, the CPU timings are competitive to timings reported in the literature. When the user initialization draws on expert a priori knowledge, homotopies do not increase expected performance, but the peak CPU time is still reduced by a factor of 5.5. In the second case study, a power curve for a dual-aircraft lift-mode AWE system is computed using the two different homotopy types for initial guess refinement. On average, the second homotopy type, which is tailored for parametric sweeps, outperforms the first type in terms of CPU time by a factor of 3. In conclusion, AWEbox provides an open-source implementation of efficient and reliable optimal control methods that both control experts and non-expert AWE developers can benefit from.

This paper presents the super-twisting algorithm (STA) direct power control (DPC) scheme for the control of active and reactive powers of grid-connected DFIG. Simulations of 5 KW DFIG has been presented to validate the effectiveness and robustness of the proposed approach in the presence of uncertainties with respect to vector control (VC). The proposed controller schemes with fixed gains are effective in reducing the ripple of active and reactive powers, effectively suppress sliding-mode chattering and the effe This paper presents a comparative study of two approaches for the direct power control (DPC) of doubly-fed induction generator (DFIG) based on wind energy conversion system (WECS). Vector Control (VC) and Sliding Mode Control (SMC). The simulation results of the DFIG of 5 KW in the presence of various uncertainties were carried out to evaluate the capability and robustness of the proposed control scheme. The (SMC) strategy is the most appropriate scheme with the best combination such as reducing high powers ripple, diminishing steady-state error in addition to the fact that the impact of machine parameter variations does not change the system performance. cts of parametric uncertainties not affecting system performance.

The incorporation of wind generation introduces challenges to the operation of the power system due to its uncertain characteristics. Therefore, the development of methods to accurately model the uncertainty is necessary. In this paper, the spatio-temporal Kriging and analog approaches are used to forecast wind power generation and used as input to solve an economic dispatch problem, considering the uncertainties of wind generation. Spatio-temporal Kriging takes into account the spatial and temporal information given by the database to enhance wind forecasts. We evaluate the performance of using the spatio-temporal Kriging, and comparisons are carried out versus other approaches in the framework of the economic power dispatch problem, for which simulations are developed on the modified IEEE 3-bus and IEEE 24-bus test systems. The results show that the use of Kriging-based spatio-temporal models in the context of economic power dispatch can provide an opportunity for lower operating costs in the presence of uncertainty when compared to other approaches.

This paper reassesses the detrimental effect on fatigue performance due to thicker sections based on extensive fatigue strength test database, taken from research program worldwide over the past half of a century in offshore oil & gas and renewable industry. The data entries in the database have been evaluated to ensure its data integrity. Statistical analyses on these S-N data are performed with or without the thickness correction at different exposure level to corrosive environment, in order to re-evaluate the suitability of current standards in regard to the thickness effect. The study has concentrated on T-joint, transverse butt welded joint and tubular joint as these are the most commonly used joint types in the offshore wind industry. The analysis indicates general agreement of fatigue strength with the thickness effects in current standard for in air conditions but great conservatism for corrosive environment.

In this paper, we presented a method of retrieving sea surface wind speed from Sentinel-1 synthetic aperture radar (SAR) horizontal-horizontal (HH) polarization data in extra-wide mode, which have been extensively acquired over the Arctic for sea ice monitoring. In contrast to the conventional algorithm, i.e., using a geophysical model function (GMF) to retrieve sea surface wind by spaceborne SAR, we introduced an alternative method based on physical model guided neural network. Parameters of SAR normalized radar cross section, incidence angle, and wind direction are used as the inputs of the backward propagation (BP) neural network, and the output is the sea surface wind speed. The network is developed based on more than 11,000 HH-polarized EW images acquired in the marginal ice zone (MIZ) of the Arctic and their collocations with scatterometer measurements. Verification of the neural network based on the testing dataset yields a bias of 0.23 m/s and a root mean square error (RMSE) of 1.25 m/s compared to the scatterometer wind speed. Further comparison of the SAR retrieved sea surface wind speed with independent buoy measurements shows a bias and RMSE of 0.12 m/s and 1.42 m/s, respectively. We also analyzed the uncertainty of retrieval when the wind direction data of a reanalysis model are used as inputs to the neural network. By combining the detected sea ice cover information based on the EW data, one can expect to derive simultaneously sea ice and marine-meteorological parameters by spaceborne SAR in a high spatial resolution in the Arctic.

We present a comprehensive database of near-shore wind observations that were carried out during the experimental campaign of the RUNE project. RUNE aims at reducing the uncertainty of the near-shore wind resource estimates from model outputs by using lidar, ocean, and satellite observations. Here we concentrate in describing the lidar measurements. The campaign was conducted from November 2015 to February 2016 at the west coast of Denmark and comprises measurements from eight lidars, an ocean buoy and three types of satellites. The wind speed was estimated based on measurements from a scanning lidar performing PPIs, two scanning lidars performing dual synchronized scans, and five vertical profiling lidars, of which one was operating offshore on a floating platform. The availability of measurements is highest for the profiling lidars, followed by the lidar performing PPIs, those peforming the dual setup, and the lidar buoy. Analysis of the lidar measurements reveals good agreement between the estimated 10-m wind speeds, although the instruments used different scanning strategies and measured different volumes in the atmosphere. The campaign is characterized by strong westerlies with occasional storms.

With the rapid development of wind power generations, the inertial response of wind turbines (WTs) are widely concerned recently, which is important for grid frequency dynamic and stability. This paper recognizes and understands the inertial response of type-3 and type-4 WTs from the view of equivalent internal voltage, in analogy with typical synchronous generators (SGs). Due to the dynamic of the equivalent inertial voltage different from SGs, the electromechanical inertia of WTs is completely hidden. The rapid power control loop and synchronization control loop is the main reasons that the WT's inertial response is disenabled. On the basis of the equivalent internal voltage's dynamic, the existing inertia control method for WTs are reviewed and summarized as three approaches from the view of WT's control, i.e. optimizing the power control or synchronization control or both. At last, the main challenges and issues of these inertia controls are attempted to explain and address.

Current global commitments to reduce emissions of greenhouse gases encourage national targets for renewable generation. Due to its small land mass, offshore wind could help Bahrain to fulfill its obligations. However, no scoping study has yet been carried out. The methodology presented here addresses this research need. It employs Analytical Hierarchy Process and pairwise comparison methods in a Geographical Information Systems environment. Publicly available land use, infrastructure and transport data are used to exclude areas unsuitable for development due to physical and safety constraints. Meteorological and oceanic opportunities are ranked, then competing uses are analyzed to deliver optimal sites for wind farms. The potential annual wind energy yield is calculated by dividing the sum of optimal areas by a suitable turbine footprint, to deliver maximum turbine number. Ten favourable wind farm areas were identified in Bahrain’s territorial waters, representing about 4% of the total maritime area, and capable of supplying 2.68 TWh/yr of wind energy or almost 10% of the Kingdom’s annual electricity consumption. Detailed maps of potential sites for offshore wind construction are provided in the paper, giving an initial plan for installation in these locations.

In this paper, the linear nonequilibrium thermodynamic approach is used to analyze energy processes in the wind energy conversion system (WECS), with a directly connected vertical axis wind turbine (VAWT) and vector controlled permanent magnet synchronous generator (PMSG). Both elements are considered as linear universal energy converters (EC) linearized at the points of the given range of common to VAWT and PMSG angular velocity. The dependences on the angular velocity of the coupling coefficients between the ECs input and output and the dimensionless parameters of their operating modes were received. This allows for choosing the optimal points of ECs operation according to the specified criteria and obtaining indicators of their maximum efficiency. To assess the quality of the cascade connection of two ECs, the appropriate coefficient was introduced, the dimensionless parameters and characteristics of the equivalent EC were obtained, and the conditions of its maximum efficiency were determined. Analysis of the VAWT-PMSG connection quality showed reserves for improving WECS efficiency. The impact of VAWT and PMSG variable parameters on the quality of this connection is studied, and further research directions are shown. The proposed thermodynamic approach allows an effective search for solutions for the efficiency improvement of various systems with energy transfer and transformation.

Accurate forecasting of wind power generation plays a key role in improving the operation and management of a power system network and thereby its reliability and security. However, predicting wind power is complex due to the existence of high non-linearity in wind speed that eventually relies on prevailing weather conditions. In this paper, a novel hybrid deep learning model is proposed to improve the prediction accuracy of very short-term wind power generation for the Bodangora Wind Farm located in New South Wales, Australia. The hybrid model consists of convolutional layers, gated recurrent unit (GRU) layers and a fully connected neural network. The convolutional layers have the ability to automatically learn complex features from raw data while the GRU layers are capable of directly learning multiple parallel sequences of input data. The data sets of five-minute intervals from the wind farm are used in case studies to demonstrate the effectiveness of the proposed model against other advanced existing models, including long short-term memory (LSTM), GRU, autoregressive integrated moving average (ARIMA) and support vector machine (SVM), which are tuned to optimise outcome. It is observed that the hybrid deep learning model exhibits superior performance over other forecasting models to improve the accuracy of wind power forecasting, numerically, up to 1.59 per cent in mean absolute error, 3.73 per cent in root mean square error and 8.13 per cent in mean absolute percentage error.

Floating wind is becoming an essential part in terms of renewable energy. Therefore, highlighting the perspectives in developing the floating wind platforms is very important. In this paper, we focus on floating wind concepts and projects around the world. This will give a taste to the reader about what is going on in terms of the projects around the world. The main aim of this work is to further explain the collected data regarding the floating wind concepts and projects, and further classify them in terms of cost, power capacity, wind speed, water depth, and distance to shore.

This study investigates the spatial and temporal distribution of litter at 7 beach sectors in Cadiz Bay, Southwest Spain. Two ten-day surveys carried out in autumn 2022 and spring 2023 revealed a total of 4,199 and 4,634 items, respectively, with plastic being the predominant material (71.13% in autumn, 88.39% in spring). Litter quantities varied significantly among beaches, La Puntilla showing the highest abundance with 0.48 ± 0.25 items m-1 in autumn and 1.34 ± 0.61 items m-1 in spring. The lowest abundance was recorded at sector 1 of Valdelagrana beach (0.08 ± 0.06 items m-1) during autumn and at El Castillito beach (0.08 ± 0.04 items m-1) during spring. Statistical analyses did not reveal significant differences in litter quantities between autumn and spring, however high significant interaction was shown considering both season and beach lo-cation. Seasonal differences were also observed in litter composition. Litter categories increased from 90 in autumn to 107 in spring. The top 10 litter categories varied between seasons and included cigarette butts, plastic fragments and plastic packaging. Cigarette butts were principally abundant in autumn because re-lated to summer beach users and wet wipes were particularly observed in spring because linked to wastewaters and river discharges especially relevant in winter months. Hydrodynamic and wind conditions were analyzed, revealing complex relationships with litter abundance.

Super Typhoon Saola came very close to Hong Kong on 1 and 2 September 2023, necessitating the issuance of No. 10 hurricane signal, the highest tropical cyclone warning signal, in Hong Kong. While there were widespread damages in Hong Kong, no people were killed in the event with effective early warning. It is rare that a super typhoon came very close to Hong Kong and this paper is the first part in the series of the documentation of Saola to summarize the interesting observations of Saola near Hong Kong for future reference by weather forecasters, including sur-face observations, upper air observations, microburst alert from weather radars, and turbulence intensity based on spectral width measurement of radars.

Wind energy is a rapidly expanding renewable energy technique. Wind farm developers need to understand the interaction between wind farms and the atmospheric flow over complex terrain. Large-eddy simulations provide valuable data for gaining further insight into the impact of rough topography on wind-farm performance. In this research, we investigate the influence of spatial heterogeneity on wind turbine performance. We conducted numerical simulations of a 12×5 wind-turbine array on various rough topographies. First, we evaluated our LES method through mesh convergence analysis, using mean vertical profiles, vertical friction velocity, and resolved and subgrid-scale kinetic energy. Next, we analyze the effects of surface roughness and dispersive stresses on the performance of fully developed large wind farms. Our results demonstrate that the ground roughness element’s flow resistance boosts large wind-farm power production by almost 68% in fully aerodynamic rough surface compared to flat terrain. Dispersive stress analysis revealed that the primary degree of spatial heterogeneity in the wind farm is in the streamwise direction, which is the “wake-occupied” region, and the relative contribution of dispersive shear stress is almost 45% to the overall drag. We also observed that the power performance of the wind farm in complex terrain outperforms the drag. Our study has implications for improving the design of wind turbines and wind farms in complex terrain to increase their efficiency and energy output.

The quantile estimation of extreme wind speed is needed in various environmental fields such as climatology, design of structures, renewable energy sources and agricultural operations. These calculations are crucial for the coding of wind speed. In this study, the required wind speed series of 16 stations in Khyber Pakhtunkhwa, Pakistan, was obtained from the NASA official website and measured in meters per second (m/s) at a 10-meter distance. A Regional Frequency Analysis of 16 AMWS stations was performed using L-moments. The quantile estimates of extreme wind speed are needed for various areas of interest using Regional Frequency Analysis (RFA) and extreme value theory. These calculations are crucial for the coding of wind speed. The data was taken from the NASA official website at a 10-meter distance and measured in meter per second (m/s). A Regional Frequency Analysis of AMWS using L-moments is performed utilizing wind speed data from sixteen sites (16) in Pakistan's Khyber Pakhtunkhwa province. There are no sites that are found to be discordant. The wards method is used to construct a homogenous region and make two homogenous regions from 16 sites. The heterogeneity test justifies that both clusters are homogeneous. The most appropriate probability distribution from the Generalized Normal (GNO), Generalized Logistic (GLO), Pearson Type-3 (P3), Generalized Pareto (GPA), and Generalized Extreme Value (GEV) distributions are chosen to calculate regional quantiles. According to the L-moments diagram and Z statistics, GEV for Cluster- Ι and GLO for Cluster- ΙΙ are the best suggestions from the others. Both clusters’ robustness is measured utilizing Relative Bias (RB) and Relative Root Mean Square Error (RRMSE). Overall, GEV distribution is fit for cluster-Ι, and the GLO distribution is fit for cluster-ΙΙ. Utilizing the site mean and median as index parameters, we can also find at-site quantiles from regional quantiles. The study’s quantile estimates can be employed in codified structural designs with policy consequences.

To deal with the uncertainties in modeling offshore wind turbines, we proposed a parameter inversion method for the pile-soil interaction model based on structural health monitoring results and the numerical model. The proposed parameter inversion method has a numerical model, an objective function selected using both the numerical and identified results, and an inverse optimization using a random search algorithm in the assumed parameter space. The parameter results in the minimum optimization objective function are identified as the in-situ parameter. The proposed method is confirmed to converge after some iterations, whatever the initial parameter values are. However, different initial parameter cases may converge to slightly different optimal parameters, implying the pile results are sensitive to geological parameters. Moreover, a comparison with the original design results shows design redundancy or risks. Though the proposed method has several flaws, it can shed some light on the influence of uncertainties in offshore wind turbines, such as soil parameters in geological surveys.

The aim of this paper is to provide a new perspective on the conditions for the multiple dimensions of concerns, and to understand why some wind power projects run smoothly while others lead to unexpected outcomes due to local resistance. The paper described how multiple community concerns about wind power project planning can be described using conflict management theory and by using different procedures to handle tangible and intangible concerns. Policy recommendations are given on how: to minimise overflowing and the risk of the conflicts; to avoid “boxing” community concerns in categories; to give more attention to the intangible and less calculable concerns; to secure appropriate and early planning with proactive involvement of local communities.

In recent years, excessive heat in the urban texture has become the main problem in the humid and calm wind city of Babolsar with high density, especially in high-rise areas. Therefore, in order to create comfort in this region, it is necessary to establish and continue the wind circulation in space with an environmentally compatible and optimal configuration. The study applies combination of literature, field measurement, experimental validation of CFD simulation output, and comparative analysis. After field measurement and validation of FLOW-3D simulation software (V11.2.2), the relationship between these parameters (height, the width of passages, enclosure between buildings, and buildings' orientation) will be studied which affects the wind’s velocity and direction. The factors of the buildings' orientation and enclosure based on the passages' width have opposite reactions in the direction of the prevailing wind especially from perpendicular side. In this study, two effective factors are on wind velocity: 1- The orientation of the buildings towards the wind flow by creating permeability 2- Reducing the enclosure by increasing the width of the passage's perpendicular to the wind flow (w '= 3w, E' = 0.33E). According to the theoretical and practical study, first, the creation of permeability in the body of the block and the separation of buildings instead of aggregation has been studied, and then reducing the confinement of streets perpendicular to the wind flow has been discussed as effective solutions to improve the wind velocity and circulation between the urban environment.

Oil palm is one of the most important crops in Malaysia. Lately, the production of oil palm has been reduced due to a variety of factors, including the weather and climate. Temperature, wind speed, relative humidity, sunshine, and rainfall distribution all have an impact on palm tree growth and development, which in turn has an impact on oil palm production. This paper aims to investigate the effects of some weather elements (temperature, wind speed, relative humidity, sunshine, and rainfall) on oil palm production in Peninsular Malaysia. Data were analyzed using the Statistical Package for Social Sciences (SPSS 20.0 version), with descriptive statistics, and multiple linear regression (MLR). The MLR model determined the strength of the relationship between oil palm yield (dependent variable) and the changing variables of temperature, sunshine, wind speed, relative humidity, and rainfall (independent variables). The findings revealed that temperature, wind speed, relative humidity, sunshine, and rainfall have a low impact on oil palm production and yield turnover. The R2 value of 0.202 shows that the independent variables explained only 20.2% of the fluctuation in palm oil production. The study recommends working within an integrated approach involving scientific research, planting, improving variety, improving regional academic leadership, and engaging private and public stakeholders, emphasized collaborative efforts with researchers in consumer countries, and strengthening the capacity of growers to best agroecological practices.

Wind is one of the factors that has a great influence on suspended matter in lakes, especially in shallow lagoons. In order to know how wind affects the water in Albufera of Valencia, a shallow coastal lagoon, the measured variables of turbidity and transparency have been correlated with the estimates by processing Sentinel-2 satellite images with the Sen2Cor processor. Data from four years of study show that most of them are light to gentle easterly breezes and moderate to fresh westerly breezes. The results obtained show significant correlations between the measured variables and those obtained from the satellite images for total suspended matter and water transparency and with the average daily wind speed. There is no significant correlation between wind and chlorophyll a. Moderate to fresh breezes resuspend the fine sediment reaching concentration values from 100 to 300 mg L-1 according to satellite data. However, it is necessary to obtain field data for the values of moderate and fresh winds, as for now there are no experimental data to verify the validity of the satellite estimates.

Amplitude modulation (AM) is a characteristic feature of wind farm noise and has the potential to contribute to annoyance and sleep disturbance. This study aimed to develop an AM detection method using a random forest approach. The method was developed and validated on 6,000 10-second samples of wind farm noise manually classified by a scorer via a listening experiment. Comparison between the random forest method and other widely-used methods showed that the proposed method consistently demonstrated superior performance. This study also found that a combination of low-frequency content features and other unique characteristics of wind farm noise play an important role in enhancing AM detection performance. Taken together, these findings support that using machine learning-based detection of AM is well suited and effective for in-depth exploration of large wind farm noise data sets for potential legislative and research purposes.

In-cloud ice mass accretion on wind turbines is a common challenge faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests--including the cloud water response to surface roughness and albedo effects related to them--must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and to present date not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME 3D NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insulation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In early season cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes.

The application of naturally ventilated pig buildings (NVPBs) with outdoor exercise yards is on the rise mainly due to animal welfare considerations, while the issue of emissions from the buildings to the surrounding environment is important. Since air pollutants are mainly transported by airflow, the knowledge on the airflow characteristics downwind the building is required. The objective of this research was to investigate airflow properties downwind of a NVPB with a roofed outdoor exercise yard for roof slopes of 5°, 15°, and 25°. Air velocities downwind a 1:50 scaled NVPB model were measured using a Laser Doppler Anemometer in a large boundary layer wind tunnel. A region with reduced mean air velocities was found along the downwind side of the building with a distance up to 0.5 m (i.e. 3.8 times building height), in which the emission concentration might be high. It was found that a smaller roof slope (i.e. 5° slope) resulted in a higher and shorter wake zone and thus a shorter air pollutant dispersion distance. It was concluded that a smaller roof slope could contribute to the dilution of air pollutants and a lower air pollutant concentration near the ground.

In 2015, the new installed capacity of global renewable energy power generation exceeded the newly installed capacity of conventional energy power generation, marking a structural change in the construction of the global power system. With the continuous improvement of wind energy utilization technology, the global wind power industry has developed rapidly in recent years. The world's available wind energy is 20 billion kilowatts and has become one of the most economical green power. In China, wind power has become the third largest source of electricity, with the installed capacity increasing from 3.1% in 2010 to 9.2% in 2017. In 2017, China's new installed capacity was 19,660 MW, accounting for 37.45% of the world's new installed capacity. This paper evaluates and compares the efficiency of wind power industry in the four regions of eastern, central, western and northeastern China through EBM models based on radial and non-radial factors. This paper discusses the contribution of China's wind power industry to CO2 emission reduction from the relationship between installed capacity efficiency and CO2 emission reduction efficiency. The conclusions show that the overall efficiency score and ranking of wind power in 2013-2017 is the best in the eastern region, followed by the northeast region and the western and central regions.

An open source computational fluid dynamics (CFD) solver has been incorporated into the WindNinja modeling framework widely used by wildland fire managers as well as researchers and practitioners in other fields, such as wind energy, wind erosion, and search and rescue. Here we describe incorporation of the CFD solver and evaluate its performance compared to the conservation of mass (COM) solver in WindNinja and previously published large-eddy simulations (LES) for three field campaigns conducted over isolated terrain obstacles of varying terrain complexity: Askervein Hill, Bolund Hill, and Big Southern Butte. We also compare the effects of two important model settings in the CFD solver and provide guidance on model sensitivity to these settings. Additionally, we investigate the computational mesh and difficulties regarding terrain representation. Two important findings from this work are: (1) the choice of discretization scheme for advection has a significantly larger effect on the simulated winds than the choice of turbulence model and (2) CFD solver predictions are significantly better than the COM solver predictions at windward and lee side observation locations, but no difference was found in predicted speed-up at ridgetop locations between the two solvers.

Wind tunnels are devices that enable researchers to study the flow over objects of interest, the forces acting on them and their interaction with the flow, which is nowadays playing an increasingly important role due to noise pollution. Since the first closed circuit wind tunnel with variable cross-section was built in G¨ottingen, its Prandtl configuration has little change. The wind tunnel with Prandtl configuration has four corners and vanes, more than 50% of the total pressure loss are caused by the corners and vanes. How to reduce the total pressure loss is a world class problem in the wind tunnel design. This study attempts to propose a novel configuration of wind tunnel, where the corners have been replaced by semi-circular tunnel. Sun wind tunnel 2 has only two corners and vanes, while Sun wind tunnel 1 has no corners and vanes at all. It is expected the new wind tunnel can reduce the total pressure loss from 50% to 10%.

Failure of wind turbines is a multi-faceted problem and its monetary impact is often unpredicted. In this study, we present a novel application of survival analysis on wind turbine reliability performance that includes accounting of previous failures and history of scheduled maintenance. We investigate the operational, climatic and geographical factors which affect wind turbine failures and model the risk rate of wind turbine failures based on data from 109 turbines in Germany operating during a period of 19 years. Our analysis showed that adequately scheduled maintenance can increase the survivorship of wind turbine systems and electric subsystems up to 2.8 and 3.8 times, respectively compared to the ones without scheduled maintenance. Geared-drive wind turbines and their electrical systems were observed to have 1.2- and 1.4-times higher survivorship, respectively, compared to direct-drive turbines and their electrical systems. It is also found that survivorship of frequently-failed wind turbine components, such as switches, is worse in geared-drive than in direct-drive wind turbines. We show that survival analysis is a useful tool for guiding the reduction of operating and maintenance costs of wind turbines.

Solar and wind resources available for power generation are subject to variability due to meteorological factors. Here, we use a new global climate reanalysis product, Version 2 of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), to quantify interannual variability of monthly-mean solar and wind resource from 1980 to 2016 at a resolution of about 0.5 degrees. We find an average coefficient of variation (CV) of 11% for monthly-mean solar radiation and 8% for windspeed. Mean CVs were about 25% greater over ocean than over land, and, for land areas, were greatest at high latitude. The correlation between solar and wind anomalies was near zero in the global mean, but markedly positive or negative in some regions. Both wind and solar variability were correlated with values of climate modes such as the Southern Oscillation Index and Arctic Oscillation, with correlations in the Northern Hemisphere generally stronger during winter. We conclude that reanalysis solar and wind fields could be helpful in assessing variability in power generation due to interannual fluctuations in the wind and solar resource. Skillful prediction of these fluctuations seems to be possible, particularly for certain regions and seasons, given persistence or predictability of climate modes with which these fluctuations are associated.

In this paper, the technical aspects of a multi-lidar instrument, the long-range WindScanner system, will be presented accompanied by an overview of the results from several field campaigns. The long-range WindScanner system consists of three spatially separated coherent Doppler scanning lidars and a remote master computer that coordinates them. The lidars were carefully engineered to perform arbitrary and time controlled scanning trajectories. Their wireless coordination via the master computer allows achieving and maintaining lidars’ synchronization within ten milliseconds. As a whole, the long-range WindScanner system can measure an entire wind field by emitting and directing three laser beams to intersect, and then by moving the beam intersection over the points of interest. The long-range WindScanner system was developed to tackle the need for high-quality observations of wind fields from scales of modern wind turbine and wind farms. It has been in operation since 2013.

Nacelle-based Doppler wind lidars have shown promising capabilities to assess power performance, detect yaw misalignment or perform feed-forward control. The power curve application requires uncertainty assessment. Traceable measurements and uncertainties of nacelle-based wind lidars can be obtained through a methodology applicable to any type of existing and upcoming nacelle lidar technology. The generic methodology consists in calibrating all the inputs of the wind field reconstruction algorithms of a lidar. These inputs are the line-of-sight velocity and the beam position, provided by the geometry of the scanning trajectory and the lidar inclination. The line-of-sight velocity is calibrated in atmospheric conditions by comparing it to a reference quantity based on classic instrumentation such as cup anemometers and wind vanes. The generic methodology was tested on two commercially developed lidars, one continuous wave and one pulsed systems, and provides consistent calibration results: linear regressions show a difference of ∼ 0.5 % between the lidar-measured and reference line-of-sight velocities. A comprehensive uncertainty procedure propagates the reference uncertainty to the lidar measurements. At a coverage factor of two, the estimated line-of-sight velocity uncertainty ranges from 3.2 % at 3 m s⁻¹ to 1.9 % at 16 m s⁻¹. Most of the line-of-sight velocity uncertainty originates from the reference: the cup anemometer uncertainty accounts for ∼ 90 % of the total uncertainty. The propagation of uncertainties to lidar-reconstructed wind characteristics can use analytical methods in simple cases, which we demonstrate through the example of a two-beam system. The newly developed calibration methodology allows robust evaluation of a nacelle lidar’s performance and uncertainties to be established in order to further be used for various wind turbines’ applications in confidence.

This paper delves into the application of digital twin monitoring techniques for enhancing offshore floating wind turbine performance, with a detailed case study. We explore the practical implementation of digital twins and their efficacy in optimizing operations and predictive maintenance. Our findings emphasize digital twins' potential as a valuable tool for renewable energy, driving efficiency and sustainability in offshore floating wind installations.

: AliCPT-1 is the first Cosmic Microwave Background (CMB) experiment in China, dedicated to achieve accurate measurements of B-mode polarization. Situated in Ali of Tibet, China, this telescope is currently undergoing deployment and will operate in two frequency bands centered at 90 and 150 GHz. The Far-Field Flat Mirror（FFF）is a calibration device of AliCPT-1 telescope for far-field beam mapping. The design of FFF is optimized for easy assembly and adjustment. Meteorological station data reveals that the maximum wind speed near FFF is 17.5 m/s, while the maximum wind speed on the windward side is 8 m/s. The wind pressure on FFF was analysed using a maximum wind speed of 17.5m/s as the input condition, based on the fluid-structure coupling method in ANSYS. The results demonstrate that it is safe and reliable when withstanding combined gravity and wind pressure loads. The torque on the mount is within the motor rated torque. The flatness of the FFF reflective surface can be adjusted to an RMS value of 0.05 mm when taken into account the effect of gravity and assembly accuracy. The deformation caused by the maximum wind loads is approximately 0.0587 mm under the protection of wind-proof wall. The combined deformation is 0.077 mm in RMS value combining the two influences, which is less than 1/20 of wavelength. The FFF mirror assembly is stable and precisely for telescope calibration.

Portugal, in line with the European Union, is aiming for carbon neutrality by 2050 (Net 1 Zero), which implies a transition to sustainable energy sources. Climate change is all too evident, extreme weather periods are occurring in a cyclical manner, with greater brevity to such an extent that the grid operator must deal with production scenarios where it can no longer rely on hydroelectric production given the recurring drought situation. This situation increases dependence on thermal production using natural gas and imports. This has significant economic implications. Portugal has exploited its onshore wind potential, reaching an installed capacity of 5.671 MW by 2022. However, the expansion of onshore wind energy is limited to reinforcing existing infrastructure. To overcome these challenges, it is necessary to expand the exploitation of offshore wind potential that is already underway. This article proposes the location of offshore wind production platforms along the Portuguese coast. This allows for an analysis of offshore production and its optimization according to the minimum cost per MWh in the face of extreme scenarios, i.e., in periods of extreme drought where hydroelectric production capacity is practically non-existent. The model is fed by using market price indications and the amount of energy needed for the following day. Using forecast data, the model adapts offshore wind production for the following day according to the minimization of the average market price. The results of the simulations allow us to conclude that despite the high cost of offshore technology (in deep waters), in extreme climate scenarios, it enables cost reduction and a clear decrease in imports.

Offshore Wind Turbines (OWT) with increasingly higher energy output are being developed to meet energy demand, posing challenges for their foundation design. Several foundation types are used to support these turbines with monopiles (MP) accounting for 80% of the installed capacity. In this study, three-dimensional (3D) nonlinear finite element models (FEM) were employed to investigate the behaviour of monopile foundation supporting a 5MW wind turbine when subjected to lateral loading. Results indicate that the MP behavior depending on the pile length to diameter (L/D) ratio and the soil shear strength. Inspection of bending moment profiles at the lateral ultimate capacity indicated the monopiles can behave in flexible manner even with low L/D ratio. The L/D ratio affected the MP normalized lateral ultimate capacity at varying degrees and the biggest effect was for soft clays, amounting to around 5 folds increase for L/D values of 3.33 to 13.33. Lesser effects were found for stiff clays.

In this paper, solar irradiance and wind speed forecasts were performed considering time horizons ranging from 10 min to 60 min, under a 10 min time-step. Global horizontal irradiance (GHI) and wind speed were computed using four forecasting models (Random Forest, k-Nearest Neighbours, Support Vector Regression, and Elastic Net) to compare their performance against two alternative dynamic ensemble methods (windowing and arbitrating). Forecasting models and dynamic forecasting ensembles were implemented in Python for performance evaluation. The performance comparison between the prediction models and the dynamic ensemble methods was carried out by evaluating the RMSE, MAE, R² and MAPE, to evaluate whether the dynamic ensemble forecasting method obtained greater. According to the results obtained windowing dynamic ensemble method was the most efficient among the tested. For the wind speed data, by varying its parameter λ (from 1 to 100), a variable performance profile was obtained, where from λ =1 to λ = 74, windowing proved to be the most efficient, reaching maximum efficiency for λ = 19. Windowing was the best method for the GHI analysis, reaching its best performance for λ = 1. The efficiency gain using windowing was 0.56% when using the wind speed model and 1.96% for GHI.

Due to the special terrain of Urumqi (in the valley area), which often triggers strong foehn weather, and causes huge losses to local people's lives and social economy. This study uses in-situ surface meteorological variables (including the hourly temperature, pressure, humidity, wind, etc.) from the Urumqi Meteorological Station (downstream station, DS) and the Dabancheng Meteorological Station (upstream station, US) in the Middle Tianshan Valley and NCEP/NCAR reanalysis data from 2008 to 2022. A dataset of the foehn weather process at DS in the past 15 years is established and the variation patterns of each meteorological variable during the process of foehn is analyzed. Based on the physical mechanism of the occurrence of foehn, a three-element identification standard for foehn in Urumqi is established by comparing and analyzing the variation of wind direction (WD), wind speed (WS), and the difference of potential temperature (Δθ) between DS and US during the period of foehn and non-foehn from 2013 to 2022, namely: 94°≤ 2-minute average WD ≤168°, 2-minute average WS ≥2.0 m/s, and Δθ between DS and US ≥ 0.29 K. According to the test and evaluation, the three-element identification standard has an accuracy of 82.96%, and a hit rate of 89.50% for the occurrence of foehn in Urumqi from 2008 to 2012. Moreover, the hit rate of foehn identification is 100% for strong wind or above (i.e., 2-minute average WS ≥10.8 m/s) WS. In addition, combined with two predictors of sea-level pressure difference (ΔP) and Δθ between DS and US, forecasting foehn can be more accurately predicted than a single forecasting factor. When ΔP ≤ -12 hPa and Δθ≥5 K, the probability of the occurrence of foehn is more than 90%. This study provides certain reference and application value for the weather forecasting operation of foehn.

The fractal dimension of geomagnetic variations at the Baigazan magnetic station at Russian Altay for 2011-2013 was calculated using the Higuchi method. The daily variation of Higuchi Fractal Dimension (HFD) for the D,H,Z-components of the geomagnetic field has been investigated, its contribution to the variability of HFD is from 30 to 40 percent of the total variance. A correlation analysis of the fractal dimension of the variations of the D,H,Z-components with Auroral Electrojet (AE) index and solar wind characteristics was carried out. A negative correlations with logarithms of AE-index, interplanetary magnetic field (IMF) strength and solar wind velocity were found. About 25 percent of the fractal dimension variance is controlled by the variability of these characteristics. Pair and partial correlation coefficients for these parameters were calculated for every month of 2011-2013.

This study explores the feasibility of using an oscillating plate downstream of a cylindrical body to produce mechanical energy from a Von Kármán vortex street. The study aims to quantify the impact of the plate length, its separation from the cylinder, and a machine damping factor on the power coefficient and the blade’s displacement to identify the optimal configuration. This preliminary assessment assumes that the plate oscillation is small enough to avoid changes in the vortex dynamics. This assumption allows the construction of a surrogate model using CFD to evaluate the effect of plate length and separation from the cylinder on the fluctuating lift forces over the plate. Later, the surrogate model, combined with varying machine damping factors, facilitates the description of the device’s dynamics through the numerical integration of an angular momentum equation. The results showed that a plate with 0.52D length, 5.548D separation from the cylinder, and a damping factor of 0.013 achieved a power coefficient of 0.147 and a perpendicular displacement of 0.266D. These results demonstrate a substantial improvement in the performance of bladeless generators.

Newly build offshore wind farms (OWFs) render a collision risk between ships and installations. The paper proposed a real-time traffic monitoring method based on machine vision and deep learning technology to improve the efficiency and accuracy of the traffic monitoring system in the vicinity of offshore wind farms. Specifically, the method employs real automatic identification system (AIS) data to train a machine vision model, which is then used to identify passing ships in OWF waters. Furthermore, the system utilizes stereo vision techniques to track and locate the positions of passing ships. The method is tested in offshore water in China to validate its reliability. The results prove that the system sensitively detects the dynamic information of the passing ships, such as the distance between ships and OWFs, ship speed and course. Overall, this study provides a novel approach to enhancing the safety of OWFs, which is increasingly important as the number of such installations continues to grow. By employing advanced machine vision and deep learning techniques, the proposed monitoring system offers an effective means of improving the accuracy and efficiency of ship monitoring in challenging offshore environments.

The prediction of an extremely severe cyclonic storm (ESCS) is one of the challenging issues due to increasing intensity and its life period. In this study, an ESCS Fani that developed over Bay of Bengal region during 27 April - 4May, 2019 and made landfall over Odisha coast of India is investigated to forecast the storm track, intensity and structure. Two numerical experiments (changing two air-sea flux parameterization schemes; namely FLUX-1 and FLUX-2) are conducted with the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) model by using a moving nest with fine horizontal resolution about 3 km. The high resolution (25 km) NCEP operational Global Forecast System (GFS) analysis and forecast datasets are used to derive the initial and boundary conditions, the ARW model initialized at 00 UTC 29 April 2019 and forecasted for 108 hours. The forecasted track and intensity of Fani is validated with available India Meteorological Department (IMD) best-fit track datasets. Result shows that the track, landfall (position and time) and intensity in terms of minimum sea level pressure (MSLP) and maximum surface wind (MSW) of the storm is well predicted in the moving nested domain of the WRF model using FLUX-1 experiment. The track forecast errors on day-1 to day-4 are ~ 47 km, 123 km, 96 km, and 27 km in FLUX-1 and ~54 km, 142 km, 152 km and 166 km in Flux-2 respectively. The intensity is better predicted in FLUX-1 during the first 60 h followed by FLUX -2 for the remaining period. The structure in terms of relative humidity, water vapor, maximum reflectivity and temperature anomaly of the storm is also discussed and compared with available satellite and Doppler Weather Radar observations.

Wind energy in Europe is aimed to grow at a steady, high pace, but opposition from residents to local wind farm plans is one of the obstacles to further growth. A large body of evidence shows that local populations want to be involved and respected for their concerns, but in practice this is a complex process that cannot be solved with simple measures such as financial compensation. The visual presence and the acoustic impact of a wind farm is an important concern for residents. Generally environmental noise management aims to reduce the exposure of the population, usually based on acoustics and restricted to a limited number of sources (such as transportation or industry) and sound descriptors (such as Lden). Individual perceptions are taken into account only at an aggregate, statistical level (such as percentage of exposed, annoyed or sleep-disturbed persons in the population). Individual perceptions and reactions to sound vary in intensity and over different dimensions (such as pleasure/fear or distraction). Sound level is in fact a weak predictor of the perceived health effects of sound. The positive or negative perception of and attitude to the source of the sound is a better predictor of its effects. This article aims to show how the two perspectives (based on acoustics and on perception) can lead to a combined approach in the management of a wind farm aimed to reduce annoyance, not primarily of sound level. An important aspect in this approach is what the sound means to people: is it associated with the experience of having no say in plans, does it lead to anxiety or worry, is it appropriate? The available knowledge will be applied to wind farm management: planning as well as operation.

In the next decade, further digitalisation of the entire wind energy project lifecycle is expected to be a major driver for reducing project costs and risks. In this paper, a literature review on the challenges related to implementation of digitalisation in the wind energy industry is first carried out, showing that there is a strong need for new solutions that enable co-innovation within and between organisations. Therefore, a new collaboration method called the WeDoWind Ecosystem is developed and demonstrated. The method is centred around specific "challenges", which are defined by "challenge providers" within a topical "space" and made available to participants via a digital platform. The data required in order to solve a particular "challenge" is provided by the "challenge providers" under the confidentiality conditions they specify. The method is demonstrated via a case study, the EDP Wind Turbine Fault Detection Challenge. Six submitted solutions using diverse approaches are evaluated. Two of the methods perform significantly better than EDP’s existing method in terms of Total Prediction Costs (saving up to €120,000). The WeDoWind Ecosystem is found to be a promising solution for enabling co-innovation in wind energy, providing a number of tangible benefits for both challenge and solution providers.

The public interest towards renewable and clean energy is an important part of shaping consumer behavior and policy towards these topics. A “big data” approach towards assessing the public interest for various topics consists in using freely available search frequency data for the Google search engine, through the Google Trends service. The search data frequency can be used to assess public opinion for a variety of topics, such as medicine, climate change and environmental concerns, finance, and economics etc. A study of the public interest towards wind energy topics is reported here. Six Google search keywords (“Wind power”, “Wind energy”, “Offshore wind”, “Wind farm”, “Wind turbine” and “Wind generator”) were investigated in the 2004–2020-time range. All keywords except “Offshore wind” show a steady decrease from a 2008 – 2010 maximum up to 2015, followed by a period limited change in the 2015 – 2020 range. The interest towards offshore wind topics follows a similar trend but increases in frequency starting from 2015 and reaches a maximum in 2018. Overall, the Google Trends data show a decrease of public interests towards most wind energy topics, with the exception of “Offshore wind”, for English speaking users, in the 2004–2020-time range.

Electric field assisted combustion is an important means to improve fuel combustion efficiency. This paper conducts extensive research on flame characteristics under different forms and different application methods of electric fields, emission of soot particles and simulation status. Different flame parameter measurement methods will lead to different degrees of error, and perfect numerical simulation can make simple predictions on experimental data. Most of the current numerical simulations are in two dimensions, and it is necessary to develop a complete and accurate three-dimensional model to simulate and predict the characteristics of the flame under an electric field. The emission of soot particles is also affected by the electric field, and reasonable electric field parameters can greatly reduce the emission of soot particles. It is recommended to conduct centralized measurement of different fuels under the electric field under high pressure and temperature conditions, so as to be able to develop a wider and more accurate flame dynamics and chemical model under the electric field.

A Life Cycle Analysis was performed considering three existing power plants of comparable size operating with different sources of renewable energy: geothermal, solar and wind. Primary data were used for building the life cycle inventories. The geothermal power plant includes emissions treatment for removal of hydrogen sulfide and mercury. The scenario about the substitution of natural emissions from geothermal energy, with specific reference to the greenhouse effect, is also investigated performing a sensitivity analysis. The results are characterized employing a wide portfolio of environmental indicators employing the Recipe 2016 and the ILCD 2011 Midpoint+ methods; normalization and weighting are also applied using the Recipe 2016 method at endpoint level. The results demonstrate a good eco-profile of geothermal power plant with respect to other renewable energy systems and allow for a critical analysis to support potential improvements of the environmental performances.

Large scale coherent structures in atmospheric boundary layer (ABL) are known to contribute to the power generation in wind farms. In the current paper, we perform a detailed analysis of the large scale structures in a finite sized wind turbine canopy using modal analysis from three dimensional proper orthogonal decomposition (POD). While POD analysis sheds light on the large scale coherent modes and scaling laws of the eigenspectra, we also observe a slow convergence of the spectral trends with the available number of snapshots. Since the finite sized array is periodic in the spanwise direction, we propose to adapt a novel approach of performing POD analysis of the spanwise/lateral Fourier transformed velocity snapshots instead of the snapshots themselves. This methodology not only helps in decoupling the length scales in the spanwise and the streamwise direction when studying the energetic coherent modes, but also provides a detailed guidance towards understanding the convergence of the eigenspectra. In particular, the Fourier-POD eigenspectra helps us illustrate if the dominant scaling laws observed in 3D POD are actually contributed by the laterally wider or thinner structures and provide more detailed insight on the structures themselves. We use the database from our previous large eddy simulation (LES) studies on finite-sized wind farms which uses wall-modeled LES for modeling the Atmospheric boundary layer laws, and actuator lines for the turbine blades. Understanding the behaviour of such structures would not only help better assess reduced order models (ROM) for forecasting the flow and power generation but would also play a vital role in improving the decision making abilities in wind farm optimization algorithms in future. Additionally, this study also provides guidance for better understanding the POD analysis in the turbulence and wind farm community.

This study explores wind energy resources in different locations through the Gulf of Oman and also their future variability due climate change impacts. In this regard, EC-EARTH near-surface wind outputs obtained from CORDEX-MENA simulations are used for historical and future projection of the energy. The ERA5 wind data are employed to assess the suitability of the climate model. Moreover, the ERA5 wave data over the study area are applied to compute sea surface roughness as an important variable for converting near-surface wind speeds to those of wind speed at turbine hub height. Considering the power distribution, bathymetry and distance from the coats, some spots as tentative energy hotspots to provide a detailed assessment of directional and temporal variability and also to investigate climate change impact studies. RCP8.5 is a common climatic scenario is used to project and extract future variation of the energy in the selected sites. The results of this study demonstrate that the selected locations have a suitable potential for wind power turbine plans and constructions.

Wind power as a renewable source of energy, has numerous economic, environmental and social benefits. In order to enhance and control the renewable wind power, it is vital to utilize models that predict wind speed with high accuracy. Due to neglecting of requirement and significance of data preprocessing and disregarding the inadequacy of using a single predicting model, many traditional models have poor performance in wind speed prediction. In the current study, for predicting wind speed at target stations in the north of Iran, the combination of a multi-layer perceptron model (MLP) with the Whale Optimization Algorithm (WOA) used to build new method (MLP-WOA) with a limited set of data (2004-2014). Then, the MLP-WOA model was utilized at each of the ten target stations, with the nine stations for training and tenth station for testing (namely: Astara, Bandar-E-Anzali, Rasht, Manjil, Jirandeh, Talesh, Kiyashahr, Lahijan, Masuleh and Deylaman) to increase the accuracy of the subsequent hybrid model. Capability of the hybrid model in wind speed forecasting at each target station was compared with the MLP model without the WOA optimizer. To determine definite results, numerous statistical performances were utilized. For all ten target stations, the MLP-WOA model had precise outcomes than the standalone MLP model. The hybrid model had acceptable performances with lower amounts of the RMSE, SI and RE parameters and higher values of NSE, WI and KGE parameters. It was concluded that WOA optimization algorithm can improve prediction accuracy of MLP model and may be recommended for accurate wind speed prediction.

The moon always use the same side to face toward the earth, but there is a dead angle in the mainstream theory of explaining this phenomenon. That is, it cannot explain why the moon doesn't rotate around the axis which is a straight line to connect the mass centers of the earth and moon. Because the numerous meteorite impact craters on the lunar surface indicate that the moon is completely possible to obtain external momentums and rotate around this axis. This paper proposes a plain explanation, that is, the universal gravitation between the earth and moon as well as the earth's magnetic field have formed a trinity restraint mechanism on the moon. According to this explanation, the moon's rotation can be locked, and the mechanism of lunar libration has been revealed out, which can also confirm mutually with the natural phenomenon that the moon has sought a balance in the swing. In addition, with the help of all kinds of detection data from the Apollo moon landings and other circumlunar spacecraft, as well as the studies and analysis of lunar soil samples, the conclusion is that as far as a whole for the moon, it belongs to paramagnetic substances, and its relative permeability is between 1.008 and 1.03. Although the magnetic flux density of the earth on the lunar orbit has been dropped below 0.0008125 nT or lower due to the impact of the solar wind, but it can be used as a reason to lock the moon without rotating around the axis which is a straight line to connect the mass centers of the earth and moon. If another main reason to cause the existence of this fact cannot be found, even if the magnetic flux density of the geomagnetism in lunar orbit is very small, it also should not be artificially ignored. In this regard, we can artificially change the intensity of the earth's magnetic field, and carefully observe the lunar libration and in the distance between the earth and the moon, to verify the arguments in this paper.

This paper aims to propose a new approach of territorial competitiveness assessment revisited from the resource-based view, as the combination of location-specific resources and capabilities can improve the territorial socio-economic development. A territorial competitiveness index is calculated in order to assess the potential of renewable energy sources to improve the sustainable development in islands. Different sources of information and methodologies have been employed to measure the variables included in the model, thus ensuring a rigorous process in the index calculation. In order to quantify the basic resources, for example, a methodology based on a multicriteria analysis (MCA) with geographic information system (GIS) is suggested, with the objective of obtaining an indicator called index of available territorial resources. This index synthesizes the map information through a numerical value that allows integrating the territorial resource with other indicators of the model. The results of the study show that capability development is a key factor to better exploit the territorial resource endowment in order to achieve a competitive advantage.

In this paper, sea surface wind speed (SSWS) retrieval from Gaofen-3 (GF-3) quad-polarization stripmap (QPS) data in vertical-vertical (VV), horizontal-horizontal (HH) and vertical-horizontal (VH) polarizations is investigated in detail based on 3,170 scenes acquired from October 2016 to May 2018. The radiometric calibration factor of the VV polarization data is examined first. This calibration factor generally meets the requirement of SSWS retrieval accuracy with an absolute bias of less than 0.5 m/s but shows highly dispersed characteristics. These results lead to SSWS retrievals with a small bias of 0.18 m/s but a rather high root mean square error (RMSE) of 2.36 m/s compared with the ERA-Interim reanalysis model data. Two refitted polarization ratio (PR) models for the QPS HH polarization data are presented. Based on a combination of the incidence angle- and azimuth angle-dependent PR model and CMOD5.N, the SSWS derived from the QPS HH data shows a bias of 0.07 m/s and an RMSE of 2.26 m/s relative to the ERA-Interim reanalysis model wind speed. A linear function relating SSWS and the normalized radar cross section (NRCS) of QPS VH data is derived. The SSWS data retrieved from the QPS VH data show good agreement with the WindSat SSWS data, with a bias of 0.1 m/s and an RMSE of 2.02 m/s. We also apply the linear function to the GF-3 Wide ScanSAR data acquired for the typhoon SOULIK, which surprisingly yields a very good agreement with the model results. A comparison of SSWS retrievals among three different polarization datasets is also presented. The current study and our previous work demonstrate that the general accuracy of the SSWS retrieval based on GF-3 QPS data has an absolute bias of less than 0.3 m/s and an RMSE of 2.0 ±0.2 m/s relative to various datasets. Further improvement will depend on dedicated radiometric calibration efforts.

Wind energy powered pumps could be an alternative to conventional fuel powered pumps for water abstraction because they rely on a free energy and they are environmentally friendly. The objective of this study was to assess the potential of wind energy to operate water abstraction systems in Teso sub-region of Uganda for livestock watering Daily mean wind speeds recorded at a height of 10 m for a period of ten years (2005–2015) were collected from Amuria and Soroti Meteorological stations in the study area. Data were analyzed using Weibull distribution to evaluate the annual wind speed frequency distributions and consequently assess their potential for water abstraction. The results indicated that warmer months (January, February and March) have higher mean wind speeds than the cold months (August, September and October). High wind speeds in the dry seasons corresponded to the periods of high water demand. The highest shape parameter (k) of 3.07 was registered in 2009 and scale parameter (c) of 3.78 in 2012. The highest wind power density of 43 W/m² was obtained the year 2012 while the lowest wind power density of 15.47 W/m² was obtained for Soroti district in the year 2009. The maximum power extractable in Amuria in 2012 was 324 W/m² which is potentially enough for water abstraction. Maximum discharges of 1.86 m³/s and 1.52 m³/s were obtained for Amuria and Soroti districts respectively at mean wind speeds of 5 m/s. Therefore, Teso sub region winds have potential for water abstraction and Amuria district better sites for livestock watering using wind energy.

The interaction between the grid network and the offshore wind power plant (WPP) network can lead to the amplification of certain harmonics and potentially resonant conditions. Offshore WPP should limit the increment of harmonic voltage distortion at the point of connection to the grid network as well as within their internal network. The harmonic distortion should be limited within the planning level limits using harmonic compensation, which is usually achieved by using static filters. In this paper an active damping compensation strategy with a STATCOM using emulation of resistance at the harmonic frequencies of concern is analysed. Such a compensation is effective for the local bus, though the performance is not guaranteed at the remote bus. This paper investigates the challenges associated with remote harmonic compensation in the offshore WPP, which is connected to the onshore grid through long high-voltage cables and transformers. First, the harmonic distortion and the compensating effects of the filter are theoretically assessed. Afterwards, they are demonstrated using harmonic propagation studies and time domain simulations in PSCAD.

Typhoons bring great damages to transmission line systems located in coastal areas. Strong wind and extreme precipitation are the main sources of damaging effects. Transmission lines suffered from wind-driven rain exhibit more susceptibility to damage due to the coupled effect of wind and rain water. This paper presents an integrated numerical simulation framework based on mesoscale WRF model, multiphase CFD model and FEM model to analyze the motions of a transmission line subjected to coupled wind and rain loads during typhoon events. A full-scale transmission line in Zhoushan island is employed to demonstrate the effectiveness of the proposed framework by simulating typhoon evolution in terms of wind fields and rainfall, solving the coupled wind and rain fields around the conductor and predicting the dynamic responses of the transmission line during Super Typhoon Lekima (2019). The results show that the horizontal displacements of the transmission line under the joint actions of wind and rain increases approximately 17%~18% compared to those of wind loads only. It is important to consider the coupled effects of wind-driven rain on conductors in the design of transmission lines under typhoon conditions.

Ensuring the accuracy of wind power prediction is paramount for the reliable and stable operation of power systems. This study introduces a novel approach aimed at enhancing the precision of wind power prediction through the development of a multiscale hybrid model. This model integrates advanced methodologies including Improved Intrinsic Mode Function with Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), Permutation Entropy(PE), Least Squares Support Vector Regression (LSSVR), Regularized Extreme Learning Machine(RELM), Multi-head Attention (MHA), and Bidirectional Gated Recurrent Unit (BiGRU). Firstly, the ICEEMDAN technique is employed to decompose the non-stationary raw wind power data into multiple relatively stable sub-modes, while concurrently utilizing PE to assess the complexity of each sub-mode. Secondly, the dataset is reconstituted into three distinct components: high-frequency, mid-frequency, and low-frequency, to alleviate data complexity. Following this, the LSSVR, RELM, and MHA-BiGRU models are individually applied to predict the high, mid,and low-frequency components, respectively. Thirdly, the parameters of the low-frequency prediction model are optimized utilizing the Dung Betele Optimizer(DBO) algorithm. Ultimately, the predicted results of each component are aggregated to derive the final prediction. Empirical findings illustrate the exceptional predictive performance of the multiscale hybrid model incorporating LSSVR, RELM,and MHA-BiGRU. In comparison to other benchmark models, the proposed model exhibits a reduction in Root Mean Square Error(RMSE) values of over 10%, conclusively affirming its superior predictive accuracy.

The dust originating from the extinct lake of the Aral Sea poses a considerable threat to the sur-rounding communities and ecosystems. The accurate location of these wind erosion areas is an essential prerequisite for controlling sand and dust activity. However, few relevant indicators re-ported in the current study can accurately describe and measure wind erosion intensity. A novel wind erosion intensity (WEI) of a resolution unit was defined in this paper based on the deformation due to the wind erosion in this resolution unit. We also derived the relationship between WEI and soil InSAR temporal decorrelation (ITD). The ITD is usually caused by the surface change over time, which is very suitable for describing wind erosion. However, within one resolution unit, the ITD signal usually includes soil and vegetation contributions, and few studies are referred to this. Therefore, we proposed an ITD decomposition model (ITDDM) to decompose the ITD signal of a resolution unit. The least-squares method (LSM) based on singular value decomposition (SVD) is used to estimate the ITD of soil (SITD) within a resolution unit. We verified the results qualitatively by the landscape photos, which can reflect the actual conditions of the soil. At last, the WEI of the Aral Sea from June 23, 2020, to July 05, 2020, was mapped. The results confirmed that (1) Based on the ITDDM model, the SITD can be accurately estimated by the LSM method, (2) the Aral Sea is experiencing severe wind erosion, and (3) The middle, northeast, and southeast bare areas of the South Aral Sea are where salt dust storms may occur.

When dealing with limited sample sizes or missing values in time series data, achieving high accuracy in forecasting becomes challenging. This challenge is particularly common in wind energy forecasting, where many wind farms lack complete data. In this paper, we employ the widely-used ARIMA (Autoregressive Integrated Moving Average) model for time series forecasting. To address the difficulties posed by limited sample sizes and missing values, we adopt a unique approach by utilizing multiple ARIMA models for different datasets. A key distinction from other multiple models methods for time series forecasting lies in each model within our approach using its own dataset, making the fusion process more intricate. To overcome this, we incorporate neural networks and two techniques for model fusion: direct fusion with a learning mechanism and compensation for missing data through training. For each ARIMA model, we introduce a noise estimation method to circumvent the white noise assumptions inherent in ARIMA models. Finally, we apply these methods to wind energy prediction, and our experimental results showcase a significant enhancement in forecasting accuracy.

The growth of the wind power sector has been marked by environmental, economic, and political drivers. Its starring role is also visible in the emergence of the so-called “green jobs”. Notwithstanding, its evolution ought not to compromise issues related to occupational risks. This exploratory study examines psychosocial risks in the operation and maintenance of onshore wind turbines in a leading Portuguese company. We conducted interviews with main stakeholders (Human Resources, OHS professionals, and team leaders); developed an “activity diary” for the operation and maintenance technicians to describe their activity and perceived impacts on health, complemented with collective interviews; and applied the Work and Health Survey. The results revealed particular risks and health impacts: working under adverse weather conditions; working at heights and in confined spaces; spending long work hours inside of the nacelles to achieve an optimum balance between favorable wind slots to intervene and avoiding additional trips up and down the wind turbines without lifts (70m-120m); and the feeling of early ageing. At a time when these workers are striving for recognition of their profession as a “rapid wear profession”, it is a key moment to discuss these results to guarantee sustainable conditions for future generations of workers.

Folk residence in the cold region of Northeast China is an important part of China's traditional folk residence, with significant geographical representation. In this paper, we take the residential compounds of villages and towns in the cold region of Northeast China as the research object, summarize four typical layout forms of residential compounds of villages and towns in the cold region of Northeast China, simulate the wind environment of compounds of different layout forms in winter by using the computer numerical simulation software Fluent, and then analyze and evaluate the wind environment of compounds by combining with the evaluation standard of wind speed ratio and considering the area of wind shadows, number of vortices and other factors.

Building situated in the flow path of wind is subjected to differential velocity and pressure distribution around the building envelope. Wind effects are influenced and vary for each individual shape of the tall building. Tall building structures are considered as cantilever structures with fixed ends at the ground. Wind exponential velocity acting along the height of the building makes velocity and pressure distribution more complex as the height of the building structure increases. This study discussed the effect of wind on an irregular cross-section shape. The study was conducted numerically with a building model placed in a virtual wind tunnel using the ANSYS (CFX) software tool. Wind effects are investigated on building model situated in a terrain category - II defined in IS: 875 (Part 3): 2015 wind scale model of 1:100 and turbulence intensity is 5 % and power law index α is considered as 0.143. Validation and verification of the study were made by comparing pressure coefficients on faces of a rectangular model of similar floor area and height as taken for a C-plan diamond-shaped model under similar boundary conditions, wind environment, and solver setting of numerical setup. The values of surface pressures generated on the recessed faces of the model and wind flow patterns within the recessed cavity were studied at wind incident angles 0°, 300, 60°, 1050, 1350 & 1800. The critical suction on all the recessed faces was observed to be at a 105° angle of wind attack.

It is imperative to examine the performance of wind turbines both in steady and unsteady states due to their significant role in generating renewable energy by utilizing wind power. The computational fluid dynamics method (CFD) is one of the most efficient tools in this field, and the unsteady state has a great deal of importance when predicting turbine performance. Using the CFD method, the hydrodynamic performance of two types of offshore and onshore horizontal-axis wind turbines in the unsteady state was examined. Offshore wind turbines were modeled using the SST turbulence model and onshore wind turbines were modeled using the large eddy simulation (LES). Three-dimensional results of the simulation were compared and validated with experimental results, and good agreement between the two results indicates that the assumptions and method were accurate. Vortices were also studied in relation to the blade tip and their formation and development. Increasing the number of blades results in a reduction in torque, as well as a rise in vortices caused by the tips of the rotor blades. Due to the intensity of turbulence, the distribution of pressure on the surfaces will become irregular as the wind speed increases.

Article contents the analytical model of the drift of a separate ice field under action of wind and current, which velocities and directions can vary during time. Model takes into account the mass of ice, added mass of sea water and the effects of the wind and current on the ice field in form the friction on its upper and underwater surfaces and frontal resistance on its end (forward and backward) surfaces. Results of performed the steady wind drift of the ice fields modelling show the drift velocity exceeds considerable known velocity of a compact ice cover wind drift. Drifting ice field has the certain kinetic energy that should be released when collision with unmovable obstacle and spent on brittle breakdown of part of the ice field. Volume of formed small ice pieces (fragments of ice field) was estimated by comparison of the specific energy of the sea ice brittle destruction and the kinetic energy of drifting ice field. Article presents the results of estimation of possible volume of the ice pieces and the scales of formed piles as result of collision with an obstacle depending on initial dimensions of ice field and wind speed. Developed models and the results of computer modelling can be used to estimate the ice pile sizes near the stationary platforms and terminals on the Arctic seas.

Increasing wind speed alleviates physiological heat strain, however, health policies have advised against using ventilators or fans under heat wave conditions with air temperatures above the typical skin temperature of 35 °C. Recent research, mostly with sedentary participants, suggests mitigating effects of wind at even higher temperatures depending on the humidity level. Our study aimed at exploring and quantifying, whether such results are transferable to moderate exercise levels, and whether the Universal Thermal Climate Index UTCI reproduces those effects. We measured heart rates, core and skin temperatures and sweat rates in 198 laboratory experiments completed by five young, semi-nude, heat-acclimated, moderately exercising males walking the treadmill with 4 km/h on the level for three hours under widely varying temperature-humidity combinations and two wind conditions. We quantified the cooling effect of increasing wind speed from 0.3 to 2 m/s by fitting generalized additive models predicting the physiological heat stress responses depending on ambient temperature, humidity and wind speed. We then compared the observed wind effects to the assessment performed by UTCI. Increasing wind speed lowered physiological heat strain for air temperatures below 35 °C, but also for higher temperatures with humidity levels above 2 kPa water vapour pressure concerning heart rate and core temperature, and 3 kPa concerning skin temperature and sweat rate, respectively. UTCI assessment of wind effects correlated positively with the observed changes in physiological responses, showing the closest agreement (r=0.9) for skin temperature and sweat rate, where wind is known for elevating the relevant convective and evaporative heat transfer. These results demonstrate the potential of UTCI for adequately assessing sustainable strategies for heat stress mitigation involving fans or ventilators depending on temperature and humidity for moderately exercising individuals.

Capabilities of hovering unmanned aerial vehicles (UAVs) in low-altitude sensing of atmospheric turbulence with high spatial resolution are studied experimentally. The experiment was carried out at the Basic Experimental Observatory of the V.E. Zuev Institute of Atmospheric Optics SB RAS. UAV findings are compared with objective data on the state of the atmosphere that were measured by acoustic anemometers installed at weather towers at altitudes of 4, 10, and 27 m. Profiles of atmospheric turbulence were recorded with three UAVs hovering at the same heights at a distance of 5 m from the anemometers. The behavior of the longitudinal and lateral wind velocity components is studied in the frequency band 0-10 Hz before and after one-minute smoothing, which reveals long turbulent wind gusts. The discrepancy between the UAV and anemometer data is analyzed. It is found that after smoothing, the discrepancy does not exceed 0.5 m/s in 95% cases. This value meets the requirements of the World Meteorological Organization for some applications in wind velocity measurements. The spectral and correlation analysis of the UAV and anemometer measurements is carried out. The profiles of the longitudinal and lateral scales of turbulence are examined based on the UAV data and are found to be in agreement with the anemometer data to a good accuracy.

The formation and localization of sporadic E(Es) layers predicted by the ions vertical drift velocity and its vertical change in the lower thermosphere during nighttime are shown analytically and by numerical simulations. The consideration of existence of a minimum negative value of the vertical change of the ions vertical drift velocity as a necessary condition of formation of Es layer and determining ions convergence rate into this layer, is extended in case of the presence of vertical wind. Upward vertical wind can shift the convergence regions upward, while downward vertical wind shift them downward, unlike the cases of presence of only meridional and zonal winds. It also changes the ion convergence rate compared to the one with just a horizontal wind. It is shown for the first time that the upward constant wind also causes the convergence of ions with maximum rate in the region where the ion-neutral collision frequency is equal to their cyclotron frequency. While demonstrating the presented theory by numerical simulations, HWM14 data is used for the meridional and zonal wind velocity profiles and the presence of its vertical component is assumed. In this case, in addition to the estimated ion drift velocity and its vertical changes, their initial distribution and ambipolar diffusion also determine the development of ion convergence/divergence processes. For small magnitude of vertical wind velocity, its significant influence on the ions/electrons behavior is demonstrated, which shows the importance of both tidal wind and wind changes caused by the propagation of atmospheric gravity waves on the formation of the Es layer. In this theoretical research it is shown that the realistic profile of the wind velocity, which takes into account the vertical component along with its zonal and meridional ones, is important for prediction of the Es layers formation, as well as regions of ion depletion.

FY-3E WindRAD (Fengyun-3E Wind Radar) is a dual-frequency rotating fan-beam scatterometer. Its data characteristics, NOC (NWP Ocean Calibration), and wind retrieval performance are investigated in this paper. The radar view geometry diversity varies across the swath, with maximum diversity in the sweet swaths and limited diversity in the outer and nadir swaths. When NOC backscatter calibration coefficients are computed as a function of incidence angle only (NOCint), a smooth correction is found. However, when relative antenna azimuth angle is included (NOCant), it appears that the corrections as a function of relative azimuth angle vary harmonically and substantially for a specific incidence angle. NOCant corrections yield a better fit of the measurements to the GMF (Geophysical Model Function). Hence NOCant is applied for the wind retrieval analysis from Ku-band, C-band. An extra engineering correction of 0.15dB and 0.2dB is applied on Ku-band and C-band backscatter values, respectively, to reduce the wind speed bias without increasing the standard deviation. Overall, NOCant is the best option for both channels. Also, the instrument backscatter data stability over time is good and the retrieved winds can fulfill operational requirements.

Monsoon winds drive upwelling along the eastern coast of India during the south-west (SW) monsoons. These winds also provide alongshore windstress (AWS) resulting in positive cross-shore Ekman transport (ET) from March to the end of September. While instances of high ET and sea surface temperature based upwelling index (UI_SST) were observed along two parts of the coast: between Kashinagara and Kakinada in the north, and between Kavali and Point Calimere in the south. The UI_SST illustrated a much poorer agreement with local ET in the northern section, where the onset of UI_SST preceded the rise of ET and the subsidence of UI_SST signals occurred during a period of rising ET. Additionally, negative sea surface height anomalies (SSHAs), typically associated with coastal upwelling, were also missing through most of the upwelling period. A complex empirical orthogonal function (CEOF) analysis revealed two coherent modes of SSHA variation. The first mode showed a SSHA signature spatio-temporally coincident with the first upwelling and downwelling Kelvin waves closely associated with the equatorial zonal winds that drive them. The second CEOF mode, with a coastal SSHA pattern similar to the SSHA signatures of coastal upwelling, was associated with local offshore ET along the Indian east coast. The CEOF analysis exhibited the triggering of coastal upwelling in April and its suppression from June by coastally trapped Kelvin waves along the northeastern coast of India, while local AWS driven ET was the primary driver of coastal upwelling along the southeastern coast. The second CEOF mode also exhibited a coherent negative coastal SSHA signature excited by local AWS driven ET during the upwelling period. This study examined the spatio-temporal variability of premonsoon and SW monsoon coastal upwelling along the western Bay of Bengal and its relation to remotely forced coastal Kelvin waves.

Psychiatric patients are particularly vulnerable to strong weather stimuli, such as foehn, a hot wind that occurs in the alps. However, there is a dearth of research regarding its impact on mental health. This study investigated the impact of foehn wind among patients of a psychiatric hospital located in a foehn area in the Swiss Alps. Analysis was based on anonymized datasets obtained from routine records on admission and discharge, including the Brief Symptom Checklist (BSCL) questionnaire, as well as sociodemographic parameters (age, sex, and diagnosis). Between 2013 and 2020 a total of 10,456 admission days and 10,575 discharge days were recorded. All meteorological data were extracted from the database of the Federal Office of Meteorology and Climatology of Switzerland. We estimated the effect of foehn on the BSCL items using a distributed lag model. Significant differences were found between foehn and non-foehn admissions in obsession-compulsion, Interpersonal Sensitivity, depression, Anxiety, Phobic Anxiety, Paranoid Ideation, and General Severity Index (GSI) (p <.05). Our findings suggest that foehn wind events may negatively affect specific mental health parameters in patients. More research is needed to fully understand the impact of foehn’s events on mental health.

Monsoon winds drive upwelling along the eastern coast of India during the south-west (SW) monsoons. These winds also provide alongshore windstress (AWS) resulting in positive cross-shore Ekman transport (ET) from late May to the end of September. While instances of high ET and sea surface temperature (SST) based upwelling index (UI_SST) were observed along different parts of the coast, UI_SST was weaker in the northern section in the earlier part of monsoon. This was even in the presence of maximum AWS and ET during the 10 years analysis period spanning January-2009 to December-2018. Additionally, negative sea surface height anomalies (SSHAs), typically associated with coastal upwelling, were observed only along the southern-most coast. An empirical orthogonal function (EOF) analysis revealed two coherent modes of SSHA variation. The first principal component (PC) showed a SSHA signature coincident spatio-temporally with the first downwelling Kelvin wave, closely associated with the equatorial zonal winds that drive coastal Kelvin waves. The third PC with a coastal SSHA pattern similar to the second upwelling Kelvin wave was associated with offshore ET along the northern part of the Indian east coast. Time series of the two PCs exhibited suppression of coastal upwelling by downwelling Kelvin waves during May-July along the northeastern coast of India. Local AWS driven ET was the primary driver of coastal upwelling with the weakening of the remotely forced Kelvin waves in August. A coherent mode consisting of negative coastal SSHA signature was excited in response to local AWS driven ET during the upwelling period. This study examined the spatio-temporal variability of SW monsoon coastal upwelling along the east coast of India and illustrated the role of equatorial windstress forced first downwelling Kelvin wave in suppressing upwelling in the northern part of the coast during early SW monsoon season.

This paper presents the implementation of a control strategy based on fuzzy logic artificial intelligence (AI) for speed regulation of an electromagnetic frequency regulator (EFR) prototype, aiming to eliminate the dependence on knowledge of physical parameters in the most diverse operating conditions. Speed multiplication is one of the most important steps in power generation wind. Gearboxes are generally used for this purpose. However, they have a reduced lifespan and a high failure rate and are still noise sources. The search for new ways to match the speed (and torque) between the turbine and the generator is an important research area to increase the energy, financial and environmental efficiency of wind systems. The EFR device is an example of an alternative technology that this team of researchers has proposed. It counts the fact of taking advantage of the main advantages of an induction machine with the rotor in a squirrel cage positively. In the first studies, the EFR control strategy consisted of the conventional PID controllers, which has several limitations widely discussed in the literature. This strategy also limits the EFR's performance, considering its entire operating range. The simulation program was developed using the Matlab/Simulink platform, while the experimental results were obtained in the laboratory emulating the EFR-based system. The EFR prototype used has 2 poles, a nominal power of 2.2 kW, and a nominal frequency of 60 Hz. Experimental results were presented to validate the efficiency of the proposed control strategy.

The Virtual Blade Model (VBM) is the implementation of the Blade element model (BEM). This was done by coupling the Blade Element Momentum theory equations to simulate rotor operation with the Reynolds Averaged Navier-Stokes (RANS) equation to simulate rotor wake and the turbulent flow field around it. Exclusion of actual geometry of blades causes lower computational cost (about 10 to 100 times). Also, due to simplifications in the meshing procedure, VBM is easier to set up than the models that consider the actual geometry of blades. One of the main unaddressed limitations of the VBM code was the constraint of modeling up to ten rotor zones within one computational domain. This paper provides a detailed and well-documented general methodology to develop a virtual blade model for simulation of ten-plus turbines within one computational domain to remove the limitation of this widely used and robust code. It is strongly believed that the technical contribution of this paper, combined with the current sky-rocketing advancement of available computational resources and hardware, would open the gates to simulate various engineering problems in the field of aerospace, clean energy, and many more.