Specific Wind Speed Research Articles

Numerical Simulation Method for the Rain-Wind Induced Vibration of the Three-Dimensional Flexible Stay Cable

Abstract Rain-wind-induced vibration is a low-frequency, large-amplitude vibration phenomenon of the cable under specific wind and rain conditions, which is one of the primary forms of vibration. The condition of this phenomenon is exceptional, so it is always a big problem to simulate it comprehensively and accurately. This article proposes a numerical simulation method of a three-dimensional flexible stay cable under the rain-wind-induced vibration, which can reflect the interaction of three phases: gas-liquid-solid. Based on the lubrication theory and the three-dimensional rigid mathematical model of bidirectional coupling of rain-wind induced vibration created by the previous authors, this method considers the cable as a flexible structure, which is more suitable for the actual situation and uses the Ansys software to calculate the vibration of the three-dimensional flexible cable and realizes the coupling effect by transmitting the calculated information through the software, which simulates different phase states. The rain-wind-induced vibration phenomenon of the three-dimensional flexible stay cable at a specific wind speed is reproduced by numerical simulation. The calculated results agree with the experimental results, confirming the method's accuracy and feasibility. The spatial evolution of the water film on the surface of the three-dimensional stay cable is analyzed, and the mechanism of rain-wind-induced vibration is explained from the three-dimensional level.

Non-Gaussian non-stationary wind speed simulation based on time-varying autoregressive model and maximum entropy method

Accurate simulation of non-Gaussian nonstationary wind speeds is a prerequisite for the wind resistant design of some nonlinear structures. Due to its efficiency, the time-varying autoregressive (TVAR) model has been extensively employed for simulating non-Gaussian nonstationary processes. Nevertheless, these simulation techniques based on TVAR exhibit suboptimal performance when confronted with nonstationary and highly non-Gaussian processes. Furthermore, they are unable to replicate the bimodal characteristics of specific wind speeds. This paper presents a new method for simulating univariate non-Gaussian nonstationary wind speeds using the TVAR model and the maximum entropy method. Herein, the connection between the statistical moments of input and output processes in TVAR is firstly derived. Secondly, the maximum entropy method is utilized to reconstruct the probability density function of input process and the time-varying translation function is determined. Finally, the translation process theory is applied to generate the input process, which is then input into the TVAR model to output the non-Gaussian nonstationary wind speed. The numerical results demonstrate that the proposed method exhibits superior simulation accuracy for nonstationary and strongly non-Gaussian wind speed processes. Furthermore, it is capable of capturing the bimodal characteristics of certain hardening non-Gaussian nonstationary wind speeds and possesses a broader range of applications.

Assessment of wind power plant performance using turbine performance and power curves: a case study of PLTB TOLO I Jeneponto

Jeneponto Regency in South Sulawesi possesses significant wind potential, making it an ideal location for the development of Wind Power Plants (WPP). However, these WPPs are intermittent due to the inconsistent nature of wind energy, presenting challenges that affect the performance and efficiency of turbines in generating electricity. Therefore, this study aims to evaluate the performance of the SWT-3.6-130 wind turbines at the Tolo 1 WPP in Jeneponto to determine their capability in converting wind energy into electrical energy at specific wind speeds. The evaluation results indicate that the performance of the SWT-3.6-130 wind turbines at the Tolo WPP in February 2022 was not optimal. The maximum output power generated by these turbines approached the maximum capacity of 3.6 MW, with Turbine 06 producing 3.57 MW at a wind speed of 13.07 m/s, Turbine 09 producing 3.57 MW at a wind speed of 12.27 m/s, and Turbine 013 producing 3.58 MW at a wind speed of 12.11 m/s. Although the power generated was close to the maximum capacity, the performance variation among turbines indicates the need for further evaluation to address factors reducing efficiency. Power coefficient analysis shows that Turbine T13 exhibited the best performance, with the fewest instances of power coefficient values not meeting standards. This study provides crucial insights for improving performance and preventing failures at the Tolo WPP in the future.

Evaluation of Nine Planetary Boundary Layer Turbulence Parameterization Schemes of the Weather Research and Forecasting Model Applied to Simulate Planetary Boundary Layer Surface Properties in the Metropolitan Region of São Paulo Megacity, Brazil

This study evaluates nine Planetary Boundary Layer (PBL) turbulence parameterization schemes from the Weather Research and Forecasting (WRF) mesoscale meteorological model, comparing hourly values of meteorological variables observed and simulated at the surface of the Metropolitan Region of São Paulo (MRSP). The numerical results were objectively compared with high-quality observations carried out on three micrometeorological platforms representing typical urban, suburban, and rural land use areas of the MRSP, during the 2013 summer and winter field campaigns as part of the MCITY BRAZIL project. The main objective is to identify which PBL scheme best represents the diurnal evolution of conventional meteorological variables (temperature, relative and specific humidity, wind speed, and direction) and unconventional (sensible and latent heat fluxes, net radiation, and incoming downward solar radiation) on the surface. During the summer field campaign and over the suburban area of the MRSP, most PBL scheme simulations exhibited a cold and dry bias and overestimated wind speed. They also overestimated sensible heat flux, with high agreement index and correlation values. In general, the PBL scheme simulations performed well for latent heat flux, displaying low mean bias error and root square mean error values. Both incoming downward solar radiation and net radiation were also accurately simulated by most of them. The comparison of the nine PBL schemes indicated the local Mellor-Yamada-Janjic (MYJ) scheme performed best during the summer period, particularly for conventional meteorological variables for the land use suburban in the MRSP. During the winter field campaign, simulation outcomes varied significantly based on the site’s land use and the meteorological variable analyzed. The MYJ, Bougeault-Lacarrère (BouLac), and Mellor-Yamada Nakanishi-Niino (MYNN) schemes effectively simulated temperature and humidity, especially in the urban land use area. The MYNN scheme also simulated net radiation accurately. There was a tendency to overestimate sensible and latent heat fluxes, except for the rural land use area where they were consistently underestimated. However, the rural area exhibited superior correlations compared to the urban area. Overall, the MYJ scheme was deemed the most suitable for representing the convectional and nonconventional meteorological variables on the surface in all urban, suburban, and rural land use areas of the MRSP.

Turbine-Level Possible Power Prediction using Farm-Wide Spatial Information through Similarity-Based Multivariate Gaussians

Wind farms usually comprise several turbines of the same type in proximity to one another. Therefore, similarities exist between the power production of specific turbines within the wind farm over time. Considering this, it is possible to find a way to express the similarity between turbines and exploit their properties to find a formulation of the expected behavior of a turbine. With this estimation of possible power output, one can analyze the losses generated by curtailments or transients with a higher precision. Based on this, a probabilistic model is proposed that can be used to calculate energy losses due to maintenance or environmental reasons. On top of that, heavy deviations in the behavior of specific wind turbines can be detected on high-frequency (1-second) data. Overall, the goal of this work is to predict possible power on high-frequency SCADA data using a statistical white-box modeling approach. The presented method is based on a probabilistic framework, constructing a system of linear combinations that permits analytically tracking the expected behavior of a turbine, even if it is non-operational for a specific amount of time. The methodology includes two parts, the first one is the use of data-driven power curves, and the second one consists of an inferential framework based on the environmental conditions of the farm. Results show that the method presented performs better than the manufacturer’s power curves under specific wind speeds and wind directions.

Changes in wet bulb globe temperature and risk to heat-related hazards in Bangladesh

The rise in temperatures and changes in other meteorological variables have exposed millions of people to health risks in Bangladesh, a densely populated, hot, and humid country. To better assess the threats climate change poses to human health, the wet bulb globe temperature (WBGT) is an important indicator of human heat stress. This study utilized high-resolution reanalysis data from the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF ERA5) to analyze the spatiotemporal changes in outdoor WBGT across Bangladesh from 1979 to 2021, employing Liljegren's model. The study revealed an increase in the annual average WBGT by 0.08–0.5 °C per decade throughout the country, with a more pronounced rise in the southeast and northeast regions. Additionally, the number of days with WBGT levels associated with high and extreme risks of heat-related illnesses has shown an upward trend. Specifically, during the monsoon period (June to September), there has been an increase of 2–4 days per decade, and during the pre-monsoon period (March to May), an increase of 1–3 days per decade from 1979 to 2021. Furthermore, the results indicated that the escalation in WBGT has led to a five-fold increase in affected areas and a three-fold increase in days of high and extreme heat stress during the monsoon season in recent years compared to the earlier period. Trend and relative importance analyses of various meteorological variables demonstrated that air temperature is the primary driver behind Bangladesh's rising WBGT and related health risks, followed by specific humidity, wind speed, and solar radiation.

Uncertainty evaluation for wind speed measurement part (1): “GUM method and Monte Carlo method”

Due to the lack of analysis and research on the performance of different uncertainty evaluation methods in the field of wind speed measurement, it is difficult to choose the most favorable uncertainty evaluation method in the specific wind speed measurement, which will affect the efficiency and accuracy of results. In view of the above situation, this study applied three commonly used uncertainty evaluation methods (conventional GUM method, correlation GUM method and MCM method) to the uncertainty evaluation of wind speed measurement, and analyzed the performance of different methods to provide technical support for specific applications. Firstly, taking the pitot tube wind speed measurement system as an example, the principle and model of wind speed measurement are introduced; Secondly, explain the steps and processes of the above three methods for evaluating uncertainty; Finally, taking a 10 m/s wind speed measurement as an example, the above three methods were used (The correlation GUM method incorporates the correlation between wind tunnel stability and uniformity in its evaluation) to evaluate the uncertainty of wind speed measurement in the Pitot tube wind speed measurement system, and the evaluation results were verified and compared accordingly. The following results were obtained:1) The three uncertainty evaluation methods are all applicable to the evaluation of wind speed measurement uncertainty in this field; 2) The accuracy of evaluation results: MCM method > correlation GUM > conventional GUM, among which correlation GUM method effectively improves the accuracy of uncertainty U95 by 23 % compared to conventional GUM method; 3) Evaluation method operability: MCM method > conventional GUM > correlated GUM. Therefore, we suggest that, when evaluating the uncertainty of wind speed measurement, the MCM method should be given priority when there are high requirements for accuracy and operability. When there are difficulties in the use and promotion of MCM, but there is a high requirement for accuracy, the correlation GUM method can be used. When the accuracy requirement is not high and the calculation is not too complicated, the conventional GUM method can be used.

The wind tunnel test research on the aerodynamic stability of wind turbine airfoils

The issue of nonlinear aerodynamic stability of blades is a significant technological bottleneck in the development of large-scale wind turbines. In order to explore the influencing parameters and mechanisms of the nonlinear aerodynamic stability of large-scale wind turbine blades, the flexible blade was simplified into a two-dimensional rigid blade segment with elastic supports, which formed the pitch single-degree-of-freedom aeroelastic wind tunnel test system. Through wind tunnel vibration and pressure measurement synchronization tests, the torsional vibration characteristics and the flow field development mechanism of the airfoil under different wind speeds and attack angles were studied in detail. The wind tunnel tests revealed two distinct torsional aeroelastic behaviors: the static equilibrium state with negligible amplitude and high vibrational randomness, and the stall flutter state with larger amplitude, which was changed according to sinusoidal law substantially. The stall flutter state was confined within a specific wind speed range, and its stability boundary, which included the critical initiation wind speed and the critical cessation wind speed, all varied linearly with the installation attack angle. The growth rate of the critical cessation wind speed with the installation attack angle was significantly higher than that of the critical initiation wind speed, making the wind speed range for the occurrence of stall flutter also linearly larger. Additionally, the frequency of the stall flutter was significantly higher than the natural frequency of the model, and it exhibited a positive correlation with the critical initiation wind speed. The flow state around the airfoil during stall flutter was primarily distinguished from its static counterpart by the presence of leading-edge vortices. The formation and shedding of these leading-edge vortices would significantly influence the characteristics of stall flutter.

Distribution Characteristics of Near Surface Ozone Volume Fraction in Shanxi Province Based on Atmospheric Composition Observation Network

Based on the continuous data of O3， NO， NO2， and NOx and the meteorological data from March 2019 to February 2020 at six atmospheric composition observation stations in Shanxi Province， the characteristics and influence factors of O3 volume fractions were studied using statistical analysis and backward trajectory analysis. The results showed that O3 volume fractions were generally higher from April to September and lower from October to the following March. During the study period， O3 pollution represented by φ（MDA8O3）， i.e.， the maximum daily 8-h average of O3 volume fractions， was the most serious at the Jincheng and Linfen stations in the south of Shanxi， followed by that in the Wutaishan， Shuozhou， and Datong stations in the north， with the least pollution occurring at the Taiyuan station in the middle. There were differences between the urban and alpine stations， although their seasonal O3 volume fractions were both summer > spring > autumn > winter. O3 volume fractions at the urban station were usually lower than those at the alpine station； O3 at the urban station might have been influenced by photochemical reactions with precursor NOx； however， this was not the main source of high O3 at the alpine station. The peak and valley values appeared at 15：00 and 06：00， respectively， at the urban station， whereas they appeared at 20：00 and 10：00， respectively， at the alpine station， representing diametrically opposite diurnal variation patterns. Further， the daily amplitude of O3 at the urban station was much larger than that at the alpine station. For urban stations specifically， temperature was the most important meteorological factor affecting O3 volume fraction， compared with sunlight hours， precipitation， and total cloud cover. The NO2 volume fraction in the daytime affected the daily amplitude of O3； although the photochemical generation potential of O3 at the Taiyuan station was good， the O3 volume fractions were the lowest among urban stations due to strong NO titration. The higher O3 corresponded to lower NOx in which NO2 was dominant， and the higher NOx was largely composed of NO， under which conditions O3 would be depleted completely. The surface wind that affected O3 volume fractions of all stations primarily came from the southeast， south， and southwest， and specific wind speed led to the increase in O3 volume fraction. The geographical situation of the station would cause the difference in the transport of atmospheric pollutants， whereas the horizontal transmissions of high O3 from the North China Plain and Fenwei Plain were likely to be the common reason for the increase in O3 volume fraction in Shanxi.

Echo-Level SAR Imaging Simulation of Wakes Excited by a Submerged Body.

The paper introduces a numerical simulation method for Synthetic Aperture Radar (SAR) imaging of submerged body wakes by integrating hydrodynamics, electromagnetic scattering, and SAR imaging simulation. This work is helpful for better understanding SAR images of submerged body wakes. Among these, the hydrodynamic model consists of two sets of ocean dynamics closely related to SAR imaging, namely the wake of the submerged body and wind waves. For the wake, we simulated it using computational fluid dynamics (CFD) numerical methods. Furthermore, we compared and computed the electromagnetic scattering characteristics of wakes under various navigation parameters and sea surface conditions. Following that, based on the operational principles and imaging theory of synthetic aperture radar (SAR), we established the SAR raw echo signal of the wake. Employing a Range-Doppler (RD) algorithm, we generated simulated SAR images of the wake. The results indicate that utilizing Computational Fluid Dynamics (CFD) numerical methods enables the simulation of wake characteristics generated by the motion of a submerged body with different velocities. The backscattering features of wakes are closely associated with the relative orientation between the wake and the radar line of sight. Under specific wind speeds, the wake gets masked within the sea surface background, resulting in less discernible characteristics of the wake in SAR images. This suggests that at lower speeds of submerged body or under specific wind conditions, the detectability of the wake in SAR images significantly diminishes.

Prediction of thermal infrared radiation using an artificial neural network applied to the projection and design of processes in renewable energies

This work aims to predict thermal infrared radiation in geographical areas where the necessary measurement devices are not available, through the design of an artificial neural network (RNA). The RNA uses the following variables as input data: specific humidity, relative humidity, ambient temperature, wind speed, and atmospheric pressure, it is important to mention that the sample of space of time is from, (1990 - 2019), they are data from Mexico City, as it is a metropolis with an extensive air quality database, which are obtained from two online tools developed by the National Aeronautics and Space Administration (NASA). In addition, thermal infrared radiation data from NASA are included, to validate the prediction made by the algorithm. Matlab was used to implement RNA, a multiplatform software that offers an integrated development environment with its own programming language. It is recognized for its computational ability and is considered a suitable tool for this purpose.

Recent warm-season dryness/wetness dominated by hot-dry wind in Northern China

The concurrent occurrence of high temperature, low humidity, and specific wind speed, known as hot-dry wind (HDW), is a widespread agro-meteorological hazard in Northern China. HDW can significantly impact surface dryness/wetness by influencing atmospheric water demand. To understand the divergent effect of HDW and precipitation on the spatiotemporal variations of surface dryness/wetness, we collected meteorological data from 673 meteorological stations across Northern China for the warm season (May to September) during 1960–2019. Results reveal a significant (p < 0.05) wetting trend from 1983 to 2019 and a significant (p < 0.01) weakening of HDW across Northern China from 1960 to 2019. Notably, the primary driver of warm-season dryness has transitioned from precipitation before 1982 to HDW in recent decades. Regionally, the wetting trends observed in Northwest (NW) and North China (NC) are primarily attributed to the weakening HDW. Conversely, in Inner Mongolia (IM), a drying trend is noted due to a decline in precipitation that outweighs the reduction in water consumption caused by weakened HDW. During 1960–2019, our analysis affirms that the relative contribution of HDW to variations in warm-season dryness/wetness surpasses that of precipitation in Northern China, particularly in the hyper-arid NW. The persistent HDW is anticipated to exacerbate warm-season dryness and increase water demand for crop growth and animal husbandry in Northern China.

Nonlinear buckling analysis of cat-head transmission tower under strong wind load

Based on ANSYS APDL finite element analysis software and B-R criterion combined with displacement equality criterion, the dynamic stability of the cat-head transmission tower is analyzed. In this paper, the static characteristics of the cat-head transmission tower are analyzed first, and the wind load is gradually increased according to the wind speed gradient of 5 m/s. The results show that the cat-head transmission tower cannot be normally served under the wind speed of 45 m/s. In order to analyze the specific instability wind speed of the transmission tower in detail, the nonlinear buckling analysis is used to analyze the cat-head transmission tower. The nonlinear buckling analysis results of the cat-head transmission tower are as follows: the wind speed of instability is V10=43.65 m/s. Therefore, the influence of wind load fluctuation on the dynamic stability of the transmission tower should not be ignored, and the influence of fluctuating wind should be considered in the design of the transmission tower.

Microclimate Multivariate Analysis of Two Industrial Areas

Most of the existing studies on the increase in air temperature (AT) in industrial neighborhoods (UIs) approach the subject from the analysis of the land surface temperature (LST). Therefore, the objective of this study was to analyze, in addition to LST, the variables of air temperature, relative and specific humidity, wind speed and direction, sky view factor and the albedo of the material surfaces, and to verify which of them has a greater impact on the urban microclimate of the UIs of two cities, Sintra/PT and Uberlândia/BR. To develop this analysis, representative sections of industrial urban areas in the previously mentioned cities were selected and computational simulations were carried out with the ENVI-met software to obtain results related to the studied variables. The results of the simulations, analyzed using multivariate analysis, showed that even though the Udia UI has materials with lower albedo (−45%), lower percentages of vegetation (−20%) and lower WS (−40%) than the Sin UI, the AT inside it may be lower than in the unshaded surroundings around 1.3 °C. For Sin UI, a difference in WS of −1.9 m/s, compared to the control points, caused a peak of +1.5 °C in the industrial environment at 13 h, contrary to what happened in Udia UI.

Impact of climate change on SARS-CoV-2 epidemic in China.

The outbreak and prevalence of SARS-CoV-2 have severely affected social security. Physical isolation is an effective control that affects the short-term human-to-human transmission of the epidemic, although weather presents a long-term effect. Understanding the effect of weather on the outbreak allow it to be contained at the earliest possible. China is selected as the study area, and six weather factors that receive the most attention from January 20, 2020 to April 30, 2020 are selected to investigate the correlation between weather and SARS-CoV-2 to provide a theoretical basis for long-term epidemic prevention and control. The results show that (1) the average growth rate (GR) of SARS-CoV-2 in each province is logarithmically distributed with a mean value of 5.15%. The GR of the southeastern region is higher than that of the northwestern region, which is consistent with the Hu Line. (2) The specific humidity, 2-m temperature (T), ultraviolet (UV) radiation, and wind speed (WS) adversely affect the GR. By contrast, the total precipitation (TP) and surface pressure (SP) promote the GR. (3) For every 1 unit increase in UV radiation, the GR decreases by 0.30% in 11 days, and the UV radiation in China is higher than that worldwide (0.92% higher per day). Higher population aggregation and urbanization directly affect the epidemic, and weather is an indirect factor.

Adaptation of a Thermorheological Lava Flow Model for Venus Conditions

AbstractActive volcanism was (and potentially still is) an important process that shapes the Venus surface and its detection is a primary goal for the planned VERITAS and EnVision missions. Therefore, understanding lava flow emplacement and timing on Venus is important. We adapt the terrestrial PyFLOWGO thermorheological model to Venus conditions to assess the effects on channelized lava flow propagation. We first initiate the model with terrestrial basaltic parameters and progressively adapt it to Venusian conditions in five steps: (a) gravity, (b) ambient atmospheric temperature, (c) specific heat capacity and wind speed, (d) atmospheric density, and (e) coupled convective and radiative heat flux. Compared to Earth, the slightly lower gravity on Venus resulted in a lower flow velocity, a higher crust coverage, and a very minor increase in flow length (0.1%). Increasing the ambient atmospheric temperature reduced heat loss and produced a (77%) longer flow; whereas next accounting for the atmospheric specific heat capacity and wind speed increased the flow length slightly more (81%). However, increasing the atmospheric density resulted in a shorter lava flow (13%) due to more efficient cooling. Finally, accounting for coupled convective and radiative heat loss due to the strong CO2 infrared absorption resulted in an increase of the flow length (∼75%). Although the model applies only to channelized, cooling‐limited flows, these results reveal that for the same effective effusion rate and topography, a Venusian lava flow travels a longer distance than the equivalent flow on Earth and its cooling should be detectable by future orbital instruments.

A Statistical Analysis of Tropical Cyclone-Induced Low-Level Winds near Taiwan Island

Using ERA5 reanalysis data and the tropical cyclone (TC) best track datasets from the China Meteorological Administration and Joint Typhoon Warning Center (from 1979 to 2021), TC-induced low-level winds near Taiwan Island are statistically analyzed. This study mainly concerns TC activity, low-level wind fields around Taiwan Island under TCs, and the detailed characteristics of TC wind structure. Results show that on average, 8.3 TCs enter the study region near Taiwan Island every year mainly from May to November, with more frequent and stronger TCs on the eastern and southern sides of Taiwan Island. For TC centers located at different positions around Taiwan Island, positive and negative vertical vorticity belts alternate between Taiwan Island and the TC center. Moreover, stronger and more frequent TC-induced winds mainly occur on the eastern side of Taiwan Island and the north of Taiwan Strait. TCs to the east of Taiwan Island have stronger maximum sustained wind than those on the western side of the island. Radii of the maximum wind (RMW) for TCs around Taiwan Island range from 5 to 90 nautical mile (nm, 9.3 to 116.7 km) with a mean value of 24.7 nm (44.4 km). Moreover, the RMWs of TCs are the largest (smallest) when the TC centers are located to the southwest (east) of the island. In addition, the outer sizes of TC winds vary from 52 to 360 nm (17.2 to 666.7 km) in the study region, with 187.4 nm (347.1 km) on average, and smaller values for TCs on the western side of the island. The average radii of severe winds, including R34, R50, and R64, are largest in the northeast quadrant and smallest in the southwest quadrant of the TC. The higher the specific wind speed is, the smaller the TC radius and the more symmetric its wind circle. These statistical results may provide references for TC gale forecasting and wind-resistant design for offshore engineering to mitigate TC-induced wind hazards.

Smoke exposure levels prediction following laboratory combustion of Pinus koraiensis plantation surface fuel

High concentrations of harmful gases released from forest fire will pose a short-term hazard to fire-fighters' cardiopulmonary function, even threaten their lives. In this study, laboratory experiments were conducted to examine the relationship between harmful gases concentrations and burning environment and fuel characteristics. In the experiments, fuel beds were created with controlled moisture contents and fuel loads; a wind tunnel device was used to conduct 144 trials, each with a specific wind speed. The easily predicted fire behavioral characteristics and the harmful gases concentrations such as CO, CO2, NOx, SO2 which were released during fuel combustion were measured and analyzed. The results showed that the influences of wind speed, fuel moisture content, and fuel load on the flame length are in accordance with the fundamental theory of forest combustion. The contributions by controled variables to the influence on the short-term exposure concentration of CO and CO2 can be ranked as fuel load > wind speed > fuel moisture. The R2 of the established linear model that was used to predict Mixed Exposure Ratio was 0.98. Our results can help protect the health and lives of forest fire-fighters and can be used by forest fire smoke management to guide fire suppression.

Stability Analysis for DFIG-Based Wind Farm Grid-Connected System Under All Wind Speed Conditions

The stable operation capability of the doubly-fed induction generation-based wind farm grid-connected system (DFIG-WFGS) is closely related to wind speed, and the windward velocity of wind turbine unit at different locations may be discrepant due to wake effect. However, the existing mathematical models of DFIG is limited to some specific wind speed points, which may not be directly applied to stability analysis in all wind speed operating conditions. The wind speed is used to characterize the steady state operating point in this paper, meanwhile considering the wake effect and single-input and dual-output (SIDO) characteristics, the two-variable admittance models of wind farm based on DFIG are proposed. Further, the improved analysis method based on two-variable open-loop transfer function is proposed to investigate the stable wind speed interval with different series compensation level for a 50MW DFIG-WFGS in Qinghai, China. In addition, a design guideline of wind farm for oscillation suppression is studied to enhance the performance of DFIG-WFGS and avoid unstable operations. Theoretical analysis and simulation results show that the wake effect may discontinuous the stable wind speed interval, and the damping variation is not positively correlated with the wind speed, which provides basis for accurate analysis and effective improvement of the stability for wind power generation system.

Predictive Modelling of Wind-Influenced Dynamic Fire Spread Probability in Tank Farm Due to Domino Effect by Integrating Numerical Simulation with ANN

Pool fires cause immense damage to fuel storage tank farms. Reduced fire escalation risk in tank farms improves fire safety. Computational fluid dynamics (CFD) has proven effective in assessing escalation of fire-related domino effects and is being utilized for pool fire consequences in tank farms. The past CFD-based analysis focused on primary fire effects on secondary targets. This study used fire dynamics simulator (FDS) to model complete evolution of the domino effect under different wind speeds and primary pool fire locations. Dynamic escalation probability (DEP) and fire spread probability of the tank farm were calculated. Offset tank failure increased by 3% and 31%, while inline tank failure dropped by 36% and 90%, at 2 and 8 m/s, respectively. An artificial neural network (ANN) incorporating the Levenberg–Marquardt algorithm is used to predict fire spread probability based on numerical data set. The use of ANNs for this purpose is one of the first attempts in this regard. ANNs can reliably predict dynamic fire spread probability and could be utilized to manage fire-induced domino effects. Moreover, dynamic fire spread probability in tank farms obtained from ANN modelling can be used for safety applications, such as updating mitigation time when fire spread probability is unacceptable for a specific wind speed.