Wind Speed Values Research Articles

A Review on Wind Speed Extreme Values Modeling and Bayes Estimation for Wind Power Plant Design and Construction

Rapid growth of the use of wind energy calls for a more careful representation of wind speed probability distribution, both for identification and estimation purposes. In particular, a key point of the above identification and estimation aspects is representing the extreme values of wind speed probability distributions, which are of great interest both for wind energy applications and structural tower reliability analysis. The paper reviews the most adopted probability distribution models and estimation methods. In particular, for reasons which are properly discussed, attention is focused on the evaluation of an opportune “safety index” related to extreme values of wind speeds or gusts. This topic has gained increasing attention in recent years in both wind energy generation assessment and also in risk and structural reliability and safety analysis. With regard to wind energy generation, there is great sensitivity in the relationship between wind speed extreme upper quantiles and the corresponding wind energy quantiles. Concerning the risk and reliability analysis of structures, extreme wind speed value characterization is useful for a proper understanding of the destructive wind forces that may affect structural tower reliability analysis and, consequently, the proper choice of the cut off wind speed value; therefore, the above two kinds of analyses are somewhat related to each other. The focus is on the applications of the Bayesian inference technique for estimating the above safety index due to its effectiveness and usefulness.

Study on optimization of shelter locations and evacuation routes of gas leakage accidents in chemical industrial park

Safety hazards cannot be ignored during the promotion of local economic development in chemical parks. In a crowded chemical industrial park, heavy casualties and serious economic losses may be incurred in a toxic gas leak accident. Accordingly, the location of emergency shelters and occupant escape routes in chemical parks during gas leakage accidents were examined in this study. Additionally, the risk of leakage in chemical parks throughout the year was assessed by selecting the average values of wind direction, wind speed and temperature across four seasons, and criteria for selecting emergency shelters were set according to the minimum risk of toxic gas leakage throughout the year. Moreover, a 30,000 t/a carbon-five separation construction project was adopted as a case study, where instantaneous leakage of an auxiliary raw material liquid ammonia storage tank occurred. The Floyd algorithm was then used to calculate the evacuation paths for people at multiple sources and multiple endpoints. The influence of the dynamic diffusion of toxic gas around the leakage source point on evacuation route safety was thoroughly analyzed, and occupant evacuation plans were employed in the chemical park based on the shortest evacuation path with the least impact from toxic gases. The findings produced by this study may provide reliable technical support guidance for safety evacuation in regard to toxic gas leakage accidents for personnel in chemical industry parks.

Study Gaussian plume model and the Gradient Transport (K) of the advection-diffusion equation and its applications

In this paper, one dimension time dependent and the steady state three dimensions of advection-diffusion equation (ADE) have been solved analytically to estimate the concentration in the atmospheric boundary layer (ABL) taking into account the assumption that the ABL height (h) is divided into sub-layers and the downwind distance is also divided into intervals within each rectangular area the ADE is estimated by using the Laplace transform method assuming that the mean values of wind speed and eddy diffusivity. The proposed model, Gaussian plume model and previous work (Essa et al.2019) was compared with the observed concentration of Iodine-135 which was measured at Egyptian Atomic Energy Authority, Nuclear Research Reactor, Inshas, Cairo Egypt. The statistical analysis shows that there is a good agreement between the proposed and experimental values of concentration.

Control a Photovoltaic/Wind Turbine/Diesel generator with storage battery

Wind/Photovoltaic energy systems are among the most used configurations in multi-sources energy systems because their reliability, robustness and power sources complementarily. For heavy loads, it is more convenient to add backup systems (diesel generator) for an enhanced power availability. In order to protect power sources and increase their lifespan, several power management strategies are such as fuzzy logic control, artificial neural networks and metaheuristic algorithms are proposed and used in literature. This paper presents a power supervisory control (PMC) based on fuzzy logic control dedicated for photovoltaic/wind turbine/ diesel generator/battery systems. The application of the aforementioned technique makes it possible to predict how the hybrid system various operating processes would change in response to solar irradiation and wind speed variations. The study was implemented under Matlab/Simulink. To obtain more realistic results, measured weather values have been incorporated in the simulation. The application is made in a coastal town which has a good potential values of solar irradiance and wind speeds. The obtained results show that the load have been supplied while the batteries were protected due to the PMC.

SWSA transformer: A forecasting method of ultra-short-term wind speed from an offshore wind farm using global attention mechanism

Accurate ultra-short-term wind speed forecasting is great significance to ensure large scale integration of wind power into the power grid, but the randomness, instability, and non-linear nature of wind speed make it very difficult to be predicted accurately. To solve this problem, shifted window stationary attention transformer (SWSA transformer) is proposed based on a global attention mechanism for ultra-short-term forecasting of wind speed. SWSA transformer can sufficiently extract these complicated features of wind speed to improve the prediction accuracy of wind speed. First, positional embedding and temporal embedding are added at the bottom of the proposed method structure to mark wind speed series, which enables complicated global features of wind speed to be more effectively extracted by attention. Second, a shifted window is utilized to enhance the ability of attention to capture features from the edge sequences. Third, a stationary attention mechanism is applied to not only extract features of wind speed but also optimize the encoder-decoder network for smoothing wind speed sequences. Finally, the predicted values of wind speed are obtained using the calculation in the decoder network. To verify the proposed method, tests are performed utilizing data from an real offshore wind farm. The results show that the proposed method outperforms many popular models evaluated by many indexes including gated recurrent unit, Gaussian process regression, long-short term memory, shared weight long short-term memory network, and shared weight long short-term memory network -Gaussian process regression, in terms of mean absolute error, mean square error (MSE), root mean square error, mean absolute percentage error, mean square percentage error, and coefficient of determination (R2).

Which power cycle is the best fit for parabolic trough solar collectors? A comparative and comprehensive case study for six sub-configurations of the three main cycles

In this study, the integration of a Parabolic Trough Collector with different power cycles was investigated on an annual basis in terms of Energy, Exergy, Economics and Environmental under different meteorological conditions. A parabolic trough collector with 500 collectors with a gross and net aperture area of 432,000 and 817.43 m2, was installed in a place that has a high solar energy potential. With a Parabolic trough collector, hourly Direct Normal Irradiation, wind speed, wind direction, ambient temperature and incident angle values were obtained for the 15th of each month for a year. The performance of the 3 power cycles with 6 different configurations using the Parabolic trough collector as the heat source was comprehensively analyzed and compared. During the dynamic data use and various commonly used power systems comparing study, it was aimed to answer the most commonly asked questions by the researchers in this area. To do this, the effect of direct normal irradiation and incident angle on the performance of systems to reach the maximum net power was studied. After calculations, the maximum net power was not found on July 15 (12:00) when the maximum direct normal irradiation (840.868 W/m2) was seen. The maximum net power (67867 kW) was found on September 15 (12:00) when the incident angle was minimum (1.71°) along with the high direct normal irradiation. Steam Rankine Cycle, Organic Rankine Cycle and Kalina Cycle performance comparisons were made both annually depending on time and with different configurations and fluids. In addition to tangibly showing the superiority of incident angle on direct normal irradiation, the present study aimed to present the best-performing system configuration for the researcher, user, scientists, and manufacturers. Interestingly, while the Organic Rankine Cycle with heat exchanger with R123 showed better performance in terms of power production and carbon dioxide emission reduction, the Kalina Cycle was found much more feasible in terms of economics.

Investigation of the effect of climate change on reference evapotranspiration in Tekirdag, Turkiye

It is important to determine the impact of global climate change on water resources. In the effective use of water resources, the amount of water required for agricultural irrigation should be planned under these conditions. In this study, the trend analysis of the climate data required for the calculation of reference evapotranspiration (ET0) between 2011 and 2020 for the meteorology station of Tekirdag, Turkey was carried out. Analysis of change in the study was carried out according to the methods of Linear Regression Test, Mann-Kendall Test and Sen T Test. As a result of the change analysis, it was determined that the reference evapotranspiration (ET0) values had a decreasing trend in June and July and this decrease was statistically significant. As a result of the analysis of the changes in the climate parameters used in the calculation of reference evapotranspiration (ET0), it was determined that the values of maximum temperature, average relative humidity and average sunshine duration were in a decreasing trend, while minimum temperature and wind speed values were in an increasing trend. In the study, the change in monthly precipitation amounts during the measurement periods was also examined. As a result of the analysis of the changes, it was determined that the monthly precipitation amounts have a decreasing trend and the changes especially in April, September, October and December are statistically significant. It is thought that the results obtained will contribute to the future agricultural production planning in the regional conditions.

The impact of the ecological and climatic characteristics of the territory on the condition of the housing stock

The problem of environmental pollution is relevant at the present time. Any enterprise is a potential source of environmental pollution, and the production of road construction materials is one of the enterprises that pose a significant danger to the environment. As an example, we chose Primasfalt LLC, which is one of the main enterprises serving the roads of the city of Vladivostok. At all stages of the preparation of asphalt concrete mixtures, pollutants are released. Toxic substances accumulate in the atmospheric air, then fall on the ground in the form of liquid and solid precipitation, penetrating into the soil, groundwater is polluted, and the balance of nutrients in the soil is disturbed. In the course of the study, an assessment was made of the impact of asphalt concrete production on the condition of soils through the use of test objects — living organisms that are able to respond to environmental changes. The test object was oats, the most common and widely available bioindicator of soil conditions. Sampling points are located within the sanitary protection zone of the enterprise. When sampling, the climatic characteristics of the city of Vladivostok were taken into account. The results of the study showed that high toxicity of soils is observed at points located in the zone of maximum values of wind speed and its frequency. With the help of bioindicator organisms, it is possible to quickly and inexpensively analyze the state of the natural environment. Assessing the activity of an asphalt concrete plant with the help of biological objects makes it possible to identify the intensity of its impact not only within the framework of normative values that are aimed specifically at humans, but also at biological objects in general, which determines the relevance of the chosen topic. The purpose of the study is to assess the level of soil toxicity within the regulatory sanitary protection zone of the LLC Primasfalt enterprise in the city of Vladivostok, Primorsky Krai.

Validation of Himawari-8 Sea Surface Temperature Retrievals Using Infrared SST Autonomous Radiometer Measurements

This study has evaluated five years (2016–2020) of Himawari-8 (H8) Sea Surface Temperature (SST) Level 2 Pre-processed (L2P) data produced by the Australian Bureau of Meteorology (Bureau) against shipborne radiometer SST measurements obtained from the Infrared SST Autonomous Radiometer (ISAR) onboard research vessel RV Investigator. Before being used, all data sets employed in this study have gone through careful quality control, and only the most trustworthy measurements are retained. With a large matchup database (31,871 collocations in total, including 16,418 during daytime and 15,453 during night-time), it is found that the Bureau H8 SST product is of good quality, with a mean bias ± standard deviation (SD) of −0.12 °C ± 0.47 °C for the daytime and −0.04 °C ± 0.37 °C for the night-time. The performance of the H8 data under different environmental conditions, determined by the observations obtained concurrently from RV Investigator, is examined. Daytime and night-time satellite data behave slightly differently. During the daytime, a cold bias can be seen under almost all environmental conditions, including for most values of wind speed, SST, and relative humidity. On the other hand, the performance of the night-time H8 SST product is consistently more stable under most meteorological conditions with the mean bias usually close to zero.

Insight into seasonal aerosol concentrations and meteorological influence over a flood affected area using satellite data and statistical model simulation

Aerosol particles in the atmosphere are one of the many factors that might affect floods. One of India's most flood‐prone regions, Muzaffarpur district in Bihar, has been chosen as the study area. The time period considered for the satellite data on meteorological influence is from the year 2000 to 2021. The correlation coefficient between past forecasts and its confirming data is often used to assess the effectiveness of weather and climate forecasting systems. Therefore, changes in correlation can be utilized to gauge advancements in forecasting ability. In this study, the relationship between aerosol optical depth (AOD) 550 nm, temperature, relative humidity, wind speed, PM2.5 and precipitation are carried out with correlation co‐efficient. The average rainfall throughout the monsoon was found to be 162.5 mm, during the period 2000–2021. The descriptive statistical data for seasonal data were determined for AOD (550 nm), PM2.5, wind speed, relative humidity, and temperature values. It is inferred that there is a positive correlation between precipitation and AOD for the monsoon season. Hence the fitting of meteorological parameter AOD for the monsoon season are done with six different probability distributions Gamma (3P), Logistics, Lognormal (3P), Normal, Rayleigh (2P) and Weibull (3P). The parameters of these distributions are evaluated using the Maximum Likelihood Estimation and the goodness of fit is tested using the test statistics Kolmogorov Smirnov and Anderson Darling test. Among the six discussed distributions, Weibull (3P) distribution provides the best fit to model the meteorological data from the satellite, the flood prediction would be obtained from the model proposed.

An Artificial Neural Network-Based Approach for Real-Time Hybrid Wind–Solar Resource Assessment and Power Estimation

The precise prediction of power estimates of wind–solar renewable energy sources becomes challenging due to their intermittent nature and difference in intensity between day and night. Machine-learning algorithms are non-linear mapping functions to approximate any given function from known input–output pairs and can be used for this purpose. This paper presents an artificial neural network (ANN)-based method to predict hybrid wind–solar resources and estimate power generation by correlating wind speed and solar radiation for real-time data. The proposed ANN allows optimization of the hybrid system’s operation by efficient wind and solar energy production estimation for a given set of weather conditions. The proposed model uses temperature, humidity, air pressure, solar radiation, optimum angle, and target values of known wind speeds, solar radiation, and optimum angle. A normalization function to narrow the error distribution and an iterative method with the Levenberg–Marquardt training function is used to reduce error. The experimental results show the effectiveness of the proposed approach against the existing wind, solar, or wind–solar estimation methods. It is envisaged that such an intelligent yet simplified method for predicting wind speed, solar radiation, and optimum angle, and designing wind–solar hybrid systems can improve the accuracy and efficiency of renewable energy generation.

Assessment of Long Term Spatial-Temporal Variability of Wind Speed of Kalaburgi District, Karnataka, India

Accurate wind power estimates (based on variable wind speeds) are necessary for successful planning and investment in wind power development. In order to inform the development of wind energy, it is essential to acquire a trustworthy quantification and spatiotemporal characteristics of wind speeds. This research used the ArcGIS, Mann-Kendall (MK) test, and Sen's slope to analyze long-term wind speed data from 7 stations in the Kalaburgi District, North Eastern Region of Karnataka State, from 1981 to 2018. The findings of this study contribute to our knowledge of how wind speeds in Kalaburgi District vary and are distributed over long time scales. Over 35 years, there has been a slight and steady rise or decrease in the average wind speed (aveWS). Second, over a span of about 35 years, the annual aweWS varied greatly at various points within the Kalaburgi District. Additionally, the annual aveWS at each station showed a rising tendency. Last but not least, values of wind speeds varied geographically were not very consistent throughout the year, and gradually decreased.

City-Wise Assessment of Suitable CMIP6 GCM in Simulating Different Urban Meteorological Variables over Major Cities in Indonesia

This study evaluates the performance of 6 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for simulating temperature, precipitation, wind speed, and relative humidity over 29 cities in Indonesia. Modern-Era Retrospective Analysis for Research Applications (MERRA-2) was considered as reference data to assess the city-wise performance of surface air temperature, precipitation, wind speed, and relative humidity simulated by the CMIP6 GCMs during 1980–2014. Six statistical measures were computed in this process (mean annual, seasonal amplitude, mean annual bias, root mean square error, correlation coefficient, and standard deviation). For 29 cities, the mean annual values of surface air temperature, precipitation, wind speed, and relative humidity obtained from the GCMs range between 290 to 302 K, 100 cm to 450 cm, 1 to 6 m/s, and 70 to 94%, respectively. The correlation coefficient between the GCMs and the surface air temperature (precipitation) reanalysis dataset ranges from 0.3 to 0.85 (−0.14 to 0.77). The correlation coefficient for wind speed (relative humidity) varies from 0.2 to 0.6 and is positive in some cases (0.2 to 0.8). Subsequently, the relative error that combines the statistical measurement results was calculated for each city and meteorological variable. Results show that for surface air temperature and precipitation, the performance of TaiESM was outstanding over the 10 or more cities. In contrast, for wind speed and relative humidity, NOR-MM and MPI-HR were the best over 7 and 19 cities, respectively. For all the meteorological variables, the performance of AWI was found to be worst over all the cities. The outcomes of this study are essential for climate-resilience planning and GCM selection while performing downscaling experiments. It will also be useful for producing updated national climate change projections for each city in Indonesia and providing new insights into the climate system.

Wind field and pressure characteristics on wind turbine surface under moving thunderstorms

Based on computational fluid dynamics and large-eddy simulation technologies, a numerical simulation method of a moving thunderstorm field is established by considering the impinging jet model. In addition, the influence of movement speed of the storm center and jet velocity changes on the characteristics of the wind field is presented. By drawing horizontal wind speed radial profile curves, the vertical profile curves of horizontal wind velocity, radial wind profile curves of vertical wind speed, and transient wind speed characteristics of a moving thunderstorm downburst are illustrated. The results demonstrate that the wind field of a moving thunderstorm exhibits clear asymmetric characteristics. As the height from the ground increases, the horizontal wind speed first increases and then decreases. The extreme value of the horizontal wind speed appears at the position of (0.01–0.03) Djet (where Djet is the jet spout diameter) near the ground, which is consistent with the characteristics of a static thunderstorm wind field. Simultaneously, the distribution characteristics of wind pressure on the surface of wind turbines under moving thunderstorms is further studied. By considering variations of the wind attack angle, jet velocity, and moving speed, the results of wind pressure on the tower and blades of the wind turbine are presented. The coupling of the moving speed and jet velocity has a significant influence on the wind field and pressure on the wind turbine surface.

ANALYSIS AND IMPROVEMENT OF SINGLE-PHASE FLOW FIELD INSIDE THE CRUSHING CHAMBER OF MACHINE FOR LENTINUS EDODES STIPE CRUSHING

In order to analyze the flow field inside the crushing chamber of machine for lentinus edodes stipe crushing and improve performance of the machine based on the results of the flow field analysis, this paper applied the computational fluid dynamics software FLUENT to numerically simulate the flow field inside the crushing chamber of the machine for lentinus edodes stipe crushing. Thus, the flow field characteristics and flow state inside the crushing chamber were intuitively displayed, and the visualization of the flow field in the crushing chamber was realized. Then, the wind speed value obtained by simulation was compared with the value measured by experiment, and the average relative error between them was less than 10%. Finally, according to the simulation results of flow field, the flow field generated by one air inlet and two air inlets was analyzed, and then the blade structure, outlet area parameters, and rotation speed parameters were compared, simulated and optimized. Results analysis: the pressure distribution and velocity distribution of the flow field inside the crushing chamber were obtained, and the optimal structure and parameters were two inlets, the rotation speed of 2000 r/min and the outlet area of 160×80 mm2, the crushing chamber with the new blade parameters and structure had greater turbulent kinetic energy and velocity gradient, which was more favorable to the discharge, and provided a basis for further optimization and improvement of the crushing machine.

Diffuser augmented wind turbines: A critical analysis of the design practice based on the ducting of an existing open rotor

The study investigates the soundness of a popular uncoupled design strategy for diffuser-augmented wind turbines (DAWTs), namely the use of an annular wing to enclose an existing open-rotor. To this aim, the paper presents a numerical analysis of the NREL-Phase-VI rotor enclosed into a shroud whose cross-section consists of the Selig-S1223 airfoil. Particular attention is devoted to the analysis of the blade pressure fields, velocity triangles, blade forces, tip-vortex and wake development. The data show that the duct induces a gain in the rotor inlet axial velocity and, therefore, in the local flow-angle. Consequently, the blade forces, the extracted work, and the risk of flow separation considerably rise. Thanks to the simultaneous increase in the ingested mass flow rate and extracted work, the DAWT experiences a higher power coefficient (CP,exit) which, however, would be further improved if a coupled design-procedure was used. Indeed, in the present case, the maximum CP,exit is obtained for the wind-speed value corresponding to the duct optimal flow behaviour. However, in this condition, the rotor operates at off-design with an extensive flow-separation on the blade suction-side. Finally, while the inefficiencies magnitude is specific of the analysed case, the conceptual relevance of the achievements remains valid in general.

Direct power control using space vector modulation strategy control for wind energy conversion system using three-phase matrix converter

Introduction. Wind energy conversion system is getting a lot of attention since, they are provide several advantages, such as cost competitive, environmentally clean, and safe renewable power source as compared with the fossil fuel and nuclear power generation. A special type of induction generator, called a doubly fed induction generator is used extensively for high-power wind energy conversion system. They are used more and more in wind turbine applications due to the advantages of variable speed operation range and its four quadrants active and reactive power capabilities, high energy efficiency, and the improved power quality. Wind energy conversion systems require a good choice of power electronic converters for the improvement of the quality of the electrical energy produced at the generator terminals. There are several power electronics converters that are the most popular such as the two stage back-back converter. Because of the disadvantage of these converters to produce large harmonics distortions, we will choose using of three-phase matrix converter. Purpose. Work presents a direct power control using space vector modulation for a doubly fed induction generator based wind turbine. The main strategy control is to control the active and reactive powers and reduce the harmonic distortion of stator currents for variable wind speed. The novelty of the work is to use a doubly fed induction machine and a three pulses matrix converter to reduce the low cost, volume and the elimination of the grid side converter controller are very attractive aspects of the proposed topology compared to the conventional methods such as back-to-back converters. Simulation results are carried out on a 1.5 MW of wind energy conversion system connected to the grid. The efficiency of the proposed system has been simulated and high results performances are evaluated to show the validity of the proposed control strategy to decouple and control the active and reactive power for different values of wind speed.

Turbulent structure of the Arctic boundary layer in early summer driven by stability, wind shear and cloud-top radiative cooling: ACLOUD airborne observations

Abstract. Clouds are assumed to play an important role in the Arctic amplification process. This motivated a detailed investigation of cloud processes, including radiative and turbulent fluxes. Data from the aircraft campaign ACLOUD were analyzed with a focus on the mean and turbulent structure of the cloudy boundary layer over the Fram Strait marginal sea ice zone in late spring and early summer 2017. Vertical profiles of turbulence moments are presented from contrasting atmospheric boundary layers (ABLs) from 4 d. They differ by the magnitude of wind speed, boundary-layer height, stability, the strength of the cloud-top radiative cooling and the number of cloud layers. Turbulence statistics up to third-order moments are presented, which were obtained from horizontal-level flights and from slanted profiles. It is shown that both of these flight patterns complement each other and form a data set that resolves the vertical structure of the ABL turbulence well. The comparison of the 4 d shows that especially during weak wind, even in shallow Arctic ABLs with mixing ratios below 3 g kg−1, cloud-top cooling can serve as a main source of turbulent kinetic energy (TKE). Well-mixed ABLs are generated where TKE is increased and vertical velocity variance shows pronounced maxima in the cloud layer. Negative vertical velocity skewness points then to upside-down convection. Turbulent heat fluxes are directed upward in the cloud layer as a result of cold downdrafts. In two cases with single-layer stratocumulus, turbulent transport of heat flux and of temperature variance are both negative in the cloud layer, suggesting an important role of large eddies. In contrast, in a case with weak cloud-top cooling, these quantities are positive in the ABL due to the heating from the surface. Based on observations and results of a mixed-layer model it is shown that the maxima of turbulent fluxes are, however, smaller than the jump of the net terrestrial radiation flux across the upper part of a cloud due to the (i) shallowness of the mixed layer and (ii) the presence of a downward entrainment heat flux. The mixed-layer model also shows that the buoyancy production of TKE is substantially smaller in stratocumulus over the Arctic sea ice compared to subtropics due to a smaller surface moisture flux and smaller decrease in specific humidity (or even humidity inversions) right above the cloud top. In a case of strong wind, wind shear shapes the ABL turbulent structure, especially over rough sea ice, despite the presence of a strong cloud-top cooling. In the presence of mid-level clouds, cloud-top radiative cooling and thus also TKE in the lowermost cloud layer are strongly reduced, and the ABL turbulent structure becomes governed by stability, i.e., by the surface–air temperature difference and wind speed. A comparison of slightly unstable and weakly stable cases shows a strong reduction of TKE due to increased stability even though the absolute value of wind speed was similar. In summary, the presented study documents vertical profiles of the ABL turbulence with a high resolution in a wide range of conditions. It can serve as a basis for turbulence closure evaluation and process studies in Arctic clouds.

Numerical analysis and optimization of a novel photovoltaic thermal solar unit improved by Nano-PCM as an energy storage media and finned collector

An increment in temperature will deteriorate the efficiency of photovoltaic systems dramatically. The application of a cooling mechanism can reduce the operating temperature and perform a better operation. Therefore, in this research, a nanoparticle-based phase change material (PCM) layer is combined with finned collectors as the condenser for higher electricity generation in photovoltaic/thermal (PV/T) collectors. The temperature distribution of the PCM layer in both solid and fully melted phases are poked to identify the effect of the Nano-PCM layer on the mentioned system efficiency. Afterward, a big data collection is created and employed to introduce a deep learning model to tune and find the best network. Ultimately, the gilt-edged network is optimized using LINMAP, TOPSIS, as well as Shannon entropy decision makings and Gray Wolf Optimization (GWO), Bat algorithm (BA), Particle swarm optimization (PSO), and Biogeography-based optimization (BBO) techniques. The results indicated that the maximum thermal efficiency values are obtained at wind speed values less than 2 m/s and DNI higher than 950 W/m2. Considering their mentioned impacts on thermal efficiency, this variable of the renewable unit changes by 10–24%. Moreover, the optimal condition reveals the optimum melted PCM, the coolant outlet temperature, and the electrical efficiency of 6.497 kg, 37.72 °C, and 13.92%, respectively. It is concluded that compared with the traditional systems, enhancement in electrical efficiency can be achieved by Nano-PCM layer utilization as cooling media.

Implementation of hybrid wind speed prediction model based on different data mining and signal processing approaches

Accurate estimation of wind speed (WS) data, which greatly influences meteorological parameters, plays a vital role in the safe operation and optimization of the power system and water resource management. The study's main aim is to combine artificial intelligence and signal decomposition techniques to improve WS prediction accuracy. Feed-forward back propagation neural network (FFBNN), support vector machine (SVM) and Gaussian processes regression (GPR) models, discrete wavelet transform (DWT), and empirical mode decomposition (EMD) were used to forecast the WS values ​​1 month ahead in Burdur meteorology station. Statistical criteria such as Willmott's index of agreement, mean bias error, mean squared error, determination coefficient, Taylor diagram and regression analysis, and graphical indicators were used to evaluate the prediction success of the models. As a result of the study, it was determined that both wavelet transform and EMD signal processing increased the WS prediction performance of the stand-alone ML model. The best performance was obtained with the hybrid EMD-Matern 5/2 kernel GPR with test (R2:0.802) and validation (R2:0.606). The most successful model structure was obtained using input variables with a delay of up to 3 months. The study's results contribute to wind energy-related institutions in terms of practical use, planning, and management of wind energy.