Annual Mean Wind Speed Research Articles

Offshore Wind Resource Assessment of Thailand Using Remote Sensing Technique

This paper presents the evaluation of the offshore wind resource of Thailand (the Gulf of Thailand and the Andaman Sea) using remote sensing technique. The wind speed at height of 10 m above mean sea level (A.M.S.L.) was measured using SeaWinds Scatterometer on QuickSCAT by NASA. The QuickSCAT satellite images in 1999-2009 with resolution of 1ox1o was interpreted and validated using the measured wind speed provided by the ship observation, buoy data and numerical weather prediction models. The wind speed was interpolated for 1 km resolution enhancement and extrapolated to the height of 50 m A.M.S.L.. The monthly and annual mean wind speed maps were presented in order to show the spatial and temporal variation of offshore wind energy potential. Results showed that QuickSCAT satellite images interpretation gave lower bias in the rage of wind speed of 3-18 m/s, however, the bias was high for wind speed more than 20 m/s. It found that offshore mean wind speed at height of 50 m A.M.S.L. was in the range of 3.0-6.0 m/s where the middle part of Thai offshore had the highest potential with the wind speed in the rage of 7.0-10.0 m/s. The offshore wind speed had high potential during June until August due to the influence of southwest monsoon.

Wind flow simulation and characteristics prediction using WAsP software for energy planning over the region of Hassi R’mel

ABSTRACT In this study, we analyzed the wind potential of Hassi R’mel (Algeria) under the Wind Atlas Analysis and Application Program (WAsP) environment, using data measurements at a height of 10 m provided by the National Office of Meteorology (NOM) over the period of 14 years (2003–2017). The results are used as input for predicting wind characteristics (speed and direction) for four other sites covering the studied region where the measurement stations are not available. The pre-feasibility study of large-scale energy and hydrogen production focuses on four sites, namely Telghemt, Delaa, Bouzbier, and Bellil. Two different wind turbine models, Bonus B54 and Nordex N100 with a rated power of 1000 kW and 2500 kW, respectively, were selected. The study pointed out that the region of Hassi R’mel has an important wind potential with an annual mean wind speed of 6.73 m/sec and power density of 365 W/m2 at 10 m. The maximum of energy and hydrogen produced occurs for the site of Hassi R’mel with 12.41 GWh/yr, and 177.37 tons H2/yr, with minimal costs of 5.5 c$/kWh, and 18.42 $/kg H2 respectively using Nordex N100 wind turbine at 100 m. Similarly for the site of Bellil where the maximum of energy and hydrogen production of 5.395 GWh/yr, and 77.08 tons H2/yr were obtained with minimal costs of 5.06 c$/kWh, and 17.12 $/kg H2 respectively using Bonus B54 wind turbine at 60 m. Therefore, the high rate of carbon dioxide (CO2) emissions avoided by N100 was 5428.2 tons CO2/kWh for Hassi R’mel, and 2359.2 tons CO2/kWh for Bellil using the B54 wind turbine.

Estimation of Weibull parameters for wind energy analysis across the UK

Harvesting wind energy resources is a major part of the UK strategy to diversify the power supply portfolio and mitigate environmental degradation. Based on wind speed data for the period 1981–2018, collected at 38 surface observation stations, this study presents a comprehensive assessment of wind speed characteristics by means of statistical analysis using the Weibull distribution function. The estimated Weibull parameters are used to evaluate wind power density at both station and regional levels and important, turbine-specific wind energy assessment parameters. It is shown that the Weibull distribution function provides satisfactory modeling of the probability distribution of daily mean wind speeds, with the correlation coefficient generally exceeding 0.9. Site-to-site variability in wind power density and other essential parameters is apparent. The Weibull scale parameter lies in the range between 4.96 m/s and 12.06 m/s, and the shape parameter ranges from 1.63 to 2.97. The estimated wind power density ranges from 125 W/m2 to 1407 W/m2. Statistically significant long-term trends in annual mean wind speed are identified for only 15 of the 38 stations and three of the 11 geographical regions. The seasonal variability of Weibull parameters and wind power density is confirmed and discussed.

Wind turbine modelling and simulation using Matlab / SIMULINK

Malaysia is aiming to reduce the dependency on oil and gas by increasing the utilization of renewable energy. One of the promising renewable energy available is wind energy. Malaysia is located near the equator which is situated in a low wind speed region with an annual mean wind speed of 1.2-4.1 m/s. However, Malaysia also experiences two different monsoon seasons which is the southwest monsoon and the northeast monsoon. Wind speed during the southwest monsoon season can reach 7 m/s while the wind speed during the northeast monsoon can exceed 15 m/s. Limited researches and studies had been done to investigate the potentiality of wind energy in Sarawak, Malaysia. In this paper, modelling and simulation of different wind energy conversion system (WESC) using different generators operating under the same parameters will be carried out using MATLAB/SIMULINK to investigate the efficiency of the generators. PMSG has shown to be more efficient over SCIG and DFIG for lower wind speed although all of them eventually reaches the similar efficiency. Efficiency of SCIG, DFIG and PMSG for rated wind speed are 66.25%, 69.38% and 71.88% respectively.

Assessment of Wind Characteristics and Wind Power Potential of Gharo, Pakistan

The objective of this research work is to assess the wind characteristics and wind power potential of Gharo site. The wind parameters of the site have been used to calculate the wind power density, annual energy yield, and capacity factors at 10, 30, and 50 m. The wind frequency distribution including seasonal as well as percentage of seasonal frequency distribution has been investigated to determine accurately the wind power of the site. The coefficient of variation is calculated at three different heights. Also, economic assessment per kWh of energy has been carried out. The site-specific annual mean wind speeds were 6.89, 5.85, and 3.85 m/s at 50, 30, and 10 m heights with corresponding standard deviations of 2.946, 2.489, and 2.040. The mean values of the Weibull k parameter are estimated as 2.946, 2.489, and 2.040 while those of scale parameter are estimated as 7.634, 6.465, and 4.180 m/s at 50, 30, and 10 m, respectively. The respective mean wind power and energy density values are found to be 118.3, 92.20, and 46.10 W/m2 and 1036.6, 807.90, and 402.60 kWh/m2. As per cost estimation of wind turbines, the wind turbine WT-C has the lowest cost of US$ Cents 0.0346/kWh and highest capacity factors of 0.3278 (32.78%). Wind turbine WT-C is recommended for this site for the wind farm deployment due to high energy generation and minimum price of energy. The results show the appropriateness of the methodology for assessing the wind speed and economic assessment at the lowest price of energy.

The Vector dynamics of Ikogosi Wind Speed/direction relative to Climate Change

This study appraises anticipated vicissitudes to surface wind characteristics from 1980-2018 in Ikogosi South-Western Nigeria. Changes in wind speeds at regional and global levels are signals of global warming. A concern about climate change has been a major driving force for the speedy expansion experienced in wind energy projects. Yearly investigation of wind speed disguises seasonal variation in predictive planning. At times, these changes fluctuate across seasons in some zones. The Inter-governmental Panel on Climate Change (IPCC) gave a proponent for long-term changes in the large-scale atmospheric circulation. In effect, observed changes such as poleward shifts and reinforcement of westerly winds will likely be promoted. Projected changes to annual wind speed display altitudinal variability compared to seasonal and annual mean wind speed. An evaluation of wind changes at specific locations is therefore necessary for site-specific application. This paper presents experience at Ikogosi warm spring site with varying return periods, analysedfor identificationof the behaviour of its wind using several statisticsprobability distribution. Average wind speed of 2.2 m/s in Ikogosi certainly portends a future for hydro-electricity alternative in Nigeria.

Climate observation of the Three Gorges Region of the Yangtze River in 2019

This report provides a broad overview of the climate and the major weather and climate events over the Three Gorges Region of the Yangtze River (TGR) in 2019. The year 2019, a 0.3 °C warmer year than normal, had a colder winter and warmer spring, summer, and autumn. Annual precipitation in 2019 was 13% less than normal. Below average normal rainfall amounts were received in all four seasons, with 28% and 16% less-than-normal in winter and summer, respectively. The annual mean wind speed in the TGR was higher than normal, and relative humidity was near normal for all four seasons. The intensity of acid rain in 2019 was the weakest since 1999. The major climate events and meteorological disasters in the TGR in 2019 included heat waves, drought, and rainstorms. Heat waves occurred frequently and persisted for long durations. Summer and autumn drought occurred in central and eastern regions of the TGR. The autumn rains of West China occurred earlier this year, which brought much more rainfall than normal in central and western regions of the TGR.摘要2019年, 长江三峡地区年平均气温17.5°C, 较常年偏高0.3°C; 冬季偏冷, 春,夏,秋三季气温均偏高; 年高温日数偏多. 2019年三峡地区年降水量1035.1毫米, 较常年偏少13%; 四季降水均偏少; 年暴雨日数偏少. 2019年, 长江三峡地区年平均风速较常年偏大; 年平均相对湿度接近常年; 酸雨强度弱, 为1999年以来的最弱年, 近十余年酸雨强度呈现明显的减弱趋势. 2019年, 长江三峡地区高温过程多, 持续时间长; 三峡中东部地区出现伏秋连旱; 华西秋雨开始早, 三峡中西部雨量多.

Neopredelennost' otsenki vetroenergeticheskogo potentsiala Azovo-Chernomorskoy pribrezhnoy zony vsledstviye klimaticheskikh izmeneniy vetrovogo rezhima

The paper deals with assessing an impact of wind climate change on the wind energy potential of the Azov and Black Sea coast region. A lower estimate of operating time for wind power installation and a potential annual energy output for the region are given for the case of Vestas V117-4.2MW. Calculation has been performed of a long-term mean wind speed for two adjacent climatic periods (1954–1983 and 1984–2013) based on data from meteorological stations of the Black and Azov Sea region. The results show a decrease in wind speed at all meteorological stations except for Novorossiysk. The wind climate change is confirmed by comparing two adjoined 30-year periods and by estimating linear trends of the mean annual wind speed for the period 1954–2013, which are negative and significant for almost all meteorological stations in the region (α = 1 %). The trend values were estimated by the nonparametric method of robust linear smoothing using the Theil – Sen function. In the present study, the uncertainty of wind energy resource induced by a gradual wind climate change is estimated for perspective planning of this branch of energy sector. Despite the observed trends in the wind regime, average wind speeds in the Azov and Black Sea region are sufficient for planning the location of wind power plants.

Evaluation and Comparison of the Effectiveness Rate of the Various Meteorological Parameters on UNEP Aridity Index Using Backward Multiple Ridge Regression

Climate changes and its undesirable impacts (such as melting glaciers, the occurrence of floods, hurricanes and droughts, etc.) are among the most important disasters that human beings have faced in recent decades. Considering the important role of the meteorological parameters on climate change, in this research the effectiveness rate of various meteorological parameters including the mean minimum and maximum annual temperature (Max-Temp and Min-Temp), the mean annual temperature (M-Temp), the mean annual sunshine (Sunshine), the mean annual relative humidity (Humidity), the mean annual wind speed (Wind) and the mean of annual precipitation (Rainfall) on United Nations Environmental Programme (UNEP) aridity index was assessed and prioritized using the Backward Multiple Ridge Regression (BMRR). In this study, the meteorological data series of 25 synoptic stations in Iran with different climate conditions during 1967–2017 was used. The results indicated that the BMRR method had a nice capability to predict the UNEP index using the above-mentioned meteorological parameters (the linear regression between observed and predicted the UNEP index had no difference with perfect reliable line (Y = X) at 0.05 significant levels and the R2 between two mentioned data series were significant at 0.01 levels at all stations). According to the results, Rainfall, Wind and Max-Temp parameters were the most effective parameters on the UNEP aridity index, respectively and the Min-Temp, M-Temp and Sunshine parameters were the least effective parameters on the UNEP index, respectively. Therefore, it is suggested that all human activities that have direct or indirect effects in the increasing temperature and reducing the rainfall must be revised and optimized based on the principles of sustainable development.

Wind Resource Assessment and Economic Viability of Conventional and Unconventional Small Wind Turbines: A Case Study of Maryland

Annual mean wind speed distribution models for power generation based on regional wind resource maps are limited by spatial and temporal resolutions. These models, in general, do not consider the impact of local terrain and atmospheric circulations. In this study, long-term five-year wind data at three sites on the North, East, and West of the Baltimore metropolitan area, Maryland, USA are statistically analyzed. The Weibull probability density function was defined based on the observatory data. Despite seasonal and spatial variability in the wind resource, the annual mean wind speed for all sites is around 3 m/s, suggesting the region is not suitable for large-scale power generation. However, it does display a wind power capacity that might allow for non-grid connected small-scale wind turbine applications. Technical and economic performance evaluations of more than 150 conventional small-scale wind turbines showed that an annual capacity factor and electricity production of 11% and 1990 kWh, respectively, are achievable. It results in a payback period of 13 years. Government incentives can improve the economic feasibility and attractiveness of investments in small wind turbines. To reduce the payback period lower than 10 years, modern/unconventional wind harvesting technologies are found to be an appealing option in this region. Key contributions of this work are (1) highlighting the need for studying the urban physics rather than just the regional wind resource maps for wind development projects in the build-environment, (2) illustrating the implementation of this approach in a real case study of Maryland, and (3) utilizing techno-economic data to determine suitable wind harnessing solutions for the studied sites.

The making of the New European Wind Atlas – Part 1: Model sensitivity

Abstract. This is the first of two papers that document the creation of the New European Wind Atlas (NEWA). It describes the sensitivity analysis and evaluation procedures that formed the basis for choosing the final setup of the mesoscale model simulations of the wind atlas. The suitable combination of model setup and parameterizations, bound by practical constraints, was found for simulating the climatology of the wind field at turbine-relevant heights with the Weather Research and Forecasting (WRF) model. Initial WRF model sensitivity experiments compared the wind climate generated by using two commonly used planetary boundary layer schemes and were carried out over several regions in Europe. They confirmed that the most significant differences in annual mean wind speed at 100 m a.g.l. (above ground level) mostly coincide with areas of high surface roughness length and not with the location of the domains or maximum wind speed. Then an ensemble of more than 50 simulations with different setups for a single year was carried out for one domain covering northern Europe for which tall mast observations were available. We varied many different parameters across the simulations, e.g. model version, forcing data, various physical parameterizations, and the size of the model domain. These simulations showed that although virtually every parameter change affects the results in some way, significant changes in the wind climate in the boundary layer are mostly due to using different physical parameterizations, especially the planetary boundary layer scheme, the representation of the land surface, and the prescribed surface roughness length. Also, the setup of the simulations, such as the integration length and the domain size, can considerably influence the results. We assessed the degree of similarity between winds simulated by the WRF ensemble members and the observations using a suite of metrics, including the Earth Mover's Distance (EMD), a statistic that measures the distance between two probability distributions. The EMD was used to diagnose the performance of each ensemble member using the full wind speed and direction distribution, which is essential for wind resource assessment. We identified the most realistic ensemble members to determine the most suitable configuration to be used in the final production run, which is fully described and evaluated in the second part of this study (Dörenkämper et al., 2020).

Evaluation of Wind Energy Potential in a Sahelian Zone: A Case Study of Ouahigouya, Burkina Faso

This study investigates the characteristics of the wind energy potential in Ouahigouya, Burkina Faso. For this purpose, eleven-years data (2006-2016) of wind speed (at 10 m above ground level (AGL)) and surface temperature data from Burkina Faso meteorological agency and wind speed (50 m AGL) from the NASA were used. Based on the mean vertical profile of wind speed at monthly and annual scales, the Weibull function was used to characterize the wind speed frequency distribution and to calculate the wind power density. Major results indicate that the peaks of mean wind speeds are estimated at 3.51 m.s-1 (May) and 5.18 m.s-1 (March) for the 20 m and 50 m altitudes respectively. The mean annual wind speed at the 20 m AGL at the site is estimated at 2.87 m.s-1 while at 50 m AGL, a value of 4.33 m.s-1 is recorded. The estimated wind power density reveals that the largest amounts of energy are generally collected during the months corresponding to the dry season with peaks in March or May depending on the height. The amount of energy available at 20 m AGL varies from 32.90 W/m2 (September) to 84.97 W/m2 (May). At 50 m AGL, this value varies respectively from 68.68 W/m2 (August) to 346.47 W/m2 (March). Average annual power density amounts are estimated at 65.92 W/m2 at 20 m and 223.17 W/m2 at 50 m, respectively, for a growth rate of 70.46 %. In view of these results, the Ouahigouya site could be conducive to the installation of small and medium-sized turbines to supply rural communities with electrical energy.

Changes in wind turbine power characteristics and annual energy production due to atmospheric stability, turbulence intensity, and wind shear

The power generation of wind turbines varies depending on external environmental conditions. To present universal correlations between conditions that affect wind speed and wind turbine power, this study analyzed the effects of three atmospheric factors—atmospheric stability, turbulence intensity (TI), and wind shear exponent (WSE)—on the power performance and annual energy production (AEP) of wind turbines. Additionally, the horizontal and vertical speed components of the 3D sonic anemometer were investigated. At two measurement heights, unstable regimes showed an ascending air current, whereas stable regimes simultaneously showed both ascending and descending currents. Power curves calculated for each atmospheric factor regime revealed that atmospheric stability (200 kW–11 m/s) exhibited the greatest difference, followed by TI (91 kW–11 m/s) and WSE (32 kW–10.5 m/s). Finally, AEP was calculated at the annual mean wind speed of the study site and exhibited variations of 1.4–4% according to the factor regime. The AEP difference due to the change in atmospheric stability was greatest, and AEP was highest in moderately unstable atmospheric conditions. Clearer understanding of the effects of atmospheric factors on the power characteristics and AEP of wind turbines is expected to deliver practical benefits for wind-resource assessment and power-production prediction.

Influence of non-Gaussian characteristics of wind load on fatigue damage of wind turbine

Based on translation models, both Gaussian and non-Gaussian wind fields are generated using spectral representation method for investigating the influence of non-Gaussian characteristics and directivity effect of wind load on fatigue damage of wind turbine. Using the blade aerodynamic model and multi-body dynamics, dynamic responses are calculated. Using linear damage accumulation theory and linear crack propagation theory, crack initiation life and crack propagation life are discussed with consideration of the joint probability density distribution of the wind direction and mean wind speed in detail. The result shows that non-Gaussian characteristics of wind load have less influence on fatigue life of wind turbine in the area with smaller annual mean wind speeds. Whereas, the influence becomes significant with the increase of the annual mean wind speed. When the annual mean wind speeds are 7 m/s and 9 m/s at hub height of 90 m, the crack initiation lives under softening non-Gaussian wind decrease by 10% compared with Gaussian wind fields or at higher hub height. The study indicates that the consideration of the influence of softening non-Gaussian characteristics of wind inflows can significantly decrease the fatigue life, and, if neglected, it can result in non-conservative fatigue life estimates for the areas with higher annual mean wind speeds.

Study on the characteristics of climate change in Changbai Mountain National Natural Reserve from 1958 to 2017

Climate change is an important factor affecting the ecological environment of regions, and the local climate is closely related to the ecological environment. Taking the Changbai Mountain National Natural Reserve as an example, the regional climate change was studied by analyzing the data from the years 1953–2017. It is found that the temperature of Changbai Mountain is on the rise; the maximum monthly mean temperature difference is approximately 35 °C and the annual mean temperature is 2–5 °C. The monthly mean wind speed in this area has a wavy distribution and obvious seasonal variation. The correlation analysis shows that the correlation coefficient of the monthly mean value of cumulative photosynthetically active radiation (PAR) and total solar radiation (TSR), cumulative evaporation and cumulative PAR, cumulative evaporation and TSR, temperature and cumulative PAR, and temperature and cumulative evaporation were more than 0.9, indicating a significant correlation. The annual cumulative precipitation in this area is between 600 and 1000 mm, the annual cumulative evaporation is between 1000 and 1500 mm, the annual cumulative PAR is between 6000 and 10,000 mol m−2 s−1, and the annual TSR is between 4000 and 6000 MJ m−2. The annual cumulative precipitation, annual cumulative evaporation, annual mean wind speed, annual cumulative PAR, and annual TSR show a downward trend. The climate change in this area will not have a greater negative impact on the forest, but it still needs to pay close attention to the further climate change.

Correlation of spatial distribution and habitat factors of Firmiana danxiaensis based on GeoDetector

Firmiana danxiaensis is an endemic species of Danxia landform in China. Identifying the main driving factors of its distribution can provide scientific basis for the conservation of F. danxiaensis and related habitats. With GeoDetector, we analyzed the correlation (measured by q value) between the spatial distribution of F. danxiaens and its habitat factors in F. danxiaens Nature Reserve in Nanxiong City and the Guangdong Danxia Mountain Tourism Scenic Area (core scenic area). Factors measured in this study included geographical elements (geomorphological type, soil subtype, elevation, slope, aspect) and climatic elements (annual precipitation and annual sunshine hours, mean annual relative humidity and mean annual wind speed). Our results showed that the main habitat factors affecting the spatial distribution of F. danxiaensis were soil subtype, annual sunshine hours, and geomorphologic genesis type. The q values of those three factors were higher than the mean values of all factors. In the pairwise combination of habitat factors, the interaction between geomorphologic genesis types ∩ annual sunshine hours and soil subtypes ∩ annual sunshine hours was enhanced by two factors and the q value was greater than the mean value of all combinations, with a strong correlation. Compared with other factors, the q value of soil subtypes, annual sunshine hours and geomorphologic genesis types were significantly different in the ecological detection of spatial distribution correlation of F. danxiaensis. The spatial distribution of F. danxiaensis was significantly correlated with soil subtypes, geomorphologic genesis types and annual sunshine hours, indicating that the GeoDetector is a useful method for vegetation habitat factor analysis and species distribution prediction.

Local Climate Zone Classification Scheme Can Also Indicate Local-Scale Urban Ventilation Performance: An Evidence-Based Study

Studies on urban ventilation indicate that urban ventilation performance is highly dependent on urban morphology. Some studies have linked local-scale urban ventilation performance with the local climate zone (LCZ) that is proposed for surface temperature studies. However, there is a lack of evidence-based studies showing LCZ ventilation performance and affirming the reliability of using the LCZ classification scheme to demonstrate local-scale urban ventilation performance. Therefore, this study aims to analyse LCZ ventilation performances in order to understand the suitability of using the LCZ classification scheme to indicate local-scale urban ventilation performance. This study was conducted in Shenyang, China, with wind information at 16 weather stations in 2018. The results indicate that the Shenyang weather station had an annual mean wind speed of 2.07 m/s, while the mean wind speed of the overall 16 stations was much lower, only 1.44 m/s in value. The mean wind speed at Shenyang weather station and the 16 stations varied with seasons, day and night and precipitation conditions. The spring diurnal mean wind was strong with the speeds of 3.56 m/s and 2.21 m/s at Shenyang weather station and the 16 stations, respectively. The wind speed (2.21 m/s at Shenyang weather station) under precipitation conditions was higher than that (1.75 m/s at Shenyang weather station) under no precipitation conditions. Downtown ventilation performance was weaker than the approaching wind background, where the relative mean wind speed in the downtown area was only 0.53, much less than 1.0. The downtown ventilation performance also varied with seasons, day and night and precipitation conditions, where spring diurnal downtown ventilation performance was the weakest and the winter nocturnal downtown ventilation performance was the strongest. Moreover, the annual mean wind speed of the 16 zones decreased from the sparse, open low-rise zones to the compact midrise zones, indicating the suitability of using LCZ classification scheme to indicate local-scale urban ventilation performance. The high spatial correlation coefficients under different seasons, day and night and precipitation conditions, ranging between 0.68 and 0.99, further affirmed that LCZ classification scheme is also suitable to indicate local-scale urban ventilation performance, despite without the consideration of street structure like precinct ventilation zone scheme.

Evaluation of the Wind Potential and Optimal Design of a Wind Farm in The Arzew Industrial Zone in Western Algeria

This work presents an assessment of the wind potential and a design methodology for a 10 MW wind farm in the Arzew industrial region, located in northwest Algeria, to improve the quality of service of the electricity grid and increase Algeria's participation in the use of renewable energy. The hourly wind data of 10 years (2005-2015) that correspond to the wind potential of the site were analyzed, such as: dominant wind directions, probability distribution, Weibull parameters, mean wind speed and power potential. The site has a mean annual wind speed of 4.46 m/s at 10m height, and enough space to locate the wind turbines. A comparative study was carried out between four wind turbine technologies to improve the site's efficiency and select the appropriate technology: PowerWind 56/ 900 kW, Nordex N50/800 kW, Vestas V50/850 kW, NEG-Micon 44/750 kW. The estimate of the energy produced using WAsP software and the choice of the optimal architectural configuration for wind turbines installation was confirmed. A techno-economic and environmental study was carried out by HOMER software, to choose the model that produces the maximum annual net energy with a competitive cost in the global wind energy market, $ 0.068/kWh, and that provides clean energy with a reduced emission of polluting gases. Finally, this work provides a good indicator for the construction of a wind farm in Arzew.

Predictive model and assessment of the potential for wind and solar power in Rayak region, Lebanon

With the increasing consumption of fossil fuel, reducing greenhouse gas (GHG) emissions has become a serious issue that has attracted worldwide attention. Therefore, Lebanon is currently interested in utilizing renewable energy technologies to reduce energy dependence on oil reserves and GHG emissions. The present study is focused on solar and wind power potential and the economic viability of wind/solar systems for the Rayak region in Lebanon for the first time. The input data sources for the study including the Meteorological data for wind speed and NASA database for solar energy. In the assessment of wind energy, a two-parameter Weibull distribution function was used to analyze the characteristics of wind speed. Yearly and seasonal Weibull parameters were calculated for 10 m height using the Maximum likelihood method. In addition, yearly and seasonal wind power density values were calculated. The results showed that the mean annual wind speed and wind power density values were 5.884 m/s and 124.534 W/m2, respectively, during the investigation period. It can be concluded that the value of wind power density at the region was classified as marginal wind power potential and high-scale wind turbines can be used to gather wind energy potential in the region. Furthermore, predicting wind speed depends on various atmospheric factors and random variables. Therefore, 63 ANN models are developed by varying the meteorological parameters to predict the daily wind speed in the selected region. All the models with various combinations are validated and the performances of the models are analyzed using root mean squared error. The results demonstrated that the most relevant input variables for predicting the daily wind speed were found to be temperature, pressure, and relative humidity. In the assessment of wind energy, average monthly global solar radiation data were evaluated. It is found that the annual global solar radiation was 1877.41 kWh/m2, which indicates the selected region has high solar resources and is categorized as an excellent potential class. Moreover, this study provides a comprehensive and integrated feasibility analysis of 100 MW grid-connected wind and solar projects economic projects that can be developed in the country to reduce the electricity crisis and GHG emissions. Several different economic and financial indicators were calculated. The results indicate that the wind farm is a more economical option than the solar plant because of the higher values of NPV, BCR, ALCS, and IRR as well as the lower values of EB, SB, and LCOE.

Sakarya Nehri Deltası’nda Uzun Süreli Rüzgar ve Dalga İklimi Değişimleri

Global projections on the concept of climate change mainly indicate global warming, sea level rise and increases in climatic extremes. The main drivers of coast evolution related to climate change are rising sea levels, wave characteristics, storm frequency/intensity, and river floods. Delta plains are densely populated, and large numbers of people are often impacted by external terrestrial influences (e.g., river floods) and/or external marine influences (storm surges, erosion). Estuaries and deltas are widely recognized as highly vulnerable to the impacts of climate change, particularly sea-level rise and changes in runoff. The goal of this study is to evaluate the impact of climate change on wind and wave climate in a deltaic area. Sakarya River Delta system, a vulnerable deltaic area with a shoreline stretching approximately 80 km in Karasu province on the Black Sea coast of Turkey, is selected as a case study. Long-term wind and wave data in the study area were obtained from the NOAA CFSRR database and validated with measurements at different locations over the Black Sea. Annual mean wind speed and significant wave height show long-term decreasing trends (~4% and ~11%, respectively). Maximum wind speed and significant wave height tend to increase by 12% and 6%, respectively. In addition to the storm intensities, storm frequency also increases significantly (up to a 100% increase). The results of this study indicate that long-term changes in wind and wave climate in the study area are broadly consistent with climate change indicators.