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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.

In the present paper, the wind speed characteristics of three coastal regions in Lebanon, Beirut, Sidon, and Tripoli, were analyzed using ten statistical distributions. The wind speed data were collected from the meteorological service during a 7-year period (2010–2016).The maximum likelihood method was used to determine the parameters of the distribution functions. For the assessment of the reliability of the distribution functions, the Kolmogorov–Smirnov (KS) statistic was calculated. The wind power density values for the regions were also calculated at various heights using the power law model. The results showed that the wind power density value in the region is considerable and can be exploited using small-scale wind turbines. Moreover, the economic analyses of four wind turbine models of various types and sizes were estimated using the present value cost method. It is found that vertical axis wind turbines (VAWTs) offer the potential to outperform horizontal axis wind turbines in urban environments. VAWTs can handle unconventional wind and at slower speeds, which were found in these regions. Consequently, the Winddam (VWAT) turbine is strongly recommended for installation in the selected regions.

The current study is focused on the economic and financial assessments of solar and wind power potential for nine selected regions in Libya for the first time. As the existing meteorological data, including wind speed and global solar radiation, are extremely limited due to the civil war in the country, it was therefore decided to use the NASA (National Aeronautics and Space Administration) database as a source of meteorological information to assess the wind and solar potential. The results showed that the country has huge solar energy potential compared to wind energy potential. Additionally, it is found that Al Kufrah is a suitable region for the future installation of the Photovoltaic (PV) power plant due to high annual solar radiation. Based on the actual wind speed analysis, Benghazi and Dernah are the best regions for large-scale wind farm installation in the future taking into account existing meteorological data limitations. The values of the wind power density in all regions are considerable and small-scale wind turbines can be used to generate electricity based on NASA average monthly wind data for 37 years (1982–2019). Moreover, this work aimed to evaluate the wind/PV systems technical and economically through RETScreen Expert (Version 6.0, CanmetENERGY Varennes Research Centre of Natural Resources Canada, Varennes, Canada). Focusing on the power supply crisis in the country, the potential of electricity production by 5 kW grid-connected residential/household rooftop PV in all regions is proposed and presented. Additionally, this paper evaluated a techno-economic analysis of the 50MW wind/PV system in suitable places. The performance of a 5 kW and 50 MW PV solar system with three PV technologies, namely mono-crystalline silicon, poly-crystalline silicon, and thin-film (CdTe), was also analyzed. The results demonstrated that the development of the wind/PV system in the selected regions is both technically and economically feasible. The outcomes of this study can help decision-makers in designing and installing PV power plants as an alternative source for the future.

The present paper aims to investigate the wind power potential at seven selected locations, namely, Gujranwala, Islamabad Capital Territory, Jhimpir, Kati Bandar, Khanewal, Multan and Sialkot in Pakistan. Wind speeds were collected over a period of 2005–2016 and measured at 10 m height. In this study, ten distribution functions were applied to analyze the wind speed characteristics of these selected locations and estimate the wind power density. The results showed that Kati Bandar has the highest annual wind speed of 4.04 m/s in comparison to other locations, while the lowest value of 1.33 m/s was obtained in Islamabad Capital Territory. During the investigation period, it is observed that the maximum power density of 258.75 W/m2 is occurred in July at Kati Bandar, while the lowest minimum wind power density of 1.68 W/m2 occurred in September at Islamabad at 10 m height. The analysis result of the wind power and energy density as functions of tower height shows that higher tower height will produce higher wind power and energy density. Therefore, it is concluded that the wind power density values in the locations (Gujranwala, Islamabad Capital Territory, Khanewal, Multan, and Sialkot) are substantial and can be utilized using small-scale wind turbines for generating electricity. Consequently, the performances of four small-scale wind turbines were evaluated. Based on the results, the Pitch wind/30 kW Grid wind turbine had the highest annual capacity factor of 56.366%, whereas, WS-12/8 kW wind turbine had a minimum at 15.416%. The Minimum and the Maximum annual electricity cost in the studied locations are 0.005 $/kW h and 0.032 $/kW h using Pitch wind/30 kW Grid and WS-12/8 kW, respectively.

The increased energy demand and related environmental problems caused by burning fossil fuels have raised interest in alternative energy sources. This study investigated the wind characteristics and available wind energy for three urban regions in Northern Cyprus using the Weibull distribution function. The results illustrate that Gazimağusa is the most applicable location for harvesting the kinetic energy of the wind compared to Lefkoşa and Girne. Moreover, the solar potential at a specific location can be analyzed using a different simulation tool. In the present paper, the performance of a rooftop Photovoltaic (PV) system for household buildings in three selected is assessed. Three types of simulation software (PVGIS, PV*SOL, and PVWatts) are used to evaluate the performance of the 6.4 kWp grid-connected rooftop PV system. This study assessed the energy generation, performance ratio and capacity factor for this PV system. The results concluded that PVGIS is an easy, fast, and reliable software tool that can be used for the simulation of a solar PV system in the studied regions. Furthermore, an economic evaluation of renewable systems in the three urban regions is presented. As a result, a small-scale grid-connected solar/wind system that is able to generate electricity with an excellent percentage of clean energy was proposed and developed. The analysis indicates that the proposed PV projects showed significant potential in the studied locations. In addition, the proposed PV system is the most economical option for generating electricity compared to wind systems due to the low electricity prices and of the ability to recover the initial investment. Consequently, it is expected that the simulation results will help in demonstrating the advantages and challenges of installing grid-connected PV systems for households in Northern Cyprus in order to reduce the electricity consumption produced by fossil fuels.

This work focuses on the application of Multilayer Perceptron Neural Network (MLPNN), Radial Basis Function Neural Network (RPFNN) and Auto Regressive Integrated Moving Average (ARIMA) as predictive tools for the production of wind power density (WPD). The air temperature (AT), dew point (DP), atmospheric humidity (AH), pressure (P) and wind speed (WS) were used as the input variables for the models. Moreover, the performance of the models based on the R-squared value is presented. The results demonstrated that the MLPNN and ARIMA have the best accuracy for the prediction of WPD with the highest correlation coefficient of 0.99 compared to RPFNN. Consequently, it can be concluded that the MLPNN models developed in this study can be attractive for their incorporation in simulators.

Wind speed data is one of the most critical factors affecting the operation of wind power farm systems. This paper examines the forecasting performance of Auto-Regressive Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANN) models for predicting wind speeds in four regions in Northern Cyprus: Lefkosa, Girne, Salamis, and Bogaz. For the application of the methodology, the meteorological measurements including wind speed, air temperature, humidity, sunshine duration, global solar radiation and rainfall values, from 1 January 2013 to 31 December 2016, were used. The obtained results demonstrated that the ANN model realizes the best accuracy for the prediction of the wind speeds with the highest R-squared value.

This paper presents a techno-economic assessment of the wind power potential for eight locations distributed over the Northern part of Cyprus. The wind speed data were collected from the meteorological department located in Lefkoşa, Northern Cyprus.Ten distribution models were used to analyze the wind speed characteristics and wind energy potential at the selected locations. The maximum-likelihood method was used for calculating the parameters of the distribution functions.The power law model is utilized to determine the mean wind speed at various heights. In addition, the wind power density for each location was estimated. Furthermore, the performances of different small-scale vertical axis 3&ndash, 10 kW wind turbines were evaluated to find those that were suitable and efficient for power generation in the studied locations.The results showed that the annual mean wind speed in the regions is greater than 2 m/s at a height of 10 m. Moreover, it is indicated that Generalized Extreme Value distribution provided the best fit to the actual data for the regions of Lefkoşa, Ercan, Girne, G&uuml, zelyurt, and Dipkarpaz. However, the Log-Logistic, Weibull, and Gamma distributions gave a better fit to the actual data of Gazimağusa, YeniBoğazi&ccedil, i, and Salamis, respectively. The Rayleigh distribution does not fit the actual data from all regions. Furthermore, the values of wind power densityat the areas studied ranged from 38.76 W/m2 to 134.29 W/m2 at a height of 50 m, which indicated that wind energy sources in these selected locations are classified as poor. Meanwhile, based on the wind analysis, small-scale wind turbine use can be suitable for generating electricity in the studied locations. Consequently, an Aeolos-V2 with a rating of 5 kW was found to be capable of producing the annual energy needs of an average household in Northern Cyprus.

The purpose of this work is to determine the drag characteristics and the torque of three C-section blades wind car. Three C-section blades are directly connected to wheels by using of various kinds of links. Gears are used to convert the wind energy to mechanical energy to overcome the load exercised on the main shaft under low speed. Previous work on three vertical blades wind car resulted in discrepancies when compared to this work. Investigating these differences was the motivation for this series of work. The calculated values were compared to the data of three vertical blades wind car. The work was conducted in a low wind speed. The drag force acting on each model was calculated with an airflow velocity of 4 m/s and angular velocity of the blade of 13.056 rad/s.

Savonius is a drag type vertical axis wind turbine. Savonius wind turbines have a low cut-in speed and can operate at low wind speed. It is suitable for small scale power generation, such as individual domestic installations. In this paper, investigation into the relationship between the type of Savonius rotor, the torque and the mechanical power generated was carried out. Also an illustration on how the type of rotor plays an important role in the prediction of mechanical power of wind turbine powered car. The main purpose of this paper is to predict and investigate the aerodynamic effects by means of velocity analysis on the performance of a wind turbine powered car by converting the wind energy to mechanical energy to overcome load applied on the rotating main shaft. The predicted result based on theoretical analysis is compared with experimental results obtained from literature. Prediction of the torque was done at a wind speed of 4 m/s, and an angular velocity of 130 RPM according to meteorological statistics in Northern Cyprus.