Wind power is rapidly growing worldwide as a renewable and clean energy of choice due to its competitiveness in cost and technology advancement. However, as the wind turbines grow, the aerodynamic noise generated from the rotating blades is becoming a major concern that limits the use of wind turbines, especially near residential housing areas. A significant low sleep quality has been reported within 2km of wind turbines locations that is becoming a problem for wider use of wind energy. [1]. Generally, continuous exposure to 85-90 dBA noise causes permanent hearing loss to human [2]. To reduce the aerodynamic noise, channeled blades were implemented in this work to damp the airflow turbulence that causes the aerodynamic noise. Samples of different diameter sizes and angle of inclinations with respect to the cord have been tested and compared to a regular unchanneled blade. Noise measurements have been carried out using low-frequency microphones with frequencies ranging between 0-10000 Hz. While turbulence measurements were performed using a hot-wire anemometer. The measured noise around the blades ranged between 20-70 dB up to 600 Hz has proven to be directly related to turbulence intensity. The best low noise blade design was recommended based on noise measurement.

This paper presents linear regression models to predict the daily energy production of three photovoltaic (PV) systems located in southeast Virginia. The prediction is based on daylight duration, sky index, the average relative humidity, and the presence of fog or mist. No other daily weather report components were statistically significant. The proposed method is easy to implement, and it can be used in conjunction with other advanced methods in estimating any given future day’s energy production if weather prediction is available. Data from 2013-2015 was used in the model construction. Model validation was performed using newer (2016, 2017, 2020, and 2021) data not used in the model construction. Results show good prediction accuracy for a simple methodology, free of system parameters, that can be utilized by ordinary photovoltaic energy users. The entire data set can be downloaded using the link provided.

In this work, we demonstrate the improvement of thermal performances of a heat pipe parabolic trough solar collector by optimizing the annulus space, between the evaporator and the glass envelope, and using an appropriate filling gas. We compared the system thermal effectiveness for nine filling gases (hydrogen, air, helium, neon, oxygen, nitrogen, argon, krypton, and xenon). The results showed that using xenon or krypton leads to the best thermal yield (70%). While krypton arises to be the most energetically efficient filling gas, argon, with a thermal yield of 62%, presents a best compromise as the cheapest inert gas. In addition, we showed that the annular space size should be less than a critical value to minimize heat losses and to reduce the material cost during manufacturing.

Accurate forecasting is the key factor in promoting wind power consumption and improving the stable operation of power systems. A short-term wind power forecasting (WPF) and uncertainty analysis method based on whale optimization algorithm (WOA), least squares support vector machine (LSSVM), and nonparametric kernel density estimation (NPKDE) was proposed in this paper. The advantages of WOA (fast convergence speed and high convergence accuracy) were used to optimize the penalty factor and kernel function width of the LSSVM model, and the calculation speed and forecasting accuracy of the LSSVM model were improved. The training sample set is classified according to the wind speed interval, and the WOA-LSSVM forecasting model is trained by subclass after classification to further improve the accuracy of short-term WPF. The NPKDE method is used to accurately calculate the probability density distribution characteristics of the forecasting error of wind power, and the confidence interval of the WPF is accurately calculated based on the probability density distribution characteristics. The calculation results show that the forecasting accuracy of the WOA-LSSVM model is higher than those of the LSSVM, long short-term memory (LSTM), and particle swarm optimization and least squares support vector machine (PSO-LSSVM) models, and the forecasting accuracy of the WOA-LSSVM model can be further improved after classifying the training sample set. The coverage of the confidence intervals in different time scales is higher than the corresponding confidence level, indicating that the NPKDE method can accurately describe the probability density distribution characteristics of the WPF errors.

This article presents a comprehensive study of the dynamic behavior of small vertical-axis wind turbines (VAWTs) based on local fabricated Savonius VAWTs, which is suitable for countries that have a moderate wind speed. The merits of this design are cleanliness, silent, start-up under low wind speed, independent wind directions, adaptability, and ease of manufacturing. Also, this article presents an experimental validation study for the optimized Savonius VAWT. Four verification test configurations of the optimized VAWT composite blades are designed, simulated, and fabricated of Glass—Polyester with different stacking sequence layout for each. Modified mechanical parameters are introduced to improve the scalability, reliability, and accuracy of the developed models. Based on wind energy conversion system basics, aerodynamic characteristics (tip speed ratio (λ) and coefficient of power (C p )) and dynamic characteristics (natural frequencies and mode shapes) of Savonius rotor models are presented and simulated within solidworks simulation 2020 software. The dynamic characteristics such as frequency, mode shape, and damping factor are extensively investigated using fast Fourier transform (FFT) analyzer. The results show that the role of composite material blades in improving the dynamic performance of a wind turbine is significant.

The treatment of sludge, which is produced from raw water treatment, has been considered as an ecologically sensitive problem in terms of energy and pollution. In this context, this study presents many series of solar drying tests that were carried on three samples of sludge obtained from several drinking water treatment plants in Marrakech-Safi regions, Morocco. The main aim is to develop further management processes of these wastes such as upgrading or storage. A partially solar indirect convective dryer operating in forced convection was used to run experiment tests. The temperature of air has ranged from 50 to 90°C and the relative humidity from 24% to 46%. The drying airflow was kept at about 0.0833 m 3 /s. An estimation of the mass diffusion coefficient and the activation energy during vacuum drying besides the characteristic convective drying curve were established. In addition, six semi-theoretical and/or empirical and statistical models were used to predict experimental data. It was found that the temperature was the most important factor during the drying process. Furthermore, the obtained results of mass diffusion coefficient and activation energy were found consistent with those already existing in the literature. The mathematical model called “Midilli–Kucuk” was found to be the most appropriate to describe the drying curves of the three samples. The total energy consumption was also studied. It showed a downward tendency with the increase in temperature. The efficiency of drying energy ranged from 4.89% to 7.5%. Although it was found to be low, it can be improved by increasing the load.

In this paper, a ZnO/CdS/CuO:Co solar cell was prepared on a glass/indium oxide (ITO) substrate. First, we use RF-sputtering to deposit the window (ZnO) layer by optimizing the oxygen pressure while keeping the RF power at 200 W. Fourier transform infrared and X-ray reflectometry spectra were carried out, and it is found that 30% of O 2 is the optimal percentage to obtain the best density and the best refractive index for the ZnO layer. The CdS layer was then deposited by the sol–gel method to align the energy bands, and a layer of CuO:Co with a thickness of 750 nm was deposited, also by reactive RF-sputtering technique. Finally, the electrical contacts were made by depositing circular silver electrodes. The obtained photovoltaic activity of device confirms that the aforementioned method is promising for further future optimizations.

Concentrating solar power (CSP) development has focused on increasing the energy conversion efficiency and lowering the capital cost. To improve performance, CSP research is moving to high-temperature and high-efficiency designs. One technology approach is to use inexpensive, high-temperature heat transfer fluids and storage, integrated with a high-efficiency power cycle such as the supercritical carbon dioxide (sCO 2 ) Brayton power cycle. The sCO 2 Brayton power cycle has strong potential to achieve performance targets of 50% thermal-to-electric efficiency and dry cooling at an ambient temperature of up to 40 °C and to reduce the cost of power generation. Solid particles have been proposed as a possible high-temperature heat transfer or storage medium that is inexpensive and stable at high temperatures above 1000 °C. The particle/sCO 2 heat exchanger (HX) provides a connection between the particles and sCO 2 fluid in emerging sCO 2 power cycles. This article presents heat transfer modeling to analyze the particle/sCO 2 HX design and assess design tradeoffs including the HX cost. The heat transfer process was modeled based on a particle/sCO 2 counterflow configuration, and empirical heat transfer correlations for the fluidized bed and sCO 2 were used to calculate heat transfer area and estimate the HX cost. A computational fluid dynamics simulation was applied to characterize particle distribution and fluidization. This article shows a path to achieve the cost and performance objectives for a particle/sCO 2 HX design by using fluidized-bed technology.

The structural and architectural elements of building-integrated photovoltaic-thermal (BIPVT) systems are made up of photovoltaic (PV) modules and these are required to be fixed at an optimum inclination angle for generating maximum exergy. This work presents an attempt to determine the amount of exergy generated by an optimally inclined double-storied BIPV thermal system by considering the actual cyclic nature of insolation, surrounding air temperature, PV cell temperature, intermediate slab temperature, and the chamber temperature. The insolation value, which is computed by an anisotropic sky model along with these cyclic variables, is used for solving the set of governing differential equations for evaluating the exergy of the system. Other influencing parameters of the BIPV thermal systems such as air changes in both chambers, packing factor of PV module, the orientation of PV module, and thickness of the intermediate slab are considered for finding its effect on the total exergy of the system. Numerical results show that for packing factor more than 0.6, there is no significant change in total heat exergy with respect to the inclination angle. For packing factor more than 0.3, the generation of electrical exergy exceeds the heat exergy, and the overall exergy of BIPVT system decreases with rise in packing factor (β m ) up to 0.3 and then rises nonlinearly.

Power generation from renewable energy sources, in particular solar photovoltaics (PV), has become extremely attractive thanks to its very low levelized cost of electricity (LCoE). In desert-like environments, the energy yield is drastically reduced due to dust accumulation. While effective and affordable cleaning strategies can be implemented in large, MW-size PV power plants, soiling remains an economic and logistic challenge. In this article, we analyze the soiling loss rates of PV modules for different tilt angles measured during a period of 15 months in the Western Region of Saudi Arabia. We observe a strong correlation between weather parameters like humidity and wind speed and the mechanism of dust accumulation. Our measurements show that, for specific weather conditions, soiled modules undergo a partial cleaning process. As a consequence, and for the first time, the soiling loss rates are shown to have a clear dependence on the current soiling state of the modules, with clean modules soiling twice as fast as soiled ones. This dependency is a key for predicting the correct cleaning frequency of a PV power plant. Finally, the results obtained for vertically mounted modules (90 deg), where dust accumulation is negligible, point to a favorable case for the use of bifacial PV modules.

A method for optimizing the geometrical layout for a façade-mounted solar photovoltaic array is presented. Unlike conventional studies, this work takes into account the finite height of the façade, which is more realistic. The proposed analytical relationships and optimization routine evaluate the best tilt angle and the number of panels such that the whole layout receives the maximum solar radiation, year-round. This is achieved while ensuring that the panels are at a safe minimum distance to avoid mutual shading issues. Validation was performed by simulating the scenarios and comparing the results with manual measurements taken in a three-dimensional drafting program. The method was then used to evaluate designs for facades with a variety of orientations, hypothetically located in Auckland, New Zealand. For this case study, the per-panel and total year-round energy accumulation associated with the number of panels were determined. The results showed that more panels can be integrated into constrained fields by sacrificing the year-round best value of the tilt angle. Therefore, increasing the number of panels may decrease the energy accumulation performance.

Renewable energy sources are being considered an alternative for the provision of an uninterrupted supply of power to cover the extensive mobile services. The main purpose of this study is to determine a cost-effective way of achieving environmental sustainability of electricity supply in Global System for Mobile (GSM) communications mobile phone applications using photovoltaic systems. A specific installation of base transceiver stations and base station located in an arid and remote area was used as a case study. Using PV solar systems to secure a GSM relay in remote areas with hot climate is a very attractive alternative because of the solar irradiation accessible in the desert. The economic study carried out using the “Hybrid Optimization Model for Electric Renewable” simulation tool showed that the best configuration of the solar photovoltaic system for the case study in the present work consisted of 6 kW photovoltaic panels, 4 kW converter, and 24 storage batteries. The solar energy contribution in the electricity consumption was around 38%, and the other 62% was supplied by the power grid. The total net present cost (NPC) of the solar system was 43,946$. Regarding the environmental impact, all energy scenarios investigated showed a significant improvement in the environmental life cycle; especially the emissions of carbon dioxide were reduced by 65% by replacing the diesel generator backup system with the photovoltaic-assisted system.

A performance assessment was conducted for a solar–biogas hybrid micro gas turbine integrated with a solar power tower technology. The considered system is a solar central receiver integrated with a micro gas turbine hybrid with biogas fuel as a backup. The Brayton cycle is designed to receive a dual integrated heat source input that works alternatively to keep the heat input to the system continuous. The study considered several key performance parameters including meteorological condition effects, recuperator existence and effectiveness, solar share, and gas turbine components performance. This study shows a significant reduction in CO 2 emissions due to the utilization and hybridization of the renewable energies, solar, and biogas. The study reveals that the solar–biogas hybrid micro gas turbine for 100-kW power production has a CO 2 emission less than a conventional fossil fuel gas turbine. Finally, the study shows that the method of power generation hybridization for solar and biogas gas turbines is a promising technique that leads to fuel-savings and lower CO 2 emissions.

Organic solar cells are considered to be the promising solar technology for the coming year because of their ease of manufacture. In the present study, the Aloe Latex as a yellow orange Solid (ALS) collected from the leaves of Aloe Vera plant (aloe barbadensis miller) was used as a natural and cheap sensitizer thin film. The ALS powder was analyzed using X-ray diffraction,UHPLC-MS, and Fourier transform infrared (FT-IR) spectroscopy to determine the chemical composition and the structural properties. While the impedance spectroscopy was performed for the dielectrical properties. The optical properties were detemined using UV–Vis absorption of the ALS thin film deposited in a glass. For the first trial, a planar heterojunction solar cell using zinc oxide (ZnO) thin film as an electron selective layer was build. The band gap was found to be 1.88 eV. The electrical properties of the investigated cell by the current–voltage (I–V) measurements showed an open-circuit voltage (Voc) of 0.74 V, an important efficiency of 0.50%, and a great fill factor (FF) of 0.70.

A magnetohydrodynamic (MHD) generator is a device that generates electrical energy through the interaction between a conductive fluid and a magnetic field. This method of direct energy conversion allows the use of a renewable energy source such as solar energy and represents an alternative to tackle the greenhouse effect. This paper presents the development of an MHD solar generator, which is constituted by a solar thermal system and an MHD cell. The solar thermal system consists of a set of tubes with copper fins, connected in parallel and placed inside of a 1 m 2 panel. In which, an electrolytic mixture of H 2 O and NaCl at 20% vol. was introduced as a working fluid. In order to increase the kinetic energy of the fluid, the panel was exposed to solar radiation, where it reached temperatures above 373 K and pressures above 96 kPa. This solar thermal system operates in closed cycle conditions by including a check valve in its inlet–outlet junction; in this way, the fluid travels through the MHD generator. The MHD cell was composed of a block of polytetrafluoroethylene, two cylindrical stainless-steel electrodes, and four neodymium magnets. For simulation purposes, comsol multiphysics was used to reproduce the current density produced by the MHD solar generator. Pressure and temperature quantities obtained experimentally in the MHD cell were employed as boundary conditions. The experimental maximal current density obtained corresponds to 4.30 mA/m 2 , and the comparison between theoretical and experimental results shows that the model fits fairly well.

This article presents a study of modeling and optimization for the dynamic performance of wind turbine composite material blades and investigates the effects of composite material stacking sequence in addition to some design parameters such as twist angle (ɸ) and aspect ratio (AR) on the whole wind turbine performance. The two-stage Savonius rotor VAWT composite blades are designed and simulated within the solidworks simulation 2020 package. Modified mechanical parameters are introduced to improve the scalability, reliability, and accuracy of the developed models. The lamination plate theory is used to compute the equivalent mechanical properties for each composite blade. The finite element analyses (FEAs) are conducted to investigate the dynamic characteristics (frequency and associated mode shapes) of wind turbine models. Taguchi tools such as analysis of variance (ANOVA), signal-to-noise (S/N) ratio and additive model were employed to evaluate and obtain the significant factors and determine the optimal combination levels of wind turbine design parameters. Mathematical modeling based on response surface methodology (RSM) has been established. The analysis of results shows that the aspect ratio with a contribution of 48.08% had the dominant impact on the rotor performance followed by the stacking sequence and twist angle.

In the current research, the sensitivity analysis of N alike in parts covered photovoltaic thermal compound parabolic concentrator collectors integrated single-slope solar distiller unit is performed and examined. The analysis is done using computational programming in matlab (month: May and location: New Delhi). The parametric values of potable water and DC electric power outputs have been figured for different values of mass flow rate (MFR), number of collectors (N), packing factor (PF), and water depth (WD). Elaborative observations says that the value of potable water output declines and DC electric power output increases with the increase in MFR for the considered values of N, PF, and WD. Also the values of DC electric power increases by 81.63% if packing factor is increased from 0.4 to 0.6 for the considered values of MFR, N, and WD. Based on the results of all the analysis, sensible and effective conclusions are made.

The fixed setup angles of photovoltaic (PV) panels are typically optimized properly in order to maximize the electrical energy harvest. In the present work, the sunlight availability or sky coverage conditions of sufficiently small time intervals for everyday around the year are counted in the modeling for computation of solar energy on the PV panel in order to optimize the panel tilt angles. Maximal energy harvest in a year is the objective of choosing the optimal tilt angles. The analysis calculates vectors of instantaneous sunray and solar panel normal direction to consider the ‘cosine’ effect. The energy harvested in every 6 min by a PV panel of per square meter is summated for day-long period from sunrise to sunset when the sun elevation angle is above 5 deg. The general model is applied to the authors’ local city, Tucson, Arizona, USA. The results show that the annual solar energy received by a solar panel tilted with a fixed angle of equal to the local latitude could reach to 2297 kWh/m 2 with the 10-year averaged sky coverage conditions of every 6 min considered. However, if a PV panel is inclined using the discovered optimal angles with two times, four-seasonal, and monthly adjustments, the gain in the yearly solar energy harvest can be 7.59%, 7.60%, and 9.19%, respectively, greater than that with the fixed angle equal to local latitude.

This article proposes a new hybrid least squares-support vector machine and artificial bee colony algorithm (ABC-LS-SVM) for multi-hour ahead forecasting of global solar radiation (GHI) data. The framework performs on training the least squares-support vector machine (LS-SVM) model by means of the ABC algorithm using the measured data. ABC is developed for free parameters optimization for the LS-SVM model in a search space so as to boost the forecasting performance. The developed ABC-LS-SVM approach is verified on an hourly scale on a database of five years of measurements. The measured data were collected from 2013 to 2017 at the Applied Research Unit for Renewable Energy (URAER) in Ghardaia, south of Algeria. Several combinations of input data have been tested to model the desired output. Forecasting results of 12 h ahead GHI with the ABC-LS-SVM model led to the root-mean-square error (RMSE) equal to 116.22 Wh/m 2 , Correlation coefficient r = 94.3%. With the classical LS-SVM, the RMSE error equals to 117.73 Wh/m 2 and correlation coefficient r = 92.42%; for cuckoo search algorithm combined with LS-SVM, the RMSE = 116.89 Wh/m 2 and r = 93.78%. The results achieved reveal that the proposed hybridization scheme provides a more accurate performance compared to cuckoo search-LS-SVM and the stand-alone LS-SVM.

Multi-megawatt wind turbines are nowadays a mature technology, and therefore, there is considerable scientific and industrial attention to the opportunity of further improving the efficiency of wind kinetic energy conversion into electricity. One of the major developments in this field of research regards the optimization of wind turbine control. This work deals with a test case of yaw control optimization on a 2-MW wind turbine sited in Italy. The objective of the work is to compute the performance improvement provided by the upgrade after some months of operation. This has been accomplished through the formulation of an appropriate model for the power of the wind turbine of interest and the analysis of the residuals between model estimates and measurements before and after the upgrade. In this work, a general procedure for selecting a robust multivariate linear model is adopted, and the resulting model, employing as input variables several operational variables from the nearby wind turbines in the farm, is used for quantifying the performance improvement. The estimate is that this upgrade provides a 0.8% improvement of the annual energy production.