The present study presents two techniques of Maximum Power Point Tracking (MPPT) via DC/DC converter to enhance the performance of the grid-connected Photovoltaic (PV) generation system to participate effectively within microgrids. The two techniques of MPPT are Perturb-Observe (P&O) and Incremental Conductance (IC). The variation of the solar radiation and temperature is considered during employing the two MPPT techniques. Besides, the performance of the system under the random variation of solar radiation was investigated. The authors used two types of controllers at the three-phase inverter, Proportional Integral (PI) and H-infinity Control (H∞C). The output voltage, current, and power at each type of inverter controller are compared along with the two techniques of MPPT. The effectiveness of the developed controllers together with MPPT techniques is demonstrated by comparing the obtained results with some previously reported research in the literature. In the case of MPPT via P&O and IC techniques along with the H∞C controller, the results show that the technique of IC is more robust, and the obtained output power is well matched with the references one as compared with the P&O technique which records a 7% error from MPP. Besides, the P&O technique has a high voltage and current ripple with a percentage of 20% at the starting time of the simulation.

This paper is intended to determine the space-charge-free field on the stressed discharge wires’ surface, the corona-onset voltage of wire-duct electrostatic precipitators (ESP) as influenced by the variation of the velocities of the incoming flow gases. The corona current-voltage (I-V) characteristics of wire-duct ESP is calculated under varying velocities of incoming flow gases. The calculation is made using the improvement of Deutsch’s Method. The method is endorsed by an iterative process to determine an estimate for the underlying dissemination of the charge density close to the surface of the stressed discharge wire(s). The electric potential, field, space-charge density in the interelectrode spacing, corona onset voltage and current-voltage characteristics of the precipitator are considered. Besides, the effect of gradually increase of the velocities of incoming flow gases, changing the number of stressed wires and changing the wire radius of wire-duct ESP are investigated. An experimental set-up has made in the Laboratory of High Voltage Engineering, Czech Technical University (CTU) in Prague, Czech Republic to investigate the accuracy of mathematical/simulation analyzed of the corona-onset voltage as well as the validation of the developed Deutsch’s Method in modeling the I-V characteristics of wire-duct ESPs. The experimental results reasonably agree with the theoretical analysis.

This paper is intended to determine the space-charge-free field on the stressed discharge wires’ surface, the corona-onset voltage of wire-duct electrostatic precipitators (ESP) as influenced by the variation of the velocities of the incoming flow gases. The corona current-voltage (I-V) characteristics of wire-duct ESP is calculated under varying velocities of incoming flow gases. The calculation is made using the improvement of Deutsch’s Method. The method is endorsed by an iterative process to determine an estimate for the underlying dissemination of the charge density close to the surface of the stressed discharge wire(s). The electric potential, field, space-charge density in the interelectrode spacing, corona onset voltage and current-voltage characteristics of the precipitator are considered. Besides, the effect of gradually increase of the velocities of incoming flow gases, changing the number of stressed wires and changing the wire radius of wire-duct ESP are investigated. An experimental set-up has made in the Laboratory of High Voltage Engineering, Czech Technical University (CTU) in Prague, Czech Republic to investigate the accuracy of mathematical/simulation analyzed of the corona-onset voltage as well as the validation of the developed Deutsch’s Method in modeling the I-V characteristics of wire-duct ESPs. The experimental results reasonably agree with the theoretical analysis.

The main purpose of this paper to compare and analyze three types of controllers in the three phases DC–AC inverters in hybrid renewable energy source (HRES) systems. To achieve this, two modern controllers are developed and compared based on sliding mode control (SMC) and artificial neural network techniques. The HRESs comprise photovoltaic (PV), wind turbines, battery storage systems, and transmission lines connected to infinite bus bars via a step-up transformer. The developed controllers at the inverter side utilize both voltage control and current regulation. A DC–DC boost converter is employed to set up a voltage demand at the point of common coupling (PCC). Then, the formulation of an HRES with the developed controllers is presented. The developed controllers are considered to operate under various solar radiations, temperatures, and wind speed loading conditions. The HRESs with the developed controllers are simulated via MATLAB/ Simulink to verify the effectiveness of the developed controllers. The obtained results demonstrate that adaptive SMC and artificial ANN control techniques give better results in terms of input power, output power, current, and voltage when compared to classic PI control.

The main purpose of this paper to compare and analyze three types of controllers in the three phases DC–AC inverters in hybrid renewable energy source (HRES) systems. To achieve this, two modern controllers are developed and compared based on sliding mode control (SMC) and artificial neural network techniques. The HRESs comprise photovoltaic (PV), wind turbines, battery storage systems, and transmission lines connected to infinite bus bars via a step-up transformer. The developed controllers at the inverter side utilize both voltage control and current regulation. A DC–DC boost converter is employed to set up a voltage demand at the point of common coupling (PCC). Then, the formulation of an HRES with the developed controllers is presented. The developed controllers are considered to operate under various solar radiations, temperatures, and wind speed loading conditions. The HRESs with the developed controllers are simulated via MATLAB/ Simulink to verify the effectiveness of the developed controllers. The obtained results demonstrate that adaptive SMC and artificial ANN control techniques give better results in terms of input power, output power, current, and voltage when compared to classic PI control.

The main purpose of this paper to compare and analyze three types of controllers in the three phases DC–AC inverters in hybrid renewable energy source (HRES) systems. To achieve this, two modern controllers are developed and compared based on sliding mode control (SMC) and artificial neural network techniques. The HRESs comprise photovoltaic (PV), wind turbines, battery storage systems, and transmission lines connected to infinite bus bars via a step-up transformer. The developed controllers at the inverter side utilize both voltage control and current regulation. A DC–DC boost converter is employed to set up a voltage demand at the point of common coupling (PCC). Then, the formulation of an HRES with the developed controllers is presented. The developed controllers are considered to operate under various solar radiations, temperatures, and wind speed loading conditions. The HRESs with the developed controllers are simulated via MATLAB/ Simulink to verify the effectiveness of the developed controllers. The obtained results demonstrate that adaptive SMC and artificial ANN control techniques give better results in terms of input power, output power, current, and voltage when compared to classic PI control.

Rechargeable batteries with Li‐metal anodes and Ni‐rich LiNixMnyCozO2 (x + y + z = 1, NMC) cathodes promise high‐energy‐density storage solutions. However, commercial carbonate‐based electrolytes (CBEs) induce deteriorative interfacial reactions to both Li‐metal and NMC, leading to Li dendrite formation and NMC degradation. Moreover, CBEs are thermally unstable and flammable, demonstrating severe safety risks. In this study, an ultrathin and non‐flammable dual‐salt polymer electrolyte (DSPE) is proposed via lightweight polytetrafluoroethylene scaffold, poly(vinylidene fluoride‐co‐hexafluoropropylene) polymeric matrix, dual‐salt, and adiponitrile/fluoroethylene carbonate functional plasticizers. The as‐obtained DSPE exhibits an ultralow thickness of 20 µm, high room temperature ionic conductivity of 0.45 mS cm−1, and a large electrochemical window (4.91 V versus Li/Li+). The dual‐salt synergized with functional plasticizers is used to fabricate a stable interface layer on both anode and cathode. In‐depth experimental and theoretical analyses have revealed the formation of stable interfaces between the DSPE and the anode/cathodes. As a result, the DSPE effectively prevents Li/DSPE/Li symmetric cell from short‐circuiting after 1200 h, indicating effective suppression of Li dendrites. Moreover, the Li/DSPE/NMC cell delivers outstanding cyclic stability at 2 C, maintaining a high capacity of 112 mAh g−1 over 1000 cycles.

Roads extraction from VHR satellite images are very paramount for GIS and map updating. Due to the high resolution of satellite images, there are many obstacles broken roads such as shadow, and vehicles. The present work aims to find the most suitable road extraction approach that can be applied in the Egyptian environment. In this study, two satellite images from WorldView-2 and WorldView-3 were used. Classification of image by pixel-based and object-based was carried out to find the appropriate classification method for road extraction. Then, road class refinement by morphology and angular texture signature are performed to decrease the misclassifications between roads and other spectrally similar objects. After that, an iterative and localized Hough transform method was compared with the thinning algorithm method to find the proper method that can extract road centerline segments from the refined images. The performance of the extracted roads was estimated by using the common metrics; completeness, correctness, and quality. The results of this work demonstrate that the random tree in object-based classification achieves the highest overall accuracy than other classification methods. Also, thinning algorithm has more advantages than Hough transform.

Roads extraction from VHR satellite images are very paramount for GIS and map updating. Due to the high resolution of satellite images, there are many obstacles broken roads such as shadow, and vehicles. The present work aims to find the most suitable road extraction approach that can be applied in the Egyptian environment. In this study, two satellite images from WorldView-2 and WorldView-3 were used. Classification of image by pixel-based and object-based was carried out to find the appropriate classification method for road extraction. Then, road class refinement by morphology and angular texture signature are performed to decrease the misclassifications between roads and other spectrally similar objects. After that, an iterative and localized Hough transform method was compared with the thinning algorithm method to find the proper method that can extract road centerline segments from the refined images. The performance of the extracted roads was estimated by using the common metrics; completeness, correctness, and quality. The results of this work demonstrate that the random tree in object-based classification achieves the highest overall accuracy than other classification methods. Also, thinning algorithm has more advantages than Hough transform.

Shadow detection is an important process for applications like classification, change detection, image interpretation, object detection, and recognition. The existence of shadow in satellite images reduce the amount of information that can be extracted and accordingly makes these applications more difficult or even impossible. Different color space is used to detect shadows based on , , and  bands. This paper aims to represent an automatic approach for shadow detection from high-resolution satellite images. In this approach, a new index to highlight shadow areas based on  color model is developed. A comparative study is carried out between the proposed index with a different photometric invariant color model, including IHS, HSV, YIQ, and  models over the ratio and single-band images. Then, an automatic thresholding method is applied in images histogram. The accuracy of the obtained results is evaluated in terms of visual comparisons and shadow detection accuracy assessments. Experimental results show that the proposed ratio method provides the best results for shadow detection. On the other hand, shallow water is still misclassified as a shadow.