This page has only limited features, please log in for full access.
The paper is concerned with designing an effective controller for a linear tubular homopolar (LT-H) motor type. The construction and operation of the LT-H motor are first described in detail. Then, the motor model is represented in the direct-quadrature (d-q) axes in order to facilitate the design of the control loops. The designed control system consists of two main loops: the current control loop and velocity adaptation loop. The determination of the regulator’s gains is accomplished through deriving and analyzing the transfer functions of the loops. To enhance the system’s robustness, a robust variable estimator is designed to observe the velocity and stator resistance. Different performance evaluation tests are performed using MATLAB/Simulink software to validate the controller’s robustness for variable-speed operation and load force changes as well. The obtained results reveal the appropriate dynamics of the motor thanks to the well-designed control system.
Mahmoud Mossa; Hamdi Echeikh; Ziad Ali; Mahrous Ahmed; Saad Al-Gahtani; Hamdy Sultan. Design and Modeling of a Robust Sensorless Control System for a Linear Permanent Magnet Synchronous Motor. Electronics 2021, 10, 966 .
AMA StyleMahmoud Mossa, Hamdi Echeikh, Ziad Ali, Mahrous Ahmed, Saad Al-Gahtani, Hamdy Sultan. Design and Modeling of a Robust Sensorless Control System for a Linear Permanent Magnet Synchronous Motor. Electronics. 2021; 10 (8):966.
Chicago/Turabian StyleMahmoud Mossa; Hamdi Echeikh; Ziad Ali; Mahrous Ahmed; Saad Al-Gahtani; Hamdy Sultan. 2021. "Design and Modeling of a Robust Sensorless Control System for a Linear Permanent Magnet Synchronous Motor." Electronics 10, no. 8: 966.
Recently, photovoltaic (PV) energy has been considered one of the most exciting new technologies in the energy sector. PV power plants receive considerable attention because of their wide applications. Consequently, it is important to study the parameters of the solar cell model to control and determine the characteristics of the PV systems. In this study, an improved bonobo optimizer (IBO) was proposed to improve the performance of the conventional bonobo optimizer (BO). Both the IBO and the BO were utilized to obtain the accurate values of the unknown parameters of different mathematical models of solar cells. The proposed IBO improved the performance of the conventional BO by enhancing the exploitation (local search) and exploration (global search) phases to find the best optimal solution, where the search space was reduced using Levy flights and the sine–cosine function. Levy flights enhance the explorative phase, whereas the sine–cosine function improves the exploitation phase. Both the proposed IBO and the conventional BO were applied on single, double, and triple diode models of solar cells. To check the effectiveness of the proposed algorithm, statistical analysis based on the results of 20 runs of the optimization program was performed. The results obtained by the proposed IBO were compared with other algorithms, and all results of the proposed algorithm showed their durability and exceeded other algorithms.
Reem Abdelghany; Salah Kamel; Hamdy Sultan; Ahmed Khorasy; Salah Elsayed; Mahrous Ahmed. Development of an Improved Bonobo Optimizer and Its Application for Solar Cell Parameter Estimation. Sustainability 2021, 13, 3863 .
AMA StyleReem Abdelghany, Salah Kamel, Hamdy Sultan, Ahmed Khorasy, Salah Elsayed, Mahrous Ahmed. Development of an Improved Bonobo Optimizer and Its Application for Solar Cell Parameter Estimation. Sustainability. 2021; 13 (7):3863.
Chicago/Turabian StyleReem Abdelghany; Salah Kamel; Hamdy Sultan; Ahmed Khorasy; Salah Elsayed; Mahrous Ahmed. 2021. "Development of an Improved Bonobo Optimizer and Its Application for Solar Cell Parameter Estimation." Sustainability 13, no. 7: 3863.
This paper proposes a modified version of a well-known optimization technique called Farmland Fertility Optimization algorithm (FFA). The modified FFA (MFFA) is developed in order to improve the performance of conventional FFA. It is mainly based on two stages. Firstly, the Levy flights are used to enhance the local searching capability in the exploitation phase and the global searching capability in the exploration phase. Secondly sine–cosine functions are used to create different solutions which fluctuate outwards or towards the best possible solution. The developed algorithm has been validated using ten benchmark functions and three mechanical engineering benchmark optimization problems. After that, the newly developed algorithm MFFA is used for extracting the effective unknown parameters of Proton Exchange Membrane Fuel Cells (PEMFCs) models. The optimal extraction of these parameters is essential to determine an accurate semi-empirical mathematical model for PEMFC. The sum of squared errors between the experimental data and the corresponding calculated ones is adopted as the objective function. Four different commercial PEMFC stacks are used to validate the effectiveness of the developed algorithm. The results obtained by MFFA are compared with those obtained by the conventional FFA and other well-known optimization techniques. Moreover, a comprehensive statistical analysis is performed to determine the accuracy and efficiency of the developed algorithm. The results prove the reliability and superiority of the developed algorithm compared with the conventional FFA and other state-of-the-art optimizers.
Ahmed S. Menesy; Hamdy M. Sultan; Ahmed Korashy; Salah Kamel; Francisco Jurado. A modified farmland fertility optimizer for parameters estimation of fuel cell models. Neural Computing and Applications 2021, 33, 12169 -12190.
AMA StyleAhmed S. Menesy, Hamdy M. Sultan, Ahmed Korashy, Salah Kamel, Francisco Jurado. A modified farmland fertility optimizer for parameters estimation of fuel cell models. Neural Computing and Applications. 2021; 33 (18):12169-12190.
Chicago/Turabian StyleAhmed S. Menesy; Hamdy M. Sultan; Ahmed Korashy; Salah Kamel; Francisco Jurado. 2021. "A modified farmland fertility optimizer for parameters estimation of fuel cell models." Neural Computing and Applications 33, no. 18: 12169-12190.
This paper mainly focuses on the optimal design of a grid-dependent and off-grid hybrid renewable energy system (RES). This system consists of Photovoltaic (PV), Wind Turbine (WT) as well as Fuel Cell (FC) with hydrogen gas tank for storing the energy in the chemical form. The optimal components sizes of the proposed hybrid generating system are achieved using a novel metaheuristic optimization technique. This optimization technique, called Improved Artificial Ecosystem Optimization (IAEO), is proposed for enhancing the performance of the conventional Artificial Ecosystem Optimization (AEO) algorithm. The IAEO improves the convergence trends of the original AEO, gives the best minimum objective function, reaches the optimal solution after a few iterations numbers as well as reduces the falling into the local optima. The proposed IAEO algorithm for solving the multiobjective optimization problem of minimizing the Cost of Energy (COE), the reliability index presented by the Loss of Power Supply Probability (LPSP), and excess energy under the constraints are considered. The hybrid system is suggested to be located in Ataka region, Suez Gulf (latitude 30.0, longitude 32.5), Egypt, and the whole lifetime of the suggested case study is 25 years. To ensure the accurateness, stability, and robustness of the proposed optimization algorithm, it is examined on six different configurations, representing on-grid and off-grid hybrid RES. For all the studied cases the proposed IAEO algorithm outperforms the original AEO and generates the minimum value of the fitness function in less execution time. Furthermore, comprehensive statistical measurements are demonstrated to prove the effectiveness of the proposed algorithm. Also, the results obtained by the conventional AEO and IAEO are compared with those obtained by several well-known optimization algorithms, Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA), and Grey Wolf Optimizer (GWO). Based on the obtained simulation results, the proposed IAEO has the best performance among other algorithms and it has successfully positioned itself as a competitor to novel algorithms for tackling the most complicated engineering problems.
Hamdy M. Sultan; Ahmed S. Menesy; Salah Kamel; Ahmed Korashy; S.A. Almohaimeed; Mamdouh Abdel-Akher. An improved artificial ecosystem optimization algorithm for optimal configuration of a hybrid PV/WT/FC energy system. Alexandria Engineering Journal 2020, 60, 1001 -1025.
AMA StyleHamdy M. Sultan, Ahmed S. Menesy, Salah Kamel, Ahmed Korashy, S.A. Almohaimeed, Mamdouh Abdel-Akher. An improved artificial ecosystem optimization algorithm for optimal configuration of a hybrid PV/WT/FC energy system. Alexandria Engineering Journal. 2020; 60 (1):1001-1025.
Chicago/Turabian StyleHamdy M. Sultan; Ahmed S. Menesy; Salah Kamel; Ahmed Korashy; S.A. Almohaimeed; Mamdouh Abdel-Akher. 2020. "An improved artificial ecosystem optimization algorithm for optimal configuration of a hybrid PV/WT/FC energy system." Alexandria Engineering Journal 60, no. 1: 1001-1025.
Proton exchange membrane fuel cell (PEMFC) is considered as propitious solution for an environmentally friendly energy source. A precise model of PEMFC for accurate identification of its polarization curve and in-depth understanding of all its operating characteristics attracted the interest of many researchers. In this paper, novel meta-heuristic optimization methods have been successfully applied to evaluate the unknown parameters of PEMFC models, particularly Harris Hawks’ optimization (HHO) and atom search optimization (ASO) techniques. The proposed optimization algorithms have been tested on three different commercial PEMFC stacks, namely BCS 500-W PEM, 500W SR-12PEM and 250W stack, under various operating conditions. The sum of square errors (SSE) between the results obtained by the application of the estimated parameters and the experimentally measured results of the fuel cell stacks was considered as the objective function of the optimization problem. In order to validate the effectiveness of the proposed methods, the results are compared with that obtained in studies. Moreover, the I/V curves obtained by the application of HHO and ASO showed a clear matching with data sheet curves for all the studied cases. Finally, PEMFC model based on HHO technique surpasses all compared algorithms in terms of the solution accuracy and the convergence speed.
Mahmoud A. Mossa; Omar Makram Kamel; Hamdy M. Sultan; Ahmed A. Zaki Diab. Parameter estimation of PEMFC model based on Harris Hawks’ optimization and atom search optimization algorithms. Neural Computing and Applications 2020, 33, 5555 -5570.
AMA StyleMahmoud A. Mossa, Omar Makram Kamel, Hamdy M. Sultan, Ahmed A. Zaki Diab. Parameter estimation of PEMFC model based on Harris Hawks’ optimization and atom search optimization algorithms. Neural Computing and Applications. 2020; 33 (11):5555-5570.
Chicago/Turabian StyleMahmoud A. Mossa; Omar Makram Kamel; Hamdy M. Sultan; Ahmed A. Zaki Diab. 2020. "Parameter estimation of PEMFC model based on Harris Hawks’ optimization and atom search optimization algorithms." Neural Computing and Applications 33, no. 11: 5555-5570.
Recently, fast uptake of renewable energy sources (RES) in the world has introduced new difficulties and challenges; one of the most important challenges is providing economic energy with high efficiency and good quality. To reach this goal, many traditional and smart algorithms have been proposed and demonstrated their feasibility in obtaining the optimal solution. Therefore, this paper introduces an improved version of Bonobo Optimizer (BO) based on a quasi-oppositional method to solve the problem of designing a hybrid microgrid system including RES (photovoltaic (PV) panels, wind turbines (WT), and batteries) with diesel generators. A comparison between traditional BO, the Quasi-Oppositional BO (QOBO), and other optimization techniques called Harris Hawks Optimization (HHO), Artificial Electric Field Algorithm (AEFA) and Invasive Weed Optimization (IWO) is carried out to check the efficiency of the proposed QOBO. The QOBO is applied to a stand-alone hybrid microgrid system located in Aswan, Egypt. The results show the effectiveness of the QOBO algorithm to solve the optimal economic design problem for hybrid microgrid power systems.
Mohammed Kharrich; Omar Hazem Mohammed; Salah Kamel; Ali Selim; Hamdy M. Sultan; Mohammed Akherraz; Francisco Jurado. Development and Implementation of a Novel Optimization Algorithm for Reliable and Economic Grid-Independent Hybrid Power System. Applied Sciences 2020, 10, 6604 .
AMA StyleMohammed Kharrich, Omar Hazem Mohammed, Salah Kamel, Ali Selim, Hamdy M. Sultan, Mohammed Akherraz, Francisco Jurado. Development and Implementation of a Novel Optimization Algorithm for Reliable and Economic Grid-Independent Hybrid Power System. Applied Sciences. 2020; 10 (18):6604.
Chicago/Turabian StyleMohammed Kharrich; Omar Hazem Mohammed; Salah Kamel; Ali Selim; Hamdy M. Sultan; Mohammed Akherraz; Francisco Jurado. 2020. "Development and Implementation of a Novel Optimization Algorithm for Reliable and Economic Grid-Independent Hybrid Power System." Applied Sciences 10, no. 18: 6604.
Developing a precise semiempirical mathematical model based on multi-nonlinear equations for the proton-exchange membrane fuel cell (PEMFC), which guarantees suitable and accurate simulation of the electrical characteristics of typical PEMFC stacks under various operating scenarios, is the main target of this study. The unknown parameters of the PEMFC model are extracted using a novel efficient optimization technique called coyote optimization algorithm (COA). To validate the effectiveness of the proposed COA-based PEMFC model, two different cases of seven and ten unknown parameters are performed on a commercial PEMFC taken from literature. The sum of squared errors (SSE) between the experimentally measured data and the corresponding computed ones is considered as the objective function. Besides, the effectiveness of the developed algorithm is validated under different operating conditions. Moreover, the results obtained by the application of the proposed COA have been compared with other recent optimization methods reported in the literature, and very competitive results have been provided. Furthermore, parametric and nonparametric statistical analyses are presented to evaluate the accuracy and viability of the developed COA-based PEMFC model.
Hamdy M. Sultan; Ahmed S. Menesy; Salah Kamel; Francisco Jurado. Developing the coyote optimization algorithm for extracting parameters of proton-exchange membrane fuel cell models. Electrical Engineering 2020, 103, 563 -577.
AMA StyleHamdy M. Sultan, Ahmed S. Menesy, Salah Kamel, Francisco Jurado. Developing the coyote optimization algorithm for extracting parameters of proton-exchange membrane fuel cell models. Electrical Engineering. 2020; 103 (1):563-577.
Chicago/Turabian StyleHamdy M. Sultan; Ahmed S. Menesy; Salah Kamel; Francisco Jurado. 2020. "Developing the coyote optimization algorithm for extracting parameters of proton-exchange membrane fuel cell models." Electrical Engineering 103, no. 1: 563-577.
Recently, Proton Exchange Membrane Fuel Cells (PEMFCs) become one of the most promising friendly renewable energy sources. Therefore, developing a mathematical model for the PEMFC is an urgent necessity for simulation and evaluation of the processes occurring inside the fuel cell (FC) stack. In this paper, a precis model, which can stimulate the electrical and electrochemical phenomenon of the PEMFC is introduced. Improved salp swarm algorithm (ISSA) is proposed to enhance the performance of the conventional SSA and avoid getting stuck on local optimum. The proposed ISSA has been utilized for identifying the unknown parameter values of PEMFC stack models. The proposed ISSA is validated on four different FC stacks and a comparison between the computed and measured results has been accomplished. The Sum of Squared Errors (SSE) between experimental and estimated voltages is adopted as the objective function which has to be minimized. For validating the goodness of the ISSA, the generated values of the unknown parameters and the value of SSE using the ISSA-based PEMFC model are compared with the corresponding ones obtained by other optimization techniques. Furthermore, statistical analysis of proposed ISSA compared with the conventional SSA is carried out for all the PEMFC stacks involved in this work. The simulation results under various conditions of operation and the statistical results proved the stability and reliability of ISSA in comparison with recently utilized algorithms.
Hamdy M. Sultan; Ahmed S. Menesy; Salah Kamel; Ali Selim; Francisco Jurado. Parameter identification of proton exchange membrane fuel cells using an improved salp swarm algorithm. Energy Conversion and Management 2020, 224, 113341 .
AMA StyleHamdy M. Sultan, Ahmed S. Menesy, Salah Kamel, Ali Selim, Francisco Jurado. Parameter identification of proton exchange membrane fuel cells using an improved salp swarm algorithm. Energy Conversion and Management. 2020; 224 ():113341.
Chicago/Turabian StyleHamdy M. Sultan; Ahmed S. Menesy; Salah Kamel; Ali Selim; Francisco Jurado. 2020. "Parameter identification of proton exchange membrane fuel cells using an improved salp swarm algorithm." Energy Conversion and Management 224, no. : 113341.
Among all renewable energy sources, solar cells are considered the most popular solution for a clean source of energy and have a wide range of applications from few watts to Megawatt industrial and domestic loads. Building a precise mathematical model based on nonlinear equations for solar cells as well as photovoltaic (PV) modules is an essential issue for reasonable performance assessment, control and optimal operation of PV energy systems. In the current study, a novel optimization algorithm, Tree Growth Algorithm (TGA), is applied for accurate and efficient extraction of the unknown solar cell and PV module parameters. TGA is applied for estimating the unidentified parameters of PV models. Single diode model (SDM), double diode model (DDM) and three diode model (TDM) are investigated in the mathematical models of both solar cells and PV modules. The obtained results from the application of TGA to achieve this objective are compared with different algorithms reported in the literature. Moreover, the results demonstrated that the proposed algorithm of TGA superior to other reported methods. The good matching of the I-V characteristic curve of the computed parameters with those of the measured data from the manufacturer’s PV modules/cells datasheet proved that the proposed TGA may function as a competitor to the methods provided in literature for parameters’ identification of PV of solar cells.
Ahmed A. Zaki Diab; Hamdy M. Sultan; Raseel Aljendy; Ameena Saad Al-Sumaiti; Masahito Shoyama; Ziad M. Ali. Tree Growth Based Optimization Algorithm for Parameter Extraction of Different Models of Photovoltaic Cells and Modules. IEEE Access 2020, 8, 119668 -119687.
AMA StyleAhmed A. Zaki Diab, Hamdy M. Sultan, Raseel Aljendy, Ameena Saad Al-Sumaiti, Masahito Shoyama, Ziad M. Ali. Tree Growth Based Optimization Algorithm for Parameter Extraction of Different Models of Photovoltaic Cells and Modules. IEEE Access. 2020; 8 ():119668-119687.
Chicago/Turabian StyleAhmed A. Zaki Diab; Hamdy M. Sultan; Raseel Aljendy; Ameena Saad Al-Sumaiti; Masahito Shoyama; Ziad M. Ali. 2020. "Tree Growth Based Optimization Algorithm for Parameter Extraction of Different Models of Photovoltaic Cells and Modules." IEEE Access 8, no. : 119668-119687.
Recently, building an accurate mathematical model with the help of the experimentally measured data of solar cells and Photovoltaic (PV) modules, as a tool for simulation and performance evaluation of the PV systems, has attracted the attention of many researchers. In this work, Coyote Optimization Algorithm (COA) has been applied for extracting the unknown parameters involved in various models for the solar cell and PV modules, namely single diode model, double diode model, and three diode model. The choice of COA algorithm for such an application is made because of its good tracking characteristics and the balance creation between the exploration and exploitation phases. Additionally, it has only two control parameters and such a feature makes it very simple in application. The Root Mean Square Error (RMSE) value between the data based on the optimized parameters for each model and those based on the measured data of the solar cell and PV modules is adopted as the objective function. Parameters’ estimation for various types of PV modules (mono-crystalline, thin-film, and multi-crystalline) under different operating scenarios such as a change in intensity of solar radiation and cell temperature is studied. Furthermore, a comprehensive statistical study has been performed to validate the accurateness and stability of the applied COA as a competitor to other optimization algorithms in the optimal design of PV module parameters. Simulation results, as well as the statistical measurement, validate the superiority and the reliability of the COA algorithm not only for parameter extraction of different PV modules but also under different operating scenarios. With the COA, precise PV models have been established with acceptable RMSE of $7.7547\times 10^{-4}$ , $7.64801\times 10^{-4}$ , and $7.59756 \times 10^{-4}$ for SDM, DDM, and TDM respectively considering R.T.C. France solar cell.
Ahmed A. Zaki Diab; Hamdy M. Sultan; Ton Duc Do; Omar Makram Kamel; Mahmoud A. Mossa. Coyote Optimization Algorithm for Parameters Estimation of Various Models of Solar Cells and PV Modules. IEEE Access 2020, 8, 111102 -111140.
AMA StyleAhmed A. Zaki Diab, Hamdy M. Sultan, Ton Duc Do, Omar Makram Kamel, Mahmoud A. Mossa. Coyote Optimization Algorithm for Parameters Estimation of Various Models of Solar Cells and PV Modules. IEEE Access. 2020; 8 ():111102-111140.
Chicago/Turabian StyleAhmed A. Zaki Diab; Hamdy M. Sultan; Ton Duc Do; Omar Makram Kamel; Mahmoud A. Mossa. 2020. "Coyote Optimization Algorithm for Parameters Estimation of Various Models of Solar Cells and PV Modules." IEEE Access 8, no. : 111102-111140.
In recent years, modular multilevel converters (MMC) are becoming popular in the distribution and transmission of electrical systems. The multilevel converter suffers from circulating current within the converter that increases the conduction loss of switches and increases the thermal stress on the capacitors and switches’ IGBTs. One of the main solutions to control the circulating current is to keep the capacitor voltage balanced in the MMC. In this paper, a new hybrid control algorithm for the cascaded modular multilevel converter is presented. The Harris hawk’s optimization (HHO) and Atom search optimization (ASO) are used to optimally design the controller of the hybrid MMC. The proposed structure of modular multilevel inverters allows effective operation, a low level of harmonic distortion in the absence of output voltage filters, a low switching frequency, and excellent flexibility to achieve the requirements of any voltage level. The effectiveness of the proposed controller and the multilevel converter has been verified through testing with the application of the MMC-static synchronous compensator (STATCOM). The stability of the voltage capacitors was monitored with balanced and unbalanced loads on the studied network.
Ahmed A. Zaki Diab; Terad Ebraheem; Raseel Aljendy; Hamdy M. Sultan; Ziad M. Ali. Optimal Design and Control of MMC STATCOM for Improving Power Quality Indicators. Applied Sciences 2020, 10, 2490 .
AMA StyleAhmed A. Zaki Diab, Terad Ebraheem, Raseel Aljendy, Hamdy M. Sultan, Ziad M. Ali. Optimal Design and Control of MMC STATCOM for Improving Power Quality Indicators. Applied Sciences. 2020; 10 (7):2490.
Chicago/Turabian StyleAhmed A. Zaki Diab; Terad Ebraheem; Raseel Aljendy; Hamdy M. Sultan; Ziad M. Ali. 2020. "Optimal Design and Control of MMC STATCOM for Improving Power Quality Indicators." Applied Sciences 10, no. 7: 2490.
Hamdy Sultan; Oleg N. Kuznetsov; Ahmed S. Menesy; Salah Kamel. Optimal Configuration of a Grid-Connected Hybrid PV/Wind/Hydro-Pumped Storage Power System Based on a Novel Optimization Algorithm. 2020 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE) 2020, 1 .
AMA StyleHamdy Sultan, Oleg N. Kuznetsov, Ahmed S. Menesy, Salah Kamel. Optimal Configuration of a Grid-Connected Hybrid PV/Wind/Hydro-Pumped Storage Power System Based on a Novel Optimization Algorithm. 2020 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE). 2020; ():1.
Chicago/Turabian StyleHamdy Sultan; Oleg N. Kuznetsov; Ahmed S. Menesy; Salah Kamel. 2020. "Optimal Configuration of a Grid-Connected Hybrid PV/Wind/Hydro-Pumped Storage Power System Based on a Novel Optimization Algorithm." 2020 International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE) , no. : 1.
Recently, extracting the precise values of unknown parameters of the polymer electrolyte membrane fuel cell (PEMFC) is considered one of the most widely nonlinear and semi-empirical optimization problems. This paper proposes and applies a Modified Artificial Ecosystem Optimization (MAEO) algorithm to solve the problem of PEMFC parameters extraction. The conventional AEO is a novel optimization technique that is inspired by the energy flow in a natural ecosystem which is defined as abiotic, which includes non-living bodies and elements such as light, water and air. The proposed optimization algorithm, MAEO, is used to enhance the performance of conventional AEO and provide faster convergence rate as well as to be far away from falling into the local optima. In the proposed MAEO, an operator is suggested to improve the balance between exploitation and Exploration phases. The accurate estimation of PEMFC unknown parameters leads to develop a precise mathematical model which simulates the electrochemical and electrical characteristics of PEMFC. The objective function of the studied optimization problem is formulated as the sum of squared errors (SSE) between the measured and simulated stack voltages. To prove the reliability and capability of the proposed MAEO algorithm in solving this problem compared with other recent algorithms, it is tested on four different PEMFC stack models, namely, BCS-500W, SR-12 500W, 250W and Temasek 1 kW stacks. Moreover, statistical measures are performed to assess the superiority and robustness of the proposed algorithm. In addition, the accuracy of optimized parameters is assessed through the dynamic characteristics of PEMFCs under varying the reactants’ pressures and temperature of the cell. However, the simulation results confirm that the proposed MAEO algorithm has high accuracy and reliability in extracting the PEMFC optimal parameters compared with the conventional AEO and other effective algorithms.
Ahmed S. Menesy; Hamdy M. Sultan; Ahmed Korashy; Fahd A. Banakhr; Mohamed G. Ashmawy; Salah Kamel. Effective Parameter Extraction of Different Polymer Electrolyte Membrane Fuel Cell Stack Models Using a Modified Artificial Ecosystem Optimization Algorithm. IEEE Access 2020, 8, 31892 -31909.
AMA StyleAhmed S. Menesy, Hamdy M. Sultan, Ahmed Korashy, Fahd A. Banakhr, Mohamed G. Ashmawy, Salah Kamel. Effective Parameter Extraction of Different Polymer Electrolyte Membrane Fuel Cell Stack Models Using a Modified Artificial Ecosystem Optimization Algorithm. IEEE Access. 2020; 8 (99):31892-31909.
Chicago/Turabian StyleAhmed S. Menesy; Hamdy M. Sultan; Ahmed Korashy; Fahd A. Banakhr; Mohamed G. Ashmawy; Salah Kamel. 2020. "Effective Parameter Extraction of Different Polymer Electrolyte Membrane Fuel Cell Stack Models Using a Modified Artificial Ecosystem Optimization Algorithm." IEEE Access 8, no. 99: 31892-31909.
Recently, meeting the strict criteria of grid codes for the integrating renewable energy sources (RES) has become a challenge for engineers and researchers. Moreover, voltage stability is an essential criterion for the stable performance of grid connected wind and Photovoltaic (PV) power plants during grid disturbances and fault ride through. This paper investigates the implementation of fuzzy logic-based Static VAR Compensator (SVC) for the voltage stability issue of IEEE-9 bus test system in the presence of Wind and PV energy systems. This paper introduces the application of the fuzzy logic-based SVC as a dynamic voltage restorer to maintain stable voltage and thereby protecting the RES during and after the disturbances. The effectiveness of the controller is evaluated under different fault conditions including three phase and single phase to ground faults. The power system model is simulated in MATLAB / SIMULINK and the comprehensive comparisons have been reported.
Hamdy Sultan; Oleg N. Kuznetsov; Ahmed A. Zaki Diab; Salama Abu-Zaid. Enhancement of Transient Voltage Stability of Wind/PV Power System using Fuzzy Logic Based-SVC. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) 2020, 1227 -1233.
AMA StyleHamdy Sultan, Oleg N. Kuznetsov, Ahmed A. Zaki Diab, Salama Abu-Zaid. Enhancement of Transient Voltage Stability of Wind/PV Power System using Fuzzy Logic Based-SVC. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). 2020; ():1227-1233.
Chicago/Turabian StyleHamdy Sultan; Oleg N. Kuznetsov; Ahmed A. Zaki Diab; Salama Abu-Zaid. 2020. "Enhancement of Transient Voltage Stability of Wind/PV Power System using Fuzzy Logic Based-SVC." 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) , no. : 1227-1233.
Energy saving, increasing the energy efficiency and reducing the power losses are strategic tasks for any electric network. Despite the numerous scientific studies, the level of power loss during transmission through the electric networks of the Republic of Tajikistan, and in particular the republican subordination areas of Tajikistan, exceeds the optimal values of 5-10%. Based on this, in this paper, a structural analysis and assessment of technical power losses in the 0.4-500 kV electric networks of the republican subordination areas in Tajikistan was carried out. The structure of technical power losses by voltage levels and types of losses is introduced. The enterprises of electric networks of the republican subordination regions with high levels of relative power losses have been identified. The values of the components of the technical power losses are compared with the average values of these components in the electric networks of Russia
Sirojiddin R. Chorshanbiev; Saiyod G. Jononaev; Ashur M. Ashurov; Behruzi S. Jamolzoda; Hamdy Sultan. Structural Analysis and Assessment of Technical Power Losses in 0.4-500 kV Electric Networks of the Republican Subordination Areas in Tajikistan. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) 2020, 1194 -1197.
AMA StyleSirojiddin R. Chorshanbiev, Saiyod G. Jononaev, Ashur M. Ashurov, Behruzi S. Jamolzoda, Hamdy Sultan. Structural Analysis and Assessment of Technical Power Losses in 0.4-500 kV Electric Networks of the Republican Subordination Areas in Tajikistan. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). 2020; ():1194-1197.
Chicago/Turabian StyleSirojiddin R. Chorshanbiev; Saiyod G. Jononaev; Ashur M. Ashurov; Behruzi S. Jamolzoda; Hamdy Sultan. 2020. "Structural Analysis and Assessment of Technical Power Losses in 0.4-500 kV Electric Networks of the Republican Subordination Areas in Tajikistan." 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) , no. : 1194-1197.
The Electric energy became the backbone of the life and as a result the demand for electric energy has been sharply increased worldwide especially in the few last years. Therefore, the electrical power that will be delivered to the grid and after that to the consumers have to be provided within the range allowable of the international standards. A detailed study of the status of the electric energy system in Iraq has been introduced. In particular, this work is applied on Iraqi national power system and focused on the Iraqi 400 kV super grid. The Iraqi 400 kV super grid has been deeply introduced by its modeling steady state simulation. DigSILENT PowerFactory simulation package was used to simulate the grid model based on the real data. The performance analysis of the grid is based on the voltage profile, power losses and transmission lines loading according to the power flow results.
Ahmed S. Al-Akayshee; Oleg N. Kuznetsov; Hamdy Sultan. Modelling and Performance Evaluation of the 400kV National Grid in Iraq in DigSILENT PowerFactory. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) 2020, 1151 -1156.
AMA StyleAhmed S. Al-Akayshee, Oleg N. Kuznetsov, Hamdy Sultan. Modelling and Performance Evaluation of the 400kV National Grid in Iraq in DigSILENT PowerFactory. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). 2020; ():1151-1156.
Chicago/Turabian StyleAhmed S. Al-Akayshee; Oleg N. Kuznetsov; Hamdy Sultan. 2020. "Modelling and Performance Evaluation of the 400kV National Grid in Iraq in DigSILENT PowerFactory." 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) , no. : 1151-1156.
The increasing demand for electrical energy and fossil fuels that must be a one-day depleted lead the humanity to discover alternative energy sources. Solar energy is a one of these sources and to determine the suitable place to build a photovoltaic power plants it's so important. In this study, 20 locations in Iraq are tested for building a 100 Mw PV power plant to support the Iraqi national grid with additional generations. These locations are chosen in different places according to the solar radiation estimations, Iraqi climate conditions, environmental and economic aspects, availability of lands for installation and future developments, water resources and the distance from transmission lines, substations, and highways. The results have been accomplished via RETScreen Expert package. This study clearly demonstrates that photovoltaic power system will be effective solution in Iraq thanks for the long sunshine.
Ahmed S. Al-Akayshee; Oleg N. Kuznetsov; Hamdy Sultan. Viability Analysis of Large Photovoltaic Power Plants as a Solution of Power Shortage in Iraq. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) 2020, 1145 -1150.
AMA StyleAhmed S. Al-Akayshee, Oleg N. Kuznetsov, Hamdy Sultan. Viability Analysis of Large Photovoltaic Power Plants as a Solution of Power Shortage in Iraq. 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). 2020; ():1145-1150.
Chicago/Turabian StyleAhmed S. Al-Akayshee; Oleg N. Kuznetsov; Hamdy Sultan. 2020. "Viability Analysis of Large Photovoltaic Power Plants as a Solution of Power Shortage in Iraq." 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus) , no. : 1145-1150.
In this paper, an efficient optimization technique called Chaotic Harris Hawks optimization (CHHO) is proposed and applied for estimating the accurate operating parameters of proton exchange membrane fuel cell (PEMFC), which simulate and mimic its electrical performance. The conventional Harris Hawks optimization (HHO) is a recent optimization technique that is based on the hunting approach of Harris hawks. In this proposed optimization technique, ten chaotic functions are applied for tackling with the studied optimization problem. The CHHO is proposed to enhance the search capability of conventional HHO and avoid its trapping into local optima. The sum of squared errors (SSE) between the experimentally measured output voltage and the corresponding simulated ones is adopted as the objective function. The developed CHHO technique is tested on four various commercial PEMFC stacks to assess and validate its effectiveness compared with other well-known optimization techniques. A statistical study is performed to appreciate the stability and reliability of the proposed CHHO technique. However, the results show the effectiveness and superiority of proposed CHHO compared with the conventional HHO and other competitive metaheuristic optimization algorithms under the same study cases.
Ahmed S. Menesy; Hamdy M. Sultan; Ali Selim; Mohamed G. Ashmawy; Salah Kamel. Developing and Applying Chaotic Harris Hawks Optimization Technique for Extracting Parameters of Several Proton Exchange Membrane Fuel Cell Stacks. IEEE Access 2019, 8, 1146 -1159.
AMA StyleAhmed S. Menesy, Hamdy M. Sultan, Ali Selim, Mohamed G. Ashmawy, Salah Kamel. Developing and Applying Chaotic Harris Hawks Optimization Technique for Extracting Parameters of Several Proton Exchange Membrane Fuel Cell Stacks. IEEE Access. 2019; 8 (99):1146-1159.
Chicago/Turabian StyleAhmed S. Menesy; Hamdy M. Sultan; Ali Selim; Mohamed G. Ashmawy; Salah Kamel. 2019. "Developing and Applying Chaotic Harris Hawks Optimization Technique for Extracting Parameters of Several Proton Exchange Membrane Fuel Cell Stacks." IEEE Access 8, no. 99: 1146-1159.
Providing access to clean, reliable, and affordable energy by adopting hybrid power systems is important for countries looking to achieve their sustainable development goals. This paper presents an optimization method for sizing a hybrid system including photovoltaic (PV), wind turbines with a hydroelectric pumped storage system. In this paper, the implementation of different optimization techniques has been investigated to achieve optimal sizing of grid-connected hybrid renewable energy systems. A comprehensive study has been carried out between Whale Optimization Algorithm (WOA), Water Cycle Algorithm (WCA), Salp Swarm Algorithm (SSA), and Grey Wolf optimizer (GWO) to validate each one. Moreover, the optimal sizing of the system’s components has been studied using real-time information and meteorological data of Ataka region located in Egypt. The purpose of the optimization process is to minimize the cost of energy from this hybrid system while satisfying the operation constraints including high reliability of the hybrid power supply, small fluctuation in the energy injected to the grid, and high utilization of the photovoltaic and wind complementary properties. MATLAB software package has been used to evaluate each optimization algorithm for solving the considered optimization problem. Simulation results proved that WOA has the most promising performance over other techniques.
Ahmed A. Zaki Diab; Hamdy Sultan; Oleg N. Kuznetsov. Optimal sizing of hybrid solar/wind/hydroelectric pumped storage energy system in Egypt based on different meta-heuristic techniques. Environmental Science and Pollution Research 2019, 27, 32318 -32340.
AMA StyleAhmed A. Zaki Diab, Hamdy Sultan, Oleg N. Kuznetsov. Optimal sizing of hybrid solar/wind/hydroelectric pumped storage energy system in Egypt based on different meta-heuristic techniques. Environmental Science and Pollution Research. 2019; 27 (26):32318-32340.
Chicago/Turabian StyleAhmed A. Zaki Diab; Hamdy Sultan; Oleg N. Kuznetsov. 2019. "Optimal sizing of hybrid solar/wind/hydroelectric pumped storage energy system in Egypt based on different meta-heuristic techniques." Environmental Science and Pollution Research 27, no. 26: 32318-32340.
Recently, the policy of most countries is to use renewable energy sources (RES) together with traditional sources to meet the growing demand for electricity. In the Syrian Arab Republic, in order for eliminating the shortage of active power production, maintaining the required voltage level at the nodes of the electric network and minimizing the power losses, it is planned for integrating solar and wind power plants into the grid in conjunction with the existing traditional sources. In this paper, an approach for selecting the installed capacity of solar and wind power plants at the specified locations for installation has been provided. To demonstrate the efficiency of the proposed algorithm, the results were compared with another algorithm applied in the same field. Modeling and simulation of the regional power system, as well as the optimization algorithms of the installed capacities of the proposed RES were carried out using Simulink MATLAB package.
Raseel I. Aljendy; R.R. Nasyrov; V.N. Tulsky; Hamdy Sultan. Optimal Installed Capacity of Renewable Energy Sources for Active Power Shortage Minimization. 2019 International Ural Conference on Electrical Power Engineering (UralCon) 2019, 349 -354.
AMA StyleRaseel I. Aljendy, R.R. Nasyrov, V.N. Tulsky, Hamdy Sultan. Optimal Installed Capacity of Renewable Energy Sources for Active Power Shortage Minimization. 2019 International Ural Conference on Electrical Power Engineering (UralCon). 2019; ():349-354.
Chicago/Turabian StyleRaseel I. Aljendy; R.R. Nasyrov; V.N. Tulsky; Hamdy Sultan. 2019. "Optimal Installed Capacity of Renewable Energy Sources for Active Power Shortage Minimization." 2019 International Ural Conference on Electrical Power Engineering (UralCon) , no. : 349-354.