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Dr. Salah Kamel
Aswan University

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Research Keywords & Expertise

0 Optimization
0 Biomass and bioenergy
0 Power system analysis
0 Reneawable Energy System
0 Smart Grid Application

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Optimization
Power system analysis

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Journal article
Published: 07 August 2021 in Sustainability
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This paper presents an effective solution for the short-term hydrothermal generation scheduling (STHS) problem using an integration of wind and photovoltaic power (PV) system. Wind and PV power are integrated into the power system to minimize the total fuel cost of thermal units. In this paper, the lightning attachment procedure optimization algorithm (LAPO) is employed to solve the STHS problem using the wind and PV power integration system. The proposed method is applied for solving five test systems with different characteristics, considering the valve-point loading impact of the thermal unit. The first and third test systems include hydro and thermal units only, and the rest of the systems consist of hydro and thermal units with integrating wind and PV power-generating units to inspect the effect of renewable energy sources in the selected test systems. The simulation results are compared with other studied methods. It is found that the proposed method is superior, and it has the ability to obtain the best solutions with respect to other optimization methods that are implemented to solve the STHS problem.

ACS Style

Maha Mohamed; Abdel-Raheem Youssef; Salah Kamel; Mohamed Ebeed; Ehab Elattar. Optimal Scheduling of Hydro–Thermal–Wind–Photovoltaic Generation Using Lightning Attachment Procedure Optimizer. Sustainability 2021, 13, 8846 .

AMA Style

Maha Mohamed, Abdel-Raheem Youssef, Salah Kamel, Mohamed Ebeed, Ehab Elattar. Optimal Scheduling of Hydro–Thermal–Wind–Photovoltaic Generation Using Lightning Attachment Procedure Optimizer. Sustainability. 2021; 13 (16):8846.

Chicago/Turabian Style

Maha Mohamed; Abdel-Raheem Youssef; Salah Kamel; Mohamed Ebeed; Ehab Elattar. 2021. "Optimal Scheduling of Hydro–Thermal–Wind–Photovoltaic Generation Using Lightning Attachment Procedure Optimizer." Sustainability 13, no. 16: 8846.

Journal article
Published: 19 July 2021 in Applied Sciences
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The paper proposes a real-time model for electric vehicles (EVs) controlled load charging. The proposed demand-side management (DSM) of EVs is implemented based on queuing analysis with a nonhomogeneous arrival rate and charging service periods dataset. An electric vehicle model is used which is based on a statistical survey to represent the uncontrolled demand of the EVs. A probability distribution for the time at which EVs are plugged and the corresponding value of the state of charges (SOCs) are considered. The preferences of individual EVs have been fully exploited through a set of instructions to fulfill the needs of the vehicles’ owners. The designated preferences include the owner setting for both, charging price preferences (OPR), and the maximum estimated parking time duration (EPTD). The quasi-static time-series (QSTS) simulation is used to simulate real-time scenarios of the 24-h simulation period. The IEEE 123 nodes radial test feeder is analyzed with different daily load curves, EV charging scenarios, and wind power penetrations. The results show the effectiveness of the proposed DSM in avoiding excessive levels of charging with/without penetration of non-dispatchable wind power generation. The proposed DSM enables the EVs to charge with low tariff rates either at excessive renewable power generation or late evening hours with available committed bulk power plants and light loading conditions.

ACS Style

Ali Selim; Mamdouh Abdel-Akher; Salah Kamel; Francisco Jurado; Sulaiman Almohaimeed. Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles. Applied Sciences 2021, 11, 6632 .

AMA Style

Ali Selim, Mamdouh Abdel-Akher, Salah Kamel, Francisco Jurado, Sulaiman Almohaimeed. Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles. Applied Sciences. 2021; 11 (14):6632.

Chicago/Turabian Style

Ali Selim; Mamdouh Abdel-Akher; Salah Kamel; Francisco Jurado; Sulaiman Almohaimeed. 2021. "Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles." Applied Sciences 11, no. 14: 6632.

Journal article
Published: 13 July 2021 in IEEE Access
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Today’s electrical power system became more complex interconnected network that is expanding every day. The transmission lines of the power system are more severely loaded than ever before. Hence, the power system is facing many problems such as power losses increasing, voltage instability, line overloads, etc. The optimization of real and reactive powers due to the installation of energy resources at appropriate buses can minimize the losses and improve the voltage profile especially, for congested networks. As a result, the optimal power flow problem (OPF) is considered more important tool for the processes of planning and operation of power systems. OPF is a very significant tool for power system operators to meet the electricity demand of the consumers efficiently, and for the reliable operation of the power system. However, the incorporation of renewable energy sources (RESs) into the electrical grid is a very challenging problem due to their intermittent nature. In this paper, the proposed power flow model contains three different types of energy sources: thermal power generators representing the conventional energy sources, wind power generators (WPGs), and solar photovoltaic generators (SPGs) representing RESs. Uncertain output powers from WPGs and SPGs are forecasted with the aid of Weibull and lognormal probability distribution functions (PDF), respectively. The under and overestimation output powers of RESs are taken into consideration while formulating the objective function through adding a penalty and reserve cost, respectively. Moreover, carbon tax is imposed to the main objective function to help in reducing carbon emissions. A jellyfish search optimizer (JS) is employed to reach optimization in the modified IEEE 30-bus test system to validate its feasibility. To examine the effectiveness of the proposed JS algorithm, its simulation results are compared with the results of four other nature-inspired global optimization algorithms. The developed OPF algorithm considers several practical cases such as generation uncertainty of renewable energy sources, time-varying load and the ramp rate limits of thermal generators. The simulation results show the effectiveness of the JS algorithm in solving the OPF problem in terms of minimization of total generation cost and solution convergence.

ACS Style

Mohamed Farhat; Salah Kamel; Ahmed M. Atallah; Baseem Khan. Optimal Power Flow Solution Based on Jellyfish Search Optimization Considering Uncertainty of Renewable Energy Sources. IEEE Access 2021, 9, 100911 -100933.

AMA Style

Mohamed Farhat, Salah Kamel, Ahmed M. Atallah, Baseem Khan. Optimal Power Flow Solution Based on Jellyfish Search Optimization Considering Uncertainty of Renewable Energy Sources. IEEE Access. 2021; 9 ():100911-100933.

Chicago/Turabian Style

Mohamed Farhat; Salah Kamel; Ahmed M. Atallah; Baseem Khan. 2021. "Optimal Power Flow Solution Based on Jellyfish Search Optimization Considering Uncertainty of Renewable Energy Sources." IEEE Access 9, no. : 100911-100933.

Journal article
Published: 07 July 2021 in Energies
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This work presents a comprehensive analysis of two cubic techniques for Power Flow (PF) studies. In this regard, the families of Weerakoon-like and Darvishi-like techniques are considered. Several theoretical findings are presented and posteriorly confirmed by multiple numerical results. Based on the obtained results, the Weerakoon’s technique is considered more reliable than the Newton-Raphson and Darvishi’s methods. As counterpart, it presents a high computational burden. Regarding this point, the Darvishi’s technique has turned out to be quite efficient and fully competitive with the Newton’s scheme.

ACS Style

Marcos Tostado-Véliz; Salah Kamel; Francisco Jurado; Francisco Ruiz-Rodriguez. On the Applicability of Two Families of Cubic Techniques for Power Flow Analysis. Energies 2021, 14, 4108 .

AMA Style

Marcos Tostado-Véliz, Salah Kamel, Francisco Jurado, Francisco Ruiz-Rodriguez. On the Applicability of Two Families of Cubic Techniques for Power Flow Analysis. Energies. 2021; 14 (14):4108.

Chicago/Turabian Style

Marcos Tostado-Véliz; Salah Kamel; Francisco Jurado; Francisco Ruiz-Rodriguez. 2021. "On the Applicability of Two Families of Cubic Techniques for Power Flow Analysis." Energies 14, no. 14: 4108.

Journal article
Published: 01 July 2021 in Applied Sciences
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This paper presents a novel Power-Flow solution paradigm based on the structure of the members of the Runge–Kutta family. Solution approaches based on the introduced solution paradigm are intrinsically robust and can achieve high-order convergences rates. It is demonstrated that some well-known Power-Flow solution methods are in fact special cases of the developed framework. Explicit and embedded formulations are discussed, and two novel solution methodologies based on the Explicit Heun and Embedded Heun–Euler’s methods are developed. The introduced solution techniques are validated in the EU PEGASE systems, considering different starting points and loading levels. Results show that the developed methods are quite reliable and efficient, outperforming other robust and standard methodologies. On the basis of the results obtained, we can affirm that the introduced solution paradigm constitutes a promising framework for developing novel Power-Flow solution techniques.

ACS Style

Marcos Tostado-Véliz; Salah Kamel; Antonio Escamez; David Vera; Francisco Jurado. A Common Framework for Developing Robust Power-Flow Methods with High Convergence Rate. Applied Sciences 2021, 11, 6147 .

AMA Style

Marcos Tostado-Véliz, Salah Kamel, Antonio Escamez, David Vera, Francisco Jurado. A Common Framework for Developing Robust Power-Flow Methods with High Convergence Rate. Applied Sciences. 2021; 11 (13):6147.

Chicago/Turabian Style

Marcos Tostado-Véliz; Salah Kamel; Antonio Escamez; David Vera; Francisco Jurado. 2021. "A Common Framework for Developing Robust Power-Flow Methods with High Convergence Rate." Applied Sciences 11, no. 13: 6147.

Journal article
Published: 29 June 2021 in Mathematics
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In this paper, a modified Rao-2 (MRao-2) algorithm is proposed to solve the problem of optimal power flow (OPF) in a power system incorporating renewable energy sources (RES). Quasi-oppositional and Levy flight methods are used to improve the performance of the Rao algorithm. To demonstrate effectiveness of the MRao-2 technique, it is tested on two standard test systems: an IEEE 30-bus system and an IEEE 118-bus system. The objective function of the OPF is the minimization of fuel cost in five scenarios. The IEEE 30-bus system reflects fuel cost minimization in three scenarios (without RES, with RES, and with RES under contingency state), while the IEEE 118-bus system reflects fuel cost minimization in two scenarios (without RES and with RES). The achieved results of various scenarios using the suggested MRao-2 technique are compared with those obtained using five recent techniques: Atom Search Optimization (ASO), Turbulent Flow of Water-based Optimization (TFWO), Marine Predators Algorithm (MPA), Rao-1, Rao-3 algorithms, as well as the conventional Rao-2 algorithm. Those comparisons confirm the superiority of the MRao-2 technique over those other algorithms in solving the OPF problem.

ACS Style

Mohamed Hassan; Salah Kamel; Ali Selim; Tahir Khurshaid; José Domínguez-García. A Modified Rao-2 Algorithm for Optimal Power Flow Incorporating Renewable Energy Sources. Mathematics 2021, 9, 1532 .

AMA Style

Mohamed Hassan, Salah Kamel, Ali Selim, Tahir Khurshaid, José Domínguez-García. A Modified Rao-2 Algorithm for Optimal Power Flow Incorporating Renewable Energy Sources. Mathematics. 2021; 9 (13):1532.

Chicago/Turabian Style

Mohamed Hassan; Salah Kamel; Ali Selim; Tahir Khurshaid; José Domínguez-García. 2021. "A Modified Rao-2 Algorithm for Optimal Power Flow Incorporating Renewable Energy Sources." Mathematics 9, no. 13: 1532.

Journal article
Published: 29 June 2021 in Processes
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Clean energy resources have become a worldwide concern, especially photovoltaic (PV) energy. Solar cell modeling is considered one of the most important issues in this field. In this article, an improvement for the search steps of the bald eagle search algorithm is proposed. The improved bald eagle search (IBES) was applied to estimate more accurate PV model parameters. The IBES algorithm was applied for conventional single, double, and triple PV models, in addition to modified single, double, and triple PV models. The IBES was evaluated by comparing its results with the original BES through 15 benchmark functions. For a more comprehensive analysis, two evaluation tasks were performed. In the first task, the IBES results were compared with the original BES for parameter estimation of original and modified tribe diode models. In the second task, the IBES results were compared with different recent algorithms for parameter estimation of original and modified single and double diode models. All tasks were performed using the real data for a commercial silicon solar cell (R.T.C. France). From the results, it can be concluded that the results of the modified models were more accurate than the conventional PV models, and the IBES behavior was better than the original BES and other compared algorithms.

ACS Style

Abdelhady Ramadan; Salah Kamel; Mohamed Hassan; Tahir Khurshaid; Claudia Rahmann. An Improved Bald Eagle Search Algorithm for Parameter Estimation of Different Photovoltaic Models. Processes 2021, 9, 1127 .

AMA Style

Abdelhady Ramadan, Salah Kamel, Mohamed Hassan, Tahir Khurshaid, Claudia Rahmann. An Improved Bald Eagle Search Algorithm for Parameter Estimation of Different Photovoltaic Models. Processes. 2021; 9 (7):1127.

Chicago/Turabian Style

Abdelhady Ramadan; Salah Kamel; Mohamed Hassan; Tahir Khurshaid; Claudia Rahmann. 2021. "An Improved Bald Eagle Search Algorithm for Parameter Estimation of Different Photovoltaic Models." Processes 9, no. 7: 1127.

Journal article
Published: 24 June 2021 in IEEE Access
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It is widely accepted that the integration of natural sources in distribution networks is becoming more attractive as they are sustainable and nonpolluting. This paper firstly proposes a modified Manta Ray Foraging Optimizer (MMRFO) to enhance the characteristic of MRFO technique. The modified MRFO technique is based on inserting the Simulated Annealing technique into the original MRFO to enhance the exploitation phase which is responsible for finding the promising region in the search area. Secondly, the developed technique is utilized for determining the best sizes and locations of multiple wind turbine (WT) and photovoltaic (PV) units in Radial Distribution System (RDS). The total system loss is taken as single-objective function to be minimized, considering the probabilistic nature of PV and WT output generation with variable load demand. Reactive loss sensitivity factor (QLSF) is utilized for obtaining the candidate locations up to fifty percent of total system buses with the aim of reducing the search space. Battery Energy Storage System (BESS) is used with PV to change it into a dispatchable supply. The changes in system performance by optimally integrating PV and WT alone or together are comprehensively studied. The proposed solution approach is applied for solving the standard IEEE 69 bus RDS. The obtained results demonstrate that installing PV and WT simultaneously achieves superior results than installing PV alone and WT alone in RDS. Further, simultaneous integration of WT and PV with BESS gives better results than simultaneous integration of WT and PV without BESS in RDS. The simulation results prove that the total system losses can be reduced by enabling the reactive power capability of PV inverters. The convergence characteristic shows that the modified MRFO gives the best solutions compared with the original MRFO algorithm.

ACS Style

H. Abdel-Mawgoud; Abdelfatah Ali; Salah Kamel; Claudia Rahmann; M. A. Abdel-Moamen. A Modified Manta Ray Foraging Optimizer for Planning Inverter-Based Photovoltaic with Battery Energy Storage System and Wind Turbine in Distribution Networks. IEEE Access 2021, 9, 1 -1.

AMA Style

H. Abdel-Mawgoud, Abdelfatah Ali, Salah Kamel, Claudia Rahmann, M. A. Abdel-Moamen. A Modified Manta Ray Foraging Optimizer for Planning Inverter-Based Photovoltaic with Battery Energy Storage System and Wind Turbine in Distribution Networks. IEEE Access. 2021; 9 ():1-1.

Chicago/Turabian Style

H. Abdel-Mawgoud; Abdelfatah Ali; Salah Kamel; Claudia Rahmann; M. A. Abdel-Moamen. 2021. "A Modified Manta Ray Foraging Optimizer for Planning Inverter-Based Photovoltaic with Battery Energy Storage System and Wind Turbine in Distribution Networks." IEEE Access 9, no. : 1-1.

Journal article
Published: 21 June 2021 in Sustainability
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The enhancement of photovoltaic (PV) energy systems relies on an accurate PV model. Researchers have made significant efforts to extract PV parameters due to their nonlinear characteristics of the PV system, and the lake information from the manufactures’ PV system datasheet. PV parameters estimation using optimization algorithms is a challenging problem in which a wide range of research has been conducted. The idea behind this challenge is the selection of a proper PV model and algorithm to estimate the accurate parameters of this model. In this paper, a new application of the improved gray wolf optimizer (I-GWO) is proposed to estimate the parameters’ values that achieve an accurate PV three diode model (TDM) in a perfect and robust manner. The PV TDM is developed to represent the effect of grain boundaries and large leakage current in the PV system. I-GWO is developed with the aim of improving population, exploration and exploitation balance and convergence of the original GWO. The performance of I-GWO is compared with other well-known optimization algorithms. I-GWO is evaluated through two different applications. In the first application, the real data from RTC furnace is applied and in the second one, the real data of PTW polycrystalline PV panel is applied. The results are compared with different evaluation factors (root mean square error (RMSE), current absolute error and statistical analysis for multiple independent runs). I-GWO achieved the lowest RMSE values in comparison with other algorithms. The RMSE values for the two applications are 0.00098331 and 0.0024276, respectively. Based on quantitative and qualitative performance evaluation, it can be concluded that the estimated parameters of TDM by I-GWO are more accurate than those obtained by other studied optimization algorithms.

ACS Style

Abd-Elhady Ramadan; Salah Kamel; Tahir Khurshaid; Seung-Ryle Oh; Sang-Bong Rhee. Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer. Sustainability 2021, 13, 6963 .

AMA Style

Abd-Elhady Ramadan, Salah Kamel, Tahir Khurshaid, Seung-Ryle Oh, Sang-Bong Rhee. Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer. Sustainability. 2021; 13 (12):6963.

Chicago/Turabian Style

Abd-Elhady Ramadan; Salah Kamel; Tahir Khurshaid; Seung-Ryle Oh; Sang-Bong Rhee. 2021. "Parameter Extraction of Three Diode Solar Photovoltaic Model Using Improved Grey Wolf Optimizer." Sustainability 13, no. 12: 6963.

Original research paper
Published: 15 June 2021 in IET Generation, Transmission & Distribution
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This paper proposes an application of the recent metaheuristic rider optimization algorithm (ROA) for determining the optimal size and location of renewable energy sources (RES) including wind turbine (WT), photovoltaic (PV), and biomass-based Distributed Generation (DG) units in distribution systems (DS). The main objective function is to minimize the total power and energy losses. Power loss-sensitivity factor (PLSF) is used with the ROA to determine the suitable candidate buses and accelerate the solution process. The Weibull and Beta probability distribution functions (PDF) are employed to characterize the variability of wind speed and solar radiation, respectively. The high penetration of intermittent renewable resource together with demand variations has introduced many challenges to distribution systems such as power fluctuations, voltage rise, high losses, and low voltage stability, therefore battery energy storage (BES) and dispatchable Biomass are considered to smooth out the fluctuations and improve supply continuity. The standard 33 and 69-bus test systems are used to verify the effectiveness of the proposed technique compared with other well-known optimization techniques. The results show that the developed approach accelerates to the near-optimal solution seamlessly, and in steady convergence characteristics compared with other techniques.

ACS Style

Mansur Khasanov; Salah Kamel; Claudia Rahmann; Hany M. Hasanien; Ahmed Al‐Durra. Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty. IET Generation, Transmission & Distribution 2021, 1 .

AMA Style

Mansur Khasanov, Salah Kamel, Claudia Rahmann, Hany M. Hasanien, Ahmed Al‐Durra. Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty. IET Generation, Transmission & Distribution. 2021; ():1.

Chicago/Turabian Style

Mansur Khasanov; Salah Kamel; Claudia Rahmann; Hany M. Hasanien; Ahmed Al‐Durra. 2021. "Optimal distributed generation and battery energy storage units integration in distribution systems considering power generation uncertainty." IET Generation, Transmission & Distribution , no. : 1.

Journal article
Published: 10 June 2021 in Sustainability
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In recent years, the integration of distributed generators (DGs) in radial distribution systems (RDS) has received considerable attention in power system research. The major purpose of DG integration is to decrease the power losses and improve the voltage profiles that directly lead to improving the overall efficiency of the power system. Therefore, this paper proposes a hybrid optimization technique based on analytical and metaheuristic algorithms for optimal DG allocation in RDS. In the proposed technique, the loss sensitivity factor (LSF) is utilized to reduce the search space of the DG locations, while the analytical technique is used to calculate initial DG sizes based on a mathematical formulation. Then, a metaheuristic sine cosine algorithm (SCA) is applied to identify the optimal DG allocation based on the LSF and analytical techniques instead of using random initialization. To prove the superiority and high performance of the proposed hybrid technique, two standard RDSs, IEEE 33-bus and 69-bus, are considered. Additionally, a comparison between the proposed techniques, standard SCA, and other existing optimization techniques is carried out. The main findings confirmed the enhancement in the convergence of the proposed technique compared with the standard SCA and the ability to allocate multiple DGs in RDS.

ACS Style

Ali Selim; Salah Kamel; Amal Mohamed; Ehab Elattar. Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique. Sustainability 2021, 13, 6644 .

AMA Style

Ali Selim, Salah Kamel, Amal Mohamed, Ehab Elattar. Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique. Sustainability. 2021; 13 (12):6644.

Chicago/Turabian Style

Ali Selim; Salah Kamel; Amal Mohamed; Ehab Elattar. 2021. "Optimal Allocation of Multiple Types of Distributed Generations in Radial Distribution Systems Using a Hybrid Technique." Sustainability 13, no. 12: 6644.

Journal article
Published: 19 May 2021 in Expert Systems with Applications
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In this paper, an Improved version of the Slime Mould Algorithm (ISMA) is proposed and applied to efficiently solve the single-and bi-objective Economic and Emission Dispatch (EED) problems considering valve point effect. ISMA is developed to improve the performance of the conventional Slime Mould Algorithm (SMA). In ISMA, the solution positions are updated depending on two equations borrowed from the sine–cosine algorithm (SCA) to obtain the best solution. Multi-objective SMA (MOSMA) and Multi-objective ISMA (MOISMA) are developed based on the Pareto dominance concept and fuzzy decision-making. In the multi-objective EED problem, MOSMA and MOISMA are applied to minimize the total fuel costs and total emission with the valve point effect simultaneously. The proposed single-and bi-objective economic emission dispatch algorithms are validated using five test systems, 6-units, 10-units, 11-units, 40-units, and 110-units. The performance of the proposed algorithm is compared with Harris Hawk Optimizer (HHO), Jellyfish Search optimizer (JS), Tunicate Swarm Algorithm (TSA), Particle swarm optimization (PSO), and SMA algorithms. The results show that the proposed algorithms are more robust than other well-known algorithms. Feasible solutions using the proposed algorithms are also achieved, which adjust the schedule of generation without violation of the operating generation limits.

ACS Style

Mohamed H. Hassan; Salah Kamel; Laith Abualigah; Ahmad Eid. Development and application of slime mould algorithm for optimal economic emission dispatch. Expert Systems with Applications 2021, 182, 115205 .

AMA Style

Mohamed H. Hassan, Salah Kamel, Laith Abualigah, Ahmad Eid. Development and application of slime mould algorithm for optimal economic emission dispatch. Expert Systems with Applications. 2021; 182 ():115205.

Chicago/Turabian Style

Mohamed H. Hassan; Salah Kamel; Laith Abualigah; Ahmad Eid. 2021. "Development and application of slime mould algorithm for optimal economic emission dispatch." Expert Systems with Applications 182, no. : 115205.

Original article
Published: 12 May 2021 in Neural Computing and Applications
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The principal motivation of the marine predators algorithm (MPA) is the common foraging technique, including Lévy and Brownian motions in ocean predators coupled with optimal contact intensity policy in predator–prey biological interaction. This paper proposes an improved marine predators algorithm (IMPA), which is an extension of the original MPA. The suggested improvements lead to rapid convergence and avoid local minima stagnation for the original MPA. IMPA controls the active and reactive power injected into distribution systems to minimize the total system losses and the total voltage deviations and maximize the voltage stability and improve the distribution system's overall performance. On the one hand, the proposed IMPA determines the optimal location and active power (location and size, respectively) of distributed generation (DG). On the other hand, the IMPA controls reactive power by optimally placing and sizing the shunt capacitors (SCs) and determining the PF of DGs. Two standard test systems, 69-bus and 118-bus distribution networks, are considered to prove the proposed algorithm’s efficiency and scalability. Results of the proposed IMPA are compared with those obtained by MPA, AEO, and PSO algorithms. The findings of the simulation results demonstrate that the proposed IMPA can effectively find the optimal problem solutions and beats the other algorithms. Moreover, the framework of multi-objective IMPA outperforms based on MPA in terms of the performance measures of diversity, spacing, coverage, and hypervolume.

ACS Style

Ahmad Eid; Salah Kamel; Laith Abualigah. Marine predators algorithm for optimal allocation of active and reactive power resources in distribution networks. Neural Computing and Applications 2021, 1 -29.

AMA Style

Ahmad Eid, Salah Kamel, Laith Abualigah. Marine predators algorithm for optimal allocation of active and reactive power resources in distribution networks. Neural Computing and Applications. 2021; ():1-29.

Chicago/Turabian Style

Ahmad Eid; Salah Kamel; Laith Abualigah. 2021. "Marine predators algorithm for optimal allocation of active and reactive power resources in distribution networks." Neural Computing and Applications , no. : 1-29.

Journal article
Published: 06 May 2021 in IEEE Access
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Centre Node Unified Power Flow Controller (CUPFC) is a developed member of Flexible Alternating Current Transmission System (FACTS) connected at midpoint of transmission line. It has ability to control the power flow in transmission line (TL) as well as the voltage of the midpoint of TL. Solving the optimal power flow (OPF) problem is crucial task, and it became a difficult problem in case of integration FACTS devices into the system. Therefore, in this paper an efficient optimizer, namely Levy Spiral Flight Equilibrium Optimizer (LSFEO), is proposed for solving the OPF problem and determining the optimal allocation of CUPFC. The proposed algorithm is based on developing the Equilibrium Optimizer (EO) to enhance its searching capabilities. In this technique, two searching strategies are applied to enhance the exploration and exploitation processes of the traditional EO. The first strategy is based on Levy Flight Distribution to enable the optimizer to jump to new search areas for avoiding the stagnation of the traditional EO while the second strategy is based on spiral motion of the particles around the sorted best solution to boost the exploitation. The considered objective functions include fuel cost, fuel cost with valve point effect, emission, voltage deviations and the power losses. The validity and applicability of the proposed algorithm is demonstrated using the IEEE 30-bus system. The simulations verify the superiority of the proposed algorithm over the other reported algorithms. In addition, optimal inclusion of the CUPFC can reduce the cost, VD, losses, and emission considerably.

ACS Style

Ashraf Mostafa; Mohamed Ebeed; Salah Kamel; M. A. Abdel-Moamen. Optimal Power Flow Solution Using Levy Spiral Flight Equilibrium Optimizer With Incorporating CUPFC. IEEE Access 2021, 9, 69985 -69998.

AMA Style

Ashraf Mostafa, Mohamed Ebeed, Salah Kamel, M. A. Abdel-Moamen. Optimal Power Flow Solution Using Levy Spiral Flight Equilibrium Optimizer With Incorporating CUPFC. IEEE Access. 2021; 9 ():69985-69998.

Chicago/Turabian Style

Ashraf Mostafa; Mohamed Ebeed; Salah Kamel; M. A. Abdel-Moamen. 2021. "Optimal Power Flow Solution Using Levy Spiral Flight Equilibrium Optimizer With Incorporating CUPFC." IEEE Access 9, no. : 69985-69998.

Journal article
Published: 01 May 2021 in Clean Technologies
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Distributed generation (DG) is becoming a prominent key spot for research in recent years because it can be utilized in emergency/reserve plans for power systems and power quality improvement issues, besides its drastic impact on the environment as a greenhouse gas (GHG) reducer. For maximizing the benefits from such technology, it is crucial to identify the best size and location for DG that achieves the required goal of installing it. This paper presents an investigation of the optimized allocation of DG in different modes using a proposed hybrid technique, the tunicate swarm algorithm/sine-cosine algorithm (TSA/SCA). This investigation is performed on an IEEE-69 Radial Distribution System (RDS), where the impact of such allocation on the system is evaluated by NEPLAN software.

ACS Style

Ayman Awad; Hussein Abdel-Mawgoud; Salah Kamel; Abdalla Ibrahim; Francisco Jurado. Developing a Hybrid Optimization Algorithm for Optimal Allocation of Renewable DGs in Distribution Network. Clean Technologies 2021, 3, 409 -423.

AMA Style

Ayman Awad, Hussein Abdel-Mawgoud, Salah Kamel, Abdalla Ibrahim, Francisco Jurado. Developing a Hybrid Optimization Algorithm for Optimal Allocation of Renewable DGs in Distribution Network. Clean Technologies. 2021; 3 (2):409-423.

Chicago/Turabian Style

Ayman Awad; Hussein Abdel-Mawgoud; Salah Kamel; Abdalla Ibrahim; Francisco Jurado. 2021. "Developing a Hybrid Optimization Algorithm for Optimal Allocation of Renewable DGs in Distribution Network." Clean Technologies 3, no. 2: 409-423.

Journal article
Published: 29 April 2021 in IEEE Access
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This paper presents an Enhanced Marine Predators Algorithm (EMPA) for simultaneous optimal distribution system reconfigurations (DSRs) and distributed generations (DGs) addition. The proposed EMPA recognizes the changes opportunity in environmental and climatic conditions. The EMPA handles a multi-objective model to minimize the power losses and enhance the voltage stability index (VSI) at different loading levels. The proposed EMPA is performed on IEEE 33-bus and large-scale 137-bus distribution systems (DSs) where three distinct loading conditions are beheld through light, nominal and heavy levels. For the 33-bus DS, the proposed EMPA successfully reduces the cumulative losses by 72.4% compared to 70.36% for MPA for the three-loading levels simultaneously. As a result, significant voltage improvement is achieved for heavy, nominal and light loadings to be 95.05, 97, 98.3%, respectively. For the 137-bus DS, it successfully minimizes the losses of 81.16% under small standard deviation 4.76%. Also, the 83-bus test system is considered for fair comparative between the proposed and previous techniques. The simulation outputs revealed significant improvements in the standard MPA and demonstrated the superiority and effectiveness of the proposed EMPA compared to other reported results by recent algorithms for DSRs associated with DGs integration.

ACS Style

Abdullah M. Shaheen; Ragab A. El-Sehiemy; Salah Kamel; Ehab E. Elattar; Abdallah M. Elsayed. Improving Distribution Networks’ Consistency by Optimal Distribution System Reconfiguration and Distributed Generations. IEEE Access 2021, 9, 67186 -67200.

AMA Style

Abdullah M. Shaheen, Ragab A. El-Sehiemy, Salah Kamel, Ehab E. Elattar, Abdallah M. Elsayed. Improving Distribution Networks’ Consistency by Optimal Distribution System Reconfiguration and Distributed Generations. IEEE Access. 2021; 9 ():67186-67200.

Chicago/Turabian Style

Abdullah M. Shaheen; Ragab A. El-Sehiemy; Salah Kamel; Ehab E. Elattar; Abdallah M. Elsayed. 2021. "Improving Distribution Networks’ Consistency by Optimal Distribution System Reconfiguration and Distributed Generations." IEEE Access 9, no. : 67186-67200.

Journal article
Published: 27 April 2021 in IEEE Access
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Sub-synchronous resonance (SSR) phenomenon occurs due to the interaction between wind turbine generators and series-compensated transmission lines. A doubly-fed induction generator (DFIG) is considered one of the most widely implemented generators in wind energy conversion systems. SSR analysis based on the eigenvalue method is the most important among the used methods. The accuracy of the eigenvalue method depends on the initial values of state variables. Previously, the initial values of the state variables were calculated based on the iterative approach which is suffering from convergence problem, lacking accuracy, and requiring a long computation time. Moreover, many steps and details haven’t been provided. Consequently, it is urgent to fill this gap and show how can implement the SSR analysis model in detail. In this paper, a new application of a recent analytical approach is proposed for SSR analysis. All information is provided, and the SSR analysis model of a DFIG-based series compensated wind farm is built step-by-step. In order to prove the effectiveness and accuracy of the proposed method, the eigenvalue analysis based on the proposed and iterative methods is compared with the time-domain simulation results at different wind speeds and variable compensation levels. The results prove that the eigenvalue analysis based on the proposed method is more precise, where it is consistent with the simulation results in all studied cases. MATLAB software is used to validate the results.

ACS Style

Mohamed Abdeen; Hui Li; Salah Kamel; Ahmed Khaled; Mahmoud El-Dabah; Mohammed Kharrich; Hatem Faiz Sindi. A Recent Analytical Approach for Analysis of Sub-Synchronous Resonance in Doubly-Fed Induction Generator-Based Wind Farm. IEEE Access 2021, 9, 68888 -68897.

AMA Style

Mohamed Abdeen, Hui Li, Salah Kamel, Ahmed Khaled, Mahmoud El-Dabah, Mohammed Kharrich, Hatem Faiz Sindi. A Recent Analytical Approach for Analysis of Sub-Synchronous Resonance in Doubly-Fed Induction Generator-Based Wind Farm. IEEE Access. 2021; 9 ():68888-68897.

Chicago/Turabian Style

Mohamed Abdeen; Hui Li; Salah Kamel; Ahmed Khaled; Mahmoud El-Dabah; Mohammed Kharrich; Hatem Faiz Sindi. 2021. "A Recent Analytical Approach for Analysis of Sub-Synchronous Resonance in Doubly-Fed Induction Generator-Based Wind Farm." IEEE Access 9, no. : 68888-68897.

Journal article
Published: 22 April 2021 in Sustainability
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Hybrid microgrids are presented as a solution to many electrical energetic problems. These microgrids contain some renewable energy sources such as photovoltaic (PV), wind and biomass, or a hybrid of these sources, in addition to storage systems. Using these microgrids in electric power generation has many advantages such as clean energy, stability in supplying power, reduced grid congestion and a new investment field. Despite all these microgrids advantages, they are not widely used due to some economic aspects. These aspects are represented in the net present cost (NPC) and the levelized cost of energy (LCOE). To handle these economic aspects, the proper microgrids configuration according to the quantity, quality and availability of the sustainable source of energy in installing the microgrid as well as the optimal design of the microgrid components should be investigated. The objective of this paper is to design an economic microgrid system for the Yanbu region of Saudi Arabia. This design aims to select the best microgrid configuration while minimizing both NPC and LCOE considering some technical conditions, including loss of power supply probability and availability index. The optimization algorithm used is Giza Pyramids Construction (GPC). To prove the GPC algorithm’s effectiveness in solving the studied optimization problem, artificial electric field and grey wolf optimizer algorithms are used for comparison purposes. The obtained results demonstrate that the best configuration for the selected area is a PV/biomass hybrid microgrid with a minimum NPC and LCOE of $319,219 and $0.208/kWh, respectively.

ACS Style

Mohammed Kharrich; Salah Kamel; Ali Alghamdi; Ahmad Eid; Mohamed Mosaad; Mohammed Akherraz; Mamdouh Abdel-Akher. Optimal Design of an Isolated Hybrid Microgrid for Enhanced Deployment of Renewable Energy Sources in Saudi Arabia. Sustainability 2021, 13, 4708 .

AMA Style

Mohammed Kharrich, Salah Kamel, Ali Alghamdi, Ahmad Eid, Mohamed Mosaad, Mohammed Akherraz, Mamdouh Abdel-Akher. Optimal Design of an Isolated Hybrid Microgrid for Enhanced Deployment of Renewable Energy Sources in Saudi Arabia. Sustainability. 2021; 13 (9):4708.

Chicago/Turabian Style

Mohammed Kharrich; Salah Kamel; Ali Alghamdi; Ahmad Eid; Mohamed Mosaad; Mohammed Akherraz; Mamdouh Abdel-Akher. 2021. "Optimal Design of an Isolated Hybrid Microgrid for Enhanced Deployment of Renewable Energy Sources in Saudi Arabia." Sustainability 13, no. 9: 4708.

Research article
Published: 22 April 2021 in Electric Power Components and Systems
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The voltage stability analysis can be carried out using different continuation techniques. The continuation power flow that evaluates all power-flow solutions at different loading levels, is typically considered the most standard one. This approach is mainly based on two stages called predictor and corrector. The standard Newton–Raphson method is usually used at the corrector stage. In this paper, several corrector techniques based on efficient Newton-like methods are proposed in order to speed up the solution of continuation power flow. Consequently, two high order Newton-like methods as well as a fast corrector technique based on the Dishonest NR method have been proposed. A comprehensive study is addressed in order to check the suitability of the proposed corrector techniques compared with the standard Newton–Raphson (NR). Several small, medium, large and very large-scale test systems are used to achieve the validation. The obtained results prove the effectiveness and superiority of proposed techniques compared with the standard NR which conventionally used in corrector stage of the continuation power flow analysis in term of computational time.

ACS Style

Marcos Tostado-Véliz; Salah Kamel; Francisco Jurado. Development and Comparison of Efficient Newton-Like Methods for Voltage Stability Assessment. Electric Power Components and Systems 2021, 1 -16.

AMA Style

Marcos Tostado-Véliz, Salah Kamel, Francisco Jurado. Development and Comparison of Efficient Newton-Like Methods for Voltage Stability Assessment. Electric Power Components and Systems. 2021; ():1-16.

Chicago/Turabian Style

Marcos Tostado-Véliz; Salah Kamel; Francisco Jurado. 2021. "Development and Comparison of Efficient Newton-Like Methods for Voltage Stability Assessment." Electric Power Components and Systems , no. : 1-16.

Journal article
Published: 16 April 2021 in Sustainability
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The optimal location of renewable distributed generations (DGs) into a radial distribution system (RDS) has attracted major concerns from power system researchers in the present years. The main target of DG integration is to improve the overall system performance by minimizing power losses and improving the voltage profile. Hence, this paper proposed a hybrid approach between an analytical and metaheuristic optimization technique for the optimal allocation of DG in RDS, considering different types of load. A simple analytical technique was developed in order to determine the sizes of different and multiple DGs, and a new efficient metaheuristic technique known as the Salp Swarm Algorithm (SSA) was suggested in order to choose the best buses in the system, proportionate to the sizes determined by the analytical technique, in order to obtain the minimum losses and the best voltage profile. To verify the power of the proposed hybrid technique on the incorporation of the DGs in RDS, it was applied to different types of static loads; constant power (CP), constant impedance (CZ), and constant current (CI). The performance of the proposed algorithm was validated using two standards RDSs—IEEE 33-bus and IEEE 69-bus systems—and was compared with other optimization techniques.

ACS Style

Amal Mohamed; Salah Kamel; Ali Selim; Tahir Khurshaid; Sang-Bong Rhee. Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads. Sustainability 2021, 13, 4447 .

AMA Style

Amal Mohamed, Salah Kamel, Ali Selim, Tahir Khurshaid, Sang-Bong Rhee. Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads. Sustainability. 2021; 13 (8):4447.

Chicago/Turabian Style

Amal Mohamed; Salah Kamel; Ali Selim; Tahir Khurshaid; Sang-Bong Rhee. 2021. "Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads." Sustainability 13, no. 8: 4447.