Article
Multidisciplinary Sciences
Mahmud Salem Alkoffash, Mohammed A. Awadallah, Mohammed Alweshah, Raed Abu Zitar, Khaled Assaleh, Mohammed Azmi Al-Betar
Summary: This paper proposes a hybridization of SSA and beta-hill climbing optimizer, named HSSA, to solve the ELD problem with valve point effect. The evaluation on real-world ELD systems shows that HSSA can produce viable and competitive solutions for the problem.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Thermodynamics
Xu Chen, Guowei Tang
Summary: An improved competitive swarm optimization (ImCSO) algorithm is proposed in this paper to solve Multi-area Economic Dispatch (MAED) problems, which enhances performance by introducing a ranking paired learning strategy and a differential evolution strategy. Experimental results show that the ImCSO algorithm has superior solution accuracy and reliability in solving MAED problems.
Article
Computer Science, Artificial Intelligence
Ling-Ling Li, Zhi-Feng Liu, Ming-Lang Tseng, Sheng-Jie Zheng, Ming K. Lim
Summary: This study proposes an improved tunicate swarm algorithm (ITSA) for solving and optimizing the dynamic economic emission dispatch (DEED) problem, in order to reduce fuel cost and pollutant emission of the power system. By employing tent mapping, gray wolf optimizer, and Levy flight, the ITSA algorithm is enhanced to provide competitive scheduling plans for different test systems containing various units, ultimately achieving optimal economic and environmental dynamic dispatch schemes.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Mohammed Azmi Al-Betar, Sofian Kassaymeh, Sharif Naser Makhadmeh, Salam Fraihat, Salwani Abdullah
Summary: This research proposes the use of FFNN neural networks to develop an accurate cost forecasting model. The parameters of the predictor are optimized using an augmented version of the SSA algorithm, with the addition of search enhancement and elitism techniques. Experimental results demonstrate the superiority of the proposed techniques and their robustness, as supported by statistical validation.
APPLIED SOFT COMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Mohamed H. Hassan, Salah Kamel, Jose Luis Dominguez-Garcia, Mohamed F. El-Naggar
Summary: Due to rising fuel costs, increased energy demand, and environmental pressures, dynamic economic emission dispatch (DEED) has become an important research topic. This article evaluates the performance of the multi-objective Salp Swarm Algorithm (MSSA) in obtaining optimal dispatching schemes. The results demonstrate the superiority of the MSSA in solving multi-objective optimization problems in power systems.
Article
Computer Science, Information Systems
Xiaoqing Zhang, Yuye Zhang, Zhengfeng Ming
Summary: The dynamic grey wolf optimizers improve the iterative convergence rate by eliminating the waiting period for updating the search wolf's position. Research shows that, for the same improved algorithm, the performance of the dynamic GWO-based algorithm is generally better than that of the static GWO-based algorithm.
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Mohammed Azmi Al-Betar, Mohammed A. Awadallah, Sharif Naser Makhadmeh, Iyad Abu Doush, Raed Abu Zitar, Samah Alshathri, Mohamed Abd Elaziz
Summary: This paper proposes a hybridized version of the Harris Hawks Optimizer (HHO) with adaptive-hill-climbing optimizer for solving economic load dispatch (ELD) problems. The proposed method achieves significant performance in various ELD cases and can be considered as an efficient alternative for solving ELD problems.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Mathematics
Rajakumar Ramalingam, Dinesh Karunanidy, Sultan S. Alshamrani, Mamoon Rashid, Swamidoss Mathumohan, Ankur Dumka
Summary: This paper proposes an Oppositional Pigeon-Inspired Optimizer (OPIO) algorithm to solve the Economic Load Dispatch (ELD) problem, by employing Oppositional-Based Learning (OBL) to improve the quality of solutions and global search capability. The experimental results demonstrate that the OPIO algorithm outperforms the conventional PIO algorithm and other state-of-the-art approaches in terms of accuracy, convergence rate, computation time, and fuel cost.
Article
Energy & Fuels
Jianming Xu, Anfeng Liu, Yang Qin, Guangrong Xu, Yibo Tang
Summary: The electricity sector has faced economic challenges in recent years, leading governments to use renewable energy sources more widely. This research proposes solving the dynamic economic load dispatch problem using an improved chimp optimizer algorithm, considering the significant contribution of renewable energy sources and electric vehicles to the test systems.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Computer Science, Information Systems
Sofian Kassaymeh, Salwani Abdullah, Mohammed Azmi Al-Betar, Mohammed Alweshah
Summary: This paper proposes a combination of the salp swarm algorithm and backpropagation neural network to solve the software fault prediction problem. The proposed method, SSA-BPNN, outperforms the conventional BPNN and state-of-the-art methods in terms of prediction accuracy on various datasets.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Chemistry, Multidisciplinary
Mohammad Khajehzadeh, Amin Iraji, Ali Majdi, Suraparb Keawsawasvong, Moncef L. Nehdi
Summary: This paper proposes an efficient metaheuristic algorithm based on the salp swarm algorithm for solving global optimization problems and optimizing geotechnical engineering structures. The algorithm, called adaptive salp swarm optimization (ASSA), introduces new equations to improve the exploration capabilities and prevent premature convergence. The proposed algorithm outperforms other optimization algorithms in benchmark tests and is significantly superior according to statistical analysis. It can also be applied to optimize low-cost retaining walls and foundations.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Divya Bairathi, Dinesh Gopalani
Summary: The proposed improved salp swarm algorithm, by integrating multiple elements, enhances exploration and exploitation capabilities, making it more effective in solving complex multimodal problems.
Article
Computer Science, Interdisciplinary Applications
Gaurav Dhiman
Summary: In this paper, a hybrid bio-inspired metaheuristic optimization approach named Emperor Penguin and Salp Swarm Algorithm (ESA) is proposed. The efficiency of the ESA is evaluated through various analyses on 53 benchmark test functions, showing that it offers optimal solutions compared to other competitor algorithms. The robustness of ESA is also demonstrated through its application on six constrained and one unconstrained engineering problems.
ENGINEERING WITH COMPUTERS
(2021)
Article
Chemistry, Analytical
Miodrag Zivkovic, Catalin Stoean, Amit Chhabra, Nebojsa Budimirovic, Aleksandar Petrovic, Nebojsa Bacanin
Summary: This study proposes a feature selection method based on swarm intelligence paradigm, which extracts the most important attributes from multiple datasets. By combining machine learning with metaheuristic approaches, feature selection is improved to enhance classification accuracy.
Article
Computer Science, Information Systems
Muhammad Azeem, Tahir Nadeem Malik, Hafiz Abdul Muqeet, Muhammad Majid Hussain, Ahmad Ali, Baber Khan, Atiq ur Rehman
Summary: The integration of renewable energy resources, such as wind and solar, into the generation mix offers a promising solution to the challenges posed by limited fossil fuel resources, global warming, and environmental concerns. This study focuses on the combined economic emission dispatch problem, which aims to reduce fuel consumption and emissions in thermal power plants through optimization. Chaotic salp swarm algorithms (CISSA) are applied to solve this complex and non-linear optimization problem. The results demonstrate the superiority of this approach in terms of cost of generation and emissions compared to existing research.
Review
Computer Science, Interdisciplinary Applications
Divya J. Navamani, Jagabar M. Sathik, A. Lavanya, Dhafer Almakhles, Ziad M. Ali, Shady H. E. Abdel Aleem
Summary: This article reviews three main reliability assessment models, compares their advantages and disadvantages in DC-DC power converters, proposes an optimal assessment tool, and discusses reliability calculation tools and fault identification methods. The importance of reliability study in applications is emphasized, and a comparative analysis of statistical approaches is provided for researchers to choose appropriate methods.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Ehab M. Esmail, Abdulaziz Almalaq, Khalid Alqunun, Ziad M. Ali, Shady H. E. Abdel Aleem
Summary: This paper introduces fault type identification, fault section selection, and fault phase selectivity using a Karen Bell Transformation matrix in earthed distribution grids coupled with Doubly Fed Induction Generator (DFIG). The Rogowski Coil's (RC) model is estimated and verified using experimental results, and the transient slope of the ground and aerial modes voltages is extracted during the fault for fault classification. The proposed scheme's behavior is evaluated through simulation results.
AIN SHAMS ENGINEERING JOURNAL
(2023)
Article
Thermodynamics
Martin Calasan, Shady H. E. Abdel Aleem, Hany M. Hasanien, Zuhair M. Alaas, Ziad M. Ali
Summary: In this study, a new mathematical expression of PEMFC current as a voltage function is derived and solved using the iterative Lambert W function for the first time. The root-mean-square error (RMSE) and sum-of-squares error (SSE) between the measured and estimated current and voltage values are calculated, analyzed, and discussed. The results validate the effectiveness of the new mathematical model and show that the solutions obtained using ChERWCA outperformed those obtained by other methods presented in the literature.
Review
Energy & Fuels
Naveed Qamar, Ammar Arshad, Karar Mahmoud, Matti Lehtonen
Summary: In recent years, there has been a significant shift towards renewable energy resources worldwide. However, the integration of distributed generation (DG) into the electrical network has brought about various limiting constraints. In this article, an extensive investigation on the methodologies of incorporating DGs into the electrical network is presented. The study reviews the different hosting capacity (HC) terms, references, limiting constraints, geographical segregation, and determination methodologies of the studied networks, as well as the factors defining HC and the architectures employed to increase it.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Energy & Fuels
Ali Asaad, Abdelfatah Ali, Karar Mahmoud, Mostafa F. F. Shaaban, Matti Lehtonen, Ahmed M. M. Kassem, Mohamed Ebeed
Summary: This paper proposes an optimal planning approach for allocating EV charging stations with controllable charging and hybrid RERs within multi-microgrids. The charging strategy in the proposed planning approach contributes to improving power quality and overall system cost, reducing voltage deviation, energy not supplied, and total cost by 26.03%, 49.57%, and 70.45% respectively.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Automation & Control Systems
Ziad M. Ali, Mujahed Al-Dhaifallah, Saad F. Al-Gahtani, Tetsuya Muranaka
Summary: This paper proposes a combinatorial technique using the developed modified manta ray foraging optimization (DMRFO) method and enhanced adaptive neuro-fuzzy inference system (ANFIS)-based incremental conductance (INC) for maximum power point tracking (MPPT) in proton exchange membrane fuel cells (PEMFC). The technique shows advantages of reduced dataset size, quick stability, and efficiency.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Energy & Fuels
Ziad M. Ali, Martin Calasan, Shady H. E. Abdel Aleem, Hany M. Hasanien
Summary: This paper presents exact analytical formulas of leakage-current-based supercapacitor models that can be used in industrial applications, i.e., constant-power-based applications. In the proposed model, current and voltage are represented as a solution of nonlinear equations that are solved using the standard Newton method. The results confirm that including leakage current represents a more accurate and realistic manner of modeling SCs.
Article
Energy & Fuels
Mohamed Abd-El-Hakeem Mohamed, Almoataz Y. Y. Abdelaziz, Mohamed M. F. Darwish, Matti Lehtonen, Karar Mahmoud
Summary: This paper presents the optimal determination of series capacitor units in a distribution system to maximize energy-saving and enhance voltage levels, taking into consideration the limitations of series compensation. The proposed hybrid strategy of Improved Grey Wolf Optimization (I-GWO) and Tabu Search (TS) can solve mixed-integer programming and achieve the planning and optimal load flow objectives. The method can be applied to a real heavily loaded Egyptian distribution system with poor voltage regulation and high-power losses, and it successfully determines the optimal location and sizing of series capacitors to maximize energy savings and improve network performance.
ENERGY SCIENCE & ENGINEERING
(2023)
Review
Energy & Fuels
Ziad M. Ali, Martin Calasan, Shady H. E. Abdel Aleem, Francisco Jurado, Foad H. Gandoman
Summary: With the growing global population and increased energy demand, sustainable and efficient energy systems are urgently needed. Renewable energy sources, such as wind and solar power, have the potential to meet this demand, but their intermittent nature poses challenges for integration into existing energy systems. Recent events such as declining fuel prices, geopolitical conflicts, and the COVID-19 pandemic have made the development of sustainable energy systems even more critical, highlighting the need for resilient and self-sufficient energy systems. Energy storage technologies, such as batteries and flywheels, play a vital role in achieving this goal by providing reliable backup power and enabling independent operation of microgrids.
Article
Computer Science, Information Systems
Ehab Mahmoud Mohamed, Sherief Hashima, Kohei Hatano, Eiji Takimoto, Mohamed Abdel-Nasser
Summary: This paper presents the deployment of multiple reconfigurable intelligent surface (RIS) boards to enhance mmWave communication in a harsh blockage environment. The RIS-user association is considered to maximize achievable data rates and ensure load balance among the installed RIS panels. Instead of using maximum received power (MRP) based RIS-user association, an online learning methodology using centralized multi-player multi-armed bandit (MP-MAB) with arms' load balancing is proposed. Numerical analysis shows the superior performance of the proposed algorithms over MRP-based RIS-user association and other benchmarks.
Article
Multidisciplinary Sciences
Muhyaddin Rawa, Yusuf Al-Turki, Hatem Sindi, Martin Calasan, Ziad M. Ali, Shady H. E. Abdel Aleem
Summary: This study aims to mathematically model the current-voltage curves of planar heterojunction perovskite solar cells using Perovich Special Trans Function Theory (STFT) and propose novel analytical closed-form solutions for their short-circuit current and open-circuit voltage in terms of STFT. The safety and accuracy of the proposed expressions are evaluated by comparison with known methods. A new hybrid metaheuristic algorithm called particle swarm optimization (PSO) - evaporation rate water cycle algorithm (ERWCA) is introduced to determine the equivalent circuit parameters of the perovskite solar cell, with a new objective function for parameter estimation. The results show that STFT is highly applicable and efficient in representing the current-voltage expressions of perovskite solar cells, providing more accurate solutions with fewer order members.
JOURNAL OF ADVANCED RESEARCH
(2023)
Article
Engineering, Multidisciplinary
Mahendiran Vellingiri, Muhyaddin Rawa, Sultan Alghamdi, Abdullah Ali Alhussainy, Ziad M. Ali, Rania A. Turky, Mohamed M. Refaat, Shady H. E. Abdel Aleem
Summary: This paper proposes a framework to effectively maximize the hosting of RESs and storage systems in power systems. The penetration of RESs and storage systems was maximized by increasing the number of candidate circuits.
AIN SHAMS ENGINEERING JOURNAL
(2023)
Article
Mathematics, Interdisciplinary Applications
Mahendiran Vellingiri, Muhyaddin Rawa, Sultan Alghamdi, Abdullah A. Alhussainy, Ahmed S. Althobiti, Martin Calasan, Mihailo Micev, Ziad M. Ali, Shady H. E. Abdel Aleem
Summary: This paper proposes three variants of the single-diode model and derives analytical relationships between the current and voltage for each model using the Lambert W function. These models and an algorithm combining chaotic sequences with the snake optimization algorithm were applied to two solar photovoltaic cells, showing improved accuracy compared to the standard single-diode model. Experimental investigation on a solar laboratory module further confirmed the relevance and effectiveness of the proposed models.
FRACTAL AND FRACTIONAL
(2023)
Article
Computer Science, Artificial Intelligence
Saif Khalid, Hatem A. Rashwan, Saddam Abdulwahab, Mohamed Abdel-Nasser, Facundo Manuel Quiroga, Domenec Puig
Summary: This study presents a novel framework called FGR-Net, which automatically assesses and interprets the quality of fundus images by merging an autoencoder network with a classifier network. FGR-Net utilizes a deep autoencoder to extract visual characteristics and a deep classifier network to distinguish between different levels of image quality. The framework also provides visual feedback for ophthalmologists to understand how the model evaluates image quality.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Green & Sustainable Science & Technology
Mohammed M. Alhaider, Ziad M. Ali, Mostafa H. Mostafa, Shady H. E. Abdel Aleem
Summary: Recent developments have increased the availability and prevalence of renewable energy sources in grid-connected microgrids. However, the variability and unpredictability of renewable energy sources have a substantial adverse effect on the accuracy of microgrid energy management. In order to address this issue, this study proposes a two-stage optimization method that enhances microgrid performance through proper energy storage positioning and reduces operating costs.
