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RagabA. El-Sehiemy (SMIEEE). He gained B.Sc., M.Sc., and Ph.D. degrees in electrical power systems from Menoufia University, Egypt, in 1996, 2005, and 2008, respectively. Now, he is a Professor of Electrical Power Systems with Kafrelshiekh University, Egypt. He was the receipt of Prof. Mahmoud Khalifia Award in Power System Engineering from the Academy of Research and Technology in 2016. His research interests include power systems operation, planning and control, smart grid, renewable energy, AI, and its application to power systems.
This paper proposes a hybrid algorithm that combines two prominent nature-inspired meta-heuristic strategies to solve the combined heat and power (CHP) economic dispatch. In this line, an innovative hybrid heap-based and jellyfish search algorithm (HBJSA) is developed to enhance the performance of two recent algorithms: heap-based algorithm (HBA) and jellyfish search algorithm (JSA). The proposed hybrid HBJSA seeks to make use of the explorative features of HBA and the exploitative features of the JSA to overcome some of the problems found in their standard forms. The proposed hybrid HBJSA, HBA, and JSA are validated and statistically compared by attempting to solve a real-world optimization issue of the CHP economic dispatch. It aims to satisfy the power and heat demands and minimize the whole fuel cost (WFC) of the power and heat generation units. Additionally, a series of operational and electrical constraints such as non-convex feasible operating regions of CHP and valve-point effects of power-only plants, respectively, are considered in solving such a problem. The proposed hybrid HBJSA, HBA, and JSA are employed on two medium systems, which are 24-unit and 48-unit systems, and two large systems, which are 84- and 96-unit systems. The experimental results demonstrate that the proposed hybrid HBJSA outperforms the standard HBA and JSA and other reported techniques when handling the CHP economic dispatch. Otherwise, comparative analyses are carried out to demonstrate the suggested HBJSA’s strong stability and robustness in determining the lowest minimum, average, and maximum WFC values compared to the HBA and JSA.
Ahmed Ginidi; Abdallah Elsayed; Abdullah Shaheen; Ehab Elattar; Ragab El-Sehiemy. An Innovative Hybrid Heap-Based and Jellyfish Search Algorithm for Combined Heat and Power Economic Dispatch in Electrical Grids. Mathematics 2021, 9, 2053 .
AMA StyleAhmed Ginidi, Abdallah Elsayed, Abdullah Shaheen, Ehab Elattar, Ragab El-Sehiemy. An Innovative Hybrid Heap-Based and Jellyfish Search Algorithm for Combined Heat and Power Economic Dispatch in Electrical Grids. Mathematics. 2021; 9 (17):2053.
Chicago/Turabian StyleAhmed Ginidi; Abdallah Elsayed; Abdullah Shaheen; Ehab Elattar; Ragab El-Sehiemy. 2021. "An Innovative Hybrid Heap-Based and Jellyfish Search Algorithm for Combined Heat and Power Economic Dispatch in Electrical Grids." Mathematics 9, no. 17: 2053.
The extraction of parameters of solar photovoltaic generating systems is a difficult problem because of the complex nonlinear variables of current-voltage and power-voltage. In this article, a new implementation of the Gorilla Troops Optimization (GTO) technique for parameter extraction of several PV models is created. GTO is inspired by gorilla group activities in which numerous strategies are imitated, including migration to an unknown area, moving to other gorillas, migration in the direction of a defined site, following the silverback, and competition for adult females. With numerical analyses of the Kyocera KC200GT PV and STM6-40/36 PV modules for the Single Diode (SD) and Double-Diode (DD), the validity of GTO is illustrated. Furthermore, the developed GTO is compared with the outcomes of recent algorithms in 2020, which are Forensic-Based Investigation Optimizer, Equilibrium Optimizer, Jellyfish Search Optimizer, HEAP Optimizer, Marine Predator Algorithm, and an upgraded MPA. GTO’s efficacy and superiority are expressed by calculating the standard deviations of the fitness values, which indicates that the SD and DD models are smaller than 1E−16, and 1E−6, respectively. In addition, validation of GTO for the KC200GT module is demonstrated with diverse irradiations and temperatures where great closeness between the emulated and experimental P-V and I-V curves is achieved under various operating conditions (temperatures and irradiations).
Ahmed Ginidi; Sherif M. Ghoneim; Abdallah Elsayed; Ragab El-Sehiemy; Abdullah Shaheen; Attia El-Fergany. Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems. Sustainability 2021, 13, 9459 .
AMA StyleAhmed Ginidi, Sherif M. Ghoneim, Abdallah Elsayed, Ragab El-Sehiemy, Abdullah Shaheen, Attia El-Fergany. Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems. Sustainability. 2021; 13 (16):9459.
Chicago/Turabian StyleAhmed Ginidi; Sherif M. Ghoneim; Abdallah Elsayed; Ragab El-Sehiemy; Abdullah Shaheen; Attia El-Fergany. 2021. "Gorilla Troops Optimizer for Electrically Based Single and Double-Diode Models of Solar Photovoltaic Systems." Sustainability 13, no. 16: 9459.
Voltage stability and power quality play very effective issues in power systems. This paper aims to improve the voltage stability and enhance system power quality in the AC-DC micro-grid system based on intelligent fuzzy controllers. These controllers are fuzzy-PI (FPI) and fuzzy-PID (FPID) current-controller with the existence of distribution static synchronous compensator (D-STATCOM). The capability of proposed system has been applied in two case studies that emulate abrupt fault and dynamic load changes on AC-DC hybrid micro-grid that collects different types of renewable energy sources. In addition to, the proposed fuzzy-based controllers produce the optimum dynamic response and resolve the power quality issues. Numerical simulations associated with detailed comparisons between different controllers are provided. It was found that when the studied system is subjected to a 3-phase fault, the voltage fluctuation at the D-STATCOM is reduced by 7.86% and 4.62% and the dynamic system performance is improved by 12.9% and 8.8% with using Fuzzy-PID and fuzzy-PI, respectively. Also with the dynamic load changes, the fluctuation of system voltages at the D-STATCOM is reduced by 0.982% and 0.577 % and the dynamic system performance is improved with 6.67%, 5.71% when comparing Fuzzy-PID controller and Fuzzy-PI to the uncontrolled system. The Fuzzy-PID provides a capability to enhance dynamic performance and system power quality because achieve less fluctuation and more smoothing for signals makes it is superior for voltage control for AC-DC micro-grid.
Abdelnasser A. Nafeh; Aya Heikal; Ragab A. El-Sehiemy; Waleed A.A. Salem. Intelligent fuzzy-based controllers for voltage stability enhancement of AC-DC micro-grid with D-STATCOM. Alexandria Engineering Journal 2021, 1 .
AMA StyleAbdelnasser A. Nafeh, Aya Heikal, Ragab A. El-Sehiemy, Waleed A.A. Salem. Intelligent fuzzy-based controllers for voltage stability enhancement of AC-DC micro-grid with D-STATCOM. Alexandria Engineering Journal. 2021; ():1.
Chicago/Turabian StyleAbdelnasser A. Nafeh; Aya Heikal; Ragab A. El-Sehiemy; Waleed A.A. Salem. 2021. "Intelligent fuzzy-based controllers for voltage stability enhancement of AC-DC micro-grid with D-STATCOM." Alexandria Engineering Journal , no. : 1.
This paper proposes an improved marine predators’ optimization algorithm (IMPOA) for solving the combined heat and power (CHP) economic dispatch problem. This problem provides optimal scheduling of heat and power generation supplies and pursues to minimize the overall fuel cost (OFC) supply of cogeneration units considering their operational constraints. Four test systems are considered to check the performance of both the MPOA and the proposed IMPOA. The first test system is small sized which involve 5-unit, whereas the second system is medium sized which contains 48-unit system. The third and fourth test systems are large sized systems. The third test system includes 84-unit, which are divided into 40 power-only units, 20 heat only units, and 24 CHP units. The fourth test system includes 96-unit, which are divided into 52 power-only units, 20 heat-only units, and 24 CHP units. The obtained results clearly show the capability, efficiency, and feasibility of the IMPOA with respect to other relevant optimization techniques for optimal solutions of small, medium and large-scale systems. Additionally, the convergence characteristics of the proposed IMPOA are stable and the arrival of the optimal solution is faster than the conventional MPOA.
Abdullah M. Shaheen; Abdallah M. Elsayed; Ahmed R. Ginidi; Ragab A. El-Sehiemy; Mosleh M. Alharthi; Sherif S.M. Ghoneim. A novel improved marine predators algorithm for combined heat and power economic dispatch problem. Alexandria Engineering Journal 2021, 1 .
AMA StyleAbdullah M. Shaheen, Abdallah M. Elsayed, Ahmed R. Ginidi, Ragab A. El-Sehiemy, Mosleh M. Alharthi, Sherif S.M. Ghoneim. A novel improved marine predators algorithm for combined heat and power economic dispatch problem. Alexandria Engineering Journal. 2021; ():1.
Chicago/Turabian StyleAbdullah M. Shaheen; Abdallah M. Elsayed; Ahmed R. Ginidi; Ragab A. El-Sehiemy; Mosleh M. Alharthi; Sherif S.M. Ghoneim. 2021. "A novel improved marine predators algorithm for combined heat and power economic dispatch problem." Alexandria Engineering Journal , no. : 1.
An enhanced multi-objective Quasi-Reflected Jellyfish Search Optimizer (MOQRJFS) is presented in this article for solving multi-dimensional Optimal Power Flow (MDOPF) issue with diverse objectives which display the minimization of economic fuel cost, total emissions, and the active power loss with satisfying operational constraints. Despite the simple structure of JFS with control of exploitation and exploration, searching capability of the JFS requires more support. Hence, two modifications are performed on the standard JFS algorithm. the first modification is that a cluster with a random size has been proposed which illustrates the social community that can share the data in the cluster and are dissimilar from one to another. The second modification is that a quasi-opposition-based learning is emerged in JFS to support the exploration phase. As selection criteria for the best solutions, a fuzzy decision-making strategy is joint into MOQRJFS optimizer. Additionally, the Pareto optimality concept is added to extract the non-dominated solutions. The superiority of the MOQRJFS is proved throughout application on IEEE 30-bus system, IEEE 57-bus system, the West Delta Region System of 52 bus (WDRS-52) in Egypt, and a large scale 118-bus system. Thirteen cases with economic, environmental, and technical objectives of MDOPF are included in this study. The outcomes of the proposed MOQRJFS have been compared with the conventional MOJFS and the reported techniques in the literature. It is clearly observed that the MOQRJFS give the minimum values compared with these techniques which reveals its robustness, effectiveness, and superiority when handling MDOPF among other techniques.
Abdullah M. Shaheen; Ragab A. El-Sehiemy; Mosleh M. Alharthi; Sherif S.M. Ghoneim; Ahmed R. Ginidi. Multi-objective jellyfish search optimizer for efficient power system operation based on multi-dimensional OPF framework. Energy 2021, 237, 121478 .
AMA StyleAbdullah M. Shaheen, Ragab A. El-Sehiemy, Mosleh M. Alharthi, Sherif S.M. Ghoneim, Ahmed R. Ginidi. Multi-objective jellyfish search optimizer for efficient power system operation based on multi-dimensional OPF framework. Energy. 2021; 237 ():121478.
Chicago/Turabian StyleAbdullah M. Shaheen; Ragab A. El-Sehiemy; Mosleh M. Alharthi; Sherif S.M. Ghoneim; Ahmed R. Ginidi. 2021. "Multi-objective jellyfish search optimizer for efficient power system operation based on multi-dimensional OPF framework." Energy 237, no. : 121478.
This paper proposes an improved binary bat algorithm (IBBA) for solving static and dynamic transmission network expansion planning (TNEP) problems for standard and realistic networks considering different objective functions (OFs). The proposed IBBA has two modifications to enhance the solution quality based on multi V-shaped transfer function and adaptive search space (ASS). The IBBA is applied to solve the static TNEP problem. A two-stage procedure is employed to solve the dynamic TNEP problem. In stage-1, the adaptive neuro-fuzzy inference system (ANFIS) is utilized to find the long-term load forecasting (LTLF) up to 2039. In stage-2, the IBBA is used to solve the dynamic TNEP problem. Two OFs are considered for solving TNEP problems. The first OF achieves the investment cost reduction. The second OF aims to minimize the total costs, which include the investment cost and the total costs of energy losses and reactive power compensation (RPC). The proposed procedure is applied to Garver’s 6-bus system and the West Delta Network (WDN) as a part of the Unified Egyptian Transmission Network (UETN) to solve TNEP problems. The obtained results are compared with other methods to show the robustness of the proposed procedure for solving TNEP problems.
Mohamed T. Mouwafi; Adel A. Abou El-Ela; Ragab A. El-Sehiemy; Waleed K. Al-Zahar. Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm. Alexandria Engineering Journal 2021, 1 .
AMA StyleMohamed T. Mouwafi, Adel A. Abou El-Ela, Ragab A. El-Sehiemy, Waleed K. Al-Zahar. Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm. Alexandria Engineering Journal. 2021; ():1.
Chicago/Turabian StyleMohamed T. Mouwafi; Adel A. Abou El-Ela; Ragab A. El-Sehiemy; Waleed K. Al-Zahar. 2021. "Techno-economic based static and dynamic transmission network expansion planning using improved binary bat algorithm." Alexandria Engineering Journal , no. : 1.
Mosleh Alharthi; Sherif Ghoneim; Abdallah Elsayed; Ragab El-Sehiemy; Abdullah Shaheen; Ahmed Ginidi. A Multi-Objective Marine Predator Optimizer for Optimal Techno-Economic Operation of AC/DC Grids. Studies in Informatics and Control 2021, 30, 89 -99.
AMA StyleMosleh Alharthi, Sherif Ghoneim, Abdallah Elsayed, Ragab El-Sehiemy, Abdullah Shaheen, Ahmed Ginidi. A Multi-Objective Marine Predator Optimizer for Optimal Techno-Economic Operation of AC/DC Grids. Studies in Informatics and Control. 2021; 30 (2):89-99.
Chicago/Turabian StyleMosleh Alharthi; Sherif Ghoneim; Abdallah Elsayed; Ragab El-Sehiemy; Abdullah Shaheen; Ahmed Ginidi. 2021. "A Multi-Objective Marine Predator Optimizer for Optimal Techno-Economic Operation of AC/DC Grids." Studies in Informatics and Control 30, no. 2: 89-99.
Power system operators and planners have progressively shown an interest in maximizing distribution automation technologies. The automated distribution systems (ADS) provide the capability of efficient and reliable control which require an optimal operation strategy to control the status of the line switches and also dispatch the controllable devices. Therefore, this paper introduces an efficient and robust technique based on Jellyfish Search Algorithm (JFSA) for optimal Volt/VAr coordination in ADSs based on joint distribution system reconfiguration (DSR), distributed generation units (DGs) integration and Distribution static VAr compensators (SVCs) operation. The suggested technique is used for the dynamic operation of ADS in order to minimize losses and reduce emissions when considering regular daily loading conditions. The 33-bus and 69-bus delivery DSs have been subjected to a variety of scenarios. These situations are mostly concerned with achieving optimum distribution system operation and control, as well as validating the proposed methodology. Despite the problem’s complexity, the proposed technique based on JFSA is shown to be the best solution in all of the cases considered. Furthermore, a comparison of the proposed JFSA with other similar approaches demonstrates its usefulness as a method to be used in modern ADS control centers.
Abdullah M. Shaheen; Abdullah M. ElSAYED; Ahmed R. Ginidi; Ehab E. Elattar; Ragab A. El-Sehiemy. Effective Automation of Distribution Systems with Joint Integration of DGs/ SVCs considering reconfiguration capability by Jellyfish Search Algorithm. IEEE Access 2021, 9, 1 -1.
AMA StyleAbdullah M. Shaheen, Abdullah M. ElSAYED, Ahmed R. Ginidi, Ehab E. Elattar, Ragab A. El-Sehiemy. Effective Automation of Distribution Systems with Joint Integration of DGs/ SVCs considering reconfiguration capability by Jellyfish Search Algorithm. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StyleAbdullah M. Shaheen; Abdullah M. ElSAYED; Ahmed R. Ginidi; Ehab E. Elattar; Ragab A. El-Sehiemy. 2021. "Effective Automation of Distribution Systems with Joint Integration of DGs/ SVCs considering reconfiguration capability by Jellyfish Search Algorithm." IEEE Access 9, no. : 1-1.
Enhancing distribution system operation accomplished with the integration of renewable energy resources (RERs) has several technical, economical, and environmental dimensions. In this regard, this paper presents an optimal integration procedure of Distributed Generation (DG) based on Photovoltaic panel (PV) and Distribution Static Compensator (DSTATCOM) in Electrical Distribution System (EDS). The proposed procedure is formulated as a multi-objective function (MOF). The considered objectives that reflect the technical, economic, and environmental issues, are Active Power Loss Level (APLL), Short Circuit Level (SCL), Voltage Deviation Level (VDL), Net Saving Level (NSL), and Environmental Pollution Reduction Level (EPRL). The proposed procedure investigates several hybrid optimization methods that combine the firefly algorithm (FA) with various acceleration coefficients PSO algorithms to improve the overall solution quality of the hybrid algorithms compared with the individual algorithms. To prove the capability of the proposed procedure, four different cases are tested on IEEE 33-bus and 69-bus EDSs. Added to that, the proposed algorithms are extended to practical Algerian EDS in Adrar City 205-bus. Results obtained by the hybrid FA-SCAC-PSO algorithm showed that the simultaneous allocation of multiple DG and DSTATCOM in all standard and practical test systems significantly reduces the loss and enhances the voltage profile. An energy-efficient analysis to proceed for different cases studied based on the best hybrid FA-SCAC-PSO algorithm to reach the best value of MOF compared to other algorithms, moreover the capability to achieve the optimal allocation of DG and DSTATCOM by maintaining the voltages profile within the permissible limit, whatever the variation of load. Significant technical economic and environmental achievements are found for different case studies especially in the existence of DGs and DSTATCOM devices.
Mohamed Zellagui; Adel Lasmari; Samir Settoul; Ragab A. El‐Sehiemy; Claude Ziad El‐Bayeh; Rachid Chenni. Simultaneous allocation of photovoltaic DG and DSTATCOM for techno‐economic and environmental benefits in electrical distribution systems at different loading conditions using novel hybrid optimization algorithms. International Transactions on Electrical Energy Systems 2021, 31, e12992 .
AMA StyleMohamed Zellagui, Adel Lasmari, Samir Settoul, Ragab A. El‐Sehiemy, Claude Ziad El‐Bayeh, Rachid Chenni. Simultaneous allocation of photovoltaic DG and DSTATCOM for techno‐economic and environmental benefits in electrical distribution systems at different loading conditions using novel hybrid optimization algorithms. International Transactions on Electrical Energy Systems. 2021; 31 (8):e12992.
Chicago/Turabian StyleMohamed Zellagui; Adel Lasmari; Samir Settoul; Ragab A. El‐Sehiemy; Claude Ziad El‐Bayeh; Rachid Chenni. 2021. "Simultaneous allocation of photovoltaic DG and DSTATCOM for techno‐economic and environmental benefits in electrical distribution systems at different loading conditions using novel hybrid optimization algorithms." International Transactions on Electrical Energy Systems 31, no. 8: e12992.
Cogeneration systems economic dispatch (CSED) provides an optimal scheduling of heat/ power generating units. The CSED aims to minimize the whole fuel cost (WFC) of the cogeneration units taking into consideration their technical and operational limits. Then, the current paper examines the first implementation of dominant bio-inspired metaheuristic called heap-based optimization algorithm (HBOA). The HBOA is powered by an adaptive penalty functions for getting the optimal operating points. The HBOA is inspired from the organization hierarchy, where the mechanism consists of the interaction among the subordinates and their immediate boss, the interaction among the colleagues, and the employee’s self-contribution. Based on the infeasible solutions’ remoteness from the nearest feasible point, HBOA penalizes them with various degrees. Four case studies of the CSED are implemented and analyzed, which comprise of 4, 24, 84 and 96 generating units. The HBOA is proposed to solve CSED problem with consideration of transmission losses and the valve point impacts. An investigation with the recent optimization algorithms, which are supply demand optimization (SDO), jellyfish search optimization algorithm (JFSOA), and marine predators’ optimization algorithm (MPOA), the improved MPOA (IMPOA) and manta ray foraging (MRF), is developed and elaborated. From the obtained results, it is clearly observed that the optimal solutions gained, in terms of WFC, reveal the feasibility, capability, and efficiency of HBOA compared with other optimizers especially for large-scale systems. case
Ahmed R. Ginidi; Abdallah M. Elsayed; Abdullah M. Shaheen; Ehab E. Elattar; Ragab A. El-Sehiemy. A Novel Heap based Optimizer for Scheduling of Large-scale Combined Heat and Power Economic Dispatch. IEEE Access 2021, 9, 1 -1.
AMA StyleAhmed R. Ginidi, Abdallah M. Elsayed, Abdullah M. Shaheen, Ehab E. Elattar, Ragab A. El-Sehiemy. A Novel Heap based Optimizer for Scheduling of Large-scale Combined Heat and Power Economic Dispatch. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StyleAhmed R. Ginidi; Abdallah M. Elsayed; Abdullah M. Shaheen; Ehab E. Elattar; Ragab A. El-Sehiemy. 2021. "A Novel Heap based Optimizer for Scheduling of Large-scale Combined Heat and Power Economic Dispatch." IEEE Access 9, no. : 1-1.
This article develops a nonlinear, multimodal, and multiobjective formulation of the combined economic environmental operation (CEEO) problem in hybrid AC-multiterminal (AC-MT) high-voltage direct current grids. In these grids, the technologies of voltage source converters support more active and reactive power control in AC grids. The aim of the CEEO issue is to minimize the overall cost of fuel and the pollutant emissions of generators. Also, transmission loss minimization is another target. An improved crow search algorithm (ICSA) is proposed for obtaining the solution of the formulated problem. The proposed ICSA combines the merits of CSA by randomly switching into local search around the best crows’ position. Pareto dominance is activated to improve the crow's memory and the external repository for multiobjective models. The ICSA is tested on modified IEEE 30-bus, the Egyptian West Delta Power Network, and the large-scale 118-bus system to solve the CEEO problem in AC-MTDC grids. The simulation results illustrate the proposed ICSA capability for finding diversified Pareto solutions with several possible operating points. Furthermore, the effectiveness of the proposed ICSA is demonstrated in terms of its solution robustness compared with previous techniques.
Abdullah M. Shaheen; Abdallah M. Elsayed; Ragab A. El-Sehiemy. Optimal Economic–Environmental Operation for AC-MTDC Grids by Improved Crow Search Algorithm. IEEE Systems Journal 2021, PP, 1 -8.
AMA StyleAbdullah M. Shaheen, Abdallah M. Elsayed, Ragab A. El-Sehiemy. Optimal Economic–Environmental Operation for AC-MTDC Grids by Improved Crow Search Algorithm. IEEE Systems Journal. 2021; PP (99):1-8.
Chicago/Turabian StyleAbdullah M. Shaheen; Abdallah M. Elsayed; Ragab A. El-Sehiemy. 2021. "Optimal Economic–Environmental Operation for AC-MTDC Grids by Improved Crow Search Algorithm." IEEE Systems Journal PP, no. 99: 1-8.
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.
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 StyleAbdullah 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 StyleAbdullah 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.
Recently, the use of diverse renewable energy resources has been intensively expanding due to their technical and environmental benefits. One of the important issues in the modeling and simulation of renewable energy resources is the extraction of the unknown parameters in photovoltaic models. In this regard, the parameters of three models of photovoltaic (PV) cells are extracted in this paper with a new optimization method called turbulent flow of water-based optimization (TFWO). The applications of the proposed TFWO algorithm for extracting the optimal values of the parameters for various PV models are implemented on the real data of a 55 mm diameter commercial R.T.C. France solar cell and experimental data of a KC200GT module. Further, an assessment study is employed to show the capability of the proposed TFWO algorithm compared with several recent optimization techniques such as the marine predators algorithm (MPA), equilibrium optimization (EO), and manta ray foraging optimization (MRFO). For a fair performance evaluation, the comparative study is carried out with the same dataset and the same computation burden for the different optimization algorithms. Statistical analysis is also used to analyze the performance of the proposed TFWO against the other optimization algorithms. The findings show a high closeness between the estimated power–voltage (P–V) and current–voltage (I–V) curves achieved by the proposed TFWO compared with the experimental data as well as the competitive optimization algorithms, thanks to the effectiveness of the developed TFWO solution mechanism.
Mokhtar Said; Abdullah Shaheen; Ahmed Ginidi; Ragab El-Sehiemy; Karar Mahmoud; Matti Lehtonen; Mohamed Darwish. Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer. Processes 2021, 9, 627 .
AMA StyleMokhtar Said, Abdullah Shaheen, Ahmed Ginidi, Ragab El-Sehiemy, Karar Mahmoud, Matti Lehtonen, Mohamed Darwish. Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer. Processes. 2021; 9 (4):627.
Chicago/Turabian StyleMokhtar Said; Abdullah Shaheen; Ahmed Ginidi; Ragab El-Sehiemy; Karar Mahmoud; Matti Lehtonen; Mohamed Darwish. 2021. "Estimating Parameters of Photovoltaic Models Using Accurate Turbulent Flow of Water Optimizer." Processes 9, no. 4: 627.
A modified marine predators optimizer (MMPO) is proposed for simultaneous distribution network reconfiguration (DNR) associated with the allocation of distributed generators (DGs). In the MMPO, the predator’s strategies are merged to consider the possibilities for variation in the environmental and climatic circumstances. The suggested MMPO is contrasted with the standard marine predators optimizer (MPO) and genetic, harmony search, fireworks, firefly and improved sine–cosine optimizers. The proposed MMPO is validated on single and multiple objectives using 33- and 69-bus distribution systems at light, nominal and heavy loading levels. The results obtained by the proposed MMPO are compared with those obtained by the original MPO and other optimizers. The achieved simulation outputs reveal a great improvement over the standard MPO and demonstrate the superiority of the proposed MMPO for simultaneous DNR and DG allocation.
Abdullah M. Shaheen; Abdallah M. Elsayed; Ragab A. El-Sehiemy; Salah Kamel; Sherif S. M. Ghoneim. A modified marine predators optimization algorithm for simultaneous network reconfiguration and distributed generator allocation in distribution systems under different loading conditions. Engineering Optimization 2021, 1 -22.
AMA StyleAbdullah M. Shaheen, Abdallah M. Elsayed, Ragab A. El-Sehiemy, Salah Kamel, Sherif S. M. Ghoneim. A modified marine predators optimization algorithm for simultaneous network reconfiguration and distributed generator allocation in distribution systems under different loading conditions. Engineering Optimization. 2021; ():1-22.
Chicago/Turabian StyleAbdullah M. Shaheen; Abdallah M. Elsayed; Ragab A. El-Sehiemy; Salah Kamel; Sherif S. M. Ghoneim. 2021. "A modified marine predators optimization algorithm for simultaneous network reconfiguration and distributed generator allocation in distribution systems under different loading conditions." Engineering Optimization , no. : 1-22.
This paper presents an Improved Multi-Objective Marine Predators Optimizer (IMMPO) for optimal operation of hybrid AC and multi-terminal-high voltage direct current (AC/MT-HVDC) power systems. The proposed IMMPO incorporates an external repository to conserve the non-dominated preys. Furthermore, fuzzy decision making is employed to select the best compromise operating point for the hybrid AC/HVDC power systems. In these systems, the active and reactive power controllability of the voltage source converters (VSCs) are activated besides the full control in AC grids via the committed generators, transformer tap settings and VAR compensations. The modelling of the VSC losses is integrated in its quadratic function of the converter current. The optimal operation of AC/MT-HVDC power systems is handled as a multi-objective problem for minimizing the total fuel costs, the environmental emissions of the generation units and the total losses over the AC, HVDC transmission lines and VSCs stations. For solving this problem, several recent optimization algorithms are applied on a modified standard IEEE 30-bus. Also, a real part of the Egyptian West Delta Region Power Network emerged with VSC-HVDC grids is considered as a practical case study. The simulation results demonstrate the effectiveness and preponderance of the proposed algorithm with great stability indices over several competitive algorithms. Nevertheless, the proposed IMMPO is successfully extracting well-diversified Pareto solutions while a compromise operating point is effectively produced to satisfy the operator requirements.
Abdallah M. Elsayed; Abdullah M. Shaheen; Mosleh M. Alharthi; Sherif S. M. Ghoneim; Ragab A. El-Sehiemy. Adequate Operation of Hybrid AC/MT-HVDC Power Systems using an Improved Multi-Objective Marine Predators Optimizer. IEEE Access 2021, PP, 1 -1.
AMA StyleAbdallah M. Elsayed, Abdullah M. Shaheen, Mosleh M. Alharthi, Sherif S. M. Ghoneim, Ragab A. El-Sehiemy. Adequate Operation of Hybrid AC/MT-HVDC Power Systems using an Improved Multi-Objective Marine Predators Optimizer. IEEE Access. 2021; PP (99):1-1.
Chicago/Turabian StyleAbdallah M. Elsayed; Abdullah M. Shaheen; Mosleh M. Alharthi; Sherif S. M. Ghoneim; Ragab A. El-Sehiemy. 2021. "Adequate Operation of Hybrid AC/MT-HVDC Power Systems using an Improved Multi-Objective Marine Predators Optimizer." IEEE Access PP, no. 99: 1-1.
The output generations of renewable energy sources (RES) depend basically on climatic conditions, which are the main reason for their uncertain nature. As a result, the performance and security of distribution systems can be significantly worsened with high RES penetration. To address these issues, an analytical study was carried out by considering different penetration strategies for RES in the radial distribution system. Moreover, a bi-stage procedure was proposed for optimal planning of RES penetration. The first stage was concerned with calculating the optimal RES locations and sites. This stage aimed to minimize the voltage variations in the distribution system. In turn, the second stage was concerned with obtaining the optimal setting of the voltage control devices to improve the voltage profile. The multi-objective cat swarm optimization (MO-CSO) algorithm was proposed to solve the bi-stages optimization problems for enhancing the distribution system performance. Furthermore, the impact of the RES penetration level and their uncertainty on a distribution system voltage were studied. The proposed method was tested on the IEEE 34-bus unbalanced distribution test system, which was analyzed using backward/forward sweep power flow for unbalanced radial distribution systems. The proposed method provided satisfactory results for increasing the penetration level of RES in unbalanced distribution networks.
Eman Ali; Ragab El-Sehiemy; Adel Abou El-Ela; Karar Mahmoud; Matti Lehtonen; Mohamed Darwish. An Effective Bi-Stage Method for Renewable Energy Sources Integration into Unbalanced Distribution Systems Considering Uncertainty. Processes 2021, 9, 471 .
AMA StyleEman Ali, Ragab El-Sehiemy, Adel Abou El-Ela, Karar Mahmoud, Matti Lehtonen, Mohamed Darwish. An Effective Bi-Stage Method for Renewable Energy Sources Integration into Unbalanced Distribution Systems Considering Uncertainty. Processes. 2021; 9 (3):471.
Chicago/Turabian StyleEman Ali; Ragab El-Sehiemy; Adel Abou El-Ela; Karar Mahmoud; Matti Lehtonen; Mohamed Darwish. 2021. "An Effective Bi-Stage Method for Renewable Energy Sources Integration into Unbalanced Distribution Systems Considering Uncertainty." Processes 9, no. 3: 471.
This paper presents two multi-stage fuzzy logic controllers for switched filter compensation scheme. It aims to improve and ensure effective voltage stabilization in power systems. Dynamic simulations are employed on normal and during short circuit faults. The effect of dynamic gains is compared with a classical fixed gains control strategy. Several test and validation cases achieve efficient energy utilization and feeder power loss reduction.
Abdel-Fattah Attia; Adel Sharaf; Ragab El Sehiemy. Multi-stage fuzzy based flexible controller for effective voltage stabilization in power systems. ISA Transactions 2021, 1 .
AMA StyleAbdel-Fattah Attia, Adel Sharaf, Ragab El Sehiemy. Multi-stage fuzzy based flexible controller for effective voltage stabilization in power systems. ISA Transactions. 2021; ():1.
Chicago/Turabian StyleAbdel-Fattah Attia; Adel Sharaf; Ragab El Sehiemy. 2021. "Multi-stage fuzzy based flexible controller for effective voltage stabilization in power systems." ISA Transactions , no. : 1.
Economic Dispatch in Cogeneration Systems (EDCS) provides the optimal scheduling of heat and power of generation units. This can be achieved by minimizing the total cost of fuel (TCF) of the cogeneration units taking into consideration their operational limits. A manta ray foraging MRF optimizer, in this paper, is developed to solve the EDCS problem including the valve point impacts, and wind power. MRF optimizer is designed with adaptive penalty functions for acquiring the most feasible and best operational points for the EDCS problem. Infeasible solutions are handled with various degrees and penalized depending on their remoteness from the closest possible point. The overall power and heat loading are completely achieved by the equality constraints. Also, the cogeneration units’ dynamic operating limits are not adversely affected since its concerning limitations of heat-only and power-only units are fulfilled. Two test systems of small 5 and large 96-units, are analyzed. In addition to this, an assessment of the recent optimization techniques, which are applied on to EDCS, has been developed and discussed. The applications are carried out for two scenarios at peak and daily variation in the power and heat loading condition. The wind power inclusion is assessed for each scenario in terms of the overall reduction in the total fuel costs. It was proven also; the inclusion of wind power achieves more economical solution at different scenarios with reduction up to 8%. It is crystal clear that the outputs obtained illustrate MRF optimizer efficiency, feasibility, and capability to obtain better solutions in minimizing the fuel cost compared to other optimization techniques at acceptable convergence rates. Moreover, the solutions demonstrate the ability of MRF optimizer application on the large-scale 96-unit systems.
Abdullah M. Shaheen; Ahmed R. Ginidi; Ragab A. El-Sehiemy; Ehab E. Elattar. Optimal economic power and heat dispatch in Cogeneration Systems including wind power. Energy 2021, 225, 120263 .
AMA StyleAbdullah M. Shaheen, Ahmed R. Ginidi, Ragab A. El-Sehiemy, Ehab E. Elattar. Optimal economic power and heat dispatch in Cogeneration Systems including wind power. Energy. 2021; 225 ():120263.
Chicago/Turabian StyleAbdullah M. Shaheen; Ahmed R. Ginidi; Ragab A. El-Sehiemy; Ehab E. Elattar. 2021. "Optimal economic power and heat dispatch in Cogeneration Systems including wind power." Energy 225, no. : 120263.
An aerial metallic pipeline experiences induced voltage if drawn in close vicinity of a high voltage power transmission line as suggested by Faraday's law of electromagnetic induction. Such voltages, if not appropriately mitigated, may prove fatal. This paper initially focuses on the evaluation of the induced voltage under the normal operating condition of power transmission lines followed by methods of passive mitigation of the induced voltages. The research also formulates the strategies to enhance mitigation efficiency by optimizing certain features of passive loop techniques using a new optimization algorithm called Slime Mould Algorithm (SMA). A 400 kV single circuit horizontal configuration line with an aboveground pipeline serves as a comprehensive test case to study the efficacy of the proposed algorithm. Results show that the induced voltage levels can be reduced up to 60% using the optimal location of loop conductors and the number of loops, in addition to using shielding material with high permeability. Comparing the obtained results with those obtained using Carson's formula and with genetic algorithm indicates the superior performance of the proposed technique.
Rabah Djekidel; Bachir Bentouati; M.S. Javaid; H.R.E.H. Bouchekara; Ahmed Saeed Bayoumi; Ragab A. El-Sehiemy. Mitigating the effects of magnetic coupling between HV transmission line and metallic pipeline using slime mould algorithm. Journal of Magnetism and Magnetic Materials 2021, 529, 167865 .
AMA StyleRabah Djekidel, Bachir Bentouati, M.S. Javaid, H.R.E.H. Bouchekara, Ahmed Saeed Bayoumi, Ragab A. El-Sehiemy. Mitigating the effects of magnetic coupling between HV transmission line and metallic pipeline using slime mould algorithm. Journal of Magnetism and Magnetic Materials. 2021; 529 ():167865.
Chicago/Turabian StyleRabah Djekidel; Bachir Bentouati; M.S. Javaid; H.R.E.H. Bouchekara; Ahmed Saeed Bayoumi; Ragab A. El-Sehiemy. 2021. "Mitigating the effects of magnetic coupling between HV transmission line and metallic pipeline using slime mould algorithm." Journal of Magnetism and Magnetic Materials 529, no. : 167865.
Enhancing the distribution systems performance is an important target for system operators. This article proposes an enhanced grey wolf algorithm (EGWA) for allocating the distributed generation units (DGUs)which is coordinated with the capacitor banks (CBs) and the voltage regulators (VRs) to achieve the target. Diversified tasks aims at minimizing the investment expenses of the coordinated equipment's, maximizing the benefits resulted from power losses reduction and the purchased power from the grid. In the technical direction, it is investigated through ameliorating the voltage profile and the loading capacity. Also, the loading variations are incorporated via light, shoulder and peak levels of demand. Dynamic adaptation mechanism is used for updating the control parameters of the GWA. The proposed EGWA is employed for solving the optimal allocation problem (OAP) for two Egyptian distribution systems. Simulation results declare the proposed EGWA capability for solving the coordinated allocation of CBs, DGUs and VRs. Great reduction of power losses is achieved with high improvement of the minimum voltage and loading capacity. Also, a comparative and statistical analysis is executed for the application of the proposed EGWA with different optimization techniques which derives superior capabilities of the proposed EGWA over the others in the literature.
Abdullah M. Shaheen; Ragab A. El-Sehiemy. Optimal Coordinated Allocation of Distributed Generation Units/ Capacitor Banks/ Voltage Regulators by EGWA. IEEE Systems Journal 2021, 15, 257 -264.
AMA StyleAbdullah M. Shaheen, Ragab A. El-Sehiemy. Optimal Coordinated Allocation of Distributed Generation Units/ Capacitor Banks/ Voltage Regulators by EGWA. IEEE Systems Journal. 2021; 15 (1):257-264.
Chicago/Turabian StyleAbdullah M. Shaheen; Ragab A. El-Sehiemy. 2021. "Optimal Coordinated Allocation of Distributed Generation Units/ Capacitor Banks/ Voltage Regulators by EGWA." IEEE Systems Journal 15, no. 1: 257-264.