This page has only limited features, please log in for full access.

Prof. Ali Eltamaly
king saud university

Basic Info


Research Keywords & Expertise

0 Optimization Algorithms
0 Power Electronics
0 Renewable and clean energies
0 Electric power conversion
0 Photovoltaic and wind energy systems

Fingerprints

Photovoltaic and wind energy systems
Optimization Algorithms

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

Ali Mohamed Eltamaly (Ph.D.-2000) is a full professor at Mansoura University, Egypt, and King Saud University, Saudi Arabia. He received the B.Sc. and M.Sc. degrees in electrical engineering from Al-Minia University, Egypt in 1992 and 1996, respectively. He received his Ph.D. Degree in Electrical Engineering from Texas A&M University in 2000. His current research interests include renewable energy, smart grid, power electronics, motor drives, power quality, artificial intelligence, evolutionary and heuristic optimization techniques, and distributed generation. He published 20 book and book chapters and he has authored or coauthored more than 200 refereed journal and conference papers. He published several patents in the USA patent office. He has supervised several M.S. and Ph.D. theses worked on several National/International technical projects. He got distinguish professor award for scientific excellence, Egyptian supreme council of Universities, Egypt, June 2017, and he has awarded many prizes in different universities in Egypt and Saudi Arabia. He is participating as an editor and associate editors in many international journals and chaired many international conferences’ sessions. He is chair professor of Saudi Electricity Company Chair in power system reliability and security, King Saud University, Riyadh, Saudi Arabia.

Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 31 July 2021 in Sustainability
Reads 0
Downloads 0

There is a growing interest in increasing the penetration rate of renewable energy systems due to the drawbacks associated with the use of fossil fuels. However, the grid integration of renewable energy systems represents many challenging tasks for system operation, stability, reliability, and power quality. Small hybrid renewable energy systems (HRES) are small-scale power systems consisting of energy sources and storage units to manage and optimize energy production and consumption. Appropriate real-time monitoring of HRES plays an essential role in providing accurate information to enable the system operator to evaluate the overall performance and identify any abnormal conditions. This work proposes an internet of things (IoT) based architecture for HRES, consisting of a wind turbine, a photovoltaic system, a battery storage system, and a diesel generator. The proposed architecture is divided into four layers: namely power, data acquisition, communication network, and application layers. Due to various communication technologies and the missing of a standard communication model for HRES, this work, also, defines communication models for HRES based on the IEC 61850 standard. The monitoring parameters are classified into different categories, including electrical, status, and environmental information. The network modeling and simulation of a university campus is considered as a case study, and critical parameters, such as network topology, link capacity, and latency, are investigated and discussed.

ACS Style

Ali Eltamaly; Majed Alotaibi; Abdulrahman Alolah; Mohamed Ahmed. IoT-Based Hybrid Renewable Energy System for Smart Campus. Sustainability 2021, 13, 8555 .

AMA Style

Ali Eltamaly, Majed Alotaibi, Abdulrahman Alolah, Mohamed Ahmed. IoT-Based Hybrid Renewable Energy System for Smart Campus. Sustainability. 2021; 13 (15):8555.

Chicago/Turabian Style

Ali Eltamaly; Majed Alotaibi; Abdulrahman Alolah; Mohamed Ahmed. 2021. "IoT-Based Hybrid Renewable Energy System for Smart Campus." Sustainability 13, no. 15: 8555.

Journal article
Published: 28 June 2021 in IEEE Access
Reads 0
Downloads 0

A hybrid energy system (HES) is a perfect option for supplying electric energy to remote areas. A HES normally uses renewable energy sources such as wind and PV. Owing to the intermittent nature of these sources, HES should have batteries and/or conventional energy sources. HES proposed in this study is having wind, PV, batteries, and diesel generators. The design and operation of HES are considerably improved with the use of smart grid concepts. This study introduced a fuzzy logic controller to implement a new demand response strategy (DRS) where the electricity tariff is determined based on the state of charge of the battery, the charging/discharging power from the battery, and the previous response from the customers. A modified cuckoo search (MCS) optimization algorithm is introduced for sizing HES components for the lowest cost of energy (CoE) and loss of load probability (LOLP). A multiobjective function consisting of the CoE and LOLP is used to get the optimal design of HES. The MCS reduces the number of times that the optimization algorithm executes the objective function. The continuous reduction of the swarm size proposed in this paper enhances the exploration in the beginning and enhances exploitation at the final stage. The MCS is compared with 10 state-of-the-art optimization algorithms. The results from using MCS reduced the convergence time to 25-63% of the time needed by other optimization algorithms and the DRS introduced in this study reduced the CoE by 34% compared with the flat-rate pricing.

ACS Style

Ali M. Eltamaly; Majed A. Alotaibi. Novel Fuzzy-Swarm Optimization for Sizing of Hybrid Energy Systems Applying Smart Grid Concepts. IEEE Access 2021, 9, 1 -1.

AMA Style

Ali M. Eltamaly, Majed A. Alotaibi. Novel Fuzzy-Swarm Optimization for Sizing of Hybrid Energy Systems Applying Smart Grid Concepts. IEEE Access. 2021; 9 ():1-1.

Chicago/Turabian Style

Ali M. Eltamaly; Majed A. Alotaibi. 2021. "Novel Fuzzy-Swarm Optimization for Sizing of Hybrid Energy Systems Applying Smart Grid Concepts." IEEE Access 9, no. : 1-1.

Journal article
Published: 07 May 2021 in Renewable and Sustainable Energy Reviews
Reads 0
Downloads 0

Due to the multiple peaks generated in the power to voltage characteristics of partially shaded photovoltaic (PV) arrays there is an urgent need for an effective optimization algorithm to capture its global peak instead of the local peaks. The required optimization algorithm should converge very fast and accurately capture the global peak. Many metaheuristic optimization algorithms have been introduced to tackle this problem and balance exploration and exploitation performances. These algorithms use a constant number of searching agents (swarm size) through all iterations. The maximum power point tracker (MPPT) of the PV system requires high numbers of searching agents in the initial steps of optimization to enhance explorations, whereas the final stage of optimization requires lower numbers of searching agents to enhance exploitations, which are conditions that are currently unavailable in optimization algorithms. This was the research gap that was the main motive of creating the new algorithm introduced in this paper, where a high number of searching agents is used at the beginning of the optimization steps to enhance exploration and reduce the convergence failure. The number of searching agents should be reduced gradually to have a lower number of search agents at the end of searching steps to enhance exploitation. This need is inspired by the well-known musical chairs game in which the players and chairs start with high numbers and are reduced one by one in each round which enhances the exploration at the start of the search and exploitation at the end of the search steps. For this reason, a novel optimization algorithm called the musical chairs algorithm (MCA) is introduced in this paper. Using the MCA for MPPT of PV systems considerably provided lower convergence times and failure rates than other optimization algorithms. The convergence time and failure rate are the crucial factors in assessing the MPPT because they should be minimized as much as possible to improve the PV system efficiency and assure its stability especially in the high dynamic change of shading conditions. The convergence time was reduced to 20%–50% of those obtained using five benchmark optimization algorithms. Moreover, the oscillations at steady state is reduced to 20%–30% of the values associated the benchmark optimization algorithms. These results prove the superiority of the newly proposed MCA in the MPPTs of the PV system.

ACS Style

Ali M. Eltamaly. A novel musical chairs algorithm applied for MPPT of PV systems. Renewable and Sustainable Energy Reviews 2021, 146, 111135 .

AMA Style

Ali M. Eltamaly. A novel musical chairs algorithm applied for MPPT of PV systems. Renewable and Sustainable Energy Reviews. 2021; 146 ():111135.

Chicago/Turabian Style

Ali M. Eltamaly. 2021. "A novel musical chairs algorithm applied for MPPT of PV systems." Renewable and Sustainable Energy Reviews 146, no. : 111135.

Chapter
Published: 27 April 2021 in Smart and Sustainable Planning for Cities and Regions
Reads 0
Downloads 0

The generated power from the photovoltaic (PV) array is a function in its terminal voltage. The relation between the generated power and the terminal voltage of the PV array is called the P–V curve. The point corresponding to the highest generated power in this relation is called maximum power point (MPP). This relation has only one peak in the case of uniformly distributed irradiance over the PV array. Meanwhile, it has multiple peaks in the case of partial shading conditions (PSC). The one with the highest power is called global peak (GP) and the other peaks are called local peaks (LPs). The control system should track this point to improve the efficiency of the PV system by extracting the maximum available power from the PV array. The controller used to track this point is called the maximum power point tracker (MPPT). Traditional MPPTs such as hill-climbing or incremental conductance are adequate to track the MPP in the case of uniform irradiance, but it may stick at one of the LPs in the case of PSC. For this reason an unlimited number of MPPT techniques are introduced in the literature to track this point. This chapter introduces an overview of the PV maximum power point trackers (MPPT) techniques. The classifications of MPPT of the PV system is introduced in detail in this chapter. The operating principles, advantages, and disadvantages of each technique are introduced in detail for famous and important techniques and in brief for the less famous techniques or the techniques that are not showing good performance in tracking the MPP. A comprehensive comparison between these techniques is presented in detail in this chapter. Important recommendations and conclusions are introduced at the end of this chapter to show the advantages and disadvantages of these PV MPPT techniques.

ACS Style

Ali M. Eltamaly. Photovoltaic Maximum Power Point Trackers: An Overview. Smart and Sustainable Planning for Cities and Regions 2021, 117 -200.

AMA Style

Ali M. Eltamaly. Photovoltaic Maximum Power Point Trackers: An Overview. Smart and Sustainable Planning for Cities and Regions. 2021; ():117-200.

Chicago/Turabian Style

Ali M. Eltamaly. 2021. "Photovoltaic Maximum Power Point Trackers: An Overview." Smart and Sustainable Planning for Cities and Regions , no. : 117-200.

Chapter
Published: 27 April 2021 in Smart and Sustainable Planning for Cities and Regions
Reads 0
Downloads 0

In this chapter the performance of various maximum power point tracking techniques for Photovoltaic (PV) systems has been presented, under uniform and non-uniform irradiance conditions. Under uniform irradiance conditions, the power-voltage curve of PV systems is nonlinear and contains one peak point whose location appertains to the irradiation and surface temperature of the PV system. Partial shading on PV modules reduces the generated power than the maximum power generated from each module separately. The traditional techniques of tracking the maximum power point are designed to track the global peak but they always failed to capture the exact point. In this chapter, different techniques of maximum power point tracking have been introduced, analyzed, and simulated. MATLAB, SIMULINK, and PSIM software have been utilized to simulate the PV systems under various shading conditions. Furthermore, the response of the different techniques of maximum power point trackers has been evaluated under different weather conditions.

ACS Style

Ali M. Eltamaly; Mohamed A. Mohamed; Ahmed G. Abo-Khalil. Design and Comprehensive Analysis of Maximum Power Point Tracking Techniques in Photovoltaic Systems. Smart and Sustainable Planning for Cities and Regions 2021, 253 -284.

AMA Style

Ali M. Eltamaly, Mohamed A. Mohamed, Ahmed G. Abo-Khalil. Design and Comprehensive Analysis of Maximum Power Point Tracking Techniques in Photovoltaic Systems. Smart and Sustainable Planning for Cities and Regions. 2021; ():253-284.

Chicago/Turabian Style

Ali M. Eltamaly; Mohamed A. Mohamed; Ahmed G. Abo-Khalil. 2021. "Design and Comprehensive Analysis of Maximum Power Point Tracking Techniques in Photovoltaic Systems." Smart and Sustainable Planning for Cities and Regions , no. : 253-284.

Research article electrical engineering
Published: 13 April 2021 in Arabian Journal for Science and Engineering
Reads 0
Downloads 0

Saudi Arabia tries to build local desalination water stations to supply water to remote areas. Due to the low cost and energy requirements of reverse osmosis (RO) desalination technology, it has been used to supply fresh water to Arar City in the northeast of Saudi Arabia. In this paper, it is proposed to provide an average of 1000 cubic meters of water per day by using autonomous hybrid renewable energy system (RES). This proposed system contains wind turbines (WTs), photovoltaic (PV), battery, and it is designed to feed the RO system with the energy adequate to produce the required amount of fresh water for the minimum cost and minimum loss of supply probability. The proposed system was designed to generate 2440 kW power to produce this amount of water. Matching study between the site and the best WT among 10 market-available WTs is introduced. Three optimization strategies were used and compared for the design of the proposed system to ensure that no premature convergence can occur. These strategies consisted of two well-known techniques, particle swarm optimization and bat algorithm (BA), and a relatively new technique: social mimic optimization. The simulation results obtained from the proposed system showed the superiority of using a RES for feeding a RO desalination power plant in Arar City, and they also showed that the BA is the fastest and most accurate optimization technique to perform this design problem compared with the other two optimization techniques. This detailed analysis shows that the cost of production of fresh water is $0.745/m3.

ACS Style

Ali M. Eltamaly; Emad Ali; Mourad Bumazza; Sarwono Mulyono; Muath Yasin. Optimal Design of Hybrid Renewable Energy System for a Reverse Osmosis Desalination System in Arar, Saudi Arabia. Arabian Journal for Science and Engineering 2021, 1 -19.

AMA Style

Ali M. Eltamaly, Emad Ali, Mourad Bumazza, Sarwono Mulyono, Muath Yasin. Optimal Design of Hybrid Renewable Energy System for a Reverse Osmosis Desalination System in Arar, Saudi Arabia. Arabian Journal for Science and Engineering. 2021; ():1-19.

Chicago/Turabian Style

Ali M. Eltamaly; Emad Ali; Mourad Bumazza; Sarwono Mulyono; Muath Yasin. 2021. "Optimal Design of Hybrid Renewable Energy System for a Reverse Osmosis Desalination System in Arar, Saudi Arabia." Arabian Journal for Science and Engineering , no. : 1-19.

Journal article
Published: 10 March 2021 in Engineering Optimization
Reads 0
Downloads 0

This article introduces a novel strategy for determining the optimal control parameters of particle swarm optimization (PSO) for the shortest convergence time and lowest failure rate of photovoltaic (PV) maximum power point tracker (MPPT) systems. This strategy is used offline to determine these parameters and then the control system uses them in the online MPPT. The strategy uses two nested particle swarm optimization (NESTPSO) search loops: the inner one involves the PV system and the outer one uses the inner PSO as a fitness function. The control parameters and swarm size of the inner PSO loop are used as optimization variables in the outer PSO loop. This strategy can be used not only for PSO but also for all other optimization techniques. The simulation and experimental results obtained using the NESTPSO strategy show a great reduction of 77–681% in convergence time and failure rate compared to 10 benchmark strategies, proving the superiority of this technique.

ACS Style

Ali M. Eltamaly. A novel particle swarm optimization optimal control parameter determination strategy for maximum power point trackers of partially shaded photovoltaic systems. Engineering Optimization 2021, 1 -17.

AMA Style

Ali M. Eltamaly. A novel particle swarm optimization optimal control parameter determination strategy for maximum power point trackers of partially shaded photovoltaic systems. Engineering Optimization. 2021; ():1-17.

Chicago/Turabian Style

Ali M. Eltamaly. 2021. "A novel particle swarm optimization optimal control parameter determination strategy for maximum power point trackers of partially shaded photovoltaic systems." Engineering Optimization , no. : 1-17.

Chapter
Published: 05 March 2021 in Smart and Sustainable Planning for Cities and Regions
Reads 0
Downloads 0

In order to achieve maximum power point tracking (MPPT) of wind energy systems, the rotating speed of wind turbines (WTs) ought to be adjusted in the constant as indicated by wind speeds. However, fast wind speed varieties and heavy inertia bargain the MPPT control of WTs. This chapter proposes a fuzzy logic controller (FLC)-based MPPT strategy for Wind Energy Conversion Systems (WECS). The performance of the proposed MPPT strategy is analyzed mathematically and verified by simulation using MATLAB/PSIM/Simulink software. The proposed method improves the speed and accuracy of MPPT. Furthermore, the simulation results have been conducted to approve the performance of the proposed MPPT strategy, and all results have confirmed the adequacy of the proposed MPPT strategy.

ACS Style

Ali M. Eltamaly; Mohamed A. Mohamed; Ahmed G. Abo-Khalil. Maximum Power Point Tracking Strategies of Grid-Connected Wind Energy Conversion Systems. Smart and Sustainable Planning for Cities and Regions 2021, 193 -225.

AMA Style

Ali M. Eltamaly, Mohamed A. Mohamed, Ahmed G. Abo-Khalil. Maximum Power Point Tracking Strategies of Grid-Connected Wind Energy Conversion Systems. Smart and Sustainable Planning for Cities and Regions. 2021; ():193-225.

Chicago/Turabian Style

Ali M. Eltamaly; Mohamed A. Mohamed; Ahmed G. Abo-Khalil. 2021. "Maximum Power Point Tracking Strategies of Grid-Connected Wind Energy Conversion Systems." Smart and Sustainable Planning for Cities and Regions , no. : 193-225.

Chapter
Published: 05 March 2021 in Smart and Sustainable Planning for Cities and Regions
Reads 0
Downloads 0

Wind energy system is becoming a mature technology for generating electric energy from the wind. The design of the wind energy system should take into consideration the matching between the wind speed site characteristics and the performance characteristics of the wind turbine. This chapter is introduced to perform the matching process between the site and the wind turbines (WTs) for minimum cost and highest reliability. An accurate matching methodology for pairing between site and WTs has been introduced. The pairing methodology is designed in Matlab code to perform this study. The input data for 32 Saudi Arabia sites and 140 market available WTs have been selected to validate the right operation of the new proposed computer program. This program will select the best site and the most suitable WT for this site based on techno-economical methodology. This program can help researchers, designers, experts, and decision-makers to select the best site among many sites and the best WT for each site. The results obtained from this site show a substantial reduction in cost when the best site is selected as the most suitable WT for this site.

ACS Style

Ali M. Eltamaly. New Software for Matching Between Wind Sites and Wind Turbines. Smart and Sustainable Planning for Cities and Regions 2021, 275 -317.

AMA Style

Ali M. Eltamaly. New Software for Matching Between Wind Sites and Wind Turbines. Smart and Sustainable Planning for Cities and Regions. 2021; ():275-317.

Chicago/Turabian Style

Ali M. Eltamaly. 2021. "New Software for Matching Between Wind Sites and Wind Turbines." Smart and Sustainable Planning for Cities and Regions , no. : 275-317.

Chapter
Published: 05 March 2021 in Smart and Sustainable Planning for Cities and Regions
Reads 0
Downloads 0

Wind generation is considered as one of the optimum renewable energy sources due to its more saving running cost, zero-emission, and friendly environment at comparing with the traditional power plants. Using the wind farms with the utility grid can’t reach the optimum compensation during any abnormal condition in the power system. Distributed Static Synchronous Compensators (D-STATCOM) is a power electronic control system to be used with the distribution power network for harmonics current elimination, reactive power compensation, voltage regulation, voltage flicker mitigation, and frequency regulation. D-STATCOM provides effective compensation to the unbalance or the nonlinear loads by injecting the required accurate value at the Point of Common Coupling (PCC) depending on the Voltage Source Converter (VSC). This chapter proposes a design procedure of a high-power D-STATCOM with the distribution network linked with the wind generation for enhancing the power system quality. The proposed simulation in this chapter has been done using the MATLAB/Simulink software for distribution voltage control, loadability, and power loss reduction using the D-STATCOM control techniques with the electrical distribution network.

ACS Style

Ali M. Eltamaly; Yehia Sayed Mohamed; Abou-Hashema M. El-Sayed; Amer Nasr A. Elghaffar; Ahmed G. Abo-Khalil. D-STATCOM for Distribution Network Compensation Linked with Wind Generation. Smart and Sustainable Planning for Cities and Regions 2021, 87 -107.

AMA Style

Ali M. Eltamaly, Yehia Sayed Mohamed, Abou-Hashema M. El-Sayed, Amer Nasr A. Elghaffar, Ahmed G. Abo-Khalil. D-STATCOM for Distribution Network Compensation Linked with Wind Generation. Smart and Sustainable Planning for Cities and Regions. 2021; ():87-107.

Chicago/Turabian Style

Ali M. Eltamaly; Yehia Sayed Mohamed; Abou-Hashema M. El-Sayed; Amer Nasr A. Elghaffar; Ahmed G. Abo-Khalil. 2021. "D-STATCOM for Distribution Network Compensation Linked with Wind Generation." Smart and Sustainable Planning for Cities and Regions , no. : 87-107.

Chapter
Published: 05 March 2021 in Smart and Sustainable Planning for Cities and Regions
Reads 0
Downloads 0

The objective of this chapter is to introduce the state of the art technology in wind power plant control and automation. This chapter starts with a historical background about supervisory control and automation evolution in the last decades. Several remarks are made regarding the use of SCADA Systems in wind turbine power plants. The Supervisory Control and Data Acquisition (SCADA) systems are responsible for controlling and monitoring many of the processes that make life in the industrial world possible, such as power distribution, oil flow, communications, and many more. In this chapter, an overview of SCADA at the wind power plant is presented, and operational concerns are addressed and examined. Notes on future trends will be provided. Finally, recommendations are provided regarding SCADA systems and their application in the wind power plant environment. One of the most significant aspects of SCADA is its ability to evolve with the ever-changing face of Information Technology (IT) systems.

ACS Style

Khairy Sayed; Ahmed G. Abo-Khalil; Ali M. Eltamaly. Wind Power Plants Control Systems Based on SCADA System. Smart and Sustainable Planning for Cities and Regions 2021, 109 -151.

AMA Style

Khairy Sayed, Ahmed G. Abo-Khalil, Ali M. Eltamaly. Wind Power Plants Control Systems Based on SCADA System. Smart and Sustainable Planning for Cities and Regions. 2021; ():109-151.

Chicago/Turabian Style

Khairy Sayed; Ahmed G. Abo-Khalil; Ali M. Eltamaly. 2021. "Wind Power Plants Control Systems Based on SCADA System." Smart and Sustainable Planning for Cities and Regions , no. : 109-151.

Chapter
Published: 05 March 2021 in Control and Operation of Grid-Connected Wind Energy Systems
Reads 0
Downloads 0

This chapter introduces a robust control scheme of load frequency control (LFC) of a micro-grid system integrated with a wind energy system. The control scheme is based on H∞ and linear quadratic Gaussian techniques. The main idea of the control design is to be stable against the parameter’s uncertainties and the load disturbance. A complete model of the power system with the DFIG has been linearized. This model has been utilized to design both controllers of H∞ and linear quadratic Gaussian. The H∞ is designed by optimal selecting of the weighting functions to ensure the robustness and to enhance the overall performance. Also, the full states considering the frequency deviation are assessed based on the standard Kalman filter method. Moreover, the states of the system are applied with the linear quadratic Gaussian feedback optimal control performance under normal and abnormal operating conditions. Simulation tests are applied with the purpose of validation of the overall controllers’ performance. The results proved the superiority of the planned integration of the wind energy system with the micro-grid.

ACS Style

Ali M. Eltamaly; Ahmed A. Zaki Diab; Ahmed G. Abo-Khalil. Robust Control Based on H∞ and Linear Quadratic Gaussian of Load Frequency Control of Power Systems Integrated with Wind Energy System. Control and Operation of Grid-Connected Wind Energy Systems 2021, 73 -86.

AMA Style

Ali M. Eltamaly, Ahmed A. Zaki Diab, Ahmed G. Abo-Khalil. Robust Control Based on H∞ and Linear Quadratic Gaussian of Load Frequency Control of Power Systems Integrated with Wind Energy System. Control and Operation of Grid-Connected Wind Energy Systems. 2021; ():73-86.

Chicago/Turabian Style

Ali M. Eltamaly; Ahmed A. Zaki Diab; Ahmed G. Abo-Khalil. 2021. "Robust Control Based on H∞ and Linear Quadratic Gaussian of Load Frequency Control of Power Systems Integrated with Wind Energy System." Control and Operation of Grid-Connected Wind Energy Systems , no. : 73-86.

Research article
Published: 20 February 2021 in International Transactions on Electrical Energy Systems
Reads 0
Downloads 0

Partial shading conditions generate multiple peaks in the P‐V curve of photovoltaic (PV) arrays. Smart MPPT optimization techniques should be used to capture the global peak (GP) and avoid being trapped in one of the local peaks (LPs). The tracking of the GP should be fast and reliable to enhance the stability and increase the generated efficiency of the PV systems. Bat algorithm (BA) is one of the fastest swarm optimization techniques. The BA control parameters (BA‐CPs) have substantial effects on their performance. This paper introduced a nested BA strategy called BA‐BA strategy to determine the optimal values of control parameters of BA for the lowest convergence time and failure convergence rate to be used in the online MPPT of PV systems. The inner BA loop used the BA as an MPPT of the PV system, meanwhile, the outer BA loop used the inner BA loop as a fitness function to determine the optimal BA‐CPs for minimum convergence time and failure rate. Ten benchmark BA strategies, particle swarm optimization (PSO), and cuckoo search (CS) algorithm have been used to compare their results with the results obtained from the BA‐BA strategy. The results of the BA‐BA strategy reduced the convergence time of 250% of the time associated with the best benchmark BA strategy, 518%, and 395% as compared to the PSO, and CS algorithm, respectively. The simulation and experimental results obtained from the BA‐BA strategy showed its superior for determining the optimal control parameters for BA in MPPT of PV systems or any other applications.

ACS Style

Ali M. Eltamaly. Optimal control parameters for bat algorithm in maximum power point tracker of photovoltaic energy systems. International Transactions on Electrical Energy Systems 2021, e12839 .

AMA Style

Ali M. Eltamaly. Optimal control parameters for bat algorithm in maximum power point tracker of photovoltaic energy systems. International Transactions on Electrical Energy Systems. 2021; ():e12839.

Chicago/Turabian Style

Ali M. Eltamaly. 2021. "Optimal control parameters for bat algorithm in maximum power point tracker of photovoltaic energy systems." International Transactions on Electrical Energy Systems , no. : e12839.

Journal article
Published: 11 February 2021 in Energies
Reads 0
Downloads 0

The problem of partial shading has serious effects on the performance of photovoltaic (PV) systems. Adding a bypass diode in shunt to each PV module avoids hot-spot phenomena, but causes multi-peaks in the power–voltage (P–V) characteristics of the PV array, which cause traditional maximum power point tracking (MPPT) techniques to become trapped in local peaks. This problem has forced researchers to search for smart techniques to track global peaks and prevent the possibility of convergence at local peaks. Swarm optimization techniques have been used to fill this shortcoming; unfortunately, however, these techniques suffer from unacceptably long convergence time. Cuckoo search (CS) is one of the fastest and most reliable optimization techniques, making it an ideal option to be used as an MPPT of PV systems under dynamic partial shading conditions. The standard CS algorithm has a long conversion time, high failure rate, and high oscillations at steady state; this paper aims to overcome these problems and to fill this research gap by improving the performance of the CS. The results obtained from this technique are compared to five swarm optimization techniques. The comparison study shows the superiority of the improved CS strategy introduced in this paper over the other swarm optimization techniques.

ACS Style

Ali Eltamaly. An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions. Energies 2021, 14, 953 .

AMA Style

Ali Eltamaly. An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions. Energies. 2021; 14 (4):953.

Chicago/Turabian Style

Ali Eltamaly. 2021. "An Improved Cuckoo Search Algorithm for Maximum Power Point Tracking of Photovoltaic Systems under Partial Shading Conditions." Energies 14, no. 4: 953.

Journal article
Published: 20 January 2021 in Membranes
Reads 0
Downloads 0

This work aimed to carry out an optimal investigation of the design and operation of a large capacity reverse osmosis (RO) desalination plant powered by wind energy. Different scenarios involving two design options, such as using storage tanks or batteries, and operation options, such as using variable or fixed feed pressure, were analyzed and optimized. In addition, another operation option, of using a fixed number of RO vessels or a varying number of active RO vessels, was also considered. It was found that an optimized plant using storage tanks can provide a less expensive water cost and a less complicated plant structure. Moreover, the use of a variable feed pressure can help in attenuating the disturbances incurred in the form of wind intermittency. Conversely, the use of fixed feed pressure and constantly supplied power per vessel can run the RO units smoothly, leading to a predictable production rate. However, this requires operating the plant on different active sets of vessels each hour, which mandates additional automatic control systems. The water cost when storage tanks are utilized can be as low as 7.42 $/m3, while it is around 19.7 $/m3 when a battery is used.

ACS Style

Emad Ali; Mourad Bumazza; Ali Eltamaly; Sarwono Mulyono; Muath Yasin. Optimization of Wind Driven RO Plant for Brackish Water Desalination during Wind Speed Fluctuation with and without Battery. Membranes 2021, 11, 77 .

AMA Style

Emad Ali, Mourad Bumazza, Ali Eltamaly, Sarwono Mulyono, Muath Yasin. Optimization of Wind Driven RO Plant for Brackish Water Desalination during Wind Speed Fluctuation with and without Battery. Membranes. 2021; 11 (2):77.

Chicago/Turabian Style

Emad Ali; Mourad Bumazza; Ali Eltamaly; Sarwono Mulyono; Muath Yasin. 2021. "Optimization of Wind Driven RO Plant for Brackish Water Desalination during Wind Speed Fluctuation with and without Battery." Membranes 11, no. 2: 77.

Journal article
Published: 19 January 2021 in Sustainability
Reads 0
Downloads 0

This study introduces a novel strategy that can determine the optimal values of control parameters of a PSO. These optimal control parameters will be very valuable to all the online optimization problems where the convergence time and the failure convergence rate are vital concerns. The newly proposed strategy uses two nested PSO (NESTPSO) searching loops; the inner one contained the original objective function, and the outer one used the inner PSO as a fitness function. The control parameters and the swarm size acted as the optimization variables for the outer loop. These variables were optimized for the lowest premature convergence rate, the lowest number of iterations, and the lowest swarm size. The new proposed strategy can be used for all the swarm optimization techniques as well. The results showed the superiority of the proposed NESTPSO control parameter determination when compared with several state of the art PSO strategies.

ACS Style

Ali Eltamaly. A Novel Strategy for Optimal PSO Control Parameters Determination for PV Energy Systems. Sustainability 2021, 13, 1008 .

AMA Style

Ali Eltamaly. A Novel Strategy for Optimal PSO Control Parameters Determination for PV Energy Systems. Sustainability. 2021; 13 (2):1008.

Chicago/Turabian Style

Ali Eltamaly. 2021. "A Novel Strategy for Optimal PSO Control Parameters Determination for PV Energy Systems." Sustainability 13, no. 2: 1008.

Journal article
Published: 18 January 2021 in IEEE Access
Reads 0
Downloads 0

The sizing problem of the hybrid energy system (HES) is a crucial issue especially in rural communities because any wrong results can mislead the decision makers for building the new HES. Due to the intermittent nature of the renewable energy sources (RES) such as wind and PV, there will be a need for a high storage system and/or a standby diesel engine, which increase the investment, required, and increases the cost of energy (CoE). The use of smart grid concepts like the demand response (DR) using dynamic tariff can improve the system performance, enhance the stability, reduces the size and investments of HES components, reduces the customers’ bills, and increases the energy providers’ profits. The DR strategy will allow the customers to share the responsibility of the HES stability with the energy providers to maintain the stability of the HES. The DR strategies should be selected to ensure the balance between the available RES and the load requirements. In this article, a novel DR strategy is introduced to model the required change in the tariff with the battery state of charge and its charging/discharging power. The novel DR strategy is used in the sizing of the HES based on techno-economic objectives using three different soft computing optimization techniques. This article introduces modeling and simulation of the smart grid integrated with hybrid energy systems to supply a standalone load for a rural site in the north of Saudi Arabia. The sizing of the HES is built based on minimizing the CoE and the loss of load probability. The novel DR strategy introduced in this article reduced the size of the HES compared to the fixed load technique by 20.66%. The results obtained from this novel strategy proved its superiority in the sizing and operation stage of the HES.

ACS Style

Ali M. Eltamaly; Majed A. Alotaibi; Abdulrahman I. Alolah; Mohamed A. Ahmed. A Novel Demand Response Strategy for Sizing of Hybrid Energy System With Smart Grid Concepts. IEEE Access 2021, 9, 20277 -20294.

AMA Style

Ali M. Eltamaly, Majed A. Alotaibi, Abdulrahman I. Alolah, Mohamed A. Ahmed. A Novel Demand Response Strategy for Sizing of Hybrid Energy System With Smart Grid Concepts. IEEE Access. 2021; 9 ():20277-20294.

Chicago/Turabian Style

Ali M. Eltamaly; Majed A. Alotaibi; Abdulrahman I. Alolah; Mohamed A. Ahmed. 2021. "A Novel Demand Response Strategy for Sizing of Hybrid Energy System With Smart Grid Concepts." IEEE Access 9, no. : 20277-20294.

Research article
Published: 16 December 2020 in International Transactions on Electrical Energy Systems
Reads 0
Downloads 0

This paper presents a model reference adaptive system (MRAS) method to estimate the position and speed of permanent magnet synchronous motor (PMSM) by considering the error between real and estimated rotor position values. A state equation of PMSM in synchronous d‐q reference frame is expressed based on the estimated speed and nominal parameter of the PMSM. The derived MRAS adaptation scheme to estimate the rotor position and speed of the main objective is to minimize the errors between the derivatives of d‐q axis currents of the real and model systems. The proposed method has been tested for various speed and load torque conditions. The experimental results show good performance and accurate speed‐tracking capability when it is compared with the sliding mode observer (SMO).

ACS Style

Ahmed G. Abo‐Khalil; Ali M. Eltamaly; Mamdooh S. Alsaud; Khairy Sayed; Ali S. Alghamdi. Sensorless control for PMSM using model reference adaptive system. International Transactions on Electrical Energy Systems 2020, 31, 1 .

AMA Style

Ahmed G. Abo‐Khalil, Ali M. Eltamaly, Mamdooh S. Alsaud, Khairy Sayed, Ali S. Alghamdi. Sensorless control for PMSM using model reference adaptive system. International Transactions on Electrical Energy Systems. 2020; 31 (2):1.

Chicago/Turabian Style

Ahmed G. Abo‐Khalil; Ali M. Eltamaly; Mamdooh S. Alsaud; Khairy Sayed; Ali S. Alghamdi. 2020. "Sensorless control for PMSM using model reference adaptive system." International Transactions on Electrical Energy Systems 31, no. 2: 1.

Original paper
Published: 15 December 2020 in Technology and Economics of Smart Grids and Sustainable Energy
Reads 0
Downloads 0

Worldwide energy consumption is increasing at a faster pace than energy generation because of enhanced industrialization, growing population and, improved living standards. Using the Distributed Generation (DG) near the end consumers can support the electrical grid stability and enhance the power system quality. The DG is consisting of a small-scale technology to generate electrical power near the end consumers, which can be renewable energy or generators. Solar Photovoltaic (PV) system is considered as one of the best renewable energy sources, due to its low running cost and low environmental affection comparing with traditional power plants. The proposed PVDG units are employing maximum power point tracking (MPPT) system to track the maximum power available in PV arrays. The proposed DG system used Particle Swarm Optimization (PSO) technique to optimally allocate the PVDG units for minimum cost, transmission line losses, and improved voltage profile of busbars under different operating conditions. This paper proposes a smart optimization technique employing PSO in the design, operation, and control of the proposed system. Also, the paper discusses the PSO algorithm for optimal DGs sizing and allocations. The simulation in this paper uses the IEEE-7 busbars system with an extension of IEEE-3 busbars as a new remote load. The simulation has been carried out by the power world simulator software to compare the voltage and the power losses with and without PVDGs connected to the system. The simulation results showed an acceptable reduction in generating cost, transmission line losses, and improvement of the busbars voltage profile which proves the success of the proposed system.

ACS Style

Ali M. Eltamaly; Yehia Sayed Mohamed; Abou-Hashema M. El-Sayed; Mohamed A. Mohamed; Amer Nasr A. Elghaffar. Power Quality and Reliability Considerations of Photovoltaic Distributed Generation. Technology and Economics of Smart Grids and Sustainable Energy 2020, 5, 1 -21.

AMA Style

Ali M. Eltamaly, Yehia Sayed Mohamed, Abou-Hashema M. El-Sayed, Mohamed A. Mohamed, Amer Nasr A. Elghaffar. Power Quality and Reliability Considerations of Photovoltaic Distributed Generation. Technology and Economics of Smart Grids and Sustainable Energy. 2020; 5 (1):1-21.

Chicago/Turabian Style

Ali M. Eltamaly; Yehia Sayed Mohamed; Abou-Hashema M. El-Sayed; Mohamed A. Mohamed; Amer Nasr A. Elghaffar. 2020. "Power Quality and Reliability Considerations of Photovoltaic Distributed Generation." Technology and Economics of Smart Grids and Sustainable Energy 5, no. 1: 1-21.

Journal article
Published: 22 October 2020 in Energies
Reads 0
Downloads 0

The grid integration of large scale photovoltaic (PV) power plants represents many challenging tasks for system stability, reliability and power quality due to the intermittent nature of solar radiation and the site accessibility issues where most PV power plants are located over a wide area. In order to enable real-time monitoring and control of large scale PV power plants, reliable two-way communications with low latency are required which provide accurate information for the electrical and environmental parameters as well as enabling the system operator to evaluate the overall performance and identify any abnormal conditions and faults. This work aims to design a communication network architecture for the remote monitoring of large-scale PV power plants based on the IEC 61850 Standard. The proposed architecture consists of three layers: the PV power system layer, the communication network layer, and the application layer. The PV power system layer consists of solar arrays, inverters, feeders, buses, a substation, and a control center. Monitoring parameters are classified into different categories including electrical measurements, status information, and meteorological data. This work considers the future plan of PV power plants in Saudi Arabia. In order to evaluate the performance of the communication network for local and remote monitoring, the OPNET Modeler is used for network modeling and simulation, and critical parameters such as network topology, link capacity, and latency are investigated and discussed. This work contributes to the design of reliable monitoring and communication of large-scale PV power plants.

ACS Style

Ali M. Eltamaly; Mohamed A. Ahmed; Majed A. Alotaibi; Abdulrahman I. Alolah; Young-Chon Kim. Performance of Communication Network for Monitoring Utility Scale Photovoltaic Power Plants. Energies 2020, 13, 5527 .

AMA Style

Ali M. Eltamaly, Mohamed A. Ahmed, Majed A. Alotaibi, Abdulrahman I. Alolah, Young-Chon Kim. Performance of Communication Network for Monitoring Utility Scale Photovoltaic Power Plants. Energies. 2020; 13 (21):5527.

Chicago/Turabian Style

Ali M. Eltamaly; Mohamed A. Ahmed; Majed A. Alotaibi; Abdulrahman I. Alolah; Young-Chon Kim. 2020. "Performance of Communication Network for Monitoring Utility Scale Photovoltaic Power Plants." Energies 13, no. 21: 5527.