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Ahmed G. Abo‐Khalil
Department of Electrical Engineering College of Engineering, Majmaah University Almajmaah Saudi Arabia

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Research article
Published: 19 July 2021 in International Transactions on Electrical Energy Systems
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To carry out the study and simulations of anti-islanding systems, it is necessary to take into account the generic system proposed by the IEEE 929-2000 and IEEE 1547 standards, where the network, the RLC load, and PV inverter are connected in parallel to the PCC. The IEEE 929-2000 standard defines the quality factor to have a standard test condition. The paper presents a modified Active Frequency Drift (AFD) algorithm to detect the islanding of grid-connected photovoltaic (PV) systems with low harmonics levels without degrading their power factor. Severe issues such as deterioration in power quality and electric shock can occur when a PV inverter operates in islanding mode. Various islanding detection techniques have been investigated in the literature in the last two decades among which, AFD is a typical method. However, a prominent drawback of AFD is its relatively large Non-Detection Zone (NDZ). The improved AFD method that this paper suggests allows the frequency of the inverter current to be controlled slightly lower (or higher) than the frequency of the terminal voltage. The islanding condition is detected by calculating the changing parameter that relates to the change of the chopping fraction and the line frequency periodically. The frequency deviation is then detected to determine the chopping and a changing parameter, which accumulates to the threshold value when the inverter is shut down. The proposed algorithm overcomes the conventional AFD issues by improving the accuracy of detection, eliminating the NDZ, and reducing the current harmonic distortion. The proposed method is validated with the help of simulated and experimental results of a 350 W PV inverter using IEEE Standards.

ACS Style

Ahmed G. Abo‐Khalil; Ali M. Eltamaly; Walied Alharbi; Abdel‐Rahman Al‐Qawasmi; Mohammad Alobaid; Ibrahem M. Alarifi. A modified active frequency islanding detection method based on load frequency and chopping fraction changes. International Transactions on Electrical Energy Systems 2021, e13033 .

AMA Style

Ahmed G. Abo‐Khalil, Ali M. Eltamaly, Walied Alharbi, Abdel‐Rahman Al‐Qawasmi, Mohammad Alobaid, Ibrahem M. Alarifi. A modified active frequency islanding detection method based on load frequency and chopping fraction changes. International Transactions on Electrical Energy Systems. 2021; ():e13033.

Chicago/Turabian Style

Ahmed G. Abo‐Khalil; Ali M. Eltamaly; Walied Alharbi; Abdel‐Rahman Al‐Qawasmi; Mohammad Alobaid; Ibrahem M. Alarifi. 2021. "A modified active frequency islanding detection method based on load frequency and chopping fraction changes." International Transactions on Electrical Energy Systems , no. : e13033.

Journal article
Published: 12 June 2021 in Energies
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In this paper, a new multi-port DC-DC power converter used to deal with the intermittent nature and slow response in renewable energy applications is proposed. The proposed converter integrates a DC-DC converter and a DC-AC inverter, and the proposed circuit integrates various renewable energy sources in addition to the energy storage unit. By combining renewable energy sources with a statistical trend to offset each other, the impact of the intermittency can be considerably minimized. This combination increases the overall system reliability and usability. Moreover, integrating such systems with energy storage systems can overcome the slow response issue of renewable sources. It can provide the additional energy required by the load or absorb the extra energy provided by the power sources, which greatly improves the dynamics of the overall system. The proposed converter can reduce the system cost and size and improve the efficiency and reliability. The operation principle is studied in detail, and the design considerations are provided. The proposed architecture and its control strategy were analyzed and studied using the Simulink/MATLAB environment. Finally, the feasibility of the proper operation of the studied converter was experimentally verified based on the results of experimental studies conducted on a 300 W prototype implemented in a laboratory.

ACS Style

Abdulaziz Almutairi; Khairy Sayed; Naif Albagami; Ahmed Abo-Khalil; Hedra Saleeb. Multi-Port PWM DC-DC Power Converter for Renewable Energy Applications. Energies 2021, 14, 3490 .

AMA Style

Abdulaziz Almutairi, Khairy Sayed, Naif Albagami, Ahmed Abo-Khalil, Hedra Saleeb. Multi-Port PWM DC-DC Power Converter for Renewable Energy Applications. Energies. 2021; 14 (12):3490.

Chicago/Turabian Style

Abdulaziz Almutairi; Khairy Sayed; Naif Albagami; Ahmed Abo-Khalil; Hedra Saleeb. 2021. "Multi-Port PWM DC-DC Power Converter for Renewable Energy Applications." Energies 14, no. 12: 3490.

Research article
Published: 10 March 2021 in International Transactions on Electrical Energy Systems
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This paper presents a mathematical modeling and current control of DFIG wind turbine system in the presence of unbalanced and harmonic distortions in the grid voltage. A proportional resonant (PR) current controller is modeled and implemented to reduce the impacts caused by the presence of double‐frequency, fifth and seventh harmonic components in the generator torque, active and reactive power and the grid active power to which the wind generation system is connected. To reduce the impacts of the presence of the harmonics and unbalanced voltage in the stator and grid active and reactive powers, the dq‐axis current components of these harmonics are controlled separately in the rotor and grid side converters. The use of PR controllers represents the addition of a specific function that eliminates the negative sequence and harmonic components from the rotor current components which reduce the oscillations of the generator torque and grid active power. The performance of the proposed control algorithm is validated through experiments and evaluated during the grid disturbances.

ACS Style

Ahmed G. Abo‐Khalil; Walied Alharbi; Abdel‐Rahman Al‐Qawasmi; Mohammad Alobaid; Ibrahim Alarifi. Modeling and control of unbalanced and distorted grid voltage of grid‐connected DFIG wind turbine. International Transactions on Electrical Energy Systems 2021, 31, e12857 .

AMA Style

Ahmed G. Abo‐Khalil, Walied Alharbi, Abdel‐Rahman Al‐Qawasmi, Mohammad Alobaid, Ibrahim Alarifi. Modeling and control of unbalanced and distorted grid voltage of grid‐connected DFIG wind turbine. International Transactions on Electrical Energy Systems. 2021; 31 (5):e12857.

Chicago/Turabian Style

Ahmed G. Abo‐Khalil; Walied Alharbi; Abdel‐Rahman Al‐Qawasmi; Mohammad Alobaid; Ibrahim Alarifi. 2021. "Modeling and control of unbalanced and distorted grid voltage of grid‐connected DFIG wind turbine." International Transactions on Electrical Energy Systems 31, no. 5: e12857.

Chapter
Published: 05 March 2021 in Smart and Sustainable Planning for Cities and Regions
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The conventional control of the voltage source converter (VSC) assumes that the input voltage is balanced. However, unbalanced voltage is a phenomenon that occurs frequently in actual industrial sites. If the grid voltage is unbalanced, THD increases due to voltage negative component, and low harmonic components appear in DC-link voltage, which adversely affects the performance of the converter. Therefore, the purpose of this study is to propose an efficient control method that can solve the problem of the AC-DC converter due to the unbalance of grid voltage. A Multivariable State-Feedback (MSF) current controller is proposed to improve the performance of the VSC under grid voltage disturbances. The control process is carried out by adjusting the extracted positive and negative components of the grid d and q-axis currents. To minimize the DC-link voltage ripple, the reference negative grid currents are obtained from the DC-link voltage controller. However, if the target is to eliminate the imbalance of the grid current, the reference negative currents are set to zero. The experimental results are discussed to validate the proposed controller. The results show that the new MSF controller reduced the DC-link ripple and provides a fast dynamic response during unbalanced grid voltage.

ACS Style

Ahmed G. Abo-Khalil; Ali M. Eltamaly. Voltage Source Converter Control Under Unbalanced Grid Voltage. Smart and Sustainable Planning for Cities and Regions 2021, 57 -72.

AMA Style

Ahmed G. Abo-Khalil, Ali M. Eltamaly. Voltage Source Converter Control Under Unbalanced Grid Voltage. Smart and Sustainable Planning for Cities and Regions. 2021; ():57-72.

Chicago/Turabian Style

Ahmed G. Abo-Khalil; Ali M. Eltamaly. 2021. "Voltage Source Converter Control Under Unbalanced Grid Voltage." Smart and Sustainable Planning for Cities and Regions , no. : 57-72.

Chapter
Published: 05 March 2021 in Smart and Sustainable Planning for Cities and Regions
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The overall efficiency of the DFIG is superior when it is working close to the rated operating point and rated flux level. However, in light loads, optimal efficiency requires operation at a reduced flux level. In this chapter, several algorithms for increasing the steady-state efficiency that integrated with the wind power generation system are proposed. The proposed algorithms are based on the flux-Elevel reduction by calculating the optimum d-axis current and also by estimating the optimum reference rotor d-axis current by using Particle Swarm Optimization- Support Vector Regression (PSO-SVR) algorithm. The PSO is implemented to automatically perform the parameter selection in SVR modeling while the SVR is used to predict the optimum rotor d-axis current corresponding to the minimum total power loss. The input of the SVR is selected to be wind speeds, d-axis current, and generator power loss. The output of the SVR is the reference d-axis current. An experimental setup has been implemented in the laboratory to validate the theoretical development.

ACS Style

Ahmed G. Abo-Khalil; Ali M. Eltamaly; Khairy Sayed. Different Approaches for Efficiency Optimization of DFIG Wind Power Generation Systems. Smart and Sustainable Planning for Cities and Regions 2021, 35 -56.

AMA Style

Ahmed G. Abo-Khalil, Ali M. Eltamaly, Khairy Sayed. Different Approaches for Efficiency Optimization of DFIG Wind Power Generation Systems. Smart and Sustainable Planning for Cities and Regions. 2021; ():35-56.

Chicago/Turabian Style

Ahmed G. Abo-Khalil; Ali M. Eltamaly; Khairy Sayed. 2021. "Different Approaches for Efficiency Optimization of DFIG Wind Power Generation Systems." Smart and Sustainable Planning for Cities and Regions , no. : 35-56.

Journal article
Published: 02 March 2021 in Sustainability
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This work presents an alternative to the conventional photovoltaic maximum power point tracking (MPPT) methods, by using an opposition-based learning firefly algorithm (OFA) that improves the performance of the Photovoltaic (PV) system both in the uniform irradiance changes and in partial shading conditions. The firefly algorithm is based on fireflies’ search for food, according to which individuals emit progressively more intense glows as they approach the objective, attracting the other fireflies. Therefore, the simulation of this behavior can be conducted by solving the objective function that is directly proportional to the distance from the desired result. To implement this algorithm in case of partial shading conditions, it was necessary to adjust the Firefly Algorithm (FA) parameters to fit the MPPT application. These parameters have been extensively tested, converging satisfactorily and guaranteeing to extract the global maximum power point (GMPP) in the cases of normal and partial shading conditions analyzed. The precise adjustment of the coefficients was made possible by visualizing the movement of the particles during the convergence process, while opposition-based learning (OBL) was used with FA to accelerate the convergence process by allowing the particle to move in the opposite direction. The proposed algorithm was simulated in the closest possible way to authentic operating conditions, and variable irradiance and partial shading conditions were implemented experimentally for a 60 [W] PV system. A two-stage PV grid-connected system was designed and deployed to validate the proposed algorithm. In addition, a comparison between the performance of the Perturbation and Observation (P&O) method and the proposed method was carried out to prove the effectiveness of this method over the conventional methods in tracking the GMPP.

ACS Style

Ahmed Abo-Khalil; Walied Alharbi; Abdel-Rahman Al-Qawasmi; Mohammad Alobaid; Ibrahim Alarifi. Maximum Power Point Tracking of PV Systems under Partial Shading Conditions Based on Opposition-Based Learning Firefly Algorithm. Sustainability 2021, 13, 2656 .

AMA Style

Ahmed Abo-Khalil, Walied Alharbi, Abdel-Rahman Al-Qawasmi, Mohammad Alobaid, Ibrahim Alarifi. Maximum Power Point Tracking of PV Systems under Partial Shading Conditions Based on Opposition-Based Learning Firefly Algorithm. Sustainability. 2021; 13 (5):2656.

Chicago/Turabian Style

Ahmed Abo-Khalil; Walied Alharbi; Abdel-Rahman Al-Qawasmi; Mohammad Alobaid; Ibrahim Alarifi. 2021. "Maximum Power Point Tracking of PV Systems under Partial Shading Conditions Based on Opposition-Based Learning Firefly Algorithm." Sustainability 13, no. 5: 2656.

Journal article
Published: 19 February 2021 in Sustainability
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In this paper, an improved Maximum Power Point Tracking (MPPT) algorithm for a tidal power generation system using a Support Vector Regression (SVR) is proposed. To perform this MPPT, a tidal current speed sensor is needed to track the maximum power. The use of these sensors has a lack of reliability, requires maintenance, and has a disadvantage in terms of price. Therefore, there is a need for a sensorless MPPT control algorithm that does not require information on tidal current speed and rotation speed that improves these shortcomings. Sensorless MPPT control methods, such as SVR, enables the maximum power to be output by comparing the relationship between the output power and the rotational speed of the generator. The performance of the SVR is influenced by the selection of its parameters which is optimized during the offline training stage. SVR has a strength and better response than the neural network since it ensures the global minimum and avoids being stuck at local minima. This paper proposes a high-efficiency grid-connected tidal current generation system with a permanent magnet synchronous generator back-to-back converter. The proposed algorithm is verified experimentally and the results confirm the excellent control characteristics of the proposed algorithm.

ACS Style

Ahmed Abo-Khalil; Ali Alghamdi. MPPT of Permanent Magnet Synchronous Generator in Tidal Energy Systems Using Support Vector Regression. Sustainability 2021, 13, 2223 .

AMA Style

Ahmed Abo-Khalil, Ali Alghamdi. MPPT of Permanent Magnet Synchronous Generator in Tidal Energy Systems Using Support Vector Regression. Sustainability. 2021; 13 (4):2223.

Chicago/Turabian Style

Ahmed Abo-Khalil; Ali Alghamdi. 2021. "MPPT of Permanent Magnet Synchronous Generator in Tidal Energy Systems Using Support Vector Regression." Sustainability 13, no. 4: 2223.

Research article
Published: 16 December 2020 in International Transactions on Electrical Energy Systems
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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.

Journal article
Published: 14 December 2020 in Sustainability
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This article focuses on the energy-saving of each driving distance for battery electric vehicle (BEV) applications, by developing a more effective energy management strategy (EMS), under different driving cycles. Fuzzy logic control (FLC) is suggested to control the power management unit (PMU) for the battery management system (BMS) for BEV applications. The adaptive neural fuzzy inference system (ANFIS) is a modeling technique that is mainly based on data. Membership functions and FLC rules can be improved by simply training the ANFIS with real driving cycle data gathered from the MATLAB/SIMULINK program. Then, FLC console blocks are rewritten by enhanced membership functions by ANFIS traineeship. Two different driving cycles are chosen to check the improvement in the efficiency of this proposed system. The suggested control system is validated by simulation and comparison with the traditional proportional-integral (PI) control. The optimized FLC shows better energy-saving.

ACS Style

Khairy Sayed; Ahmed Kassem; Hedra Saleeb; Ali Alghamdi; Ahmed Abo-Khalil. Energy-Saving of Battery Electric Vehicle Powertrain and Efficiency Improvement during Different Standard Driving Cycles. Sustainability 2020, 12, 10466 .

AMA Style

Khairy Sayed, Ahmed Kassem, Hedra Saleeb, Ali Alghamdi, Ahmed Abo-Khalil. Energy-Saving of Battery Electric Vehicle Powertrain and Efficiency Improvement during Different Standard Driving Cycles. Sustainability. 2020; 12 (24):10466.

Chicago/Turabian Style

Khairy Sayed; Ahmed Kassem; Hedra Saleeb; Ali Alghamdi; Ahmed Abo-Khalil. 2020. "Energy-Saving of Battery Electric Vehicle Powertrain and Efficiency Improvement during Different Standard Driving Cycles." Sustainability 12, no. 24: 10466.

Journal article
Published: 10 December 2020 in Sustainability
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The disadvantage of photovoltaic (PV) power generation is that output power decreases due to the presence of clouds or shade. Moreover, it can only be used when the sun is shining. Consequently, there is a need for further active research into the maximum power point tracking (MPPT) technique, which can maximize the power of solar cells. When the solar cell array is partially shaded due to the influence of clouds or buildings, the solar cell characteristic has a number of local maximum power points (LMPPs). Conventional MPPT techniques do not follow the actual maximum power point, namely, the global maximum power point (GMPP), but stay in the LMPP. Therefore, an analysis of the occurrence of multiple LMPPs due to partial shading, as well as a study on the MPPT technique that can trace GMPP, is needed. In order to overcome this obstacle, the grey wolf optimization (GWO) method is proposed in order to track the global maximum power point and to maximize the energy extraction of the PV system. In addition, opposition-based learning is integrated with the GWO to accelerate the MPPT search process and to reduce convergence time. Simultaneously, the DC link voltage is controlled to reduce sudden variations in voltage in the event of transients of solar radiation and/or temperature. Experimental tests are presented to validate the effectiveness of the proposed MPPT method during uniform irradiance and partial shading conditions. The proposed method is compared with the perturbation and observation method.

ACS Style

Abdulaziz Almutairi; Ahmed Abo-Khalil; Khairy Sayed; Naif Albagami. MPPT for a PV Grid-Connected System to Improve Efficiency under Partial Shading Conditions. Sustainability 2020, 12, 10310 .

AMA Style

Abdulaziz Almutairi, Ahmed Abo-Khalil, Khairy Sayed, Naif Albagami. MPPT for a PV Grid-Connected System to Improve Efficiency under Partial Shading Conditions. Sustainability. 2020; 12 (24):10310.

Chicago/Turabian Style

Abdulaziz Almutairi; Ahmed Abo-Khalil; Khairy Sayed; Naif Albagami. 2020. "MPPT for a PV Grid-Connected System to Improve Efficiency under Partial Shading Conditions." Sustainability 12, no. 24: 10310.

Journal article
Published: 14 October 2020 in Sustainability
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Currently, among the topologies of wind energy conversion systems, those based on full power converters are growing. The permanent magnet synchronous generator (PMSG) uses full power converter to allow wide speed ranges to extract the maximum power from the wind. In order to obtain efficient vector control in a synchronous generator with permanent magnets, it is necessary to know the position of the rotor. The PMSGs work over a wide range of speed, and it is mandatory to measure or estimate their speed and position. Usually, the position of the rotor is obtained through Resolver or Encoder. However, the presence of these sensor elements increases the cost, in addition to reducing the system’s reliability. Moreover, in high wind power turbine, the measured wind speed by the anemometer is taken at the level of the blades which makes the measurement of the wind speed at a single point inaccurate. This paper is a study on the sensorless control that removes the rotor position, speed sensors and anemometer from the speed control. The estimation of the rotor position is based on the output of a rotor current controller and the wind speed estimator is based on the opposition-based learning (OBL), particle swarm optimization and support vector regression.

ACS Style

Ahmed Abo-Khalil; Ali Eltamaly; Praveen R.P.; Ali Alghamdi; Iskander Tlili. A Sensorless Wind Speed and Rotor Position Control of PMSG in Wind Power Generation Systems. Sustainability 2020, 12, 8481 .

AMA Style

Ahmed Abo-Khalil, Ali Eltamaly, Praveen R.P., Ali Alghamdi, Iskander Tlili. A Sensorless Wind Speed and Rotor Position Control of PMSG in Wind Power Generation Systems. Sustainability. 2020; 12 (20):8481.

Chicago/Turabian Style

Ahmed Abo-Khalil; Ali Eltamaly; Praveen R.P.; Ali Alghamdi; Iskander Tlili. 2020. "A Sensorless Wind Speed and Rotor Position Control of PMSG in Wind Power Generation Systems." Sustainability 12, no. 20: 8481.

Articles
Published: 16 August 2020 in International Journal of Sustainable Energy
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Salalah is known for its Al-Khareef unique weather that is marked by influx of tourists into the community resulting in high electrical load demand during the Al-Khareef season. This paper investigates the viability of two hybridised energy systems for application in Salalah community. The result demonstrated that the Photovoltaic, Wind and Battery combination is more cost effective in terms of energy consumption, initial cost and renewal price, in comparison to the other hybrid energy system. The Homer Pro software, return on investment and internal rate of return analysis showed that the Photovoltaic/Wind/Battery scheme commands higher economic and environmental viability, presenting the Photovoltaic, Wind and Battery scheme as a better option to meet the power demand for Salalah city.

ACS Style

Paul C. Okonkwo; El Manaa Barhoumi; Srinivasan Murugan; Manaf Zghaibeh; Clement Otor; Ahmed G. Abo-Khalil; Adel Mohamed Amer Mohamed. Economic analysis of cross-breed power arrangement for Salalah region in the Al-Khareef season. International Journal of Sustainable Energy 2020, 40, 188 -206.

AMA Style

Paul C. Okonkwo, El Manaa Barhoumi, Srinivasan Murugan, Manaf Zghaibeh, Clement Otor, Ahmed G. Abo-Khalil, Adel Mohamed Amer Mohamed. Economic analysis of cross-breed power arrangement for Salalah region in the Al-Khareef season. International Journal of Sustainable Energy. 2020; 40 (2):188-206.

Chicago/Turabian Style

Paul C. Okonkwo; El Manaa Barhoumi; Srinivasan Murugan; Manaf Zghaibeh; Clement Otor; Ahmed G. Abo-Khalil; Adel Mohamed Amer Mohamed. 2020. "Economic analysis of cross-breed power arrangement for Salalah region in the Al-Khareef season." International Journal of Sustainable Energy 40, no. 2: 188-206.

Article
Published: 28 May 2020 in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
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Photovoltaic (PV) energy systems are very important electric generation sources in modern power systems. The generated power from the PV array is a function in its terminal voltage. Tracking the maximum power needs a DC/DC converter to control the PV array terminal voltage. The boost converter is used in this paper for this purpose. Due to the multiple peaks in the power versus voltage (P-V) characteristics of PV array a smart optimization technique is required to work as a maximum power point tracker (MPPT). The particle swarm optimization (PSO) is a superior technique to track the global peak (GP) and avoid getting trapped in one of the local peaks (LPs). Despite the superiority of PSO, it suffers from some shortcomings in the application of MPPT of PV systems such as its sluggishness convergence, its inability to catch the new GP in case of acute change in shading pattern, and the possibility of getting trapped in one of the LPs. All these shortcomings are solved in this paper using a new adaptive PSO (NA-PSO) strategy. This new strategy solved these problems by starting the duty ratio at an equal distance between each other and force the particles with lower generated power to work around the one with the highest generated power. This newly proposed technique reduced the convergence time by 50% and reduced the failure rate to zero. Also, the generated energy is increased by 10.4% compared to the conventional PSO. The results collected from the NA-PSO strategy show its superiority in reducing the convergence time and failure rate and increasing the generated power, and the system efficiency, especially in the dynamic variation of the shading pattern compared to the conventional PSO.

ACS Style

Ali M. Eltamaly; Hassan M. H. Farh; Ahmed G. Abokhalil. A novel PSO strategy for improving dynamic change partial shading photovoltaic maximum power point tracker. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 2020, 1 -15.

AMA Style

Ali M. Eltamaly, Hassan M. H. Farh, Ahmed G. Abokhalil. A novel PSO strategy for improving dynamic change partial shading photovoltaic maximum power point tracker. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 2020; ():1-15.

Chicago/Turabian Style

Ali M. Eltamaly; Hassan M. H. Farh; Ahmed G. Abokhalil. 2020. "A novel PSO strategy for improving dynamic change partial shading photovoltaic maximum power point tracker." Energy Sources, Part A: Recovery, Utilization, and Environmental Effects , no. : 1-15.

Journal article
Published: 04 May 2020 in Sustainability
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Since the lifespan of an electrolytic capacitor is relatively short compared to other power semiconductor devices, the failure rate accounts for 60% and, thus, it is the most vulnerable component of the power conversion device. Therefore, the accurate measurement of the lifetime of an electrolytic capacitor is very important in ensuring the reliability of the entire system, including the capacitor. In this paper, an online failure detection method for a DC-link electrolytic capacitor in a back-to-back Pulse width Modulation (PWM) converter using the opposition-based learning particle swarm optimization-based Support Vector Regression (OPSO-SVR) technique is proposed. In this method, the capacitance and the DC-link capacitor power have been used in offline mode for SVR training and testing. During the offline mode, the SVR parameters have been optimized with the OPSO algorithm to use online to estimate the real value of the DC-link capacitor. The experimental results prove the superiority of the proposed technique over the SVR.

ACS Style

Ahmed G. Abo-Khalil; Abdel-Rahman Al-Qawasmi; Ali M. Eltamaly; B. G. Yu. Condition Monitoring of DC-Link Electrolytic Capacitors in PWM Power Converters Using OBL Method. Sustainability 2020, 12, 3719 .

AMA Style

Ahmed G. Abo-Khalil, Abdel-Rahman Al-Qawasmi, Ali M. Eltamaly, B. G. Yu. Condition Monitoring of DC-Link Electrolytic Capacitors in PWM Power Converters Using OBL Method. Sustainability. 2020; 12 (9):3719.

Chicago/Turabian Style

Ahmed G. Abo-Khalil; Abdel-Rahman Al-Qawasmi; Ali M. Eltamaly; B. G. Yu. 2020. "Condition Monitoring of DC-Link Electrolytic Capacitors in PWM Power Converters Using OBL Method." Sustainability 12, no. 9: 3719.

Journal article
Published: 28 April 2020 in Sustainability
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In this paper, a wind speed sensorless control method for doubly-fed induction generator (DFIG) control in wind energy systems is proposed. This method is based on using opposition-based learning (OBL) in optimizing the parameters of the support vector regression (SVR) algorithm. These parameters are tuned by applying particle swarm optimization (PSO) method. As a general rule, wind speed measurements are usually done using an anemometer. The measured wind speed by the anemometer is taken at the level of the blades. In a high-power wind turbine, the blade diameter is very large which makes the measurement of the wind speed at a single point inaccurate. Moreover, using anemometers also increases the maintenance cost, complexity and the system cost. Therefore, estimating the wind speed in variable speed wind power systems gives a precise amount of wind speed which is then used in the generator control. The proposed method uses the generator characteristics in mapping a relationship between the generated power, rotational speed and wind speed. This process is carried on off-line and the relationship is then used online to deduce the wind speed based on the obtained relationship. Using OBL with PSO-SVR to tune the SVR parameters accelerates the process to get the optimum parameters in different wind speeds.

ACS Style

Ali Mohamed Eltamaly; Mamdooh Al-Saud; Khairy Sayed; Ahmed G. Abo-Khalil. Sensorless Active and Reactive Control for DFIG Wind Turbines Using Opposition-Based Learning Technique. Sustainability 2020, 12, 3583 .

AMA Style

Ali Mohamed Eltamaly, Mamdooh Al-Saud, Khairy Sayed, Ahmed G. Abo-Khalil. Sensorless Active and Reactive Control for DFIG Wind Turbines Using Opposition-Based Learning Technique. Sustainability. 2020; 12 (9):3583.

Chicago/Turabian Style

Ali Mohamed Eltamaly; Mamdooh Al-Saud; Khairy Sayed; Ahmed G. Abo-Khalil. 2020. "Sensorless Active and Reactive Control for DFIG Wind Turbines Using Opposition-Based Learning Technique." Sustainability 12, no. 9: 3583.

Journal article
Published: 04 March 2020 in Electronics
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Induction heating (IH) is an environmentally friendly solution for heating and melting processes. The required high-frequency magnetic field is accomplished through frequency controllers. Direct frequency controllers (DFC) are preferred to dual converters as they have low conversion losses, compact size, and simple circuit arrangement due to low component count. Numerous frequency controllers with complex switching algorithms are employed in the induction heating process. They have a complicated circuit arrangement, and complex control as their switching sequences have to synchronize with source voltage that requires the zero-crossing detection of the input voltage. They also have a shoot-through problem and poor power quality. Therefore, this research proposes a novel frequency controller with a low count of six controlled switching devices without a zero-crossing detector (ZCD) having a simple control arrangement. The required switching signals are simply generated by using any pulse-width-modulated (PWM) generator. The performance of the proposed topology is verified through simulation results obtained using the MATLAB/Simulink environment and experimental setup.

ACS Style

Naveed Ashraf; Tahir Izhar; Ghulam Abbas; Ahmed Bilal Awan; Ali S. Alghamdi; Ahmed G. Abo-Khalil; Khairy Sayed; Umar Farooq; Valentina E. Balas. A New Single-Phase Direct Frequency Controller Having Reduced Switching Count without Zero-Crossing Detector for Induction Heating System. Electronics 2020, 9, 430 .

AMA Style

Naveed Ashraf, Tahir Izhar, Ghulam Abbas, Ahmed Bilal Awan, Ali S. Alghamdi, Ahmed G. Abo-Khalil, Khairy Sayed, Umar Farooq, Valentina E. Balas. A New Single-Phase Direct Frequency Controller Having Reduced Switching Count without Zero-Crossing Detector for Induction Heating System. Electronics. 2020; 9 (3):430.

Chicago/Turabian Style

Naveed Ashraf; Tahir Izhar; Ghulam Abbas; Ahmed Bilal Awan; Ali S. Alghamdi; Ahmed G. Abo-Khalil; Khairy Sayed; Umar Farooq; Valentina E. Balas. 2020. "A New Single-Phase Direct Frequency Controller Having Reduced Switching Count without Zero-Crossing Detector for Induction Heating System." Electronics 9, no. 3: 430.

Journal article
Published: 24 February 2020 in IEEE Access
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This paper presents an improved control strategy for a doubly fed induction generator (DFIG) during unbalanced grid voltage conditions. The proposed strategy was applied in both synchronization and grid connected conditions. The synchronization process is carried by controlling the extracted positive and negative sequence components of the stator q-axis voltage to follow the grid q-axis voltage. This strategy can be accomplished by controlling the positive and negative sequence components of rotor d-axis current. By perturbing the rotor d-axis current, the stator EMF builds up and follows the grid voltage accurately. The stator frequency and the phase difference between the stator and grid voltage are compensated by adjusting the stator d-axis positive and negative voltage components to zero. After synchronization, the proposed control strategy focuses on regulating the average stator active and reactive power control by controlling the positive components of q and d-axis currents, respectively. The second target is to minimize the generator torque ripple by controlling the rotor negative sequence components. In the same time, the grid side converter is controlled to minimize the grid power pulsations to reduce the impact of the unbalanced grid voltage. This study focuses in enhancing the dynamics of DFIG during the unbalanced grid voltage by using Multivariable State Feedback (MSF) current controllers. Experiments are carried out to validate the performance improvement by using the proposed method. The simulation and experimental results showed a superior performance of the proposed control strategy.

ACS Style

Ali M. Eltamaly; M. S. Al-Saud; Ahmed G. Abo-Khalil. Dynamic Control of a DFIG Wind Power Generation System to Mitigate Unbalanced Grid Voltage. IEEE Access 2020, 8, 39091 -39103.

AMA Style

Ali M. Eltamaly, M. S. Al-Saud, Ahmed G. Abo-Khalil. Dynamic Control of a DFIG Wind Power Generation System to Mitigate Unbalanced Grid Voltage. IEEE Access. 2020; 8 (99):39091-39103.

Chicago/Turabian Style

Ali M. Eltamaly; M. S. Al-Saud; Ahmed G. Abo-Khalil. 2020. "Dynamic Control of a DFIG Wind Power Generation System to Mitigate Unbalanced Grid Voltage." IEEE Access 8, no. 99: 39091-39103.

Journal article
Published: 06 February 2020 in Sustainability
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Partial shading of PV systems generates many peaks in the P–V curve. These peaks have one global peak (GP), the remaining being local peaks (LPs). Metaheuristic techniques such as PSO have proven superiority in capturing the GP and avoiding entrapment in an LP in comparison to conventional techniques. In case of partial shading conditions (PSC), the GP may change its position and value in the P–V curve and the PSO is unable to capture the GP unless they reinitialize. Reinitialization of PSO particles spends a long time for convergence; and it may cause premature convergence. This paper proposes a novel strategy for scanning the new position of the GP in case of PSC changes without a need for reinitialization. The proposed strategy sends a particle to the anticipated places of peaks to search for any peak with power greater than the current GP and when it locates this new GP it will move the PSO particles directly to the new GP. This strategy reduced the reinitialization time by 650% as compared to the time required for the random reinitialization of the conventional PSO technique. Moreover; this proposed strategy completely avoids the premature convergence associated with conventional PSO techniques.

ACS Style

Ali M. Eltamaly; M. S. Al-Saud; A. G. Abo-Khalil. Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy. Sustainability 2020, 12, 1185 .

AMA Style

Ali M. Eltamaly, M. S. Al-Saud, A. G. Abo-Khalil. Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy. Sustainability. 2020; 12 (3):1185.

Chicago/Turabian Style

Ali M. Eltamaly; M. S. Al-Saud; A. G. Abo-Khalil. 2020. "Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy." Sustainability 12, no. 3: 1185.

Journal article
Published: 08 January 2020 in IEEE Access
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Power versus voltage curves of partial shading photovoltaic (PV) systems contain several local peaks (LPs) and one global peak (GP). Most conventional maximum power point tracker (MPPT) techniques may not follow the GP under partial shading conditions (PSC). The use of metaheuristic techniques such as the bat algorithm (BA) and particle swarm optimization (PSO) can overcome these obstacles. All problems inherent in the using of BA as MPPT of PV systems has been discussed and solved in this paper. The first problem is the random initial values of bats that may cause premature convergence. Therefore, the initial values of bats were modified to be close to the anticipated positions of peaks to reduce the convergence time and improve the chance of capturing the GP. The second problem occurs when shading pattern changes the value and position of the GP which is not configurable because all bats are concentrated at the previous GP; this can be resolved by BA re-initialization. The the third problem is the GP memorized in the execution of the BA code forces the PV system to work at the duty ratio of the highest GP ever seen, which may not be the real GP. This problem is solved by updating the memorized GP. This paper also proposes a new criterion for selecting the optimal swarm size against number of peaks to reduce the convergence time and improve the chance of capturing the GP. To the authors’ knowledge, most of these problems inherent in the BA have hitherto not been addressed in the literature. The simulation and experimental results obtained from the proposed modified BA (MBA) with re-initialization have been compared to the PSO and grey wolf optimization (GWO) techniques which show the superiority of using MBA strategy in the MPPT of partial shading PV systems.

ACS Style

Ali M. Eltamaly; M. S. Al-Saud; Ahmed G. Abokhalil. A Novel Bat Algorithm Strategy for Maximum Power Point Tracker of Photovoltaic Energy Systems Under Dynamic Partial Shading. IEEE Access 2020, 8, 10048 -10060.

AMA Style

Ali M. Eltamaly, M. S. Al-Saud, Ahmed G. Abokhalil. A Novel Bat Algorithm Strategy for Maximum Power Point Tracker of Photovoltaic Energy Systems Under Dynamic Partial Shading. IEEE Access. 2020; 8 (99):10048-10060.

Chicago/Turabian Style

Ali M. Eltamaly; M. S. Al-Saud; Ahmed G. Abokhalil. 2020. "A Novel Bat Algorithm Strategy for Maximum Power Point Tracker of Photovoltaic Energy Systems Under Dynamic Partial Shading." IEEE Access 8, no. 99: 10048-10060.

Journal article
Published: 07 November 2019 in Energies
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This paper introduces an energy management and control method for DC microgrid supplying electric vehicles (EV) charging station. An Energy Management System (EMS) is developed to manage and control power flow from renewable energy sources to EVs through DC microgrid. An integrated approach for controlling DC microgrid based charging station powered by intermittent renewable energies. A wind turbine (WT) and solar photovoltaic (PV) arrays are integrated into the studied DC microgrid to replace energy from fossil fuel and decrease pollution from carbon emissions. Due to the intermittency of solar and wind generation, the output powers of PV and WT are not guaranteed. For this reason, the capacities of WT, solar PV panels, and the battery system are considered decision parameters to be optimized. The optimized design of the renewable energy system is done to ensure sufficient electricity supply to the EV charging station. Moreover, various renewable energy technologies for supplying EV charging stations to improve their performance are investigated. To evaluate the performance of the used control strategies, simulation is carried out in MATLAB/SIMULINK.

ACS Style

Khairy Sayed; Ahmed G. Abo-Khalil; Ali S. Alghamdi. Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources. Energies 2019, 12, 4240 .

AMA Style

Khairy Sayed, Ahmed G. Abo-Khalil, Ali S. Alghamdi. Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources. Energies. 2019; 12 (22):4240.

Chicago/Turabian Style

Khairy Sayed; Ahmed G. Abo-Khalil; Ali S. Alghamdi. 2019. "Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources." Energies 12, no. 22: 4240.