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Nature-inspired metaheuristic optimization algorithms, e.g., the butterfly optimization algorithm (BOA), have become increasingly popular. The BOA, which adapts the food foraging and social behaviors of butterflies, involves randomly defined, algorithmic-dependent parameters that affect the exploration and exploitation strategies, which negatively influences the overall performance of the algorithm. To address this issue and improve performance, this paper proposes a modified BOA, i.e., the quantum chaos BOA (QCBOA), that relies on chaos theory and quantum computing techniques. Chaos mapping of unpredictable and divergent behavior helps tune critical parameters, and the quantum wave concept helps the representative butterflies in the algorithm explore the search space more effectively. The proposed QCBOA also implements a ranking strategy to maintain balance between the exploration and exploitation phases, which is lacking in conventional BOAs. To evaluate reliability and efficiency, the proposed QCBOA is tested against a well-utilized set of 20 benchmark functions and travelling salesman problem which belongs to the class of combinatorial optimization problems. Besides, the proposed method is also adopted to photovoltaic system parameter extraction to demonstrate its application to real-word problems. An extensive comparative study was also conducted to compare the performance of QCBOA with that of the conventional BOAs, fine-tuned particle swarm optimization (PSO) algorithm, differential evolution (DE), and genetic algorithm (GA). The results demonstrate that, chaos functions with the quantum wave concept yield better performance for most tested cases and comparative results in the rest of the cases. The speed of convergence also increased compared to the conventional BOAs. The proposed QCBOA is expected to provide better results in other real-word optimization problems and benchmark functions.
Achikkulath Prasanthi; Hussain Shareef; Rachid Errouissi; Madathodika Asna; Addy Wahyudie. Quantum Chaotic Butterfly Optimization Algorithm With Ranking Strategy for Constrained Optimization Problems. IEEE Access 2021, 9, 114587 -114608.
AMA StyleAchikkulath Prasanthi, Hussain Shareef, Rachid Errouissi, Madathodika Asna, Addy Wahyudie. Quantum Chaotic Butterfly Optimization Algorithm With Ranking Strategy for Constrained Optimization Problems. IEEE Access. 2021; 9 ():114587-114608.
Chicago/Turabian StyleAchikkulath Prasanthi; Hussain Shareef; Rachid Errouissi; Madathodika Asna; Addy Wahyudie. 2021. "Quantum Chaotic Butterfly Optimization Algorithm With Ranking Strategy for Constrained Optimization Problems." IEEE Access 9, no. : 114587-114608.
This paper presents the design methodology of an alternative approach for implementing proportional-resonant (PR) controller for single-phase grid-tied inverter. The developed PR controller is designed to regulate the grid current with the aim of controlling either the DC-link voltage or the active/reactive power injected into the grid. The control design is based on combining a state feedback controller with a disturbance observer. It turns out that the composite controller can be expressed as a PR controller plus an anti-windup scheme. The latter is required by the resonant portion of the PR controller to attenuate the effect of the control input saturation during transients. On the other hand, when the voltage harmonics are taken into account in the observer design, the composite controller reduces to multiple resonant controllers with an anti-windup scheme. The performance of the existing PR controller was investigated under control saturation to highlight the poor transient performances associated with modulating signal limitation. Experimental tests have been conducted to verify the the performance of the proposed controller. The obtained results demonstrated good transient performances compared with the existing PR controller, particularly during control saturation. Furthermore, performance results under voltage harmonics showed that the proposed controller can achieve accurate control of the current with low THD values.
Rachid Errouissi; Hussain Shareef; Addy Wahyudie. A Novel Design of PR Controller With Antiwindup Scheme for Single-Phase Interconnected PV Systems. IEEE Transactions on Industry Applications 2021, 57, 5461 -5475.
AMA StyleRachid Errouissi, Hussain Shareef, Addy Wahyudie. A Novel Design of PR Controller With Antiwindup Scheme for Single-Phase Interconnected PV Systems. IEEE Transactions on Industry Applications. 2021; 57 (5):5461-5475.
Chicago/Turabian StyleRachid Errouissi; Hussain Shareef; Addy Wahyudie. 2021. "A Novel Design of PR Controller With Antiwindup Scheme for Single-Phase Interconnected PV Systems." IEEE Transactions on Industry Applications 57, no. 5: 5461-5475.
Distributed Generation (DG) integration, especially based on renewable energy resources, has gained great attention by power utilities and frequently utilized in the electrical distribution systems. However, DG integration imposes some risks towards system stability which may lead to system blackouts. This mainly occurs when the grid is decoupled from a portion of the distribution system consisting DGs while the total load demand is greater than total DGs output power. In order to overcome this problem, load shedding technique can be adopted to stabilize the system frequency. However, existing load shedding techniques were unable to accurately estimate the power imbalance due the variation in system loading. This results in excessive/inadequate load shedding to stabilize the system frequency. Moreover, random selection of the loads without load prioritization might cause vital loads to be shed. Therefore, in this paper, a new load shedding strategy for islanded distribution system is proposed. Polynomial regression analysis estimates the power mismatch while MILP optimization estimates optimal load combination for shedding. Furthermore, load priority (i.e., vital, non-vital, and semi-vital) is also considered to avoid disconnecting vital loads. Efficiency of the proposed scheme is evaluated on three different test systems. Validation is performed by modelling the proposed load shedding on PSCAD/EMTDC software for dynamic analysis. From the results, it can be analyzed that the proposed technique is superior compared to other techniques proposed in the literature.
Sohail Sarwar; Hazlie Mokhlis; Mohamadariff Othman; Hussain Shareef; Li Wang; Nurulafiqah Nadzirah Mansor; Anis Salwa Mohd Khairuddin; Hasmaini Mohamad. Application of polynomial regression and MILP for under-frequency load shedding scheme in islanded distribution system. Alexandria Engineering Journal 2021, 1 .
AMA StyleSohail Sarwar, Hazlie Mokhlis, Mohamadariff Othman, Hussain Shareef, Li Wang, Nurulafiqah Nadzirah Mansor, Anis Salwa Mohd Khairuddin, Hasmaini Mohamad. Application of polynomial regression and MILP for under-frequency load shedding scheme in islanded distribution system. Alexandria Engineering Journal. 2021; ():1.
Chicago/Turabian StyleSohail Sarwar; Hazlie Mokhlis; Mohamadariff Othman; Hussain Shareef; Li Wang; Nurulafiqah Nadzirah Mansor; Anis Salwa Mohd Khairuddin; Hasmaini Mohamad. 2021. "Application of polynomial regression and MILP for under-frequency load shedding scheme in islanded distribution system." Alexandria Engineering Journal , no. : 1.
This paper proposes an optimal hybrid energy sources sizing methodology for hybrid electric vehicles comprising ultracapacitor (UC) and fuel cell (FC) with battery units (BU). For this purpose, a multi objective problem is formulated using dynamic-source models to evaluate the system’s initial cost, weight, running cost, and cost associated with source degradation. Furthermore, a novel adaptive energy management strategy (AEMS) that focuses on dynamic-source characteristics and drive cycle power demand is proposed as an integral part of the optimization problem. Finally, to solve the hybrid energy source optimization problem, the butterfly optimization algorithm (BOA) is improved by employing the quantum wave concept to explore the search space more effectively. The performance of the proposed method is evaluated with different hybrid source configurations and various drive cycles using improved BOA, BOA and particle swarm optimization. The Matlab® simulation results show that battery rating can be downsized by approximately 40% upon the inclusion of UC and FC units using improved BOA. Furthermore, when the proposed AEMS is compared with a conventional discrete wavelet transform power-splitting approach used in the optimization process, the proposed AEMS performs better and could reduce the system relative cost and weight for BU-UC-FC configuration by 16% and 10% respectively.
Achikkulath Prasanthi; Hussain Shareef; Madathodika Asna; Ahmad Asrul Ibrahim; Rachid Errouissi. Optimization of hybrid energy systems and adaptive energy management for hybrid electric vehicles. Energy Conversion and Management 2021, 243, 114357 .
AMA StyleAchikkulath Prasanthi, Hussain Shareef, Madathodika Asna, Ahmad Asrul Ibrahim, Rachid Errouissi. Optimization of hybrid energy systems and adaptive energy management for hybrid electric vehicles. Energy Conversion and Management. 2021; 243 ():114357.
Chicago/Turabian StyleAchikkulath Prasanthi; Hussain Shareef; Madathodika Asna; Ahmad Asrul Ibrahim; Rachid Errouissi. 2021. "Optimization of hybrid energy systems and adaptive energy management for hybrid electric vehicles." Energy Conversion and Management 243, no. : 114357.
This paper presents the design and performance evaluation of disturbance observer-based control for grid-tied inverter with LCL filter. The proposed controller consists of a combination of a state feedback control with disturbance observer. Specifically, the composite controller is developed to regulate the current injected to the grid despite the variation in system parameters. Such variations are compensated for by the disturbance observer, while the state feedback control takes on the responsibility to ensure the stability of the closed-loop system. The developed controller is designed in the stationary frame to cope with both balanced and unbalanced grid voltages. This mandates using a disturbance observer that has a resonant action property to compensate for sinusoidal disturbances with a view to ensure asymptotic tracking of sinusoidal current reference. However, under control saturation, the resonator buildup can cause the transient response to deteriorate by exhibiting a large overshoot. This problem is tackled by considering control saturation in the design process. As a result, an anti-windup compensator arises naturally in the composite controller. Experimental tests were conducted to evaluate the performance of the controller under different operating conditions. The obtained results show that the proposed controller is capable of achieving a perfect tracking of sinusoidal reference with a good transient response during both balanced and unbalanced grid voltages. Moreover, it was demonstrated that, without the anti-windup scheme, the percentage overshoot under the composite controller can reach 95% during control saturation, while the proposed anti-windup scheme improved the transient response by eliminating the overshoot.
Rachid Errouissi; Hussain Shareef; Falah Awwad. Disturbance Observer-Based Control for Three-Phase Grid-Tied Inverter With LCL Filter. IEEE Transactions on Industry Applications 2021, 57, 5411 -5424.
AMA StyleRachid Errouissi, Hussain Shareef, Falah Awwad. Disturbance Observer-Based Control for Three-Phase Grid-Tied Inverter With LCL Filter. IEEE Transactions on Industry Applications. 2021; 57 (5):5411-5424.
Chicago/Turabian StyleRachid Errouissi; Hussain Shareef; Falah Awwad. 2021. "Disturbance Observer-Based Control for Three-Phase Grid-Tied Inverter With LCL Filter." IEEE Transactions on Industry Applications 57, no. 5: 5411-5424.
For the large-scale promotion of electric vehicles (EV), reliable fast-charging stations (FCS) demand high priority among EV users. However, unplanned locations of charging stations (CSs) and station capacity determination have adverse effects on the operation and the performance of power-distribution network. In this study, we developed an optimal FCS-planning model considering the aspects of EV users’ convenience, station economic benefits, the impact on distribution systems and the effect on environment. A queuing-theory-based CS sizing algorithm that benefits EV users as well as improves CS capacity utilization was proposed. The proposed planning model was verified through a case study using real road network data by employing multi-objective binary and non-dominated sorting genetic algorithm. In addition, to evaluate the efficiency of the proposed sizing algorithm, sensitivity analyses for different EV penetration levels and station utilization were conducted. The simulation results show that the proposed CS-allocation model is beneficial in terms of achieving the satisfaction of EV users, cost savings, better station utilization, and less impact on power grids and the environment. Finally, to validate the effectiveness of the proposed planning model, a comparative study with one of the previous work on CS planning is also performed. The results demonstrate that the proposed charging station sizing method is highly efficient in optimizing EV users’ satisfaction and for better station utilization.
Madathodika Asna; Hussain Shareef; Prasanthi Achikkulath; Hazlie Mokhlis; Rachid Errouissi; Addy Wahyudie. Analysis of an Optimal Planning Model for Electric Vehicle Fast-Charging Stations in Al Ain City, United Arab Emirates. IEEE Access 2021, 9, 73678 -73694.
AMA StyleMadathodika Asna, Hussain Shareef, Prasanthi Achikkulath, Hazlie Mokhlis, Rachid Errouissi, Addy Wahyudie. Analysis of an Optimal Planning Model for Electric Vehicle Fast-Charging Stations in Al Ain City, United Arab Emirates. IEEE Access. 2021; 9 ():73678-73694.
Chicago/Turabian StyleMadathodika Asna; Hussain Shareef; Prasanthi Achikkulath; Hazlie Mokhlis; Rachid Errouissi; Addy Wahyudie. 2021. "Analysis of an Optimal Planning Model for Electric Vehicle Fast-Charging Stations in Al Ain City, United Arab Emirates." IEEE Access 9, no. : 73678-73694.
This paper proposes a simplified proton-exchange membrane fuel cell (PEMFC) temperature model for the purpose of estimating PEMFC temperatures with high accuracy using air-cooling systems. Besides knowing that most of the existing models were designed for specific systems, the proposed model also focuses on generalizing the conventional temperature model for easy adoption by other PEMFCs. The proposed model is developed based on the first-order exponential equation to avoid the limitations of complex mechanistic temperature models. The model uses only the information available from typical commercial PEMFCs, the main inputs of which are the current, elapsed time, and ambient temperature. In addition, the PEMFC area, number of cells in the stack, and high/low operating currents were incorporated in the proposed model to ensure its generalizability and applicability to different PEMFC technologies with air-cooling systems under various ambient conditions. The required model parameters were optimized using the Harris hawks optimization method. The proposed model was validated using experiments conducted on the Horizon-500 W and NEXA-1.2 kW PEMFC systems equipped with air-cooling mechanisms under different ambient temperatures and load currents. The root mean square error of all the examined cases was less than 0.5. The proposed model is helpful for simulations, dynamic real-time controllers, and emulators because of its fast response and high accuracy.
Saad Saleem Khan; Hussain Shareef; Mohsen Kandidayeni; Loïc Boulon; Irfan Ahmad Khan; Faisal Yamin; K.S. Phani Kiranmai. Simple temperature modeling of proton exchange membrane fuel cell using load current and ambient temperature variations. International Journal of Green Energy 2021, 18, 1352 -1368.
AMA StyleSaad Saleem Khan, Hussain Shareef, Mohsen Kandidayeni, Loïc Boulon, Irfan Ahmad Khan, Faisal Yamin, K.S. Phani Kiranmai. Simple temperature modeling of proton exchange membrane fuel cell using load current and ambient temperature variations. International Journal of Green Energy. 2021; 18 (13):1352-1368.
Chicago/Turabian StyleSaad Saleem Khan; Hussain Shareef; Mohsen Kandidayeni; Loïc Boulon; Irfan Ahmad Khan; Faisal Yamin; K.S. Phani Kiranmai. 2021. "Simple temperature modeling of proton exchange membrane fuel cell using load current and ambient temperature variations." International Journal of Green Energy 18, no. 13: 1352-1368.
Hourly global solar irradiance (GSR) data are required for sizing, planning, and modeling of solar photovoltaic farms. However, operating and controlling such farms exposed to varying environmental conditions, such as fast passing clouds, necessitates GSR data to be available for very short time intervals. Classical backpropagation neural networks do not perform satisfactorily when predicting parameters within short intervals. This paper proposes a hybrid backpropagation neural networks based on particle swarm optimization. The particle swarm algorithm is used as an optimization algorithm within the backpropagation neural networks to optimize the number of hidden layers and neurons used and its learning rate. The proposed model can be used as a reliable model in predicting changes in the solar irradiance during short time interval in tropical regions such as Malaysia and other regions. Actual global solar irradiance data of 5-s and 1-min intervals, recorded by weather stations, are applied to train and test the proposed algorithm. Moreover, to ensure the adaptability and robustness of the proposed technique, two different cases are evaluated using 1-day and 3-days profiles, for two different time intervals of 1-min and 5-s each. A set of statistical error indices have been introduced to evaluate the performance of the proposed algorithm. From the results obtained, the 3-days profile’s performance evaluation of the BPNN-PSO are 1.7078 of RMSE, 0.7537 of MAE, 0.0292 of MSE, and 31.4348 of MAPE (%), at 5-s time interval, where the obtained results of 1-min interval are 0.6566 of RMSE, 0.2754 of MAE, 0.0043 of MSE, and 1.4732 of MAPE (%). The results revealed that proposed model outperformed the standalone backpropagation neural networks method in predicting global solar irradiance values for extremely short-time intervals. In addition to that, the proposed model exhibited high level of predictability compared to other existing models.
Ahmed Aljanad; Nadia Tan; Vassilios Agelidis; Hussain Shareef. Neural Network Approach for Global Solar Irradiance Prediction at Extremely Short-Time-Intervals Using Particle Swarm Optimization Algorithm. Energies 2021, 14, 1213 .
AMA StyleAhmed Aljanad, Nadia Tan, Vassilios Agelidis, Hussain Shareef. Neural Network Approach for Global Solar Irradiance Prediction at Extremely Short-Time-Intervals Using Particle Swarm Optimization Algorithm. Energies. 2021; 14 (4):1213.
Chicago/Turabian StyleAhmed Aljanad; Nadia Tan; Vassilios Agelidis; Hussain Shareef. 2021. "Neural Network Approach for Global Solar Irradiance Prediction at Extremely Short-Time-Intervals Using Particle Swarm Optimization Algorithm." Energies 14, no. 4: 1213.
This article introduces a dynamic semiempirical model that predicts the degradation of a proton exchange membrane fuel cell (PEMFC) by introducing time-based terms in the model. The concentration voltage drop is calculated using a new statistical equation based on the load current and working time, whereas the ohmic and activation voltage drops are updated using time-based equations borrowed from the existing literature. Furthermore, the developed model calculates the membrane water content in the PEMFC, which indicates the membrane hydration state and indirectly diagnoses the flooding and drying faults. Moreover, the model parameters are optimized using a recently developed butterfly optimization algorithm. The model is simple and has a short runtime; therefore, it is suitable for monitoring. Voltage degradation under various loading currents was observed for long working hours. The obtained results indicate a significant degradation in PEMFC performance. Therefore, the proposed model is also useful for prognostics and fault diagnosis.
Saad Saleem Khan; Hussain Shareef; Mohsen Kandidayeni; Loic Boulon; Abbou Amine; El Hasnaoui Abdennebi. Dynamic Semiempirical PEMFC Model for Prognostics and Fault Diagnosis. IEEE Access 2021, 9, 10217 -10227.
AMA StyleSaad Saleem Khan, Hussain Shareef, Mohsen Kandidayeni, Loic Boulon, Abbou Amine, El Hasnaoui Abdennebi. Dynamic Semiempirical PEMFC Model for Prognostics and Fault Diagnosis. IEEE Access. 2021; 9 ():10217-10227.
Chicago/Turabian StyleSaad Saleem Khan; Hussain Shareef; Mohsen Kandidayeni; Loic Boulon; Abbou Amine; El Hasnaoui Abdennebi. 2021. "Dynamic Semiempirical PEMFC Model for Prognostics and Fault Diagnosis." IEEE Access 9, no. : 10217-10227.
This paper proposes a technique to determine the possible optimal placement of the phasor measurement unit (PMU) in power grids for normal operating conditions. All possible combinations of PMU placement, including infeasible combinations, are typically considered in finding the optimal solution, which could be a massive search space. An integer search algorithm called the bounded search technique is introduced to reduce the search space in solving a minimum number of PMU allocations whilst maintaining full system observability. The proposed technique is based on connectivity and symmetry constraints that can be derived from the observability matrix. As the technique is coupled with the exhaustive technique, the technique is called the bounded exhaustive search (BES) technique. Several IEEE test systems, namely, IEEE 9-bus, IEEE 14-bus, IEEE 24-bus and IEEE 30-bus, are considered to showcase the performance of the proposed technique. An initial Monte Carlo simulation was carried out to evaluate the capability of the bounded search technique in providing a smaller feasible search space. The effectiveness of the BES technique in terms of computational time is compared with the existing exhaustive technique. Results demonstrate that the search space can be reduced tremendously, and the computational burden can be eased, when finding the optimal PMU placement in power grids.
Ahmad Asrul Ibrahim; Khairuddin Khalid; Hussain Shareef; Nor Azwan Mohamed Kamari. A Bounded Exhaustive Search Technique for Optimal Phasor Measurement Unit Placement in Power Grids. Symmetry 2020, 12, 2021 .
AMA StyleAhmad Asrul Ibrahim, Khairuddin Khalid, Hussain Shareef, Nor Azwan Mohamed Kamari. A Bounded Exhaustive Search Technique for Optimal Phasor Measurement Unit Placement in Power Grids. Symmetry. 2020; 12 (12):2021.
Chicago/Turabian StyleAhmad Asrul Ibrahim; Khairuddin Khalid; Hussain Shareef; Nor Azwan Mohamed Kamari. 2020. "A Bounded Exhaustive Search Technique for Optimal Phasor Measurement Unit Placement in Power Grids." Symmetry 12, no. 12: 2021.
Despite the increasing utilization of renewable energy resources, such as solar and wind energy, most residential buildings still rely on conventional energy supply by public utility services. Such utility services often use time-of-use energy pricing, which compels residential consumers to reduce their energy usage. This paper presents a wireless home energy management (HEM) system that enables the automatic control of home appliances to reduce energy consumption to assist such energy users. The system consists of multiple smart sockets that measure the energy that is consumed by the connected appliances and are capable of implementing on/off commands. The system includes other support components for supplying data to a central controller, which utilizes a rule-based HEM algorithm. The control rules were designed, such that the lifestyle of the user would be preserved while the energy consumption and daily energy cost were reduced. The experimental results showed that the central controller could effectively receive data and control multiple devices. The system was also found to afford significant reductions of 23.5 kWh and $2.898 in the total daily energy consumption and bill of the considered household setup, respectively. The proposed HEM system promises to be particularly useful for households with a high daily energy consumption.
Hussain Shareef; Eslam Al-Hassan; Reza Sirjani. Wireless Home Energy Management System with Smart Rule-Based Controller. Applied Sciences 2020, 10, 4533 .
AMA StyleHussain Shareef, Eslam Al-Hassan, Reza Sirjani. Wireless Home Energy Management System with Smart Rule-Based Controller. Applied Sciences. 2020; 10 (13):4533.
Chicago/Turabian StyleHussain Shareef; Eslam Al-Hassan; Reza Sirjani. 2020. "Wireless Home Energy Management System with Smart Rule-Based Controller." Applied Sciences 10, no. 13: 4533.
An assessment of the wave power at the southern coast of the middle part of Java Island (Indonesia) was conducted based on a 15-year hindcast spectral wave model using the MIKE 21 Spectral Wave software. The model was forced with wind data with a 0.125° spatial interval and hourly time resolution. The obtained model was validated with field data collected from a buoy station that provided a set of significant wave height data with an hourly data interval for the whole month of June 2014. The validation showed that the obtained model matched the observed data with a minor average error. A spatial analysis was conducted in order to find the most suitable location for installing wave energy converters while taking into consideration the potential area demand, the wave power intensity, and the distance from the shore. Moreover, spatial analysis is conducted in order to find a suitable location to install wave energy converters, with consideration to potential area demand, wave power intensity, and distance from the shore. The best prospective location reached 30 kW/m of mean wave power intensity, 2.04 m of mean significant wave height, 8.9 s of mean wave period, 150 m of distance from the shoreline.
Addy Wahyudie; Tri Bagus Susilo; Fatima Alaryani; Cuk Supriyadi Ali Nandar; Mohammed Abdi Jama; Abdulrahman Daher; Hussain Shareef. Wave Power Assessment in the Middle Part of the Southern Coast of Java Island. Energies 2020, 13, 2633 .
AMA StyleAddy Wahyudie, Tri Bagus Susilo, Fatima Alaryani, Cuk Supriyadi Ali Nandar, Mohammed Abdi Jama, Abdulrahman Daher, Hussain Shareef. Wave Power Assessment in the Middle Part of the Southern Coast of Java Island. Energies. 2020; 13 (10):2633.
Chicago/Turabian StyleAddy Wahyudie; Tri Bagus Susilo; Fatima Alaryani; Cuk Supriyadi Ali Nandar; Mohammed Abdi Jama; Abdulrahman Daher; Hussain Shareef. 2020. "Wave Power Assessment in the Middle Part of the Southern Coast of Java Island." Energies 13, no. 10: 2633.
Recently, many new nature-inspired optimization algorithms have been introduced to further enhance the computational intelligence optimization algorithms. Among them, lightning search algorithm(LSA) is a recent heuristic optimization method for resolving continuous problems. It mimics the natural phenomenon of lightning to find out the global optimal solution around the search space. In this paper, a suitable technique to formulate binary version of lightning search algorithm(BLSA) is presented. Three common probability transfer functions, namely, logistic sigmoid, tangent hyperbolic sigmoid and quantum bit rotating gate are investigated to be utilized in the original LSA. The performances of three transfer functions based BLSA is evaluated using various standard functions with different features and the results are compared with other four famous heuristic optimization techniques. The comparative study clearly reveals that tangent hyperbolic transfer function is the most suitable function that can be utilized in the binary version of LSA.
Mainul Islam; Hussain Shareef; Mahmood Nagrial; Jamal Rizk; Ali Hellany; Saiful Nizam Khalid. Performance comparison of various probability gate assisted binary lightning search algorithm. IAES International Journal of Artificial Intelligence (IJ-AI) 2019, 8, 299 -306.
AMA StyleMainul Islam, Hussain Shareef, Mahmood Nagrial, Jamal Rizk, Ali Hellany, Saiful Nizam Khalid. Performance comparison of various probability gate assisted binary lightning search algorithm. IAES International Journal of Artificial Intelligence (IJ-AI). 2019; 8 (3):299-306.
Chicago/Turabian StyleMainul Islam; Hussain Shareef; Mahmood Nagrial; Jamal Rizk; Ali Hellany; Saiful Nizam Khalid. 2019. "Performance comparison of various probability gate assisted binary lightning search algorithm." IAES International Journal of Artificial Intelligence (IJ-AI) 8, no. 3: 299-306.
A novel power converter that can perform both voltage and frequency conversion was proposed. Inappropriate power supply can damage sensitive sub-components and render the connected device inoperable. Henceforth, the proposed voltage–frequency converter acts as an interface to plug any electrical device directly into an electrical socket and provide the voltage and frequency required. The converter used a synchronous reference frame proportional–integral (SRFPI) controller to regulate the instantaneous output voltage and to improve steady state performance. Because the PI controller works together with the synchronous reference frame controller, it is difficult to tune the PI control parameters. To overcome this issue, a new meta heuristic optimization technique called lightening search algorithm (LSA) optimization was used to identify the optimum PI parameter values. A detailed description of the system operation and control strategy was presented. Finally, the performance of the converter was analyzed and verified by simulation and experimental results. The experimental result has shown that the proposed system has satisfactory output voltage and frequency under different input voltages.
M. Asna; H. Shareef; S. N. Khalid; A. O. Idris; A. N. Aldarmaki; Basil Hamed. Universal power converter for low power applications. International Journal of Power Electronics and Drive Systems (IJPEDS) 2019, 10, 2165 -2172.
AMA StyleM. Asna, H. Shareef, S. N. Khalid, A. O. Idris, A. N. Aldarmaki, Basil Hamed. Universal power converter for low power applications. International Journal of Power Electronics and Drive Systems (IJPEDS). 2019; 10 (4):2165-2172.
Chicago/Turabian StyleM. Asna; H. Shareef; S. N. Khalid; A. O. Idris; A. N. Aldarmaki; Basil Hamed. 2019. "Universal power converter for low power applications." International Journal of Power Electronics and Drive Systems (IJPEDS) 10, no. 4: 2165-2172.
Proton‐exchange‐membrane fuel cells (PEMFCs) are a popular source of alternative energy because of their operational reliability and compactness. This paper presents an improved model to represent the semi‐empirical voltage of PEMFCs to overcome the limitations of existing models. The proposed model considers variations in ambient conditions, such as the ambient temperature and relative humidity, to obtain the accurate output voltage that corresponds to variations in dynamic and static loads. The proposed model was developed by conducting several experiments on the Horizon PEMFC system under normal, humid, and dry ambient conditions. Subsequently, the model parameters corresponding to each case were optimised using the quantum lightning search algorithm (QLSA). Parameters demonstrating significant variations with ambient conditions were finally represented as a function of the ambient temperature and relative humidity via statistical regression analysis. The voltage obtained using the modified model was verified by conducting experiments on both the Horizon and NEXA PEMFC systems by varying the ambient temperature and relative humidity with root mean square error (RMSE) less than 0.5. As observed, the results we obtained using the modified model closely approximated those obtained using PEMFCs under various operating conditions, and in both cases, the PEMFC voltage was observed to vary with the ambient and load conditions. The inherent advantages of the proposed PEMFC model include its ability to determine the membrane‐water content and water pressure inside PEMFCs. The membrane‐water content provides clear indications regarding the occurrence of drying and flooding faults. Under normal conditions, this membrane water content ranges from 11 to 7 for both the Horizon and NEXA PEMFC system. The simulation results suggested using the threshold membrane‐water‐content level as a possible indicator of fault occurrence under extreme ambient conditions. The limits of the said threshold were observed to be useful for fault diagnosis within PEMFC systems.
Saad Saleem Khan; Hussain Shareef; Chafik Bouhaddioui; Rachid Errouissi. Membrane‐hydration‐state detection in proton exchange membrane fuel cells using improved ambient‐condition‐based dynamic model. International Journal of Energy Research 2019, 44, 869 -889.
AMA StyleSaad Saleem Khan, Hussain Shareef, Chafik Bouhaddioui, Rachid Errouissi. Membrane‐hydration‐state detection in proton exchange membrane fuel cells using improved ambient‐condition‐based dynamic model. International Journal of Energy Research. 2019; 44 (2):869-889.
Chicago/Turabian StyleSaad Saleem Khan; Hussain Shareef; Chafik Bouhaddioui; Rachid Errouissi. 2019. "Membrane‐hydration‐state detection in proton exchange membrane fuel cells using improved ambient‐condition‐based dynamic model." International Journal of Energy Research 44, no. 2: 869-889.
Considering, the high penetration of plug-in electric vehicles (PHEVs), the charging and discharging of PHEVs may lead to technical problems on electricity distribution networks. Therefore, the management of PHEV charging and discharging needs to be addressed to coordinate the time of PHEVs so as to be charged or discharged. This paper presents a management control method called the charging and discharging control algorithm (CDCA) to determine when and which of the PHEVs can be activated to consume power from the grid or supply power back to grid through the vehicle-to-grid technology. The proposed control algorithm considers fast charging scenario and photovoltaic generation during peak load to mitigate the impact of the vehicles. One of the important parameters considered in the CDCA is the PHEV battery state of charge (SOC). To predict the PHEV battery SOC, a particle swarm optimization-based artificial neural network is developed. Results show that the proposed CDCA gives better performance as compared to the uncoordinated charging method of vehicles in terms of maintaining the bus voltage profile during fast charging.
Ahmed Aljanad; Azah Mohamed; Tamer Khatib; Afida Ayob; Hussain Shareef. A Novel Charging and Discharging Algorithm of Plug-in Hybrid Electric Vehicles Considering Vehicle-to-Grid and Photovoltaic Generation. World Electric Vehicle Journal 2019, 10, 61 .
AMA StyleAhmed Aljanad, Azah Mohamed, Tamer Khatib, Afida Ayob, Hussain Shareef. A Novel Charging and Discharging Algorithm of Plug-in Hybrid Electric Vehicles Considering Vehicle-to-Grid and Photovoltaic Generation. World Electric Vehicle Journal. 2019; 10 (4):61.
Chicago/Turabian StyleAhmed Aljanad; Azah Mohamed; Tamer Khatib; Afida Ayob; Hussain Shareef. 2019. "A Novel Charging and Discharging Algorithm of Plug-in Hybrid Electric Vehicles Considering Vehicle-to-Grid and Photovoltaic Generation." World Electric Vehicle Journal 10, no. 4: 61.
This paper proposes a new voltage frequency converter (VFC) that converts both voltage and frequency to the required level of voltage and frequency in low voltage networks used in various countries. The proposed converter could be used as a universal power supply for sensitive AC loads. The converter is composed of, input voltage and frequency detection circuitry, full bridge boost rectifier and a DC to AC inverter. In addition, to improve the feasibility and performance of the converter, synchronous reference based PI (SRFPI) controller is adopted, where the system behaves similar to a DC-DC converter. The parameter selection of PI controller is done using a recent optimisation technique called Lightning Search Algorithm (LSA). The simulation of VFC is conducted in MATLAB/Simulink environment. The simulation results shows that LSA based PI controller provides better output voltage regulation with respect to the reference value under various load and input conditions.
M. Asna; H. Shareef; S.N. Khalid; A. Al Dosari; B. Hamad; M. Alhammadi; N. Aldarmaki. Analysis and design of single phase voltage-frequency converter with optimized PI controller. International Journal of Power Electronics and Drive Systems (IJPEDS) 2019, 10, 522 -529.
AMA StyleM. Asna, H. Shareef, S.N. Khalid, A. Al Dosari, B. Hamad, M. Alhammadi, N. Aldarmaki. Analysis and design of single phase voltage-frequency converter with optimized PI controller. International Journal of Power Electronics and Drive Systems (IJPEDS). 2019; 10 (1):522-529.
Chicago/Turabian StyleM. Asna; H. Shareef; S.N. Khalid; A. Al Dosari; B. Hamad; M. Alhammadi; N. Aldarmaki. 2019. "Analysis and design of single phase voltage-frequency converter with optimized PI controller." International Journal of Power Electronics and Drive Systems (IJPEDS) 10, no. 1: 522-529.
This paper presents a dynamic temperature model for a proton exchange membrane fuel cell (PEMFC) system. The proposed model overcomes the complexity of conventional models using first-order expressions consisting of load current and ambient temperature. The proposed model also incorporates a PEMFC cooling system, which depends upon the temperature difference between events. A dynamic algorithm is developed to detect load changing events and calculate instantaneous PEMFC temperature variations. The parameters of the model are extracted by employing the lightning search algorithm (LSA). The temperature characteristics of the NEXA 1.2 kW PEMFC system are experimentally studied to validate model performance. The results show that the proposed model output and the temperature data obtained from experiments for linear and abrupt changes in PEMFC load current are in agreement. The root-mean-square error between the model output and experimental results is less than 0.9. Moreover, the proposed model outperforms the conventional models and provides advantages such as simplicity and adaptability for low and high sampling data rates of input variables, namely, load current and ambient temperature. The model is not only helpful for simulations but also suitable for dynamic real-time controllers and emulators.
Saad S. Khan; Hussain Shareef; Ammar Hussein Mutlag. Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature. International Journal of Green Energy 2019, 16, 361 -370.
AMA StyleSaad S. Khan, Hussain Shareef, Ammar Hussein Mutlag. Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature. International Journal of Green Energy. 2019; 16 (5):361-370.
Chicago/Turabian StyleSaad S. Khan; Hussain Shareef; Ammar Hussein Mutlag. 2019. "Dynamic temperature model for proton exchange membrane fuel cell using online variations in load current and ambient temperature." International Journal of Green Energy 16, no. 5: 361-370.
Proton exchange membrane fuel cell is an emerging renewable energy resource for transportation and power generation. Similar to other renewable resources, the performance of proton exchange membrane fuel cell is affected by ambient conditions. However, procedures for analyzing the influences of such conditions on the performance of proton exchange membrane fuel cells are expensive and time-consuming. Moreover, the commonly used models have been developed on the basis of standard ambient conditions. Thus, these models are difficult to utilize under adverse ambient conditions. This study was performed to develop suitable proton exchange membrane fuel cell models that could reflect the effects of ambient conditions on the output voltage and current of the models. The first proposed model used the advantages of electrical and thermal relationships of a complex semiempirical model of a proton exchange membrane fuel cell. A simplified proton exchange membrane fuel cell model that used passive electrical components was then developed by central composite surface design. Both proposed models were simulated using various ambient temperatures, pressures, and load resistances by considering that the applied hydrogen pressure is known. Results showed that the output voltage of proton exchange membrane fuel cell decreased when ambient temperature increased and pressure decreased. This variation was dominant when the load resistance was reduced. Computation using the simplified model was remarkably faster than that using the first model. The proposed model can be beneficial, especially for aircraft applications and unusual ambient conditions.
Saad S Khan; Hussain Shareef; Addy Wahyudie; Sn Khalid; Reza Sirjani. Influences of ambient conditions on the performance of proton exchange membrane fuel cell using various models. Energy & Environment 2018, 30, 1087 -1110.
AMA StyleSaad S Khan, Hussain Shareef, Addy Wahyudie, Sn Khalid, Reza Sirjani. Influences of ambient conditions on the performance of proton exchange membrane fuel cell using various models. Energy & Environment. 2018; 30 (6):1087-1110.
Chicago/Turabian StyleSaad S Khan; Hussain Shareef; Addy Wahyudie; Sn Khalid; Reza Sirjani. 2018. "Influences of ambient conditions on the performance of proton exchange membrane fuel cell using various models." Energy & Environment 30, no. 6: 1087-1110.
The recent increase in electricity tariff and the introduction of feed-in tariff from renewable resources have increased the interest of energy consumers, such as those in commercial and residential buildings, in reducing their energy usage. This paper proposes a smart power socket and central control system that utilizes the Zigbee communication protocol to control energy usage. The system is designed such that smart sockets wirelessly provide the necessary data to a central controller. Then, the system analyzes the data to generate control commands to turn the devices attached to the smart socket on or off. Experimental results show that the proposed smart socket can correctly read the power consumption of wirelessly connected devices from up to 18 m away without loss of data. The central controller can effectively control multiple sockets on the basis of a scheduled user program code. A 24-min implementation of the proposed energy management algorithm shows a reduction of 0.811 kWmin (0.0134 kWh) in energy usage after the use of the smart sockets as load controllers. Thus, the proposed smart socket system can be fully utilized in a home energy management system with a proper scheduling algorithm.
Eslam Al-Hassan; Hussain Shareef; Mainul Islam; Addy Wahyudie; Atef Amin Abdrabou. Improved Smart Power Socket for Monitoring and Controlling Electrical Home Appliances. IEEE Access 2018, 6, 49292 -49305.
AMA StyleEslam Al-Hassan, Hussain Shareef, Mainul Islam, Addy Wahyudie, Atef Amin Abdrabou. Improved Smart Power Socket for Monitoring and Controlling Electrical Home Appliances. IEEE Access. 2018; 6 ():49292-49305.
Chicago/Turabian StyleEslam Al-Hassan; Hussain Shareef; Mainul Islam; Addy Wahyudie; Atef Amin Abdrabou. 2018. "Improved Smart Power Socket for Monitoring and Controlling Electrical Home Appliances." IEEE Access 6, no. : 49292-49305.