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Mohammad Lutfi Othman
Advanced Lightning, Power and Energy Research (ALPER), Department of Electrical and Electronic Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), UPM Serdang, Seri Kembangan, Selangor, Malaysia

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Physical sciences
Published: 12 August 2021 in PLOS ONE
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This study presents a nature-inspired, and metaheuristic-based Marine predator algorithm (MPA) for solving the optimal power flow (OPF) problem. The significant insight of MPA is the widespread foraging strategy called the Levy walk and Brownian movements in ocean predators, including the optimal encounter rate policy in biological interaction among predators and prey which make the method to solve the real-world engineering problems of OPF. The OPF problem has been extensively used in power system operation, planning, and management over a long time. In this work, the MPA is analyzed to solve the single-objective OPF problem considering the fuel cost, real and reactive power loss, voltage deviation, and voltage stability enhancement index as objective functions. The proposed method is tested on IEEE 30-bus test system and the obtained results by the proposed method are compared with recent literature studies. The acquired results demonstrate that the proposed method is quite competitive among the nature-inspired optimization techniques reported in the literature.

ACS Style

Mohammad Zohrul Islam; Mohammad Lutfi Othman; Noor Izzri Abdul Wahab; Veerapandiyan Veerasamy; Saifur Rahman Opu; Abinaya Inbamani; Vishalakshi Annamalai. Marine predators algorithm for solving single-objective optimal power flow. PLOS ONE 2021, 16, 1 .

AMA Style

Mohammad Zohrul Islam, Mohammad Lutfi Othman, Noor Izzri Abdul Wahab, Veerapandiyan Veerasamy, Saifur Rahman Opu, Abinaya Inbamani, Vishalakshi Annamalai. Marine predators algorithm for solving single-objective optimal power flow. PLOS ONE. 2021; 16 (8):1.

Chicago/Turabian Style

Mohammad Zohrul Islam; Mohammad Lutfi Othman; Noor Izzri Abdul Wahab; Veerapandiyan Veerasamy; Saifur Rahman Opu; Abinaya Inbamani; Vishalakshi Annamalai. 2021. "Marine predators algorithm for solving single-objective optimal power flow." PLOS ONE 16, no. 8: 1.

Journal article
Published: 10 August 2021 in Energies
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Islanding detection needs are becoming a pivotal constituent of the power system, since the penetration of distributed generators in the utility power system is continually increasing. Accurate threshold setting is an integral part of the island detection scheme since an inappropriate threshold might cause a hazardous situation. This study looked at the islanding conditions as well as two transient faults, such as a single line to ground fault and a three-phase balance fault, to assess the event distinguishing ability of the proposed method. Therefore, the goal of this research was to determine the threshold of the island if the distributed generator (DG) capacity is greater than the connected feeder load, which is the over-frequency island condition, and if the DG capacity is less than the connected feeder load, which is the under-frequency island condition. The significance of this research work is to propose a new island detection threshold setting method using the slip angle and acceleration angle that comes from phasor measurement unit (PMU) voltage angle data. The proposed threshold setting method was simulated in the PowerWorld simulator on a modified IEEE 30 bus system equipped with DG. There are three different interconnection scenarios in the test system and the performance of the proposed method shows that getting the island threshold for all the scenarios requires a single time step or 20 mile seconds after incepting an island into the network. In addition, it can distinguish between the real islanding threshold and the transient faults threshold.

ACS Style

Ahmed Arefin; Khairul Hasan; Mohammad Othman; Mohd Romlie; Nordin Saad; Nursyarizal Nor; Mohd Abdullah. A Novel Island Detection Threshold Setting Using Phasor Measurement Unit Voltage Angle in a Distribution Network. Energies 2021, 14, 4877 .

AMA Style

Ahmed Arefin, Khairul Hasan, Mohammad Othman, Mohd Romlie, Nordin Saad, Nursyarizal Nor, Mohd Abdullah. A Novel Island Detection Threshold Setting Using Phasor Measurement Unit Voltage Angle in a Distribution Network. Energies. 2021; 14 (16):4877.

Chicago/Turabian Style

Ahmed Arefin; Khairul Hasan; Mohammad Othman; Mohd Romlie; Nordin Saad; Nursyarizal Nor; Mohd Abdullah. 2021. "A Novel Island Detection Threshold Setting Using Phasor Measurement Unit Voltage Angle in a Distribution Network." Energies 14, no. 16: 4877.

Journal article
Published: 18 May 2021 in Sustainability
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The need for inexpensive and sustainable electricity has become an exciting adventure due to the recent rise in the local population and the number of visitors visiting the Banana Islands. Banana Islands is a grid-isolated environment with abundant renewable energy, establishing a hybrid renewable energy-based power system may be a viable solution to the high cost of diesel fuel. This paper describes a dual-flow optimization method for electrifying the Banana Islands, a remote island in Sierra Leone. The study weighs the pros and cons of maintaining the current diesel-based power setup versus introducing a hybrid renewable energy system that takes backup component analysis into account. Hybrid Optimization of Multiple Energy Resources (HOMER) software is used in the first optimization to optimally design the various system configurations based on techno-economic and environmental characteristics. A Multi-Attribute Decision-Making (MADM) Model that takes into account in the second optimization, the Combinative Distance-based Assessment System (CODAS) algorithm, and various methods of assigning weights to the attributes is used to rank the best configuration. The results show that the hybrid renewable energy system is a better option for electrifying the Banana Islands than the current stand-alone system. The Analytical Hierarchy Process (AHP) method of weight assignment was found to be superior to the Entropy method. Biogas generator-assisted hybrid configurations outperformed diesel generator-assisted hybrid configurations. With an optimum design of 101 kW PV, 1 wind turbine, 50 kW biogas, 86 batteries, and a 37.8 kW converter, the PV-wind-biogas-battery system is rated as the best configuration. It has a net present cost (NPC) of $487,247, a cost of energy (COE) of $0.211/kWh, and CO2 emission of 17.5 kg/year. Sensitivity analyses reveal that changes in the rate of inflation and the cost of storage have a significant effect on the overall cost of the configuration.

ACS Style

Keifa Konneh; Hasan Masrur; Mohammad Othman; Hiroshi Takahashi; Narayanan Krishna; Tomonobu Senjyu. Multi-Attribute Decision-Making Approach for a Cost-Effective and Sustainable Energy System Considering Weight Assignment Analysis. Sustainability 2021, 13, 5615 .

AMA Style

Keifa Konneh, Hasan Masrur, Mohammad Othman, Hiroshi Takahashi, Narayanan Krishna, Tomonobu Senjyu. Multi-Attribute Decision-Making Approach for a Cost-Effective and Sustainable Energy System Considering Weight Assignment Analysis. Sustainability. 2021; 13 (10):5615.

Chicago/Turabian Style

Keifa Konneh; Hasan Masrur; Mohammad Othman; Hiroshi Takahashi; Narayanan Krishna; Tomonobu Senjyu. 2021. "Multi-Attribute Decision-Making Approach for a Cost-Effective and Sustainable Energy System Considering Weight Assignment Analysis." Sustainability 13, no. 10: 5615.

Journal article
Published: 26 April 2021 in IEEE Access
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The concept of introducing hybrid off-grid systems has made electricity accessible to areas that are far or have no access to grid network. This paper evaluates the techno-economic and environmental characteristics of a hybrid renewable energy system considering three different scheduling approaches, four different solar tracking systems, two different PV modules and eight scheduling scenarios to supply sustainable electricity to a rural community in Sierra Leone. Each scenario consists of a solar tracking system, a specific type of PV module and a scheduling approach. The aim is to find the most efficient and cost-effective scenario that meets the electrical demands of the village. Results revealed that the ‘Two axis tracking system’ generated the highest PV power, 28.8% additional power compared to the ‘No tracking system’ confirming the superiority of using a tracking system though it comes with initial cost repercussions. Also, systems that employed the use of Canadiasolar Dymond CS6K-285M-FG PV module tend to be more efficient and cost-effective than those that employed Sharp ND-250QCS PV module even with the same solar tracking technology and scheduling approach. From the best scheduling approach (third scheduling), Scenario 7 (SC#7) gives the lowest net present cost (NPC) of $ \$ $ 1.53M with $ \$ $ 0.173/kWh cost of energy (COE) and CO 2 emission of 8.54 kg/yr making it the optimum scenario. A daily operation of the optimum scenario on both a sunny and rainy day confirms that the system is capable of supplying the required electricity for both rainy and dry seasons. Sensitivity analyses explain the high reliance of the system cost on the erratic inflation rate, discount rate and PV derating factor. Maintaining a healthy and sustainable environment depends on the minimum load ratio of both the biogas and diesel generators.

ACS Style

Keifa Vamba Konneh; Hasan Masrur; Mohammad Lutfi Othman; Noor Izzri Abdul Wahab; Hashim Hizam; Syed Zahurul Islam; Peter Crossley; Tomonobu Senjyu. Optimal Design and Performance Analysis of a Hybrid Off-Grid Renewable Power System Considering Different Component Scheduling, PV Modules, and Solar Tracking Systems. IEEE Access 2021, 9, 64393 -64413.

AMA Style

Keifa Vamba Konneh, Hasan Masrur, Mohammad Lutfi Othman, Noor Izzri Abdul Wahab, Hashim Hizam, Syed Zahurul Islam, Peter Crossley, Tomonobu Senjyu. Optimal Design and Performance Analysis of a Hybrid Off-Grid Renewable Power System Considering Different Component Scheduling, PV Modules, and Solar Tracking Systems. IEEE Access. 2021; 9 ():64393-64413.

Chicago/Turabian Style

Keifa Vamba Konneh; Hasan Masrur; Mohammad Lutfi Othman; Noor Izzri Abdul Wahab; Hashim Hizam; Syed Zahurul Islam; Peter Crossley; Tomonobu Senjyu. 2021. "Optimal Design and Performance Analysis of a Hybrid Off-Grid Renewable Power System Considering Different Component Scheduling, PV Modules, and Solar Tracking Systems." IEEE Access 9, no. : 64393-64413.

Journal article
Published: 22 February 2021 in IEEE Access
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This paper presents the detection of High Impedance Fault (HIF) in solar Photovoltaic (PV) integrated power system using recurrent neural network-based Long Short-Term Memory (LSTM) approach. For study this, an IEEE 13-bus system was modeled in MATLAB/Simulink environment to integrate 300 kW solar PV systems for analysis. Initially, the three-phase current signal during non-faulty (regular operation, capacitor switching, load switching, transformer inrush current) and faulty (HIF, symmetrical and unsymmetrical fault) conditions were used for extraction of features. The signal processing technique of Discrete Wavelet Transform with db4 mother wavelet was applied to extract each phase's energy value features for training and testing the classifiers. The proposed LSTM classifier gives the overall classification accuracy of 91.21% with a success rate of 92.42 % in identifying HIF in PV integrated power network. The prediction results obtained from the proffered method are compared with other well-known classifiers of K-Nearest neighbor's network, Support vector machine, J48 based decision tree, and Naïve Bayes approach. Further, the classifier's robustness is validated by evaluating the performance indices (PI) of kappa statistic, precision, recall, and F-measure. The results obtained reveal that the proposed LSTM network significantly outperforms all PI compared to other techniques.

ACS Style

Veerapandiyan Veerasamy; Noor Izzri Abdul Wahab; Mohammad Lutfi Othman; Sanjeevikumar Padmanaban; Kavaskar Sekar; Rajeswari Ramachandran; Hashim Hizam; Arangarajan Vinayagam; Mohammad Zohrul Islam. LSTM Recurrent Neural Network Classifier for High Impedance Fault Detection in Solar PV Integrated Power System. IEEE Access 2021, 9, 32672 -32687.

AMA Style

Veerapandiyan Veerasamy, Noor Izzri Abdul Wahab, Mohammad Lutfi Othman, Sanjeevikumar Padmanaban, Kavaskar Sekar, Rajeswari Ramachandran, Hashim Hizam, Arangarajan Vinayagam, Mohammad Zohrul Islam. LSTM Recurrent Neural Network Classifier for High Impedance Fault Detection in Solar PV Integrated Power System. IEEE Access. 2021; 9 ():32672-32687.

Chicago/Turabian Style

Veerapandiyan Veerasamy; Noor Izzri Abdul Wahab; Mohammad Lutfi Othman; Sanjeevikumar Padmanaban; Kavaskar Sekar; Rajeswari Ramachandran; Hashim Hizam; Arangarajan Vinayagam; Mohammad Zohrul Islam. 2021. "LSTM Recurrent Neural Network Classifier for High Impedance Fault Detection in Solar PV Integrated Power System." IEEE Access 9, no. : 32672-32687.

Journal article
Published: 17 February 2021 in Energies
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Photovoltaic (PV) systems encounter substantial losses throughout their lifespan due to the different derating factors of PV modules. Those factors mainly vary according to the geographical location and PV panel characteristics. However, the available literature does not explicitly concentrate on the technical and economic impact of the derating factors within the PV system. Owing to that necessity, this study performs a comprehensive analysis of various PV loss parameters followed by a techno-economic assessment of derating factors using the average value on a grid-connected and optimally tilted PV system located in Hatiya, Bangladesh. Some criteria linked to the derating factors such as PV degradation and ambient temperature are further explored to analyze their impact on the aforementioned power system. Simulation results show that PV power generation would vary around 12% annually, subject to a 10% variation in the derating factor. Again, a 10% difference in the derating factor changes the net present cost (NPC) by around 3% to 4%. The system provides the best technical performance concerning annual PV production, power trade with the grid, and the renewable fraction at a higher value of the derating factor since it represents a lower impact of the loss parameters. Similarly, the financial performance in terms of the NPC, levelized cost of energy (LCOE), and grid power exchange cost is found to be lower when the derating factor value is higher.

ACS Style

Hasan Masrur; Keifa Konneh; Mikaeel Ahmadi; Kaisar Khan; Mohammad Othman; Tomonobu Senjyu. Assessing the Techno-Economic Impact of Derating Factors on Optimally Tilted Grid-Tied Photovoltaic Systems. Energies 2021, 14, 1044 .

AMA Style

Hasan Masrur, Keifa Konneh, Mikaeel Ahmadi, Kaisar Khan, Mohammad Othman, Tomonobu Senjyu. Assessing the Techno-Economic Impact of Derating Factors on Optimally Tilted Grid-Tied Photovoltaic Systems. Energies. 2021; 14 (4):1044.

Chicago/Turabian Style

Hasan Masrur; Keifa Konneh; Mikaeel Ahmadi; Kaisar Khan; Mohammad Othman; Tomonobu Senjyu. 2021. "Assessing the Techno-Economic Impact of Derating Factors on Optimally Tilted Grid-Tied Photovoltaic Systems." Energies 14, no. 4: 1044.

Review
Published: 09 December 2020 in IEEE Access
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With the modernization of power grids, the network optimal utilization is essential to ensure that voltage profile at each bus is maintained within an acceptable range, voltage stability of the system is enhanced, power losses in lines are minimized, reliability and security of system are improved and etc. These can be achieved by introducing reactive power compensation devices such as Flexible Alternating Current Transmission System (FACTS) devices, Custom Power (CP) devices, synchronous condenser, capacitor bank and etc in distribution or transmission networks. Optimal location and sizing of the reactive power compensation devices are significantly important to ensure sufficient investment onto this device. Recently, most of conducted studies had focused on the techniques for determining the optimal location and sizing of various reactive power compensation devices in the power system using various indices proposed in the literature to access the power loss, voltage stability, voltage profile and line loadability. However, no review paper had discussed on the application of the existing indices adopted in the available techniques for solving the optimal location and sizing problems for all types of reactive power compensation devices. In this paper, current literature survey on optimal location and sizing of reactive power compensations had been discussed which includes analytical, conventional, metaheuristic and hybrid based approaches. The main objectives are to reduce power losses, to mitigate voltage deviations, to increase voltage stability and to improve reliability and security of the system.

ACS Style

Bazilah Ismail; Noor Izzri Abdul Wahab; Mohammad Lutfi Othman; Mohd Amran Mohd Radzi; Kanendra Naidu Vijyakumar; Muhammad Najwan Mat Naain. A Comprehensive Review on Optimal Location and Sizing of Reactive Power Compensation Using Hybrid-Based Approaches for Power Loss Reduction, Voltage Stability Improvement, Voltage Profile Enhancement and Loadability Enhancement. IEEE Access 2020, 8, 222733 -222765.

AMA Style

Bazilah Ismail, Noor Izzri Abdul Wahab, Mohammad Lutfi Othman, Mohd Amran Mohd Radzi, Kanendra Naidu Vijyakumar, Muhammad Najwan Mat Naain. A Comprehensive Review on Optimal Location and Sizing of Reactive Power Compensation Using Hybrid-Based Approaches for Power Loss Reduction, Voltage Stability Improvement, Voltage Profile Enhancement and Loadability Enhancement. IEEE Access. 2020; 8 (99):222733-222765.

Chicago/Turabian Style

Bazilah Ismail; Noor Izzri Abdul Wahab; Mohammad Lutfi Othman; Mohd Amran Mohd Radzi; Kanendra Naidu Vijyakumar; Muhammad Najwan Mat Naain. 2020. "A Comprehensive Review on Optimal Location and Sizing of Reactive Power Compensation Using Hybrid-Based Approaches for Power Loss Reduction, Voltage Stability Improvement, Voltage Profile Enhancement and Loadability Enhancement." IEEE Access 8, no. 99: 222733-222765.

Journal article
Published: 18 November 2020 in Sustainability
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In this research, an effective application and performance assessment of the Neuro-Fuzzy Controller (NFC) damping controller is designed to replace a single machine infinite bus (SMIB) power system stabilizer (PSS), and coordinated multi PSSs in large interconnected power systems are presented. The limitation of the conventional PSSs on SMIB and interconnected multi-machine test power systems are exposed and disclosed by the proposed NFC stabilizer. The NFC is a nonlinear robust controller which does not require a mathematical model of the test power system to be controlled, unlike the conventional PSSs’ damping controller. The Proposed NFC is designed to improve the stability of SMIB, an interconnected IEEE 3-machine, 9-bus power system, and an interconnected two-area 10-machine system of 39-bus New England IEEE test power system under multiple operating conditions. The proposed NFC damping controller performance is compared with the conventional PSS damping controller to confirm the capability of the proposed stabilizer and realize an improved system stability enhancement. The conventional PSSs’ design problem is transformed into an optimization problem where an eigenvalue-based objective function is developed and applied to design the SMIB-PSS and the interconnected multi-machine PSSs. The time-domain phasor simulation was done in the SIMULINK domain, and the simulation results show that the transient responses of the system rise time, settling time, peak time, and peak magnitude were all impressively improved by an acceptable amount for all the test system with the proposed NFC stabilizer. Thus, the NFC was able to effectively control the LFOs and produce an enhanced performance compared to the conventional PSS damping controller. Similarly, the result validates the effectiveness of the proposed NFC damping controller for LFO control, which demonstrates more robustness and efficiency than the classical PSS damping controller. Therefore, the application and performance of the NFC has appeared as a promising method and can be considered as a remarkable method for the optimal design damping stabilizer for small and large power systems.

ACS Style

Aliyu Sabo; Noor Wahab; Mohammad Othman; Mai Mohd Jaffar; Hakan Acikgoz; Hamzeh Beiranvand. Application of Neuro-Fuzzy Controller to Replace SMIB and Interconnected Multi-Machine Power System Stabilizers. Sustainability 2020, 12, 9591 .

AMA Style

Aliyu Sabo, Noor Wahab, Mohammad Othman, Mai Mohd Jaffar, Hakan Acikgoz, Hamzeh Beiranvand. Application of Neuro-Fuzzy Controller to Replace SMIB and Interconnected Multi-Machine Power System Stabilizers. Sustainability. 2020; 12 (22):9591.

Chicago/Turabian Style

Aliyu Sabo; Noor Wahab; Mohammad Othman; Mai Mohd Jaffar; Hakan Acikgoz; Hamzeh Beiranvand. 2020. "Application of Neuro-Fuzzy Controller to Replace SMIB and Interconnected Multi-Machine Power System Stabilizers." Sustainability 12, no. 22: 9591.

Research article
Published: 12 November 2020 in PLoS ONE
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This study analyzes the performance of two PV modules, amorphous silicon (a-Si) and crystalline silicon (c-Si) and predicts energy yield, which can be seen as facilitation to achieve the target of 35% reduction of greenhouse gases emission by 2030. Malaysia Energy Commission recommends crystalline PV modules for net energy metering (NEM), but the climate regime is a concern for output power and efficiency. Based on rainfall and irradiance data, this study aims to categorize the climate of peninsular Malaysia into rainy and dry seasons; and then the performance of the two modules are evaluated under the dry season. A new mathematical model is developed to predict energy yield and the results are validated through experimental and systematic error analysis. The parameters are collected using a self-developed ZigBeePRO-based wireless system with the rate of 3 samples/min over a period of five days. The results unveil that efficiency is inversely proportional to the irradiance due to negative temperature coefficient for crystalline modules. For this phenomenon, efficiency of c-Si (9.8%) is found always higher than a-Si (3.5%). However, a-Si shows better shadow tolerance compared to c-Si, observed from a lesser decrease rate in efficiency of the former with the increase in irradiance. Due to better spectrum response and temperature coefficient, a-Si shows greater performance on output power efficiency (OPE), performance ratio (PR), and yield factor. From the regression analysis, it is found that the coefficient of determination (R2) is between 0.7179 and 0.9611. The energy from the proposed model indicates that a-Si yields 15.07% higher kWh than c-Si when luminance for recorded days is 70% medium and 30% high. This study is important to determine the highest percentage of energy yield and to get faster NEM payback period, where as of now, there is no such model to indicate seasonal energy yield in Malaysia.

ACS Style

Syed Zahurul Islam; Mohammad Lutfi Othman; Muhammad Saufi; Rosli Omar; Arash Toudeshki. Photovoltaic modules evaluation and dry-season energy yield prediction model for NEM in Malaysia. PLoS ONE 2020, 15, e0241927 .

AMA Style

Syed Zahurul Islam, Mohammad Lutfi Othman, Muhammad Saufi, Rosli Omar, Arash Toudeshki. Photovoltaic modules evaluation and dry-season energy yield prediction model for NEM in Malaysia. PLoS ONE. 2020; 15 (11):e0241927.

Chicago/Turabian Style

Syed Zahurul Islam; Mohammad Lutfi Othman; Muhammad Saufi; Rosli Omar; Arash Toudeshki. 2020. "Photovoltaic modules evaluation and dry-season energy yield prediction model for NEM in Malaysia." PLoS ONE 15, no. 11: e0241927.

Research article
Published: 02 October 2020 in IET Renewable Power Generation
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Distributed generation (DG) has rapidly increased due to many technical, environmental and economical benefits. One of the DG application challenges is to find a proper area to incorporate the DG associated to a particular location. In this study, a central photovoltaic distributed generation (PVDG) topology is proposed to distribute the optimal sizes to the optimal locations. Uncertainties of load demand and renewable power generation are also taken into consideration of the optimisation problem. This study determines the deterministic and probabilistic penetration limits based on the distribution network topologies, considering the PVDG significant impact on active power losses reduction and voltage profiles improvement. The effectiveness of the proposed topology was validated on 33- and 69-bus distribution networks adopting Monte Carlo simulation method, Newton-Raphson load flow method and biogeography based optimisation. From the results, the voltage profiles, active power loss reduction, DG capacity required and penetration limit have shown better performances on the central PVDG topology over the bus dedicated PVDG topology.

ACS Style

Mohamed Saad Suliman; Hashim Hizam; Mohammad Lutfi Othman. Determining penetration limit of central PVDG topology considering the stochastic behaviour of PV generation and loads to reduce power losses and improve voltage profiles. IET Renewable Power Generation 2020, 14, 2629 -2638.

AMA Style

Mohamed Saad Suliman, Hashim Hizam, Mohammad Lutfi Othman. Determining penetration limit of central PVDG topology considering the stochastic behaviour of PV generation and loads to reduce power losses and improve voltage profiles. IET Renewable Power Generation. 2020; 14 (14):2629-2638.

Chicago/Turabian Style

Mohamed Saad Suliman; Hashim Hizam; Mohammad Lutfi Othman. 2020. "Determining penetration limit of central PVDG topology considering the stochastic behaviour of PV generation and loads to reduce power losses and improve voltage profiles." IET Renewable Power Generation 14, no. 14: 2629-2638.

Journal article
Published: 18 August 2020 in Energies
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In this paper, a multi-objective hybrid firefly and particle swarm optimization (MOHFPSO) was proposed for different multi-objective optimal power flow (MOOPF) problems. Optimal power flow (OPF) was formulated as a non-linear problem with various objectives and constraints. Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. Finally, an optimal compromised solution was selected from the Pareto optimal set by applying an ideal distance minimization method. The efficiency of the proposed MOHFPSO technique was tested on standard IEEE 30-bus and IEEE 57-bus test systems with various conflicting objectives. Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. The achieved results revealed the potential of the proposed algorithm for MOOPF problems.

ACS Style

Abdullah Khan; Hashim Hizam; Noor Izzri Abdul-Wahab; Mohammad Lutfi Othman. Solution of Optimal Power Flow Using Non-Dominated Sorting Multi Objective Based Hybrid Firefly and Particle Swarm Optimization Algorithm. Energies 2020, 13, 4265 .

AMA Style

Abdullah Khan, Hashim Hizam, Noor Izzri Abdul-Wahab, Mohammad Lutfi Othman. Solution of Optimal Power Flow Using Non-Dominated Sorting Multi Objective Based Hybrid Firefly and Particle Swarm Optimization Algorithm. Energies. 2020; 13 (16):4265.

Chicago/Turabian Style

Abdullah Khan; Hashim Hizam; Noor Izzri Abdul-Wahab; Mohammad Lutfi Othman. 2020. "Solution of Optimal Power Flow Using Non-Dominated Sorting Multi Objective Based Hybrid Firefly and Particle Swarm Optimization Algorithm." Energies 13, no. 16: 4265.

Journal article
Published: 01 June 2020 in International Journal of Power Electronics and Drive Systems (IJPEDS)
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This paper is present a novel approach for solving the pending under-reach problem encountered by distance relay protection scheme in the 3rd zones protection coverage for a midpoint STATCOM compensated transmission lines. The propose transmission line model is develop in Matlab for analyzed feature extraction using Discrete Wavelet multiresolution analysis approach. Extracted feature from standard deviation and entropy energy contents of SLG transient faults current at location beyond the integrated STATCOM used for machine learning algorithm model building using WEKA software. The Naïve Bayes classifier model perform best with robustness prediction and detection of faults with quick convergence even with less training data. The outperformance of the proposed classifier has been 100 % for the relay algorithm modification for under-reach problem elimination in 3rd zones protection coverage.

ACS Style

Elhadi Emhemed Aker; Mohammad Lutfi Othman; Ishak Bin Aris; Noor Izzri Abdul Wahab; Hashim Hizam; Osaj Emmanuel. Transmission line fault identification and classification with integrated FACTS device using multiresolution analysis and naïve bayes classifier. International Journal of Power Electronics and Drive Systems (IJPEDS) 2020, 11, 907 -913.

AMA Style

Elhadi Emhemed Aker, Mohammad Lutfi Othman, Ishak Bin Aris, Noor Izzri Abdul Wahab, Hashim Hizam, Osaj Emmanuel. Transmission line fault identification and classification with integrated FACTS device using multiresolution analysis and naïve bayes classifier. International Journal of Power Electronics and Drive Systems (IJPEDS). 2020; 11 (2):907-913.

Chicago/Turabian Style

Elhadi Emhemed Aker; Mohammad Lutfi Othman; Ishak Bin Aris; Noor Izzri Abdul Wahab; Hashim Hizam; Osaj Emmanuel. 2020. "Transmission line fault identification and classification with integrated FACTS device using multiresolution analysis and naïve bayes classifier." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 2: 907-913.

Journal article
Published: 01 June 2020 in International Journal of Power Electronics and Drive Systems (IJPEDS)
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In Smart Grid (SG) communication network, sensors integrated communication radios namely ZigBee, Wi-Fi, and Bluetooth are becoming urgent and crucial part of SG wireless communication. Sensor nodes are generally battery powered. With the enhancement and huge utilization of sensor technologies, batteries have not been improved significantly at the same pace. However, batteries are essential to power the sensor nodes and there is no alternative of this energy bank. Therefore, to provide seamless power to the nodes is a challenge when the nodes are meant for integrating distributed renewable generations for years. Necessitate of the battery replacement is not often cost effective when the batteries are drained out. This paper presents a feasibility study of standalone Photovoltaic (PV) powered battery using Sensors-radios integrated Embedded Node (SEN) for SG application. In this study, we have analyzed charging characteristics of a lead-acid battery that can be recharged during day time by a PV module. The aim of this research is to testify the two simultaneous jobs- (i) the battery is sufficient to power Sensors-ZigBee integrated Arduino (SZA) for at least one day operation, (ii) scrutiny the optimal size of PV for recharging the battery considering three different day variations- average, cloudy, and full rainy day. The result from real data analysis reveals that the module is sufficient to recharge the battery on an average day; however, it is not sufficient for full cloudy or full rainy day. Finally, a mathematical model is obtained from regression analysis that shows battery internal resistance is exponential to voltage on both full cloudy and rainy day, but it is linear on average day.

ACS Style

Syed Zahurul Islam; Mohammad Lutfi Othman; Norman Mariun; Hashim Hizam; Nur Ayuni. Feasibility analysis of standalone PV powered battery using SEN for Smart Grid. International Journal of Power Electronics and Drive Systems (IJPEDS) 2020, 11, 667 -676.

AMA Style

Syed Zahurul Islam, Mohammad Lutfi Othman, Norman Mariun, Hashim Hizam, Nur Ayuni. Feasibility analysis of standalone PV powered battery using SEN for Smart Grid. International Journal of Power Electronics and Drive Systems (IJPEDS). 2020; 11 (2):667-676.

Chicago/Turabian Style

Syed Zahurul Islam; Mohammad Lutfi Othman; Norman Mariun; Hashim Hizam; Nur Ayuni. 2020. "Feasibility analysis of standalone PV powered battery using SEN for Smart Grid." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 2: 667-676.

Journal article
Published: 13 April 2020 in IEEE Access
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This paper presents the automatic load frequency control (ALFC) of two-area multisource hybrid power system (HPS). The interconnected HPS model consists of conventional and renewable energy sources operating in disparate combinations to balance the generation and load demand of the system. In the proffered work, the stability analysis of nonlinear dynamic HPS model was analyzed using the Hankel method of model order reduction. Also, an attempt was made to apply cascade proportional integral – proportional derivative (PI-PD) control for HPS. The gains of the controller were optimized by minimizing the integral absolute error (IAE) of area control error using particle swarm optimization–gravitational search algorithm (PSO-GSA) optimization technique. The performance of cascade control was compared with other classical controllers and the efficiency of this approach was studied for various cases of HPS model. The result shows that the cascade control produced better transient and steady state performances than those of the other classical controllers. The robustness analysis also reveals that the system overshoots/undershoots in frequency response pertaining to random change in wind power generation and load perturbations were significantly reduced by the proposed cascade control. In addition, the sensitivity analysis of the system was performed, with the variation in step load perturbation (SLP) of 1% to 5%, system loading and inertia of the system by ±25% of nominal values to prove the efficiency of the controller. Furthermore, to prove the efficiency of PSO-GSA tuned cascade control, the results were compared with other artificial intelligence (AI) methods presented in the literature. Further, the stability of the system was analyzed in frequency domain for different operating cases.

ACS Style

Veerapandiyan Veerasamy; Noor Izzri Abdul Wahab; Rajeswari Ramachandran; Mohammad Lutfi Othman; Hashim Hizam; Andrew Xavier Raj Irudayaraj; Josep M. Guerrero; Jeevitha Satheesh Kumar. A Hankel Matrix Based Reduced Order Model for Stability Analysis of Hybrid Power System Using PSO-GSA Optimized Cascade PI-PD Controller for Automatic Load Frequency Control. IEEE Access 2020, 8, 71422 -71446.

AMA Style

Veerapandiyan Veerasamy, Noor Izzri Abdul Wahab, Rajeswari Ramachandran, Mohammad Lutfi Othman, Hashim Hizam, Andrew Xavier Raj Irudayaraj, Josep M. Guerrero, Jeevitha Satheesh Kumar. A Hankel Matrix Based Reduced Order Model for Stability Analysis of Hybrid Power System Using PSO-GSA Optimized Cascade PI-PD Controller for Automatic Load Frequency Control. IEEE Access. 2020; 8 (99):71422-71446.

Chicago/Turabian Style

Veerapandiyan Veerasamy; Noor Izzri Abdul Wahab; Rajeswari Ramachandran; Mohammad Lutfi Othman; Hashim Hizam; Andrew Xavier Raj Irudayaraj; Josep M. Guerrero; Jeevitha Satheesh Kumar. 2020. "A Hankel Matrix Based Reduced Order Model for Stability Analysis of Hybrid Power System Using PSO-GSA Optimized Cascade PI-PD Controller for Automatic Load Frequency Control." IEEE Access 8, no. 99: 71422-71446.

Research article
Published: 05 March 2020 in International Transactions on Electrical Energy Systems
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ACS Style

Veerapandiyan Veerasamy; Noor Izzri Abdul Wahab; Arangarajan Vinayagam; Mohammad Lutfi Othman; Rajeswari Ramachandran; Abinaya Inbamani; Hashim Hizam. A novel discrete wavelet transform‐based graphical language classifier for identification of high‐impedance fault in distribution power system. International Transactions on Electrical Energy Systems 2020, 30, 1 .

AMA Style

Veerapandiyan Veerasamy, Noor Izzri Abdul Wahab, Arangarajan Vinayagam, Mohammad Lutfi Othman, Rajeswari Ramachandran, Abinaya Inbamani, Hashim Hizam. A novel discrete wavelet transform‐based graphical language classifier for identification of high‐impedance fault in distribution power system. International Transactions on Electrical Energy Systems. 2020; 30 (6):1.

Chicago/Turabian Style

Veerapandiyan Veerasamy; Noor Izzri Abdul Wahab; Arangarajan Vinayagam; Mohammad Lutfi Othman; Rajeswari Ramachandran; Abinaya Inbamani; Hashim Hizam. 2020. "A novel discrete wavelet transform‐based graphical language classifier for identification of high‐impedance fault in distribution power system." International Transactions on Electrical Energy Systems 30, no. 6: 1.

Journal article
Published: 03 January 2020 in Energies
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This paper presents the methodology to detect and identify the type of fault that occurs in the shunt compensated static synchronous compensator (STATCOM) transmission line using a combination of Discrete Wavelet Transform (DWT) and Naive Bayes (NB) classifiers. To study this, the network model is designed using Matlab/Simulink. Different types of faults, such as Line to Ground (LG), Line to Line (LL), Double Line to Ground (LLG) and the three-phase (LLLG) fault, are applied at disparate zones of the system, with and without STATCOM, considering the effect of varying fault resistance. The three-phase fault current waveforms obtained are decomposed into several levels using Daubechies (db) mother wavelet of db4 to extract the features, such as the standard deviation (SD) and energy values. Then, the extracted features are used to train the classifiers, such as Multi-Layer Perceptron Neural Network (MLP), Bayes and the Naive Bayes (NB) classifier to classify the type of fault that occurs in the system. The results obtained reveal that the proposed NB classifier outperforms in terms of accuracy rate, misclassification rate, kappa statistics, mean absolute error (MAE), root mean square error (RMSE), percentage relative absolute error (% RAE) and percentage root relative square error (% RRSE) than both MLP and the Bayes classifier.

ACS Style

Elhadi Aker; Mohammad Lutfi Othman; Veerapandiyan Veerasamy; Ishak Bin Aris; Noor Izzri Abdul Wahab; Hashim Hizam. Fault Detection and Classification of Shunt Compensated Transmission Line Using Discrete Wavelet Transform and Naive Bayes Classifier. Energies 2020, 13, 243 .

AMA Style

Elhadi Aker, Mohammad Lutfi Othman, Veerapandiyan Veerasamy, Ishak Bin Aris, Noor Izzri Abdul Wahab, Hashim Hizam. Fault Detection and Classification of Shunt Compensated Transmission Line Using Discrete Wavelet Transform and Naive Bayes Classifier. Energies. 2020; 13 (1):243.

Chicago/Turabian Style

Elhadi Aker; Mohammad Lutfi Othman; Veerapandiyan Veerasamy; Ishak Bin Aris; Noor Izzri Abdul Wahab; Hashim Hizam. 2020. "Fault Detection and Classification of Shunt Compensated Transmission Line Using Discrete Wavelet Transform and Naive Bayes Classifier." Energies 13, no. 1: 243.

Journal article
Published: 11 December 2019 in International Journal of Hydrogen Energy
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A Hybrid Energy System (HES) is a mechanism that combines multiple sources of energy connected together to achieve synchronised energy output. However, increased energy consumption, operator energy expenses, and the potential environmental impact of increased emissions from the exhaustion of non-renewable energy resources (fossil fuel) pose major challenges to HES. This research is to conduct energy management strategy based on a demand response (DR) program and a hydrogen storage system by designing a Program Logic Controller (PLC) unit. The hybrid system is evaluated by comparing different scenarios such as a hydrogen energy system and demand response. The purpose of this research is to reducing peak demand, minimise the cost of the system and also to extract surplus power generation out of the rate of the battery. This can be achieved by improving the system performances and by eliminating any degradation at the early stages. Organisations or companies must be sure their systems are working properly and that their investments will pay off.

ACS Style

Mohammad Reza Maghami; Rahman Hassani; Chandima Gomes; Hashim Hizam; Mohammad Lutfi Othman; Mohammad Behmanesh. Hybrid energy management with respect to a hydrogen energy system and demand response. International Journal of Hydrogen Energy 2019, 45, 1499 -1509.

AMA Style

Mohammad Reza Maghami, Rahman Hassani, Chandima Gomes, Hashim Hizam, Mohammad Lutfi Othman, Mohammad Behmanesh. Hybrid energy management with respect to a hydrogen energy system and demand response. International Journal of Hydrogen Energy. 2019; 45 (3):1499-1509.

Chicago/Turabian Style

Mohammad Reza Maghami; Rahman Hassani; Chandima Gomes; Hashim Hizam; Mohammad Lutfi Othman; Mohammad Behmanesh. 2019. "Hybrid energy management with respect to a hydrogen energy system and demand response." International Journal of Hydrogen Energy 45, no. 3: 1499-1509.

Journal article
Published: 04 December 2019 in Sustainability
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This paper proposes a new population-based hybrid particle swarm optimized-gravitational search algorithm (PSO-GSA) for tuning the parameters of the proportional-integral-derivative (PID) controller of a two-area interconnected dynamic power system with the presence of nonlinearities such as generator rate constraints (GRC) and governor dead-band (GDB). The tuning of controller parameters such as Kp, Ki, and Kd are obtained by minimizing the objective function formulated using the steady-state performance indices like Integral absolute error (IAE) of tie-line power and frequency deviation of interconnected system. To test the robustness of the propounded controller, the system is studied with system uncertainties, such as change in load demand, synchronizing power coefficient and inertia constant. The two-area interconnected power system (TAIPS) is modeled and simulated using Matlab/Simulink. The results exhibit that the steady-state and transient performance indices such as IAE, settling time, and control effort are impressively enhanced by an amount of 87.65%, 15.39%, and 91.17% in area-1 and 86.46%, 41.35%, and 91.04% in area-2, respectively, by the proposed method compared to other techniques presented. The minimum control effort of PSO-GSA-tuned PID controller depicts the robust performance of the controller compared to other non-meta-heuristic and meta-heuristic methods presented. The proffered method is also validated using the hardware-in-the-loop (HIL) real-time digital simulation to study the effectiveness of the controller.

ACS Style

Veerapandiyan Veerasamy; Noor Izzri Abdul Wahab; Rajeswari Ramachandran; Arangarajan Vinayagam; Mohammad Lutfi Othman; Hashim Hizam; Jeevitha Satheeshkumar. Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller. Sustainability 2019, 11, 6908 .

AMA Style

Veerapandiyan Veerasamy, Noor Izzri Abdul Wahab, Rajeswari Ramachandran, Arangarajan Vinayagam, Mohammad Lutfi Othman, Hashim Hizam, Jeevitha Satheeshkumar. Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller. Sustainability. 2019; 11 (24):6908.

Chicago/Turabian Style

Veerapandiyan Veerasamy; Noor Izzri Abdul Wahab; Rajeswari Ramachandran; Arangarajan Vinayagam; Mohammad Lutfi Othman; Hashim Hizam; Jeevitha Satheeshkumar. 2019. "Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller." Sustainability 11, no. 24: 6908.

Journal article
Published: 01 December 2019 in IAES International Journal of Artificial Intelligence (IJ-AI)
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Power transformer is the most expensive equipment in electrical power system that needs continuous monitoring and fast protection response. Differential relay is usually used in power transformer protection scheme. This protection compares the difference of currents between transformer primary and secondary sides, with which a tripping signal to the circuit breaker is asserted. However, when power transformers are energized, the magnetizing inrush current is present and due to its high magnitude, the relay mal-operates. To prevent mal-operation, methods revolving around the fact that the relay should be able to discriminate between the magnetizing inrush current and the fault current must be studied. This paper presents an Artificial Neural Network(ANN) based differential relay that is designed to enable the differential relay to correct its mal-operation during energization by training the ANN and testing it with harmonic current as the restraining element. The MATLAB software is used to implement and evaluate the proposed differential relay. It is shown that the ANN based differential relay is indeed an adaptive relay when it is appropriately trained using the Network Fitting Tool. The improved differential relay models also include a reset part which enables automatic reset of the relays. Using the techniques of 2nd harmonic restraint and ANN to design a differential relay thus illustrates that the latter can successfully differentiate between magnetizing inrush and internal fault currents. With the new adaptive ANN-based differential relay, there is no mal-operation of the relay during energization. The ANN based differential relay shows better performance in terms of its ability to differentiate fault against energization current. Amazingly, the response time, when there is an internal fault, is 1 ms compared to 4.5 ms of the conventional 2nd harmonic restraint based relay.

ACS Style

Azniza Ahmad; Mohammad Lutfi Othman; Kurreemun Khudsiya Bibi Zainab; Hashim Hizam. Adaptive ANN based differential protective relay for reliable power transformer protection operation during energisation. IAES International Journal of Artificial Intelligence (IJ-AI) 2019, 8, 307 -316.

AMA Style

Azniza Ahmad, Mohammad Lutfi Othman, Kurreemun Khudsiya Bibi Zainab, Hashim Hizam. Adaptive ANN based differential protective relay for reliable power transformer protection operation during energisation. IAES International Journal of Artificial Intelligence (IJ-AI). 2019; 8 (4):307-316.

Chicago/Turabian Style

Azniza Ahmad; Mohammad Lutfi Othman; Kurreemun Khudsiya Bibi Zainab; Hashim Hizam. 2019. "Adaptive ANN based differential protective relay for reliable power transformer protection operation during energisation." IAES International Journal of Artificial Intelligence (IJ-AI) 8, no. 4: 307-316.

Journal article
Published: 05 September 2019 in International Journal of Integrated Engineering
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ACS Style

Osaji Emmanue; Mohammad Lutfi Othman; Hashim Hizam; Muhammad M. Othman; Elhadi Aker; Okeke Chidiebere. A; T Nwagbara Samuel. Hybrid Signal Processing and Machine Learning Algorithm for Adaptive Fault Classification of Wind Farm Integrated Transmission Line Protection. International Journal of Integrated Engineering 2019, 11, 1 .

AMA Style

Osaji Emmanue, Mohammad Lutfi Othman, Hashim Hizam, Muhammad M. Othman, Elhadi Aker, Okeke Chidiebere. A, T Nwagbara Samuel. Hybrid Signal Processing and Machine Learning Algorithm for Adaptive Fault Classification of Wind Farm Integrated Transmission Line Protection. International Journal of Integrated Engineering. 2019; 11 (4):1.

Chicago/Turabian Style

Osaji Emmanue; Mohammad Lutfi Othman; Hashim Hizam; Muhammad M. Othman; Elhadi Aker; Okeke Chidiebere. A; T Nwagbara Samuel. 2019. "Hybrid Signal Processing and Machine Learning Algorithm for Adaptive Fault Classification of Wind Farm Integrated Transmission Line Protection." International Journal of Integrated Engineering 11, no. 4: 1.