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Dr. Baseem Khan
Hawassa University Institute of Technology (HUiT)

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Research Keywords & Expertise

0 Smart Grid
0 Renewable Energy Integration
0 Electrical Power and Energy System
0 Power System Planning
0 Micro grid and Renewable Energy

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Journal article
Published: 20 August 2021 in IEEE Access
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This work presents a new robust control technique which combines a model predictive control (MPC) and linear quadratic gaussian (LQG) approach to support the frequency stability of modern power systems. Moreover, the constraints of the proposed robust controller (MPC-LQG) are fine-tuned based on a new technique titled Chimp optimization algorithm (ChOA). The effectiveness of the proposed robust controller is tested and verified through a multi-area power system (i.e., single-area and two-area power systems). Each area contains a thermal power plant as a conventional generation source considering physical constraints (i.e. generation rate constraint, and governor dead band) in addition to a wind power plant as a renewable resource. The superiority of the proposed robust controller is confirmed by contrasting its performance to that of other controllers which were used in load frequency control studies (e.g., conventional integral and MPC). Also, the ChOA’s ingenuity is verified over several other powerful optimization techniques; particle swarm optimization, gray wolf optimization, and ant lion optimizer). The simulation outcomes reveal the effectiveness as well as the robustness of the proposed MPC-LQG controller based on the ChOA under different operating conditions considering different load disturbances and several penetration levels of the wind power.

ACS Style

Mohamed Khamies; Gaber Magdy; Salah Kamel; Baseem Khan. Optimal Model Predictive and Linear Quadratic Gaussian Control for Frequency Stability of Power Systems Considering Wind Energy. IEEE Access 2021, 9, 116453 -116474.

AMA Style

Mohamed Khamies, Gaber Magdy, Salah Kamel, Baseem Khan. Optimal Model Predictive and Linear Quadratic Gaussian Control for Frequency Stability of Power Systems Considering Wind Energy. IEEE Access. 2021; 9 ():116453-116474.

Chicago/Turabian Style

Mohamed Khamies; Gaber Magdy; Salah Kamel; Baseem Khan. 2021. "Optimal Model Predictive and Linear Quadratic Gaussian Control for Frequency Stability of Power Systems Considering Wind Energy." IEEE Access 9, no. : 116453-116474.

Journal article
Published: 20 July 2021 in Computers & Electrical Engineering
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The impact of fault circumstances on distribution grid parameters in the presence of wind power generation is explored in this research. A protection algorithm (PA) is also proposed for detecting faulty events by using the proposed wind fault index, which is computed by analysing current signals using the Wigner distribution function and the Stockwell transform (ST). The sort of fault is determined by the number of faulty phases found. The zero sequence currents introduced to identify the ground’s involvement in a fault event are analysed to calculate a wind ground fault index. Single phase to the ground, double phase to the ground, double phase, three-phases, and three phases to the ground faults are all investigated fault events. It has been determined that PA outperforms discrete Wavelet Transform and ST-based approaches in terms of fault estimation time and noise effect. The study was conducted on the IEEE-13 bus test feeder, which was connected to wind power plants (WPPs).

ACS Style

Om Prakash Mahela; Vikram Singh Bhati; Gulhasan Ahmad; Baseem Khan; P. Sanjeevikumar; Akhil Ranjan Garg; Rajendra Mahla. A protection scheme for distribution utility grid with wind energy penetration. Computers & Electrical Engineering 2021, 94, 107324 .

AMA Style

Om Prakash Mahela, Vikram Singh Bhati, Gulhasan Ahmad, Baseem Khan, P. Sanjeevikumar, Akhil Ranjan Garg, Rajendra Mahla. A protection scheme for distribution utility grid with wind energy penetration. Computers & Electrical Engineering. 2021; 94 ():107324.

Chicago/Turabian Style

Om Prakash Mahela; Vikram Singh Bhati; Gulhasan Ahmad; Baseem Khan; P. Sanjeevikumar; Akhil Ranjan Garg; Rajendra Mahla. 2021. "A protection scheme for distribution utility grid with wind energy penetration." Computers & Electrical Engineering 94, no. : 107324.

Journal article
Published: 17 July 2021 in Computers & Electrical Engineering
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In the radial distribution system, reliability is the most critical performance criterion. Additionally, optimizing the voltage profile is critical. This work proposed the optimal placement of distributed energy resources (DERs) to enhance the reliability and improve the voltage profile of the distribution feeder. To perform this research, two practical feeders of the Debre Markos (D/M) city distribution network, Ethiopia were used, which were affected by the outages. A composite system adequacy assessment, which includes the two main components of the power grid, i.e. generation and distribution, is performed using Monte Carlo simulation. The computed results show that integrating DER units improved the overall system's reliability. Further, the effect of varying DER penetration on reliability and voltage profile is also analyzed. ETAP and DIgSILENT software environments are used to perform this research.

ACS Style

Takele Ferede Agajie; Baseem Khan; Josep M. Guerrero; Om Prakash Mahela. Reliability enhancement and voltage profile improvement of distribution network using optimal capacity allocation and placement of distributed energy resources. Computers & Electrical Engineering 2021, 93, 107295 .

AMA Style

Takele Ferede Agajie, Baseem Khan, Josep M. Guerrero, Om Prakash Mahela. Reliability enhancement and voltage profile improvement of distribution network using optimal capacity allocation and placement of distributed energy resources. Computers & Electrical Engineering. 2021; 93 ():107295.

Chicago/Turabian Style

Takele Ferede Agajie; Baseem Khan; Josep M. Guerrero; Om Prakash Mahela. 2021. "Reliability enhancement and voltage profile improvement of distribution network using optimal capacity allocation and placement of distributed energy resources." Computers & Electrical Engineering 93, no. : 107295.

Journal article
Published: 13 July 2021 in IEEE Access
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Today’s electrical power system became more complex interconnected network that is expanding every day. The transmission lines of the power system are more severely loaded than ever before. Hence, the power system is facing many problems such as power losses increasing, voltage instability, line overloads, etc. The optimization of real and reactive powers due to the installation of energy resources at appropriate buses can minimize the losses and improve the voltage profile especially, for congested networks. As a result, the optimal power flow problem (OPF) is considered more important tool for the processes of planning and operation of power systems. OPF is a very significant tool for power system operators to meet the electricity demand of the consumers efficiently, and for the reliable operation of the power system. However, the incorporation of renewable energy sources (RESs) into the electrical grid is a very challenging problem due to their intermittent nature. In this paper, the proposed power flow model contains three different types of energy sources: thermal power generators representing the conventional energy sources, wind power generators (WPGs), and solar photovoltaic generators (SPGs) representing RESs. Uncertain output powers from WPGs and SPGs are forecasted with the aid of Weibull and lognormal probability distribution functions (PDF), respectively. The under and overestimation output powers of RESs are taken into consideration while formulating the objective function through adding a penalty and reserve cost, respectively. Moreover, carbon tax is imposed to the main objective function to help in reducing carbon emissions. A jellyfish search optimizer (JS) is employed to reach optimization in the modified IEEE 30-bus test system to validate its feasibility. To examine the effectiveness of the proposed JS algorithm, its simulation results are compared with the results of four other nature-inspired global optimization algorithms. The developed OPF algorithm considers several practical cases such as generation uncertainty of renewable energy sources, time-varying load and the ramp rate limits of thermal generators. The simulation results show the effectiveness of the JS algorithm in solving the OPF problem in terms of minimization of total generation cost and solution convergence.

ACS Style

Mohamed Farhat; Salah Kamel; Ahmed M. Atallah; Baseem Khan. Optimal Power Flow Solution Based on Jellyfish Search Optimization Considering Uncertainty of Renewable Energy Sources. IEEE Access 2021, 9, 100911 -100933.

AMA Style

Mohamed Farhat, Salah Kamel, Ahmed M. Atallah, Baseem Khan. Optimal Power Flow Solution Based on Jellyfish Search Optimization Considering Uncertainty of Renewable Energy Sources. IEEE Access. 2021; 9 ():100911-100933.

Chicago/Turabian Style

Mohamed Farhat; Salah Kamel; Ahmed M. Atallah; Baseem Khan. 2021. "Optimal Power Flow Solution Based on Jellyfish Search Optimization Considering Uncertainty of Renewable Energy Sources." IEEE Access 9, no. : 100911-100933.

Journal article
Published: 28 June 2021 in IEEE Access
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Renewable energy (RE) generation levels are increasing in modern power systems at a fast rate due to their advantages of clean and non-exhaustible nature of energy. However, this type of generation creates technical challenges in terms of operation and control due to uncertain and un-predictable nature of generation. Islanding is an operational scenario where there is a loss of grid and RE generators continue to feed power to the local load. This has harmful effects on the RE generators and operating personal. Hence, it is expected that islanding scenario is identified in minimum time and RE generators are disconnected within $2~s$ duration after island formation. This paper designed an islanding identification scheme (IDS) by designing a current islanding detection indicator (CIDI) that combines the features computed by processing the current signals, negative sequence current (NSC) and negative sequence voltage (NSV) using the Stockwell transform (ST) and the Hilbert transform (HT). Information contained by the total harmonic distortions of voltage ( $THD_{v}$ ) and current ( $THD_{i}$ ) is also used while designing the CIDI. Islanding and non-islanding events of category-I & II are identified and discriminated from each other by comparison of peak magnitude of CIDI with the first threshold value (FTV) and second threshold value (STV). This IDS effectively recognizes the islanding events even in the noisy environment with minimum non-detection zone (NDZ) and minimum time. The efficiency is greater than 98% even with the noise of $20dB$ SNR (signal to noise ratio). The performance of proposed IDS is better compared to IDS using discrete wavelet transform (DWT), Empirical mode decomposition (EMD), Slantlet transform & Ridgelet probabilistic neural network (RPNN), and artificial neural network (ANN). The effectiveness of IDS is validated on IEEE-13 nodes test system using MATLAB software, practical distribution network and in real time scenario by use of real time digital simulator (RTDS).

ACS Style

Nagendra Kumar Swarnkar; Om Prakash Mahela; Baseem Khan; Mahendra Lalwani. Identification of Islanding Events in Utility Grid with Renewable Energy Penetration Using Current Based Passive Method. IEEE Access 2021, 9, 1 -1.

AMA Style

Nagendra Kumar Swarnkar, Om Prakash Mahela, Baseem Khan, Mahendra Lalwani. Identification of Islanding Events in Utility Grid with Renewable Energy Penetration Using Current Based Passive Method. IEEE Access. 2021; 9 ():1-1.

Chicago/Turabian Style

Nagendra Kumar Swarnkar; Om Prakash Mahela; Baseem Khan; Mahendra Lalwani. 2021. "Identification of Islanding Events in Utility Grid with Renewable Energy Penetration Using Current Based Passive Method." IEEE Access 9, no. : 1-1.

Original research paper
Published: 28 June 2021 in IET Generation, Transmission & Distribution
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This paper introduced an advanced algorithm making hybrid use of Stockwell transform (ST), Hilbert transform (HT) and Alienation coefficient (ACF) for identification, classification and to locate faulty events on transmission line. Signals of Current are processed by application of ST, HT and ACF for computing S-index, H-index and A-index, respectively. These indices are multiplied element by element to compute proposed fault index (FI). A threshold magnitude is decided after testing the algorithm during different fault scenarios and faulty events are recognized when FI exceeds this threshold magnitude. Faults are categorized by identifying the number of phases which are faulty in nature and a ground fault index (GFI). GFI is designed by processing the zero sequence current using ST and used to identify involvement of ground during fault event. A mathematical formulation is framed to estimate location of faults on transmission line. Fault location has been estimated with a mean error less than 1%. Investigated faults include phase to ground (PGF), double phase (PPF), double phase to ground (PPGF) and three phase to ground (TPGF). Algorithm is found effective for faulty scenario such as fault impedance variations, fault incidence angle (FIA) variations, reverse power flow, effect of line loading, effect of noise, transient faults, off-nominal frequency, and presence of harmonic components. Algorithm is also effective for discriminating switching transients from faulty conditions. Effective performance of the algorithm is established by comparing with fault detection and classification approach based on alienation coefficients, discrete Fourier transform (DFT) and time-frequency approach. Study is performed on a two terminal transmission line in MATLAB/Simulink environment. Effectiveness of the algorithm is also established on a real time transmission grid of Rajasthan state of India.

ACS Style

Abhishek Gupta; Ramesh Kumar Pachar; Baseem Khan; Om Prakash Mahela; Sanjeevikumar Padmanaban; Fellow Iet. A multivariable transmission line protection scheme using signal processing techniques. IET Generation, Transmission & Distribution 2021, 1 .

AMA Style

Abhishek Gupta, Ramesh Kumar Pachar, Baseem Khan, Om Prakash Mahela, Sanjeevikumar Padmanaban, Fellow Iet. A multivariable transmission line protection scheme using signal processing techniques. IET Generation, Transmission & Distribution. 2021; ():1.

Chicago/Turabian Style

Abhishek Gupta; Ramesh Kumar Pachar; Baseem Khan; Om Prakash Mahela; Sanjeevikumar Padmanaban; Fellow Iet. 2021. "A multivariable transmission line protection scheme using signal processing techniques." IET Generation, Transmission & Distribution , no. : 1.

Journal article
Published: 22 June 2021 in IEEE Access
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The presented work in this paper deals with various step sizes used in incremental conductance (INC) related to the maximum power point tracking (MPPT) technique. In the solar photovoltaic system, the variable step size selection method for INC is proposed and compared. The MATLAB/Simulink and hardware setup are used for assessing and analyzing step size methods. The variable step size (DVS), fixed step size (DFS) are comprehensively studied and compared. This DVS method is having a lower ON delay time $\left ({{T_{d_{ON}}} }\right)$ as 148 msec as regard to 164 msec in the DFS method. On the other hand, the lowest peak-peak oscillations in load current as 0.04 amp for DVS as compared to 0.5A for the DFS method, lower peak current as 1.96A for DVS as compare to 2.37A for the DFS method. In this way, the performance of the DVS method is found superior as it is analyzed and compared with the DFS algorithm.

ACS Style

Ankur Kumar Gupta; Rupendra Kumar Pachauri; Tanmoy Maity; Yogesh K. Chauhan; Om Prakash Mahela; Baseem Khan; Pankaj Kumar Gupta. Effect of Various Incremental Conductance MPPT Methods on the Charging of Battery Load Feed by Solar Panel. IEEE Access 2021, 9, 1 -1.

AMA Style

Ankur Kumar Gupta, Rupendra Kumar Pachauri, Tanmoy Maity, Yogesh K. Chauhan, Om Prakash Mahela, Baseem Khan, Pankaj Kumar Gupta. Effect of Various Incremental Conductance MPPT Methods on the Charging of Battery Load Feed by Solar Panel. IEEE Access. 2021; 9 ():1-1.

Chicago/Turabian Style

Ankur Kumar Gupta; Rupendra Kumar Pachauri; Tanmoy Maity; Yogesh K. Chauhan; Om Prakash Mahela; Baseem Khan; Pankaj Kumar Gupta. 2021. "Effect of Various Incremental Conductance MPPT Methods on the Charging of Battery Load Feed by Solar Panel." IEEE Access 9, no. : 1-1.

Review
Published: 17 June 2021 in IEEE Access
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This paper describes a comprehensive review of microgrid control mechanism and impact assessment for hybrid grid. Building the model of sustained energy growth is one of the actions to achieve the Sustainable Development Objective (SDO) and change the global fossil fuel system. For co-operation in the development of one independent supplier of renewable energy, the microgrid is essential. Hybrid solar energy microgrid is also a solution for reducing fossil fuel consumption and providing an environmentally sustainable solution to rising rural electricity demand. The most common renewable energy options in the microgrid are solar photovoltaics, wind turbines and biomass. The environmentally sustainable and technologically innovative installation is convenient everywhere. Hybrid microgrid-based renewable energy, however, is confronted, given its intermittent and variable source efficiency, by challenges such as voltage instability, frequency instability, charge malfunction and power quality problems. The paper thus offers a critical overview of the micro grid growth, economic analysis and control strategy.

ACS Style

Shiv Prakash Bihari; Pradip Kumar Sadhu; Kumari Sarita; Baseem Khan; L. D. Arya; R. K. Saket; D. P. Kothari. A Comprehensive Review of Microgrid Control Mechanism and Impact Assessment for Hybrid Renewable Energy Integration. IEEE Access 2021, 9, 1 -1.

AMA Style

Shiv Prakash Bihari, Pradip Kumar Sadhu, Kumari Sarita, Baseem Khan, L. D. Arya, R. K. Saket, D. P. Kothari. A Comprehensive Review of Microgrid Control Mechanism and Impact Assessment for Hybrid Renewable Energy Integration. IEEE Access. 2021; 9 ():1-1.

Chicago/Turabian Style

Shiv Prakash Bihari; Pradip Kumar Sadhu; Kumari Sarita; Baseem Khan; L. D. Arya; R. K. Saket; D. P. Kothari. 2021. "A Comprehensive Review of Microgrid Control Mechanism and Impact Assessment for Hybrid Renewable Energy Integration." IEEE Access 9, no. : 1-1.

Journal article
Published: 25 May 2021 in IEEE Access
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Short-term hydrothermal scheduling (STHTS) is a highly non-linear, multi-model, non-convex, and multi-dimensional optimization problem that has been worked upon for about 5 decades. Many research articles have been published in solving different test cases of STHTS problem, while establishing the superiority of one type of optimization algorithm over the type, in finding the near global best solution of these complex problems. This paper presents the implementation of an improved version of a variant of the Particle Swarm Optimization algorithm (PSO), known as Accelerated Particle Swarm Optimization (APSO) on three benchmark test cases of STHTS problems. The adaptive and variable nature of the local and global search coefficients for the proposed APSO significantly improve its performance in obtaining the optimal solution for the STHTS test cases. Two of these cases are non-cascaded cases of STHTS problem (NCSTHTS) and one case is cascaded case of STHTS problem (CSTHTS). The results are compared with the results of the previous implementations of the other algorithms as presented in the literature. Due to the stochastic nature of the meta-heuristic algorithms, the parametric and non-parametric statistical tests have been implemented to establish the superiority of results of one type of algorithm over the results of the other type of algorithms.

ACS Style

Muhammad Salman Fakhar; Syed Abdul Rahman Kashif; Sheroze Liaquat; Akhtar Rasool; Sanjeevikumar Padmanaban; Muhammad Ahmad Iqbal; Muhammad Anas Baig; Baseem Khan. Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling. IEEE Access 2021, 9, 77784 -77797.

AMA Style

Muhammad Salman Fakhar, Syed Abdul Rahman Kashif, Sheroze Liaquat, Akhtar Rasool, Sanjeevikumar Padmanaban, Muhammad Ahmad Iqbal, Muhammad Anas Baig, Baseem Khan. Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling. IEEE Access. 2021; 9 ():77784-77797.

Chicago/Turabian Style

Muhammad Salman Fakhar; Syed Abdul Rahman Kashif; Sheroze Liaquat; Akhtar Rasool; Sanjeevikumar Padmanaban; Muhammad Ahmad Iqbal; Muhammad Anas Baig; Baseem Khan. 2021. "Implementation of APSO and Improved APSO on Non-Cascaded and Cascaded Short Term Hydrothermal Scheduling." IEEE Access 9, no. : 77784-77797.

Journal article
Published: 17 May 2021 in IEEE Access
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In this article, a hybrid Artificial Neural Network - Newton Raphson (ANN-NR) is introduced to mitigate the undesired lower-order harmonic content in the cascaded H-Bridge multilevel inverter for solar photovoltaic (PV). Harmonics are extracted by the excellent choice of opting switching angles by exploiting the Selective Harmonic Elimination (SHE) PWM technique accompanying a unified algorithm in order to optimize and reduce the Total Harmonic Distortion (THD). ANN is trained with optimum switching angles, and the estimates generated by the ANN are the initial guess for NR. In this study, the CHB-MLI is combined with a traditional boost converter, it boosts the PV voltage to a superior dc-link voltage Perturb and Observe (P&O) based Maximum Power Point Tracking (MPPT) algorithm is used for getting a stable output and efficient operation of solar PV. The proposed system is proved over an eleven-level H-bridge inverter, the work is carried out in MATLAB/Simulink environment, and the respective results are confirmed that the proposed technique is efficient, and offers an actual firing angles with a few iterations results in a better capability of confronting local optima values. The suggested algorithm is justified by the experimental development of eleven-level cascaded H-bridge inverter.

ACS Style

Sanjeevikumar Padmanaban; C. Dhanamjayulu; Baseem Khan. Artificial Neural Network and Newton Raphson (ANN-NR) Algorithm Based Selective Harmonic Elimination in Cascaded Multilevel Inverter for PV Applications. IEEE Access 2021, 9, 75058 -75070.

AMA Style

Sanjeevikumar Padmanaban, C. Dhanamjayulu, Baseem Khan. Artificial Neural Network and Newton Raphson (ANN-NR) Algorithm Based Selective Harmonic Elimination in Cascaded Multilevel Inverter for PV Applications. IEEE Access. 2021; 9 ():75058-75070.

Chicago/Turabian Style

Sanjeevikumar Padmanaban; C. Dhanamjayulu; Baseem Khan. 2021. "Artificial Neural Network and Newton Raphson (ANN-NR) Algorithm Based Selective Harmonic Elimination in Cascaded Multilevel Inverter for PV Applications." IEEE Access 9, no. : 75058-75070.

Journal article
Published: 12 May 2021 in Electronics
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Redundancy techniques are commonly used to design radiation- and fault-tolerant circuits for space applications, to ensure high reliability. However, higher reliability often comes at a cost of increased usage of hardware resources. Triple Modular Redundancy (TMR) ensures full single fault masking, with a >200% power and area overhead cost. TMR/Simplex ensures full single fault masking with a slightly more complicated circuitry, inefficient use of resource and a >200% power and area overhead cost, but with higher reliability than that of TMR. In this work, a high-reliability Spatial and Time Redundancy (TR) hybrid technique, which does not abandon a working module and is applicable for radiation hardening of half-duty limited DC-DC converters, is proposed and applied to the design of a radiation-tolerant digital controller for a Dual-Switch Forward Converter. The technique has the potential of double fault masking with a <2% increase in resource overhead cost compared to TMR. Moreover, for a Simplex module failure rate, λ, of 5%, the Reliability Improvement Factor (RIF) over the Simplex system is 20.8 and 500 for the proposed technique’s two- and three-module implementations, respectively, compared to a RIF over the Simplex system of only 7.25 for TMR and 14.3 for the regular TMR/Simplex scheme.

ACS Style

Solomon Banteywalu; Getachew Bekele; Baseem Khan; Valentijn De Smedt; Paul Leroux. A High-Reliability Redundancy Scheme for Design of Radiation-Tolerant Half-Duty Limited DC-DC Converters. Electronics 2021, 10, 1146 .

AMA Style

Solomon Banteywalu, Getachew Bekele, Baseem Khan, Valentijn De Smedt, Paul Leroux. A High-Reliability Redundancy Scheme for Design of Radiation-Tolerant Half-Duty Limited DC-DC Converters. Electronics. 2021; 10 (10):1146.

Chicago/Turabian Style

Solomon Banteywalu; Getachew Bekele; Baseem Khan; Valentijn De Smedt; Paul Leroux. 2021. "A High-Reliability Redundancy Scheme for Design of Radiation-Tolerant Half-Duty Limited DC-DC Converters." Electronics 10, no. 10: 1146.

Preprint content
Published: 11 May 2021
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This paper proposes a security algorithm based on thewavelet-alienation-neural technique for detecting, classifying, and locating faults on Thyristor-Controlled Series compensator (TCSC) compensated lines. A fault index has been calculated using wavelet transform and alienation coefficients with post-fault current signals measured/ sampled for quarter cycle time at both near and far end buses for fault detection and classification. The location of the fault is predicted using an Artificial Neural Network (ANN) after the fault has been diagnosed. Approximate coefficients (quarter cycle time) of both voltage and current signals, from both buses, were provided as input to ANN. Various case studies, such as variations in TCSC position, fault location, sampling frequency, power flow path, incipient angle of fault, TCSC control strategy, fault resistance, and load switching conditions, have verified the robustness of the proposed safety system.

ACS Style

Bhuvnesh Rathore; Amit Gangwar; Om Prakash Mahela; Baseem Khan; Sanjeevikumar padmanaban. A Fast Protection Scheme for TCSC Compensated Transmission Line Using Wavelet-Alienation-Neural Technique. 2021, 1 .

AMA Style

Bhuvnesh Rathore, Amit Gangwar, Om Prakash Mahela, Baseem Khan, Sanjeevikumar padmanaban. A Fast Protection Scheme for TCSC Compensated Transmission Line Using Wavelet-Alienation-Neural Technique. . 2021; ():1.

Chicago/Turabian Style

Bhuvnesh Rathore; Amit Gangwar; Om Prakash Mahela; Baseem Khan; Sanjeevikumar padmanaban. 2021. "A Fast Protection Scheme for TCSC Compensated Transmission Line Using Wavelet-Alienation-Neural Technique." , no. : 1.

Journal article
Published: 07 May 2021 in IEEE Access
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This research work has designed an algorithm to identify islanding events using the current signals in a distribution grid interfaced with renewable energy (RE) sources situated in remote areas. A median-based islanding recognition factor (MIRF) is designed by processing the current signal using Stockwell transform (ST). A current rate of change of islanding recognition factor (CRCIRF) is computed by differentiating the root mean square (RMS) current concerning time. The MIRF and CRCIRF are multiplied element by element to calculate the current-based islanding recognition factor (IRFC) used to recognize islanding events and non-islanding events. Simple decision rules are used to discriminate Islanding events from the faulty and the operational events by comparing peak magnitude of IRFC with pre-set threshold values. This IDM effectively recognizes islanding events in the presence of noise with 10 dB signal-to-noise ratio (SNR) level. The performance of IDM is established on a practical distribution feeder. Developed work is executed in MATLAB/Simulink.

ACS Style

Om Prakash Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Sanjeevikumar Padmanaban. Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform. IEEE Access 2021, 9, 69798 -69813.

AMA Style

Om Prakash Mahela, Yagya Sharma, Shoyab Ali, Baseem Khan, Sanjeevikumar Padmanaban. Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform. IEEE Access. 2021; 9 ():69798-69813.

Chicago/Turabian Style

Om Prakash Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Sanjeevikumar Padmanaban. 2021. "Estimation of Islanding Events in Utility Distribution Grid With Renewable Energy Using Current Variations and Stockwell Transform." IEEE Access 9, no. : 69798-69813.

Journal article
Published: 05 May 2021 in Computers & Electrical Engineering
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This research proposed the data acquisition system (DAS), which has a capability to collect real-time voltage and current at variable load resistance during an experimental characterization analysis of 3 × 3 size, photo voltaic (PV) system, under partial shading conditions (PSCs). In addition, the system is economical and minimizes the testing period for PV system characterization relative to traditional approaches. Analogue voltage and current sensors are integrated with the open-source Arduino platform to quantify and store real-time performance data in the SD card assembly. Performance parameters such as voltage and power at global maximum power point (GMPP), with minimized power loss (PL) and improved fill factor (FF) shows the effectiveness of the proposed system under the PSCs. Real-time hardware is developed and its performance is compared with the MATLAB/Simulink performance, with percentage errors as low as 0.48%, 1.95% and 1.37% under different shading case.

ACS Style

Rupendra Kumar Pachauri; Om Prakash Mahela; Baseem Khan; Ashok Kumar; Sunil Agarwal; Hassan Haes Alhelou; Jianbo Bai. Development of arduino assisted data acquisition system for solar photovoltaic array characterization under partial shading conditions. Computers & Electrical Engineering 2021, 92, 107175 .

AMA Style

Rupendra Kumar Pachauri, Om Prakash Mahela, Baseem Khan, Ashok Kumar, Sunil Agarwal, Hassan Haes Alhelou, Jianbo Bai. Development of arduino assisted data acquisition system for solar photovoltaic array characterization under partial shading conditions. Computers & Electrical Engineering. 2021; 92 ():107175.

Chicago/Turabian Style

Rupendra Kumar Pachauri; Om Prakash Mahela; Baseem Khan; Ashok Kumar; Sunil Agarwal; Hassan Haes Alhelou; Jianbo Bai. 2021. "Development of arduino assisted data acquisition system for solar photovoltaic array characterization under partial shading conditions." Computers & Electrical Engineering 92, no. : 107175.

Journal article
Published: 27 April 2021 in IEEE Access
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This paper introduces a new model to improve the wind power plant performance by modeling its reactive power demand. It develops a probabilistic model based on prediction interval to help better modeling of the reactive power demands of wind unit which needs to be compensated by the static VAr compensator (SVC). This is made possible by the use of a non-parametric neural network (NN) based model using the lower and upper bound estimation (LUBE) method. To avoid the instability arising due to the nonlinear and complex nature of NN, the idea of combined prediction intervals is used here. Due to the highly nonlinear and non-stationary characteristics of the reactive power pattern consumed in the wind power plant, a new optimization algorithm based on $\theta $ -symbiotic organisms search ( $\theta $ -SOS) is proposed to train the LUBE model parameters in the polar coordinates. In addition, a two-phase modification method is developed to enhance the local search ability of SOS and avoid premature convergence issue. The performance of the proposed model on the experimental Phasor Measurement Unit (PMU) data of a wind unit shows that the model can help to improve the performance of the wind SVC, effectively.

ACS Style

Zhen Wang; Baohua Zhang; MohammadAmin Mobtahej; Aliasghar Baziar; Baseem Khan. Advanced Reactive Power Compensation of Wind Power Plant Using PMU Data. IEEE Access 2021, 9, 67006 -67014.

AMA Style

Zhen Wang, Baohua Zhang, MohammadAmin Mobtahej, Aliasghar Baziar, Baseem Khan. Advanced Reactive Power Compensation of Wind Power Plant Using PMU Data. IEEE Access. 2021; 9 ():67006-67014.

Chicago/Turabian Style

Zhen Wang; Baohua Zhang; MohammadAmin Mobtahej; Aliasghar Baziar; Baseem Khan. 2021. "Advanced Reactive Power Compensation of Wind Power Plant Using PMU Data." IEEE Access 9, no. : 67006-67014.

Journal article
Published: 20 April 2021 in IEEE Access
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This paper investigates the effect of data integrity attacks on the central control of the microgrids (MGs), which can lead to severe blackouts and load shedding. It assesses this cyber attack from the steady state and optimal scheduling point of view. In order to stop the cyber hacking, a new deep learning-based framework has been developed based on the generative adversarial networks (GANs). In this framework, two networks compete with each other, wherein the first network generates fake data, and the second one is responsible for the data classification. In order to get into the most optimal features, a new optimization method based on a modified teaching-learning based optimization (TLBO) algorithm is also devised to reinforce the GAN model and help a better matching training process. In addition, a new modification is introduced for TLBO to avoid premature convergence and provide high population diversity. To show the effectiveness of the proposed framework, a real dataset of several smart metering devices in a MG has been tested. Results illustrate the high performance of the proposed framework, comparing to the well-known conventional detection frameworks with hit rate of 93.11%, miss rate of 6.89%, false alarm rate of 7.76% and correct reject rate of 92.24%.

ACS Style

Ziqiang Tang; Yubin Lin; Mahdi Vosoogh; Navid Parsa; Aliasghar Baziar; Baseem Khan. Securing Microgrid Optimal Energy Management Using Deep Generative Model. IEEE Access 2021, 9, 63377 -63387.

AMA Style

Ziqiang Tang, Yubin Lin, Mahdi Vosoogh, Navid Parsa, Aliasghar Baziar, Baseem Khan. Securing Microgrid Optimal Energy Management Using Deep Generative Model. IEEE Access. 2021; 9 ():63377-63387.

Chicago/Turabian Style

Ziqiang Tang; Yubin Lin; Mahdi Vosoogh; Navid Parsa; Aliasghar Baziar; Baseem Khan. 2021. "Securing Microgrid Optimal Energy Management Using Deep Generative Model." IEEE Access 9, no. : 63377-63387.

Journal article
Published: 25 March 2021 in Informatics
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This paper has introduced an algorithm for the identification of islanding events in the remotely located distribution grid with renewable energy (RE) sources using the voltage signals. Voltage signal is processed using Stockwell transform (ST) to compute the median-based islanding recognition factor (MIRF). The rate of change in the root mean square (RMS) voltage is computed by differentiating the RMS voltage with respect to time to compute the voltage rate of change in islanding recognition factor (VRCIRF). The proposed voltage-based islanding recognition factor (IRFV) is computed by multiplying the MIRF and VRCIRF element to element. The islanding event is discriminated from the faulty and operational events using the simple decision rules using the peak magnitude of IRFV by comparing peak magnitude of IRFV with pre-set threshold values. The proposed islanding detection method (IDM) effectively identified the islanding events in the presence of solar energy, wind energy and simultaneous presence of both wind and solar energy at a fast rate in a time period of less than 0.05 cycles compared to the voltage change rate (ROCOV) and frequency change rate (ROCOF) IDM that detects the islanding event in a time period of 0.25 to 0.5 cycles. This IDM provides a minimum non-detection zone (NDZ). This IDM efficiently discriminated the islanding events from the faulty and switching events. The proposed study is performed on an IEEE-13 bus test system interfaced with renewable energy (RE) generators in a MATLAB/Simulink environment. The performance of the proposed IDM is better compared to methods based on the use of ROCOV, ROCOF and discrete wavelet transform (DWT).

ACS Style

Om Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Akhil Garg. Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids. Informatics 2021, 8, 21 .

AMA Style

Om Mahela, Yagya Sharma, Shoyab Ali, Baseem Khan, Akhil Garg. Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids. Informatics. 2021; 8 (2):21.

Chicago/Turabian Style

Om Mahela; Yagya Sharma; Shoyab Ali; Baseem Khan; Akhil Garg. 2021. "Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids." Informatics 8, no. 2: 21.

Original research paper
Published: 15 March 2021 in IET Renewable Power Generation
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Large size photovoltaic (PV) systems face a large number of issues based on malfunction and unfavourable climatic conditions such as partial shading conditions (PSCs). These PSCs are the major causes of PV systems’ performance degradation. In this paper, a symmetric matrix (SM) game puzzle is used to reconfigure the electrical connections of the PV array system. Present shade dispersion methodology is based on the ‘physical reallocation of PV module‐fixed electrical connections’ principle. Modification in the electrical connections of conventional total cross‐tied (TCT) PV array configuration introduces a new ‘SM‐TCT’ configuration. An extensive comparative study of conventional TCT and novel‐TCT (NTCT) configurations with proposed SM‐TCT configuration prove the effectiveness to achieve higher performance. The MATLAB/Simulink results are obtained on the basis of the non‐linear nature of current‐voltage and power‐voltage characteristics. SM‐TCT, Shape‐do‐Ku, NTCT and TCT configurations are examined under three realistic PSCs in terms of power and voltage at global maximum power point, improved fill factor, reduced power losses, performance ratio and power enhancement.

ACS Style

Rupendra Kumar Pachauri; Jianbo Bai; Isha Kansal; Om Prakash Mahela; Baseem Khan. Shade dispersion methodologies for performance improvement of classical total cross‐tied photovoltaic array configuration under partial shading conditions. IET Renewable Power Generation 2021, 15, 1796 -1811.

AMA Style

Rupendra Kumar Pachauri, Jianbo Bai, Isha Kansal, Om Prakash Mahela, Baseem Khan. Shade dispersion methodologies for performance improvement of classical total cross‐tied photovoltaic array configuration under partial shading conditions. IET Renewable Power Generation. 2021; 15 (8):1796-1811.

Chicago/Turabian Style

Rupendra Kumar Pachauri; Jianbo Bai; Isha Kansal; Om Prakash Mahela; Baseem Khan. 2021. "Shade dispersion methodologies for performance improvement of classical total cross‐tied photovoltaic array configuration under partial shading conditions." IET Renewable Power Generation 15, no. 8: 1796-1811.

Journal article
Published: 11 February 2021 in IEEE Access
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Nowadays, microgrids with hybrid renewable energy sources are increasing, and it is a promising solution to electrify remote areas where distribution network expansion is not feasible or economical. This study aims to find an ideal hybrid system grounded on solar, wind, diesel, biomass, hydro, and battery. This study utilizes the hybrid optimization model for electric renewable (HOMER) software to size the important components, perform technical, financial evaluation, renewable factor, estimate the harmful emissions, and sensitivity analysis. For optimum system selection, the lowest cost of energy is used as the criteria. Four different configurations of renewable energy sources are analyzed and found PV-WT-MH-CT-BT-DG-BG is the most feasible hybrid system amongst all configurations. The proposed PV-WT-MH-CT-BT-DG-BG hybrid system is more economic as the lowest cost of energy 0.196$, low operating cost 36,184$, low net present cost 831,217$. Also, this hybrid system is more environmentally friendly as it has less emission and a high renewable factor of 81.2%.

ACS Style

Yashwant Sawle; Siddharth Jain; Sanjana Babu; Ashwini Ramachandran Nair; Baseem Khan. Prefeasibility Economic and Sensitivity Assessment of Hybrid Renewable Energy System. IEEE Access 2021, 9, 28260 -28271.

AMA Style

Yashwant Sawle, Siddharth Jain, Sanjana Babu, Ashwini Ramachandran Nair, Baseem Khan. Prefeasibility Economic and Sensitivity Assessment of Hybrid Renewable Energy System. IEEE Access. 2021; 9 ():28260-28271.

Chicago/Turabian Style

Yashwant Sawle; Siddharth Jain; Sanjana Babu; Ashwini Ramachandran Nair; Baseem Khan. 2021. "Prefeasibility Economic and Sensitivity Assessment of Hybrid Renewable Energy System." IEEE Access 9, no. : 28260-28271.

Journal article
Published: 18 January 2021 in IEEE Access
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Fault analysis (detection, classification and location) of transmission network is of great importance in power system. A Wavelet-Alienation-Neural (WAN) technique has been developed for the fault analysis of Unified Power Flow Controller (UPFC) compensated transmission network. The detection and classification of various outages are accomplished by alienation of wavelet based approximate coefficients computed from current signals. The precise location of faults is carried out by an Artificial Neural Network fed from estimated approximate coefficients computed from voltage and current signals of the same quarter cycle. The robustness of the algorithm is proved with the case studies of varying fault locations, sampling frequency, system parameters, effects of noise, fault incipient angle, different control strategies and fault path impedances.

ACS Style

Bhuvnesh Rathore; Om Prakash Mahela; Baseem Khan; Sanjeevikumar Padmanaban. Protection Scheme using Wavelet-Alienation-Neural Technique for UPFC Compensated Transmission Line. IEEE Access 2021, 9, 13737 -13753.

AMA Style

Bhuvnesh Rathore, Om Prakash Mahela, Baseem Khan, Sanjeevikumar Padmanaban. Protection Scheme using Wavelet-Alienation-Neural Technique for UPFC Compensated Transmission Line. IEEE Access. 2021; 9 ():13737-13753.

Chicago/Turabian Style

Bhuvnesh Rathore; Om Prakash Mahela; Baseem Khan; Sanjeevikumar Padmanaban. 2021. "Protection Scheme using Wavelet-Alienation-Neural Technique for UPFC Compensated Transmission Line." IEEE Access 9, no. : 13737-13753.