ORCID Profile
0000-0002-5068-440X
Current Organisation
Monash University
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Publisher: Institution of Engineering and Technology (IET)
Date: 02-09-2020
Publisher: IEEE
Date: 09-2019
Publisher: IEEE
Date: 18-10-2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: IEEE
Date: 04-07-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: MDPI AG
Date: 14-02-2022
Abstract: The current work contributes an estimate of the time-frequency characteristics of a leakage current in assessing the health condition of a polluted polymeric insulator. A 33 kV polymer insulator string was subjected to a series of laboratory tests under a range of environmental conditions, including pollution, wetting rate (WR), non-soluble deposit density (NSDD), and non-uniform distribution pollution (FT/B). The temporal and frequency features of the leakage current were then extracted and used as assessment indicators for insulator conditions based on laboratory test findings. Two indices were generated from the leakage current waveform in the time domain: the curve slope index (F1), which is determined by measuring the inclination of the curve between two successive time peaks of the leakage current, and the crest factor indicator (F2). The frequency domain of the leakage current signal was used to calculate the other two indices. These are the odd harmonic indicators derived from the odd frequency harmonics of the leakage current up to the 9th component (F3) and the 5th to 3rd harmonics ratio (F4). The findings showed that the suggested indicators were capable of evaluating insulator conditions. Finally, the confusion matrix for the experimental and prediction results obtained with the proposed indices was used to assess which indicator performed the best. Therefore, the analysis suggests an alternative and effective method for estimating the health condition of a polluted insulator through leakage current characteristics obtained in the time and frequency domains.
Publisher: IEEE
Date: 09-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: IEEE
Date: 15-05-2022
Publisher: Elsevier BV
Date: 2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Publisher: MDPI AG
Date: 16-03-2022
DOI: 10.3390/ELECTRONICS11060919
Abstract: The use of sensitive electronic devices has increased recently hence, power quality has become an important factor in electrical power systems. The various disturbances occurring in the electrical network (harmonics, voltage swells, sags, etc.) may lead to technical-economic damage that negatively impacts the quality of the supplied power. Therefore, the use of the Unified Power Quality Conditioner (UPQC) is a promising solution to limit such damage. In this paper, a nine-level structure of the proposed standardized power quality conditioner is analyzed. The conditioner is connected between a photovoltaic system (UPQC-PV) and a smart grid. Then, a new approach to generate switches for the switches of both the series and parallel converters is proposed. This modulation technique relies on an adaptive hysteresis band (AHB) that is determined via a fuzzy logic controller in order to obtain the required modified output voltage with minimum distortion. Simulation results, using MATLAB/Simulink, of different disturbance scenarios that may occur in the network are presented to verify the accuracy of the proposed fuzzy-logic-based AHB control system. Compared with the conventional SPWM, it is found that the proposed AHB modulation technique significantly improves the power quality in terms of producing less total harmonic distortion in both the voltage and current waveforms.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: MDPI AG
Date: 13-12-2019
DOI: 10.3390/EN12244752
Abstract: Whereas power-electronics-based power systems are expected to enable more integration of renewable energy sources, they could pose crucial challenges including stability issues due to the Thévenin impedance seen by inverters. Such problems could be mitigated by enabling the inverters to estimate the grid impedance by including a grid impedance estimation technique into their control loop. However, one aspect which has been overlooked thus far is that the accuracy of such grid impedance estimation techniques is significantly affected by various grid conditions. For instance, the unbalance in three-phase power systems causes unwanted oscillations at double the fundamental frequency in the inverters control loops. Therefore, this paper proposes a simple and reliable online estimation of the grid impedance under unbalanced conditions. The technique is based on wide-band impedance estimation incorporated into the control loop of the positive sequence of a three-phase grid-connected inverter equipped with a positive- and negative-sequence control (PNSC) strategy. Additionally, complex curve fitting is utilized to obtain parametric models of the grid impedance. To demonstrate the efficacy of the proposed grid impedance estimation technique, extensive case studies are performed. These include: (1) unbalanced operations of both resistive-inductive (RL) and resistive-inductive-capacitive (RLC) models of the grid, (2) background harmonics, and (3) asymmetrical impedances of the network.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2022
Publisher: Institute of Advanced Engineering and Science
Date: 03-2018
DOI: 10.11591/IJPEDS.V9.I1.PP180-188
Abstract: Battery energy storage system (BESS) is used in many practical applications including uninterruptible power supplies (UPS), portable devices, electrical vehicles and renewable energy systems. To utilize BESS effectively, an efficient control operation is required. Various controllers have been introduced in the open literature. However, they are not considered the best fit due to their limitations. This includes their incapability of handling high-power rating BESS, low noise immunity, short life cycle and limited number of input and output interfaces. In this paper, the programmable logic controller (PLC) is used to control and monitor a 158.8 kWh offline BESS for a typical Malaysian household. TIA Portal V13 software by siemens is used to program the proposed PLC control. Human machine interface(HMI) system is used to monitor and simulate the control performance. The results show that the PLC approach provides an efficient and reliable control of the BESS in which a compact protection against the battery overcharging, under-discharging and overheating is achieved.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: MDPI AG
Date: 25-05-2021
DOI: 10.3390/EN14113059
Abstract: As the integration of large-scale wind energy is increasing into the electricity grids, the role of wind energy suppliers should be investigated as a price-maker as their participation would influence the locational marginal price (LMP) of electricity. The existing bidding strategies for a wind energy supplier faces limitations with respect to the potential cooperation, other competitors’ bidding behavior, network loss, and uncertainty of wind production (WP) and balancing market price (BMP). Hence, to solve these problems, a novel bidding strategy (BS) for a wind power supplier as a price-maker has been proposed in this paper. The new algorithm, called the evolutionary game approach (EGA) inspired hybrid particle swarm optimization and improved firefly algorithm (HPSOIFA), has been proposed to handle the bidding issue. The bidding behavior of power suppliers, including conventional power suppliers, has been encoded as one species to obtain the equilibrium where the EGA can explore dynamically reasonable behavior changes of the opponents. Each species of behavior change has been exploited by the HPSOIFA to improve the optimization solutions. Moreover, a deep learning algorithm, namely deep belief network, has been implemented for improving the accuracy of the forecasting results considering the WP and BMP, and the uncertainty revealed in the WP and BMP has been modeled by quantile regression (QR). Finally, the Shapley value (SV) has been calculated to estimate the benefits of cooperative power suppliers. The presented case studies have verified that the proposed algorithm and the established bidding strategy exhibit higher effectiveness.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer International Publishing
Date: 27-05-2017
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 06-2022
No related grants have been discovered for Nabil Mohammed.