Mohammad A. Abido’s research while affiliated with King Fahd University of Petroleum and Minerals and other places

... Applications in fluid dynamics [21], robotics [22] and control systems [23] have all been investigated. Whilst the utilization of Koopman in order to develop linear systems capable of control has been researched heavily, with many models including optimal controls [24], Model Predictive Controllers (MPC) [25], Linear Quadratic Controllers (LQR) [26], all being successfully developed through the implementation of EDMD with control (EDMDc) [27] via analytical solutions or the development of NN's. Another advantage of using a data-driven method is that it does not require system knowledge, and the nonlinear system can be completely unknown [28,29]. ...

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Deep Learning Based Dynamics Identification and Linearization of Orbital Problems using Koopman Theory

... The computational simulations were conducted using the thermodynamics software package "Cantera" (version 2.6.0) as an add-on library to the Python programming language (version 3.8.8) [76][77][78][79]. All needed thermodynamic properties of the water (as a liquid, a vapor, or as a mixture of both) were accessed directly through the Cantera object "Water" as a pure fluid with its equation of state based on published properties [80][81]. ...

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Condenser Pressure Influence on Ideal Steam Rankine Power Vapor Cycle using the Python Extension Package Cantera for Thermodynamics

... Direct current microgrids work with two-wire cables, but AC microgrids work with three-or four-wire cables. In the DCmicrogrid, there is no reactive power flow and voltage control depends only on active power flow [74,75]. Reactive energy flow controls the voltage in an AC-microgrid, and active power injection is typically used to limit the power available in a specific area [76,77]. ...

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Droop control strategy in inverter‐based microgrids: A brief review on analysis and application in islanded mode of operation

... Regarding dependability, efficiency, control simplicity, integrating renewable energy sources, and connecting DC loads. The DC microgrids have proven superior to AC microgrids [2,3]. DC microgrids also don't have problems with synchronization, harmonics, reactive power regulation, or frequency control, which isn't the case with traditional AC systems. ...

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Dual loop voltage droop regulated controller for DC microgrid using hybrid PSO and GGO algorithms

... The energy output for wind power fluctuates with wind speed at different heights, which could be a disadvantage if the area/specific height does not have that much wind blowing or if wind speed timing is not known. In addition, such a lack of knowledge creates operational challenges for the power system operators [5]. Therefore, effective wind speed forecasting can be a game changer in tackling the mentioned challenges by better-utilizing wind energy resources. ...

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Deep learning framework for wind speed prediction in Saudi Arabia

... The conventional single-phase shift control method of the three-phase DAB has many disadvantages in fault conditions, including the high peak current, which can harm the semiconductor switches. Hence, asymmetrical duty cycle control was suggested to enable the three-phase DAB to ride through faults while realizing soft-switching operation [143][144][145][146]. ...

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A Comprehensive Survey on Advancement and Challenges of DC Microgrid Protection

... Optimization algorithms have become a cornerstone of tackling various electrical engineering challenges. From optimizing the design of electric machines, transformers, and transmission lines to enhancing the performance of fuel cells, photovoltaic modules, power system stabilizers, etc., these techniques offer powerful solutions [9][10][11][12]. In the context of parameter estimation, optimization techniques are employed to establish a correspondence between observed data and their predicted counterparts. ...

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Identification of Transformer Parameters Using Dandelion Algorithm

... A case worth mentioning is the optimization of low-inertia islanded microgrids' frequency stability using AI algorithms. The case is discussed by Hamanah (2024) in how optimized virtual inertia control, through AI capabilities, can significantly improve the dynamic stability and restore a very important factor in virtual inertia for reliable power system maintenance. This addresses typical problems of DG systems commonly replacing conventional synchronous generators with negative impacts on the frequency stability. ...

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Leveraging Artificial Intelligence for Enhanced Distributed Control Strategies in Low-Inertia Microgrids_ Current Approaches, Challenges, and Quantitative Assessment Methods

... HOMER Pro stands as the globally recognized standard for microgrid and hybrid energy system analysis. Its capabilities enable the precise modeling of renewable resources, hourly load profiles, and meticulous configuration of components to identify the most cost-effective solution [44,46]. Moreover, HOMER effectively manages potential modeling uncertainties by exploring hybridization scenarios and diversified alternatives. ...

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Techno-economic evaluation and improved sizing optimization of green hydrogen production and storage under higher wind penetration in Aqaba Gulf

... There are two methods for determining the junction temperature, i.e., electricaland optical-based techniques. The estimation based on electrical techniques includes temperature-sensitive electrical parameters (TSEPs) [12,15] and temperature-sensitive electrical devices (TSEDs) [13,16]. TSEP techniques rely on electrical parameters, such as turn-off delay [17], collector-emitter voltage [18], and on-state resistance [19], to estimate T j . ...

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Multipoint Thermal Sensing System for Power Semiconductor Devices Utilizing Fiber Bragg Gratings