Mohammad Alali - Academia.edu (original) (raw)

Papers by Mohammad Alali

Research paper thumbnail of Use of Lasers in Oral Maxillofacial Surgery; a cross-sectional study done in Riyadh, Saudi Arabia

Archives Of Pharmacy Practice, 2021

Research paper thumbnail of Meta-Analysis on Corneal Changes Following Phacoemulsification in Diabetic vs. Non-Diabetic Cataract Patients

The Egyptian Journal of Hospital Medicine, 2018

Aim of the Study: was to investigate the influence of phacoemulsification on corneal endothelial ... more Aim of the Study: was to investigate the influence of phacoemulsification on corneal endothelial cells and its injury risk factors in diabetic cataract patients and non-diabetic patients. Methods: electronic databases were searched: Scopus, EMBASE, and Google Scholer), PubMed/MEDLINE, Scopus, The Cochrane Library, and Web of Science. Econlit from 1990 to 2017. This was completed with a manual search of references of relevant papers. Risk of bias in methodology of studies was measured using the Newcastle-Ottawa Scale. Results: Observation of corneal endothelial cell density, coefficient of variation and percentage of hexagonal cells preoperatively, 1 day, 1week, 1 and 3 months postoperatively was carried out, and multiple Logistic regression analysis for risk factors of corneal endothelial cell injury was taken. Results: Out of 779 retrieved papers, 9 studies with a total of 1129 individuals were finally included (579 diabetic eyes and 550 non-diabetic eyes). For the dynamic changes between preoperative and postoperative values, significant differences were identified between the two groups in endothelial cell density (ECD) and hexagon cells (HC%) at 1 day, 1 week, 1 month, and 3 months postoperatively, in central corneal thickness (CCT) at 1 month postoperatively, and in coefficient variation (CV) at 1 week and 1 month postoperatively. However, no significant differences were observed in CCT at 1 day, 1 week and 3 months postoperatively or in CV at 1 day and 3 months postoperatively. Conclusion: it could be concluded from the current literature that aged-cataract patients with diabetes mellitus manifested poor tolerability to cataract phacoemulsification surgery in contrast to senile cataract patients.

Research paper thumbnail of Intelligent Line Congestion Prognosis in Active Distribution System Using Artificial Neural Network

2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)

This paper proposes an intelligent line congestion prognosis scheme based on wide-area measuremen... more This paper proposes an intelligent line congestion prognosis scheme based on wide-area measurements, which accurately identifies an impending congestion and the problem causing the congestion. Due to the increasing penetration of renewable energy resources and uncertainty of load/generation patterns in the Active Distribution Networks (ADNs), power line congestion is one of the issues that could happen during peak load conditions or high-power injection by renewable energy resources. Congestion would have devastating effects on both the economical and technical operation of the grid. Hence, it is crucial to accurately predict congestions to alleviate the problem in-time and command proper control actions; such as, power redispatch, incorporating ancillary services and energy storage systems, and load curtailment. We use neural network methods in this work due to their outstanding performance in predicting the nonlinear behavior of the power system. Bayesian Regularization, along with Levenberg-Marquardt algorithm, is used to train the proposed neural networks to predict an impending congestion and its cause. The proposed method is validated using the IEEE 13-bus test system. Utilizing the proposed method, extreme control actions (i.e., protection actions and load curtailment) can be avoided. This method will improve the distribution grid resiliency and ensure the continuous supply of power to the loads.

Research paper thumbnail of Resiliency-Aware Power Management of Microgrids using Agent-based Dynamic Programming and Q-learning

2021 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia), 2021

Appropriate planning and optimization strategies for day-ahead power management play important ro... more Appropriate planning and optimization strategies for day-ahead power management play important roles in efficient operation of Microgrids (MGs). Due to the uncertainties in electricity demand and renewable generations, and the multi-objective (MO) nature of MG power management, conventional optimization techniques have not been as effective in giving satisfactory results. This paper aims at solving the day-ahead power management problem as a MO optimization problem, with a focus on increasing the system's resiliency using an agent-based Dynamic Programming (DP) approach named Value Iteration (VI) and a model-free Q-learning (QL) algorithm. The two objectives of the MO problem are: maximizing load serviceability and minimizing operational cost. Both the approaches are data-driven, and the behavior of the agent of each component of a MG is formulated as a finite-horizon Markov Decision Process (MDP). VI guarantees an optimal solution to the MO problem given the MDP model, and QL has the ability to work under uncertainty and incomplete information. The effectiveness of the two algorithms have been evaluated using a benchmark MG test system.

Research paper thumbnail of Resiliency-Oriented Optimization of Critical Parameters in Multi Inverter-Fed Distributed Generation Systems

Sustainability, 2021

In the modern power grid, with the growing penetration of renewable and distributed energy system... more In the modern power grid, with the growing penetration of renewable and distributed energy systems, the use of parallel inverters has significantly increased. It is essential to achieve stable parallel operation and reasonable power sharing between these parallel inverters. Droop controllers are commonly used to control the power sharing between parallel inverters in an inverter-based microgrid. In this paper, a small signal model of droop controllers with secondary loop control and an internal model-based voltage and current controller is proposed to improve the stability, resiliency, and power sharing of inverter-based distributed generation systems. The distributed generation system’s nonlinear dynamic equations are derived by incorporating the appropriate and accurate models of the network, load, phase locked loop and filters. The obtained model is then trimmed and linearized around its operating point to find the distributed generation system’s state space representation. Moreo...

Research paper thumbnail of Use of Lasers in Oral Maxillofacial Surgery; a cross-sectional study done in Riyadh, Saudi Arabia

Archives Of Pharmacy Practice, 2021

Research paper thumbnail of Meta-Analysis on Corneal Changes Following Phacoemulsification in Diabetic vs. Non-Diabetic Cataract Patients

The Egyptian Journal of Hospital Medicine, 2018

Aim of the Study: was to investigate the influence of phacoemulsification on corneal endothelial ... more Aim of the Study: was to investigate the influence of phacoemulsification on corneal endothelial cells and its injury risk factors in diabetic cataract patients and non-diabetic patients. Methods: electronic databases were searched: Scopus, EMBASE, and Google Scholer), PubMed/MEDLINE, Scopus, The Cochrane Library, and Web of Science. Econlit from 1990 to 2017. This was completed with a manual search of references of relevant papers. Risk of bias in methodology of studies was measured using the Newcastle-Ottawa Scale. Results: Observation of corneal endothelial cell density, coefficient of variation and percentage of hexagonal cells preoperatively, 1 day, 1week, 1 and 3 months postoperatively was carried out, and multiple Logistic regression analysis for risk factors of corneal endothelial cell injury was taken. Results: Out of 779 retrieved papers, 9 studies with a total of 1129 individuals were finally included (579 diabetic eyes and 550 non-diabetic eyes). For the dynamic changes between preoperative and postoperative values, significant differences were identified between the two groups in endothelial cell density (ECD) and hexagon cells (HC%) at 1 day, 1 week, 1 month, and 3 months postoperatively, in central corneal thickness (CCT) at 1 month postoperatively, and in coefficient variation (CV) at 1 week and 1 month postoperatively. However, no significant differences were observed in CCT at 1 day, 1 week and 3 months postoperatively or in CV at 1 day and 3 months postoperatively. Conclusion: it could be concluded from the current literature that aged-cataract patients with diabetes mellitus manifested poor tolerability to cataract phacoemulsification surgery in contrast to senile cataract patients.

Research paper thumbnail of Intelligent Line Congestion Prognosis in Active Distribution System Using Artificial Neural Network

2021 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)

This paper proposes an intelligent line congestion prognosis scheme based on wide-area measuremen... more This paper proposes an intelligent line congestion prognosis scheme based on wide-area measurements, which accurately identifies an impending congestion and the problem causing the congestion. Due to the increasing penetration of renewable energy resources and uncertainty of load/generation patterns in the Active Distribution Networks (ADNs), power line congestion is one of the issues that could happen during peak load conditions or high-power injection by renewable energy resources. Congestion would have devastating effects on both the economical and technical operation of the grid. Hence, it is crucial to accurately predict congestions to alleviate the problem in-time and command proper control actions; such as, power redispatch, incorporating ancillary services and energy storage systems, and load curtailment. We use neural network methods in this work due to their outstanding performance in predicting the nonlinear behavior of the power system. Bayesian Regularization, along with Levenberg-Marquardt algorithm, is used to train the proposed neural networks to predict an impending congestion and its cause. The proposed method is validated using the IEEE 13-bus test system. Utilizing the proposed method, extreme control actions (i.e., protection actions and load curtailment) can be avoided. This method will improve the distribution grid resiliency and ensure the continuous supply of power to the loads.

Research paper thumbnail of Resiliency-Aware Power Management of Microgrids using Agent-based Dynamic Programming and Q-learning

2021 IEEE PES Innovative Smart Grid Technologies - Asia (ISGT Asia), 2021

Appropriate planning and optimization strategies for day-ahead power management play important ro... more Appropriate planning and optimization strategies for day-ahead power management play important roles in efficient operation of Microgrids (MGs). Due to the uncertainties in electricity demand and renewable generations, and the multi-objective (MO) nature of MG power management, conventional optimization techniques have not been as effective in giving satisfactory results. This paper aims at solving the day-ahead power management problem as a MO optimization problem, with a focus on increasing the system's resiliency using an agent-based Dynamic Programming (DP) approach named Value Iteration (VI) and a model-free Q-learning (QL) algorithm. The two objectives of the MO problem are: maximizing load serviceability and minimizing operational cost. Both the approaches are data-driven, and the behavior of the agent of each component of a MG is formulated as a finite-horizon Markov Decision Process (MDP). VI guarantees an optimal solution to the MO problem given the MDP model, and QL has the ability to work under uncertainty and incomplete information. The effectiveness of the two algorithms have been evaluated using a benchmark MG test system.

Research paper thumbnail of Resiliency-Oriented Optimization of Critical Parameters in Multi Inverter-Fed Distributed Generation Systems

Sustainability, 2021

In the modern power grid, with the growing penetration of renewable and distributed energy system... more In the modern power grid, with the growing penetration of renewable and distributed energy systems, the use of parallel inverters has significantly increased. It is essential to achieve stable parallel operation and reasonable power sharing between these parallel inverters. Droop controllers are commonly used to control the power sharing between parallel inverters in an inverter-based microgrid. In this paper, a small signal model of droop controllers with secondary loop control and an internal model-based voltage and current controller is proposed to improve the stability, resiliency, and power sharing of inverter-based distributed generation systems. The distributed generation system’s nonlinear dynamic equations are derived by incorporating the appropriate and accurate models of the network, load, phase locked loop and filters. The obtained model is then trimmed and linearized around its operating point to find the distributed generation system’s state space representation. Moreo...