Curriculum Vitae


Ismail, M., M. H. Alham, and D. K. Ibrahim, "A novel approach for optimal hybrid energy decarbonization using multi-criteria decision analysis: Abu Rudeis, Egypt as a case study", Energy Conversion and Management, vol. 290, issue 15 August , pp. Article no. 117199, 2023. AbstractWebsite

Converting from a complete fossil fuel energy system to a decarbonized one is crucial to mitigating climate
change and protecting human health. Hybrid energy sources are better than producing energy from a single
technology. The combination of renewable energy and fuel generators allows users to cover seasonal fluctuations of resources and protects them from the unpredictability of fuel prices and supply. Nonetheless, the large-scale industrial demand presents a real challenge due to its consistency throughout the day and the intermittent nature of renewable sources. This research proposes a novel approach for optimal hybrid energy decarbonization for any demand type in general and industrial demand in particular. The proposed framework is developed by integrating the Hybrid Optimization of Multiple Energy Resources (HOMER) for the simulations of Hybrid Configurations (HCs), the Electrical Transient Analysis Program (ETAP) for the stability studies, and the Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) method to rank the resulting configurations.
An industrial oil and gas complex with high wind and solar resource availability is adopted as a study case. It is
located in Abu Rudeis, Egypt, and currently utilizes only 11 Gas Turbine Generators (GTGs) to generate electricity. Five different HCs are investigated, including PV and wind systems. The proposed approach considers technical, environmental, economic, and socio-political criteria, with a total of 21 sub-criteria, and reveals that incorporating a wind farm of nine 2-MW wind turbines with the GTGs is the Optimal Hybrid Configuration (OHC).

Boghdady, T. A., I. A. Sweed, and D. K. Ibrahim, "Performance Enhancement of Doubly-Fed Induction Generator-Based-Wind Energy System", International Journal of Renewable Energy Research, vol. 13, issue 1, pp. 311-325, 2023. AbstractWebsite

Nowadays, the challenging errand is enhancing the wind energy system (WES) performance to be more competitive and economically viable. One of the best ways to enhance the performance of the doubly-fed induction generator (DFIG)-based-WES is the optimization of the proportional-integral (PI) controllers for the variable frequency converter system. Many objectives with different optimization techniques have been used in literature to achieve optimal performance. Each choice has its advantages and disadvantages. This paper presents a new design approach for better performance of PI controllers and, hence DFIG over a wide range of operating conditions through two main themes. The first is by introducing a new multi-objective formulation, while the second is utilizing recent optimization techniques like Grey Wolf Optimizer and Whale Optimization Algorithm. Four PI controllers are optimized using a traditional objective function and the proposed multi-objective formulation. Two are related to the Rotor Side Converter (RSC), named power regulator, and the main rotor side converter current regulator. The other two PI controllers related to Grid Side Converter (GSC) are the DC-link voltage regulator and the main grid-side converter current regulator. A performance comparison is held through normal and abnormal operating conditions on a simulation model of a 6 MW wind farm located in Jabal Alzayt along the Red Sea Coast in Egypt and directly connected to the grid. The results confirmed the effectiveness of the proposed approach to help the DFIG-based-WES to agree with the Egyptian Grid Code during disturbances compared with the traditional objective formulation.

Khalil, E. A., T. a. Boghdady, M. H. Alham, and D. K. Ibrahim, "Enhancing the Conventional Controllers for Load Frequency Control of Isolated Microgrids Using Proposed Multi-Objective Formulation Via Artificial Rabbits Optimization Algorithm", IEEE Access, vol. 11, pp. 3472- 3493, 2023. AbstractWebsite

Isolated microgrids (IMGs) power remote areas. However, IMG may lower the frequency stability and increase frequency excursions with low system inertia. Load frequency management ensures system stability. Thus, the paper proposes a novel multi-objective tuning strategy to improve IMG's load frequency control (LFC) and take the microgrid controller's control signals into account. Diesel engine generator, fuel cell, battery energy storage system, and renewable energy sources (RESs) like photovoltaic and wind systems make up the IMG. Conventional controllers such as proportional-integral (PI) and proportional integral derivative (PID) are classically tuned based on the standard error criteria as a traditional single-objective tuning approach. Due to the low inertia of the system and the stochastic nature of RES, they cannot act as required under different operating scenarios. Therefore, the PI and PID controllers are tuned using the proposed multi-objective-based tuning approach to reduce the frequency deviations. In addition, anti-windup is applied to the enhanced classic controllers to keep them distant from the nonlinear zone and beyond the source's physical constraints. The proposed tuning process also considers the maximum practical generation rates for different sources. The recent Artificial Rabbits Optimization (ARO) algorithm is applied to simultaneously adjust the controller parameters for several controlled sources in IMG. Extensive simulations in MATLAB and Simulink confirm the effectiveness of the proposed approach to keep the system stable even when facing high levels of disturbances. In addition, accomplishing sensitivity analysis, severe +-25% changes to the system's parameters guarantee that the proposed tuning strategy keeps the system stable.

Alham, M. H., M. F. Gad, and D. K. Ibrahim, "Potential of Wind Energy and Economic Assessment in Egypt Considering Optimal Hub Height by Equilibrium Optimizer", Ain Shams Engineering Journal, vol. 14, issue 1, pp. Article no.101816, 2023. Abstract

In Egypt, the wind market increases quickly to make it one of the top countries in the Middle East. This
study discusses the viability of wind resources and the economic assessment for four locations in Egypt:
Ras El-Hekma, Farafra, Nuweiba, and Aswan through two stages. In the first stage, the optimal hub height
for some wind turbines has been calculated by using Equilibrium Optimizer (EO) algorithm to achieve
maximum wind energy with overall minimum cost. The second stage, the economic assessment has been
evaluated by using such turbines to calculate the cost of energy (COE) compared to the global and
Egyptian production costs of wind energy. Developed MATLAB programs are applied for statistical analysis
of wind data. The results have shown that Ras El-Hekma’s average wind speed is higher than other
sites and its wind energy potential is the best. Moreover, the economic assessment for selected locations
turns out that Ras El-Hekma by using EWT-DW61/22 turbine has the lowest COE.

Atta, M. E. E. - D., D. K. Ibrahim, and M. I. gilany, "Broken Bar Fault Detection and Diagnosis Techniques for Induction Motors and Drives: State of the Art", IEEE Access, vol. 10, pp. 88504 - 88526, 2022. AbstractWebsite

Motors are the higher energy-conversion devices that consume around 40% of the global electrical generated energy. Induction motors are the most popular motor type due to their reliability, robustness, and low cost. Therefore, both condition monitoring and fault diagnosis of induction motor faults have motivated considerable research efforts. In this paper, a comprehensive review of the recent techniques proposed in the literature for broken bar faults detection and diagnosis is presented. This paper mainly investigates the fault detection methods in line-fed and inverter-fed motors proposed after 2015 and published in most relevant journals and conferences. The introduced review has deeply discussed the main features of the reported methods and compared them in many different aspects. Finally, the study has highlighted the main issues and the gaps that require more attention from researchers in this field.

Fayoud, A. B., H. M. Sharaf, and D. K. Ibrahim, "Optimal coordination of DOCRs in interconnected networks using shifted user-defined two-level characteristics", International Journal of Electrical Power and Energy Systems, vol. 142, issue Part A, pp. Article no. 108298, 2022. Abstract

This paper introduces a protection scheme for interconnected networks based on proposed Directional Overcurrent Relays (DOCRs) with user-defined two-level characteristics. By getting usage of the capabilities available in modern digital DOCRs, the proposed relay will have two user-defined characteristics; one for its primary operation and another for its backup operation (two-level characteristics) to fit a specific application or system. The coordination between the proposed relays is formulated and solved as a non-linear optimization problem to minimize their operating time and reduce the thermal impact caused by short circuit currents through electrical equipment while maintaining the technical constraints.
Extensive comparative studies have been performed to ensure the effectiveness of the proposed protection
scheme. Firstly, the performance of the traditional one-level characteristic relay (COLC) with two settings is
compared to the conventional two-level characteristic relay (CTLC) with three settings. Then a further investigation is carried out by suggesting increasing the number of settings to seven, named as the user-defined two-level characteristic relay (UDTLC), and then to nine settings, named as the shifted-user-defined two-level characteristic relay (SUDTLC). Finally, different multi-objective functions with proper weighting factors are investigated to determine the most effective one with the best performance for the proposed idea.
The distribution portion of the IEEE 30-bus system has been used to test and verify the proposed characteristics extensively. The optimal coordination problem is solved using the fmincon function in MATLAB. Based on the achieved results, the proposed characteristics of UDTLC and SUDTLC guaranteed a considerable reduction in operating times. In addition, the achieved results deduced that using a different multi-objective formulation has little impact on reducing operating time due to using the proposed characteristics UDTLC and SUDTLC, which means solving the coordination problem is mainly dependent on the applied characteristics.

Mokhtar, N. M., H. Mohamed Sharaf, D. K. Ibrahim, and A. ’F. El’Gharably, "Proposed Ranked Strategy for Technical and Economical Enhancement of EVs Charging with High Penetration Level", IEEE Access, vol. 10, pp. 44738-44755, 2022. Abstract

Car exhaust is one of the most common causes of ozone hole aggravation, electrical vehicles (EVs) represent a promising solution to avoid this problem. Despite the benefits of EVs, their random charging behavior causes some difficulties regarding the electric network performance, such as increased energy losses and voltage deviations. This paper aims to achieve the proper scheduling of the EVs charging process, avoid its negative impacts on the network, and satisfy the EVs users’ requirements. The EVs charging process is formulated as an optimization problem and solved using particle swarm optimization. The optimization problem formulation considers the EV arrival and departure times and the state of charge required by the user. Different strategies such as separated, accumulated, and ranked strategies with continuous or interrupted fixed charging have been applied to solve the uncoordinated EVs charging problem. These strategies are extensively tested on the modified IEEE 31 bus system (499-node network), using the combination of both Open DSS and MATLAB m-files. The simulation results confirm the effectiveness of the proposed accumulated ranked strategy with interrupted fixed charging in improving the overall power system performance. The achieved improvements include minimizing: the peak power consumed, the peak power losses, and the voltage drop. Moreover, the cost of the EVs charging in most of the feeders has been decreased to a satisfying value. A comparison between the proposed strategy and some previously reported strategies has been performed to ensure the technical and economic enhancement of the proposed strategy.

Atta, M. E. E. - D., D. K. Ibrahim, and M. I. gilany, "Detection and Diagnosis of Bearing Faults under Fixed and Time-Varying Speed Conditions Using Persistence Spectrum and Multi-Scale Structural Similarity Index", IEEE Sensors Journal, vol. 22, issue 3, pp. 2637 – 2646, 2022. Abstract

With the widespread use of variable speed drives, a robust scheme that can detect and diagnose bearing faults under fixed and variable speed conditions becomes essential for reliable operation. Unfortunately, most of the reported methods in the literature are dedicated to working under fixed speed and will face challenges under variable speed conditions. Besides, most of them require detailed bearing information that may be unavailable in the real world. Therefore, in this paper, a new scheme is proposed for bearing faults detection and diagnosis under fixed and time varying speed conditions. The proposed scheme is based on the analysis of vibration signals using the persistence spectrum that can provide images rich with health-related features largely independent from rotating speed. Then, the produced image is compared with priorly stored images of the persistence spectrum of a healthy case. This comparison is performed using the multi-scale structural similarity index, which is a robust basis for images comparison without the need for training or expert knowledge. The obtained index is compared against an adaptive threshold for fault detection. Upon detecting a fault, the persistence spectrum image is compared with that of stored different fault types for fault diagnosis. The proposed scheme is extensively validated using three experimental datasets under different speed conditions. The results show that it can detect bearing faults in an earlier stage without the need for bearing specifications or shaft speed. Moreover, it can successfully diagnose bearing faults severity with accuracy reaching 100% with the minimum required data.

Shafei, M. A. R., D. K. Ibrahim, and M. Bahaa, "Application of PSO tuned fuzzy logic controller for LFC of two-area power system with redox flow battery and PV solar park", Ain Shams Engineering Journal, vol. 13, issue 5, pp. Article No. 101710, 2022. Abstract

Nowadays, integrating large scale renewable energy sources, like solar PV parks, raises challenges for Load Frequency Controllers (LFC). The output of PV varies continuously, which requires a robust LFC deals
logically without continuous tuning and parameters optimization. In this paper, a fuzzy logic controller (FLC) is proposed to act as the main LFC instead of the traditional proportional–integral–derivative (PID) controller. The dynamic performance of FLC is enhanced by optimizing its parameters for different cost functions using particle swarm optimization technique (PSO). Another two FLCs will be added to PV system to act as an output controller instead of maximum power point tracker (MPPT) to enhance the overall system performance. To increase system reliability, a fast active power source called redox flow battery (RFB) is added in the proposed model as a frequency stabilizer. RFB can deeply discharge up to 90% with theoretically limitless number of duty cycles and has fast time response for severe load changes. The
importance of these proposed controllers side by side with RFB is to avoid disconnecting solar parks during
heavy cloudy days while preserving on maximizing its output during these periods. The superiority of the proposed FLC is examined by evaluating its performance compared to another control approach called PID-P (PID controller with P controller in the inner feedback loop). Finally, a comprehensive sensitivity analysis is also presented to investigate the controller robustness for extensive changes in power system parameters and loading.