- 169 GESR ELSUEZ ST. (5 MILITARY Buildings), Depart. 12
West heliopolis - 00201004718562
- Noha H. El-Amary was born in Cairo, Egypt, on September 21, 1978. She received B.Sc., M.Sc., and PhD degrees in elect... moreNoha H. El-Amary was born in Cairo, Egypt, on September 21, 1978. She received B.Sc., M.Sc., and PhD degrees in electrical engineering, Ain Shams University, Cairo, Egypt in 2000, 2004, and 2009 respectively.
She worked as an associate lecturer from 2004 - 2009, in Arab Academy for Science, Technology, and Maritime Transport (AASTMT), Cairo branch, Egypt. She was an Assistant Professor in AASTMT from May 2009 - 2014. She worked as an Associate Professor in AASTMT from June 2014 – May 2018. She is currently a Professor in AASTMT since June 2018.
Her special fields of interest include Artificial Intelligence (AI) techniques in electrical power system stability study, analysis, measurement, and control, smart grids, and renewable energy in power system and maritime applications.edit
No doubt, the textile business is one of the oldest and important industries worldwide but it still needs a lot of efforts and development. In this paper, an upgraded soft winding machine is targeted based on a modified variable speed... more
No doubt, the textile business is one of the oldest and important industries worldwide but it still needs a lot of efforts and development. In this paper, an upgraded soft winding machine is targeted based on a modified variable speed yarn tension modeling. Soft winding is a very critical process, because it could affect the dyeing quality throughout controlling the package density as well as the yarn imperfections. Product quality is considered a major competition edge against market rivals. In this study, micro-controller, tension sensor, tension brake, servo motor “feeder” and personal computer will be used to measure the actual yarn tension on the soft winding machine. Stack tank and noise filtering techniques will be used to filter and save the signal values from the tension sensor for durable industry application. Various tests will be applied on cotton yarn, fine, medium and coarse yarn counts will be used to cover most yarn types used in the industry. Unwinding tension equations before and after the feeder are disused and explained, in addition to the tension brake, servo motor “feeder” and winding speed tension. Curve fitting tool inside Matlab software is used to determine the new effective equations. Therefore, maximum yarn quality can be achieved at higher production capacity and machine efficiency. Implementation of Advanced yarn tension modeling can be applied to new soft winding machines generations and for modifying old machinery. The new advanced yarn tension model is tested on a soft winding machine and good results were reported in addition to recommended tension values for the different cotton yarn counts tested.
Research Interests: Engineering and Yarn
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
This paper introduces a potentially decarbonizing study on IEEE 30 bus electric network, where the target of electricity production is met the supply side by using alternative sources instead of burning fossil fuel such as renewable... more
This paper introduces a potentially decarbonizing study on IEEE 30 bus electric network, where the target of electricity production is met the supply side by using alternative sources instead of burning fossil fuel such as renewable energy resources. Continuous improvements and using low-carbon technologies is considered to decarbonize CO2emissions. A unit commitment study is to optimally minimize emission, losses and costs by replacing conventional generating units with stochastic resources and PEVs. PEVs are provided to vanquish the intermittency and uncertainty of wind and solar energies. Combined Economic Emission Dispatch problem (CEED) is proposed an optimally scheduling of Renewable Energy Resources (RERs) and predetermined processes of (charging/discharging) of PEVs with dispatchable generating units. Two algorithms are used to validate the results. Water cycle algorithm (WCA) is the metaheuristic algorithm shows its efficiency and durability in minimizing the cost function incorporating costs of CO2emission. The other conventional technique is dynamic programming (DP) is used to assure the obtained results from WCA.
Research Interests:
Continuous urban development and sustainable development goals to develop cities and transform them into smart cities faces many challenges that appear in the transfer of electricity to this place or the difficulty and high price of... more
Continuous urban development and sustainable development goals to develop cities and transform them into smart cities faces many challenges that appear in the transfer of electricity to this place or the difficulty and high price of building a station in this place. And power loss and voltage instability are major problems in distribution systems. However, these problems are typically mitigated by efficient network reconfiguration. Distributed generation (DG) can be used in the distribution systems to fight the increase of the load demand and it improve power generation systems and improvement the system efficiency. But it is very strange that if the generators are placed in an ill-considered size and in an inappropriate location, this causes the system to weaken, which has a bad effect on use, and this is not desirable. Not only that, but with the increase in the demand for power to cope with the increasing loads, stages of loss of power appear when it enters the distribution stage...
Research Interests:
NEURAL NETWORK BASED ADAPTIVE OVERCURRENT DIRECTIONAL PROTECTION IN LARGE ELECTRICAL POWER NETWORKS Noha H. El-Amary Yasser G. Monir Tarek Youssif DepartmentDepartment of Electrical and Computer Control Engineering, College of ...
Research Interests:
This paper presents a comparison between phasor measurement units' (PMUs') optimal allocation for system topological observability, and PMUs' optimal number and locations for minimum state estimation residual... more
This paper presents a comparison between phasor measurement units' (PMUs') optimal allocation for system topological observability, and PMUs' optimal number and locations for minimum state estimation residual error. A newly developed technique based on discrete particle swarm optimization (DPSO) is used in finding the PMUs' optimal allocation for different system unobservability depth. For the optimal allocation of PMUs from the
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Microgrids (MGs) are combination of energy sources such as wind energy, photovoltaic (PV) system, storage systems and loads. it can work either with grid or not. In this paper a technical, economic, and environmental solutions of MGs that... more
Microgrids (MGs) are combination of energy sources such as wind energy, photovoltaic (PV) system, storage systems and loads. it can work either with grid or not. In this paper a technical, economic, and environmental solutions of MGs that contain different renewable energy sources, Diesel generators (DGs), battery storage system (BSS) with different characteristics are proposed. Some constraints are considered, such as distributed generators output energy limits, the power move from or to the grid and battery storage system constraints. Three systems of different energy sources are investigated and compared to ensure the best incorporation for minimum economic and environmental operating cost.
Research Interests:
This paper got accepted last year but due to several circumstances me and my co other were not able to attend the conference.Hence the paper was not included in the index. Thankfully the administrative allowed us to upload the paper so... more
This paper got accepted last year but due to several circumstances me and my co other were not able to attend the conference.Hence the paper was not included in the index. Thankfully the administrative allowed us to upload the paper so that we could present and publish it beside our new work that is accepted in the conference Abstract This work presents a non-linear control technique for a grid-connected wind turbine based on Doubly Fed Induction Generator (DFIG) targeting improved adapted power efficiency with high voltage performance. The control approach is realized in the rotor reference frame and is based on Asymptotic output tracking technique. Thus, assigning specific zeros through a feedback process ensure the reproduction of an output that converges asymptotically to the required reference rotor current. As a consequence, active and reactive powers can be controlled. The mathematical models of the doubly-fed induction generator and the grid side converter command models are...
Research Interests:
This paper introduces a new theoretical control strategy that aims to adjust and control the stability of the a grid-connected wind turbine based on Doubly Fed Induction Generator (DFIG). The control approach is realized in the direct... more
This paper introduces a new theoretical control strategy that aims to adjust and control the stability of the a grid-connected wind turbine based on Doubly Fed Induction Generator (DFIG). The control approach is realized in the direct rotor reference frame where the power factor is set to unity.The base of the proposed technique is the determination of the linear approximation of the nonlinear model followed by the computation of the transfer function of the DFIG. The Laplace domain is used to study the nature of the zeros of the DFIG.Hence one can separate the unstable zeros or the unwanted ones and design a suitable feedback that treat the instability phenomena or enhance the stability performance. The introduced approach was applied to a wind turbine generator driving a 3.7 kW load connected to grid . MATLAB program was used to simulate and test the performance of the proposed control methods. The results shows that the suggested control design proved to be reliable and effective.
Research Interests:
Research Interests:
Research Interests: Engineering and Wit
Decentralized Energy Generation Systems (DEG) acquire their vital role in power systems owing to their practical and cost effectiveness advantages. This paper illustrates a new metaheuristic application called the Evaporation Rate based... more
Decentralized Energy Generation Systems (DEG) acquire their vital role in power systems owing to their practical and cost effectiveness advantages. This paper illustrates a new metaheuristic application called the Evaporation Rate based Water Cycle Algorithm (ER-WCA) for improving the inverter based (DEG) system operation. The controlling methodology of the inverter applied is the vector cascaded control technique, that depends on the Proportional-Integral (PI) controller. The optimization of the PI controller constants is carried out using ER-WCA method. The optimization problem target and constraint functions are created by the Response Surface Methodology (RSM). The validation of the suggested control technique is checked by utilizing the simulation outcomes, which are carried out by PSCAD/EMTDC program. These simulations outcomes are tested under various working settings as an example 1) system conversion from network connected to stand alone scenario, and 2) the system exposure to three lines to earth fault in the stand alone mode The adequacy of the suggested controller is proved by carrying out a comparison between its outcomes with that utilizing the Genetic Algorithm (GA) technique.
Research Interests: Computer Science and IEEE
The Microgrid achieve nowadays a great importance in providing energy to isolated areas. This paper demonstrates a new application of the Artificial Neural Networks (ANN) for online modification of the inverter based microgrid operation.... more
The Microgrid achieve nowadays a great importance in providing energy to isolated areas. This paper demonstrates a new application of the Artificial Neural Networks (ANN) for online modification of the inverter based microgrid operation. A vector cascaded control technique is utilized as an inverter control strategy, which depends on the Proportional plus Integral (PI) controller. The suggested ANN is used to adapt the controller constants instantly. The ANN is simulated using MATLAB program. The input training samples of the ANN is obtained by carrying out different working settings simulated by PSCAD/EMTDC program. The optimal output training data fed to ANN is obtained by finding the optimal PI constants utilizing Evaporation Rate Water Cycle Algorithm (ERWCA). The utilized objective optimization problem used by the ERWCA is created by the Response Surface Methodology (RSM). The working scenarios included in this paper are 1) system conversion from grid connected mode to stand alone one, 2) system exposure to three lines to earth fault in the stand alone mode and 3) The steady state operation at grid connected mode.
Research Interests:
Research Interests:
Fault diagnosing power transformers based on dissolved gas analysis (DGA) has become an important and a significant tool. There are a number of techniques developed for DGA that are represented extensively in literature. In practical... more
Fault diagnosing power transformers based on dissolved gas analysis (DGA) has become an important and a significant tool. There are a number of techniques developed for DGA that are represented extensively in literature. In practical application of DGA, there is a degree of measurement errors in obtained data. These errors are produced from inaccuracy in measurement system, environmental impact, and human errors. In the present study, it is aimed to investigate the sensitivity of different DGA techniques against measurement errors. The considered DGA techniques are IEC Ratio, Duval Triangle, and Pentagon shape. A total number of 380 actual samples were obtained from the Egyptian Electricity Network as well as published reports. Measurement errors are modeled with various levels as a percentage of original data using a random function. The three different DGA techniques are applied for error data and the corresponding diagnostic accuracy is evaluated. The techniques are compared on t...
Research Interests: Computer Science and IEEE
Smart electrical power flow control in distribution systems is targeted in this paper. Optimal electrical power continuity through energy management, self healing, high reliability and real-time pricing is one of the main aims of the... more
Smart electrical power flow control in distribution systems is targeted in this paper. Optimal electrical power continuity through energy management, self healing, high reliability and real-time pricing is one of the main aims of the researches. In this paper, a smart electrical power grid is represented to save the power flow continuity with minimum power losses in case of any abnormal condition. The optimum power continuity is achieved utilizing a developed Particle Swarm Optimization (PSO) technique. This technique is programmed to fulfill two main tasks. The first task is finding all the possible alternative paths for supplying the loads, in case of fault occur or abnormal condition. The second task is modifying the angles of the buses' voltages of the electrical power system to determine the optimal path with minimum power loss. The optimal determined path could have less power losses than that of the path already obtained by the initial power flow analysis. The buses' ...
Research Interests:
Research Interests:
The increasing daily rate of environmental pollution, due to electrical power generation from fossil fuel sources in different societies, urges the researchers to study alternative solutions. These solutions can be summarized into either... more
The increasing daily rate of environmental pollution, due to electrical power generation from fossil fuel sources in different societies, urges the researchers to study alternative solutions. These solutions can be summarized into either finding other clean, renewable sources or managing the available sources optimally. This research represents smart electrical interconnection management between some of the Egyptian seaports for optimal operation, with a clean sustainable environment as the target. The optimum ports’ commitment operation works through certain technical constraints to attain optimal economic and environmental factors. One of the main objectives of this study is the reduction of carbon dioxide (CO2) emission, which is released from the electrical power generation that covers the seaports demands. It is progressed through the green port smart commitment, by incorporating unpolluted and renewable energy resources. This study depends on the redesign of some Egyptian seap...
Research Interests:
Research Interests:
This paper represents sliding mode control adjustment for a hybrid AC/DC micro-grid. The micro-grid includes photovoltaic (PV), wind energy, diesel generator and dynamic loads. The hybrid micro-grid is capable to be synchronized with the... more
This paper represents sliding mode control adjustment for a hybrid AC/DC micro-grid. The micro-grid includes photovoltaic (PV), wind energy, diesel generator and dynamic loads. The hybrid micro-grid is capable to be synchronized with the main utility. The load variations may lead to the instability of the micro-grid and it may be out of control. Also, the load variations affect the voltage and the frequency behaviour of the system, to go out of limitations. The Sliding Mode Control (SMC) is proposed and implemented to track the reference voltage considering the system load variations. SMC is targeted to improve power sharing and performance among renewable energy resources. In addition, the sliding mode control can regulate active and reactive power via terminal voltage control, it has an optimal behaviour. Furthermore, it still suitable and robust for micro-grid it ensures power sharing with considering the load variations. The SMC is applied to AC/DC hybrid micro-grid, which consists of PV, wind and diesel power generation sources. It is tested at different location connection. It is connected to PV and wind generator’s inverters separately. It is also connected to the diesel connected bus (the main bus). The simulation results of the overall cases show that the proposed system with the sliding mode controller has satisfied performance and good prediction of the electrical parameter waveforms compared to the system behaviour without sliding mode controller.
Research Interests:
Distributed generation (DG) systems achieve an important role in electrical power networks due to their technical and economic benefits. This paper presents a novel application of the Crow Search Algorithm (CSA) with purpose of enhancing... more
Distributed generation (DG) systems achieve an important role in electrical power networks due to their technical and economic benefits. This paper presents a novel application of the Crow Search Algorithm (CSA) with purpose of enhancing the performance of an inverter-based DG system. The control strategy of the inverter is based on a vector cascaded control scheme, which relies on the Proportional plus Integral (PI) controller. The proposed CSA is utilized to fine tune the PI controller parameters. The response surface methodology (RSM) is used to create the objective and constraint function of the optimization problem. The validity of the proposed control strategy is extensively verified using the simulation results, which are performed using PSCAD/EMTDC environment. These simulation results are investigated under different operating conditions such as 1) transition of the system from grid connected to islanded mode of operation, and 2) subject the system to a single line to ground fault in the autonomous mode. The effectiveness of the proposed controller is verified by comparing its results with that obtained using the genetic algorithm-based PI controller.
Research Interests:
Research Interests:
This paper introduces a smart model predictive control system for hybrid micro-grids which are utilized for voltage regulate and controlling in transient mode operation of hybrid AC/DC micro-grid. Various voltage control approaches have... more
This paper introduces a smart model predictive control system for hybrid micro-grids which are utilized for voltage regulate and controlling in transient mode operation of hybrid AC/DC micro-grid. Various voltage control approaches have been successfully achieved within AC and DC grids, but the control of hybrid micro-grid depends upon more consideration with spotlight on inter-linking converter (ILC). Model predictive control (MPC) is applied to a hybrid micro-grid, which consists of DC and AC sources. The DC sources include photovoltaic farm, vehicle to grid, while the AC sources are Diesel farm and wind farm. They are connected to the main power grid. The power system is simulated utilizing Simulink/MATLAB. The system is operated at different loading and generation condition to determine the variation of voltage against power variation. MPC unit is added in different locations and scenarios. It is effective in controlling the main bus voltage and frequency. By testing the MPC on the simulated tested system the results are satisfied.
Research Interests:
Smart grid architecture is one of the difficult constructions in electrical power systems. The main feature is divided into three layers; the first layer is the power system level and operation, the second layer is the sensor and the... more
Smart grid architecture is one of the difficult constructions in electrical power systems. The main feature is divided into three layers; the first layer is the power system level and operation, the second layer is the sensor and the communication devices, which collect the data, and the third layer is the microprocessor or the machine, which controls the whole operation. This hierarchy is working from the third layer towards first layer and vice versa. This paper introduces an eco unit commitment study, that scheduling both conventional power plants (three IEEE) thermal plants) as a dispatchable distributed generators, with renewable energy resources (wind, solar) as a stochastic distributed generating units; and plug-in electric vehicles (PEVs), which can be contributed either loads or generators relied on the charging timetable in a trustworthy unit commitment. The target of unit commitment study is to minimize the combined eco costs by integrating more augmented clean and renewa...
Research Interests:
Research Interests:
Research Interests:
Microgrids attain a significant role in electrical power systems due to their practical and economic benefits. A novel application of an adaptive Proportional plus Integral (PI) controller with the purpose of improving the microgrid... more
Microgrids attain a significant role in electrical power systems due to their practical and economic benefits. A novel application of an adaptive Proportional plus Integral (PI) controller with the purpose of improving the microgrid performance is presented in this paper. The control strategy of the adaptive PI controller is based on Widrow-Hoff adaptation technique. The efficiency of the suggested controller is proved by comparing its outcomes with that obtained by utilizing Flower Pollination algorithm (FPA) which is used to fine tune the PI controller parameters of the inverter based microgrid. The utilized multi-objective optimization problem used by the FPA is created by the Response Surface Methodology (RSM). Simulation results are carried out using PSCAD/EMTDC environment to check the validity of the proposed control strategy. The simulation results are tested under various operating states such as 1) conversion of the system from grid connected to stand alone mode of operation, 2) subjecting the system to three line to ground fault in the autonomous mode, and 3) exposing the system to the load variability in the islanded mode.
Research Interests:
This paper aims to design a controller for a Doubly Fed Induction Generator (DFIG) targeting the Eco-Maximum Power Point Tracking (EMPPT) for environmental aspects. The proposed controller consists of two clusters, which are the novel... more
This paper aims to design a controller for a Doubly Fed Induction Generator (DFIG) targeting the Eco-Maximum Power Point Tracking (EMPPT) for environmental aspects. The proposed controller consists of two clusters, which are the novel Artificial Immunity sensorless Eco-Maximum Power Point Tracking (AI EMPPT) and the asymptotic non-linear control techniques. The main target of the AI EMPPT is to reduce the carbon dioxide emission by generating the maximum possible power from the renewable electrical energy resource, which is wind electrical power generation to replace the fossil-fuel conventional generation. To build the AI EMPPT, an Artificial Immunity System Estimator (AISE) based on artificial immunity technique and a Model Reference Adaptive System (MRAS) are used to estimate the DFIG rotor speed. Then, the AI EMPPT is applied to provide the reference electromagnetic torque signal. Subsequently, the reference electromagnetic torque interacts with the estimated generator speed, de...
Research Interests:
Research Interests:
Research Interests:
Abstract Voltage instability is considered as a major problem that faces the power systems during its operation. Voltage instability prediction is necessary for avoiding voltage collapse. This paper investigates the performance of... more
Abstract Voltage instability is considered as a major problem that faces the power systems during its operation. Voltage instability prediction is necessary for avoiding voltage collapse. This paper investigates the performance of recurrent neural network (RNN) in voltage instability prediction. A recurrent neural network trained with Particle Swarm Optimization (PSO) is proposed in this paper. The proposed method is examined on 14-bus and 30-bus IEEE standard systems. These systems are simulated using MATLAB/Power System Toolbox program. Also, a detailed comparison between PSO algorithm and Backpropagation (BP) algorithm is discussed. The results proved the effectiveness of the proposed method.
Research Interests:
No doubt, the textile business is one of the oldest and important industries worldwide but it still needs a lot of efforts and development. In this paper, an upgraded soft winding machine is targeted based on a modified variable speed... more
No doubt, the textile business is one of the oldest and important industries worldwide but it still needs a lot of efforts and development. In this paper, an upgraded soft winding machine is targeted based on a modified variable speed yarn tension modeling. Soft winding is a very critical process, because it could affect the dyeing quality throughout controlling the package density as well as the yarn imperfections. Product quality is considered a major competition edge against market rivals. In this study, micro-controller, tension sensor, tension brake, servo motor “feeder” and personal computer will be used to measure the actual yarn tension on the soft winding machine. Stack tank and noise filtering techniques will be used to filter and save the signal values from the tension sensor for durable industry application. Various tests will be applied on cotton yarn, fine, medium and coarse yarn counts will be used to cover most yarn types used in the industry. Unwinding tension equations before and after the feeder are disused and explained, in addition to the tension brake, servo motor “feeder” and winding speed tension. Curve fitting tool inside Matlab software is used to determine the new effective equations. Therefore, maximum yarn quality can be achieved at higher production capacity and machine efficiency. Implementation of Advanced yarn tension modeling can be applied to new soft winding machines generations and for modifying old machinery. The new advanced yarn tension model is tested on a soft winding machine and good results were reported in addition to recommended tension values for the different cotton yarn counts tested.
Research Interests:
The illustration of a neural network based voltage instability detector utilizing broad region observing system and the calculated angle of the installed Phasor Measurement Units (PMUs) is introduced in this paper. Voltage instability is... more
The illustration of a neural network based voltage instability detector utilizing broad region observing system and the calculated angle of the installed Phasor Measurement Units (PMUs) is introduced in this paper. Voltage instability is regarded one of the serious troubles that harshly shape the electric power quality. The system which is affected by voltage instability can be easily subjected to a rapid breakdown due to voltage collapse. A planned neural network based voltage instability detector is presented throughout this paper. This detector counts on the installed PMUs bus voltage angles. An enhanced Feed-Forward Neural Network (FFNN) is planned and trained. The FFNN includes one input layer, two hidden layers, and one output layer. The major advantage of the smart enhanced system is that, it can sense the voltage instability of the whole power system buses in the same time. The enhanced designed system is examined on 14-bus and 30-bus IEEE standard systems. The 14 bus and 30 bus IEEE systems are simulated using MATLAB/power system toolbox program to get each system load flow consequences. In addition, the influence of various loading conditions is used to the simulated system to get their equivalent bus angles values. Concerning each one of the examined system, different studied cases are held for various loading values with different power factors on different buses. The consequences of these cases are listed, normalized and processed using the ANN. While each one of the ANN is trained then the performance of the improved system is examined. The consequences of ANN are tested and regarded to be acceptable because of the high precision and dependable operation.
Research Interests:
Research Interests:
In this paper a thermal protection technique is presented by applying Particle Swarm Optimization (PSO) technique to thermally protect three phase Induction Motors (IMs), that are being successively starting, from operating beyond the IM... more
In this paper a thermal protection technique is presented by applying Particle Swarm Optimization (PSO) technique to thermally protect three phase Induction Motors (IMs), that are being successively starting, from operating beyond the IM thermal limits. This approach is implemented with PSO so as to determine the number of starting and operating times versus the IM thermal capability. This leads