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Full-Text Articles in Physical Sciences and Mathematics
Vulnerability Assessment Of A Large Sized Power System Considering A New Index Based On Power System Loss, Ahmed M. Haidar, Azah Mohamed, Aini Hussain
Vulnerability Assessment Of A Large Sized Power System Considering A New Index Based On Power System Loss, Ahmed M. Haidar, Azah Mohamed, Aini Hussain
Dr Ahmed Mohamed Ahmed Haidar
The concept of power system vulnerability assessment combines information on the level of system security as well as information on a wide range of situations, events and contingencies with regards to which a system is vulnerable. This paper attempts to investigate and evaluate the effect of line outage, generation outage and amount of load disconnected on the power transmission network losses of a large size power system. These effects will be investigated and evaluated using new proposed method based on vulnerability index of power system loss. The objectives of this work is to evaluate and compare the efficiency of the …
Grounding Locations Assessment Of Practical Power System, Nadheer Shalash, Ahmed M. Haidar, Abdul Sattar
Grounding Locations Assessment Of Practical Power System, Nadheer Shalash, Ahmed M. Haidar, Abdul Sattar
Dr Ahmed Mohamed Ahmed Haidar
Grounding Points (GPs) are installed in electrical power system to drive protective devices and accomplish the person- nel safety. The general grounding problem is to find the optimal locations of these points so that the security and reli- ability of power system can be improved. This paper presents a practical approach to find the optimal location of GPs based on the ratios of zero sequence reactance with positive sequence reactance (X0/X1), zero sequence resistance with positive sequence reactance (R0/X1) and Ground Fault Factor (GFF). The optimal values of these indicators were deter- mined by considering several scenarios of fault disturbances …
Neural Network Prediction Of Electromagnetic Field Strength In Hybrid Micro-Grid System, Ahmed Haidar, Ibrahim Ahmed, Ahmed Abdalla
Neural Network Prediction Of Electromagnetic Field Strength In Hybrid Micro-Grid System, Ahmed Haidar, Ibrahim Ahmed, Ahmed Abdalla
Dr Ahmed Mohamed Ahmed Haidar
Location of any Hybrid Micro-Grid System requires efficiently prediction of the electromagnetic field strength. This study proposes a novel Electromagnetic Field Strength (EFS) predication based on Probabilistic Neural Network (PNN). Learning data sets have been generated using Electromagnetic Transients Program EMTP. The PNN model has three input nodes representing the Switching Distance, Busbar Interference Voltage and Current waveforms, the output node representing the EFS. Testing datasets have deliberately been chosen outside the region of the learning datasets so as to check the performance of the neural network. The results indicate that the proposed technique can be used successfully to detect …
Vulnerability Control Of Large Scale Interconnected Power System Using Neuro-Fuzzy Load Shedding Approach, Ahmed Haidar, Azah Mohamed, Aini Hussain
Vulnerability Control Of Large Scale Interconnected Power System Using Neuro-Fuzzy Load Shedding Approach, Ahmed Haidar, Azah Mohamed, Aini Hussain
Dr Ahmed Mohamed Ahmed Haidar
Vulnerability control is becoming an essential requirement for security of power systems in the new utility environment. It is a difficult task for system operator who under economic pressure may be reluctant to take preventive action against harmful contingencies in order to guarantee providing continued service. For power systems which are operated closer to their stability limits, it is desirable to use load shedding as a form of vulnerability control strategy. This paper presents a neuro-fuzzy approach for determining the amount of load to be shed in order to avoid a cascading outage. The objective is to develop fast and …
Vulnerability Assessment Of Power System Using Radial Basis Function Neural Network And A New Feature Extraction Method, Ahmed M. Haidar, Azah Mohamed, Aini Hussain
Vulnerability Assessment Of Power System Using Radial Basis Function Neural Network And A New Feature Extraction Method, Ahmed M. Haidar, Azah Mohamed, Aini Hussain
Dr Ahmed Mohamed Ahmed Haidar
Vulnerability assessment in power systems is important so as to determine how vulnerable a power system in case of any unforeseen catastrophic events. This paper presents the application of Radial Basis Function Neural Network (RBFNN) for vulnerability assessment of power system incorporating a new proposed feature extraction method named as the Neural Network Weight Extraction (NNWE) for dimensionality reduction of input data. The performance of the RBFNN is compared with the Multi Layer Perceptron Neural Network (MLPNN) so as to evaluate the effectiveness of the RBFNN in assessing the vulnerability of a power system based on the indices, power system …
New Method Vulnerability Assessment Of Power System, Ahmed Haidar, Azah Mohamed, Aini Hussain
New Method Vulnerability Assessment Of Power System, Ahmed Haidar, Azah Mohamed, Aini Hussain
Dr Ahmed Mohamed Ahmed Haidar
Vulnerability assessment in power systems is to determine a power system`s ability to continue to provide service in case of an unforeseen catastrophic contingency. It combines information on the level of system security as well as information on a wide range of scenarios, events and contingencies. To assess the level of system strength or weakness relative to the occurrence of an undesired event, a quantitative measure based on vulnerability index is often considered. In this study, a new vulnerability assessment method is proposed based on total power system loss which considers power generation loss due to generation outage, power line …
Transient Stability Evaluation Of Electrical Power System Using Generalized Regression Neural Networks, Ahmed Haidar, M Mustafa, Faisal Ibrahim, Ibrahim Ahmed
Transient Stability Evaluation Of Electrical Power System Using Generalized Regression Neural Networks, Ahmed Haidar, M Mustafa, Faisal Ibrahim, Ibrahim Ahmed
Dr Ahmed Mohamed Ahmed Haidar
Transient stability evaluation (TSE) is part of dynamic security assessment of power systems, which involves the evaluation of the system’s ability to remain in equilibrium under credible contingencies. Neural networks (NN) have been applied to the security assessment of power systems and have shown great potential for predicting the security of power systems. This paper proposes a generalized regression neural networks (GRNN) based classification for transient stability evaluation in power systems. In the proposed method, learning data sets have been generated using time domain simulation (TDS). TheGRNN input nodes representing the voltage magnitude for all buses, real and reactive powers …
Smart Control Of Upcq Within Microgrid Energy System, C Benachaiba, Ahmed Haidar, O Habab, O Abdelkhalek
Smart Control Of Upcq Within Microgrid Energy System, C Benachaiba, Ahmed Haidar, O Habab, O Abdelkhalek
Dr Ahmed Mohamed Ahmed Haidar
One of the most popular issues in the future power distribution is the quality improvement of microgrid and the development of smart grid (SG). Many applications operating at the microgrid level can be considered as smart grid functions. This paper proposes the application of Fuzzy Logic (FL) technique within microgrid energy system based on the most modern power conditioning equipment devices such as Unified Power Quality Conditioner (UPQC). This technique is working together with the microgrid to track the disturbance of the smart grid and improve the quality of the system with a high flexibility. Furthermore, a control methodology developed …