Arab Academy for Science and Technology

www.aast.edu
Alexandria, Egypt

The Arab Academy for Science, Technology & Maritime Transport is a regional university operated by the Arab League which is known for its programs in Marine Transportation, Business, and Engineering. Wikipedia.


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El-Zonkoly A.M.,Arab Academy for Science and Technology
Electric Power Systems Research | Year: 2011

The penetration of distributed generation (DG) in distribution power system would affect the traditional fault current level and characteristics. Consequently, the traditional protection arrangements developed in distribution utilities are difficult in coordination. Also, the reclosing scheme would be affected. With the rapid developments in distribution system automation and communication technology, the protection coordination and reclosing scheme based on information exchange for distribution power system can be realized flexibly. This paper proposes a multi-agent based scheme for fault diagnosis in power distribution networks with distributed generators. The relay agents are located such that the distribution network is divided into several sections. The relay agents measure the bus currents at which they are located such that it can detect and classify the fault, and determine the fault location. The proposed technique uses the entropy of wavelet coefficients of the measured bus currents. The performance of the proposed protection scheme is tested through simulation of two systems. The first system is a benchmark medium voltage (MV) distribution system and the second system is practical 66 kV system of the city of Alexandria. © 2011 Elsevier B.V. All rights reserved.


El-Zonkoly A.M.,Arab Academy for Science and Technology
IET Generation, Transmission and Distribution | Year: 2011

This study proposes a multi-objective index-based approach to optimally determine the size and location of multi-distributed generation (DG) units in distribution system with non-unity power factor considering different load models. It is shown that load models can significantly affect the optimal location and sizing of DG resources in distribution systems. The proposed multi-objective function to be optimised includes a short-circuit-level parameter to represent the protective device requirements. The proposed function also considers a wide range of technical issues such as active and reactive power losses of the system, the voltage profile, the line loading and the Mega Volt Ampere (MVA) intake by the grid. The optimisation technique based on particle swarm optimisation is introduced. The analysis of continuation power flow to determine the effect of DG units on the most sensitive buses to voltage collapse is carried out. The proposed algorithm is tested using the 38-bus radial system and the IEEE 30-bus meshed system. The results show the effectiveness of the proposed algorithm. © 2011 The Institution of Engineering and Technology.


Youssef S.M.,Arab Academy for Science and Technology
Computers and Electrical Engineering | Year: 2012

A novel Integrated Curvelet-based image retrieval scheme (ICTEDCT-CBIR) has been proposed, for the purpose of effectively retrieving more similar images from large digital image databases. The proposed model Integrates Curvelet Multiscale ridgelets with Region-based vector codebook Subband Clustering for enhanced dominant colors extraction and texture analysis. An important ingredient of the curvelet transform is to restore sparsity by reducing redundancy across scales. The discrete curvelet transform makes use of a dyadic sequence of scales, and a bank of filters with the property that the pass band filter is concentrated near the frequencies. An enhanced Region-based vector codebook Sub band Clustering (RBSC) has been proposed for effectively extract dominant colors from the color histogram of the transformed image sub-bands. An integrated matching scheme, based on most similar Highest Priority (MSHP) principle, is used to compare the query and target images. Experimental analysis has been carried out to verify the efficiency of the proposed ICTEDCT-CBIR model. Experimental results showed that the proposed approach has better retrieval performance. First, curvelets capture more accurate texture information. Second, as curvelets are tuned to different orientations, it captured more accurate directional features than wavelets. As the experimental results indicated, the proposed technique outperforms other retrieval schemes in terms of average precision with higher precision-recall crossover point values. © 2012 Elsevier Ltd. All rights reserved.


Aziz A.,Arab Academy for Science and Technology
IEEE Transactions on Aerospace and Electronic Systems | Year: 2011

A new soft-decision fusion approach is formulated for multiple-sensor distributed binary detection systems according to Neyman-Pearson criterion. The fusion rule of the proposed approach is derived. Unlike the published studies, the fusion rule of the proposed approach combines reliability terms weighted by the corresponding confidence levels to derive a final binary global decision. The proposed soft-decision approach is illustrated with simulated examples highlighting its performance and benefits of fusing the reliability terms weighted by the sensor confidence levels. The results show that the proposed approach is simple and efficient. © 2006 IEEE.


Aziz A.M.,Arab Academy for Science and Technology
Signal Processing | Year: 2011

This paper proposes a novel all-neighbor fuzzy association approach for multitarget tracking in a cluttered environment. It performs data association with a little prior knowledge and updates the predicted target state estimate using a fuzzy weighted sum of innovations. Unlike the joint probabilistic data association filter, in which the similarity measures are determined in terms of the conditional probability for all feasible data association hypothesis, the proposed fuzzy association approach determines the similarity measures between measurements and tracks in terms of possibility weights based on a partition matrix. The possibility weights are determined according to the fuzzy clustering algorithm. The proposed approach is able to perform all-neighbor association with a lower computational complexity in the expense of a little lower performance compared to the standard joint probabilistic data association filter. Computer simulation shows the feasibility and the efficiency of the proposed all-neighbor fuzzy association approach. © 2011 Elsevier B.V. All rights reserved.


El-Zonkoly A.M.,Arab Academy for Science and Technology
Swarm and Evolutionary Computation | Year: 2011

This paper proposes a multi-objective index-based approach for optimally determining the size and location of multi-distributed generation (multi-DG) units in distribution systems with different load models. It is shown that the load models can significantly affect the optimal location and sizing of DG resources in distribution systems. The proposed multi-objective function to be optimized includes a short circuit level parameter to represent the protective device requirements. The proposed function also considers a wide range of technical issues such as active and reactive power losses of the system, the voltage profile, the line loading, and the Mega Volt Ampere (MVA) intake by the grid. An optimization technique based on particle swarm optimization (PSO) is introduced. An analysis of the continuation power flow to determine the effect of DG units on the most sensitive buses to voltage collapse is carried out. The proposed algorithm is tested using a 38-bus radial system and an IEEE 30-bus meshed system. The results show the effectiveness of the proposed algorithm. © 2011 Elsevier B.V. All rights reserved.


Aziz A.M.,Arab Academy for Science and Technology
Aerospace Science and Technology | Year: 2013

The main components of tracking in multisensor data fusion systems are estimation and data association. This paper proposes a new nearest-neighbor fuzzy association approach for multitarget tracking in a cluttered environment. In the proposed approach, fuzzy clustering is used to generate a likelihood measure in place of the traditional Mahalanobis distance. First, measurements-to-tracks associations are computed jointly across all targets and all validated measurements using fuzzy clustering, then nearest-neighbor correlation is performed based on fuzzy correlation weights. For a given target, the validated measurement that has the maximum fuzzy correlation weight is used for updating the state of the target. The proposed approach determines the association between the measurements and the tracks based on a single correlation matrix, thus it highly reduces the computational complexity compared to the joint probabilistic data association filter and the conventional fuzzy logic data association approaches. The performance of the proposed approach is evaluated using Monte Carlo simulations and compared to that of the nearest-neighbor association with Mahalanobis distance, conventional fuzzy logic data association approaches, and joint probabilistic data association filter. The results show that the proposed approach achieves better performance compared to the nearest-neighbor association with Mahalanobis distance and the conventional fuzzy logic data association approaches. The results also show that the performance of the proposed approach is not far from the performance of the joint probabilistic data association filter. Suggested steps for the proposed approach to be utilized to counter against Electronic Counter Measures techniques are also presented. © 2012 Published by Elsevier Masson SAS.


El-Zonkoly A.,Arab Academy for Science and Technology
International Journal of Electrical Power and Energy Systems | Year: 2014

This paper presents an artificial bee colony (ABC) based algorithm to optimally solve the problem of allocation and the problem of design and schedule of multiple hybrid photovoltaic (PV)-diesel distributed generation in distribution systems. Both problems are solved simultaneously. The objective of the proposed algorithm is to minimize the overall investment, replacement and operation and maintenance costs of each located hybrid photovoltaic-diesel system (HPVDS). As the hybrid energy systems are grid connected, the algorithm considers also the minimization of the distribution system power loss, the amount of imported power from the transmission grid and the un-served load in case of emergency. Meanwhile, the algorithm aims to maximize the excess generated power by the HPVDS that may be injected into the distribution network. These objectives are to be achieved while satisfying the operational constraints of the system. The proposed algorithm is applied to two test systems to validate its effectiveness. © 2014 Elsevier Ltd. All rights reserved.


El-Zonkoly A.M.,Arab Academy for Science and Technology
IET Generation, Transmission and Distribution | Year: 2013

In this study, a multistage expansion and unit commitment (UC) planning for distribution networks using artificial bee colony (ABC) is presented. A dynamic model for expansion considers installation of new distributed generation units, expansion of pre-installed generating units' capacities, rewiring and addition of new load points. The expansion plane is carried out in three stages. In each stage, an hourly-day-ahead UC schedule is determined over the course of the stage period. The proposed algorithm uses the ABC to obtain a feasible commitment schedule for the generating units installed. An economical dispatch of these units along with load shedding is then carried out in each stage period to satisfy the system's equality and inequality constraints. The proposed algorithm is applied to different test systems to verify its efficiency. © The Institution of Engineering and Technology 2013.


El-Zonkoly A.M.,Arab Academy for Science and Technology
International Journal of Electrical Power and Energy Systems | Year: 2012

When a system is restored after an extended outage, the demand is greater than that was before the outage. The increase in the demand is due to the cold load pickup (CLPU) condition. The attempt to restore such load simultaneously will cause an excessive loading on the network elements in addition to limits violation. For these reasons, step-by-step restoration was suggested by researchers to overcome such problem. However, this way of restoration requires a long time for the complete system to be back to service. In this paper, simultaneous single step restoration of transmission and distribution networks is introduced with the help of distributed generation (DG) units optimally sited and sized by particle swarm optimization (PSO) algorithm. The aim of the proposed DG allocation algorithm is to reduce the distribution substation transformer loss of life due to overloading and to reduce the lost load and hence the additional power demand caused by CLPU. The capacity of the DG required is determined on the basis of additional power demand and the load diversity preserved. The proposed algorithm is applied to the Egyptian 66 kV transmission network in the city of Alexandria including a 33-bus and a 69-bus, 11 kV primary distribution feeders. © 2011 Elsevier Ltd. All rights reserved.

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