Future University In Egypt (FUE)
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Altagamoa Al Khames, Main centre of town, end of 90th Street
New Cairo
Egypt
Faculty of Engineering & Technology

Said Fouad Mohamed Mekhemar

Basic information

Name : Said Fouad Mohamed Mekhemar
Title: Professors

Education

Certificate Major University Year
PhD * Dalhousie University - Canada 2002
Bachelor Electrical Power Ain Shams University 1993

Researches /Publications

Enhancing radial distribution system performance by optimal placement of DSTATCOM - 01/0

Said Fouad Mohamed Mekhemar

Shehata, R.H., Abdelaziz, A.Y., Al-Gabalawy, M.A.,

01/06/2020

In this paper, A novel modified optimization method was used to find the optimal location and size for placing distribution Static Compensator in the radial distribution test feeder in order to improve its performance by minimizing the total power losses of the test feeder, enhancing the voltage profile and reducing the costs. The modified grey wolf optimization algorithm is used for the first time to solve this kind of optimization problem. An objective function was developed to study the radial distribution system included total power loss of the system and costs due to power loss in system. The proposed method is applied to two different test distribution feeders (33 bus and 69 bus test systems) using different Dstatcom sizes and the acquired resultswere analyzed and compared to other recent optimization methods applied to the same test feedersto ensure the effectiveness ofthe used method and its superiority over other recent optimization mehods. The major findings from obtained results that the applied technique foundthe most minimized total power loss in system, the best improved voltage profile and most reduction in costs due power loss compared to other methods

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Population based optimization algorithms improvement using the predictive particles - 01/0

Said Fouad Mohamed Mekhemar

Elroby, M.M.H., Moustafa. Hassan, M.A.,

01/06/2020

A new efficient improvement, called Predictive Particle Modification (PPM), is proposed in this paper. This modification makes the particle look to the near area before moving toward the best solution of the group.This modification can be applied to any population algorithm. The basic philosophy of PPM is explained in detail. To evaluate the performance of PPM, it is applied to Particle Swarm Optimization (PSO) algorithm and Teaching Learning Based Optimization (TLBO) algorithm then tested using 23 standard benchmark functions. The effectiveness of these modifications are compared with the other unmodified population optimization algorithms based on the best solution, average solution, and convergence rate

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Enhancing radial distribution system performance by optimal placement of DSTATCOM - 01/0

Said Fouad Mohamed Mekhemar

Almoataz Y. Abdelaziz; R H Shehata; M. A. Algabalawy

01/06/2020

In this paper, A novel modified optimization method was used to find the optimal location and size for placing distribution Static Compensator in the radial distribution test feeder in order to improve its performance by minimizing the total power losses of the test feeder, enhancing the voltage profile and reducing the costs. The modified grey wolf optimization algorithm is used for the first time to solve this kind of optimization problem. An objective function was developed to study the radial distribution system included total power loss of the system and costs due to power loss in system. The proposed method is applied to two different test distribution feeders (33 bus and 69 bus test systems) using different Dstatcom sizes and the acquired results were analyzed and compared to other recent optimization methods applied to the same test feeders to ensure the effectiveness of the used method and its superiority over other recent optimization mehods. The major findings from obtained results that the applied technique found the most minimized total power loss in system, the best improved voltage profile and most reduction in costs due power loss compared to other methods.

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Population based optimization algorithms improvement using the predictive particles - 01/0

Said Fouad Mohamed Mekhemar

M. M. H. Elroby, M. A. Moustafa Hassan

01/06/2020

A new efficient improvement, called Predictive Particle Modification (PPM), is proposed in this paper. This modification makes the particle look to the near area before moving toward the best solution of the group. This modification can be applied to any population algorithm. The basic philosophy of PPM is explained in detail. To evaluate the performance of PPM, it is applied to Particle Swarm Optimization (PSO) algorithm and Teaching Learning Based Optimization (TLBO) algorithm then tested using 23 standard benchmark functions. The effectiveness of these modifications are compared with the other unmodified population optimization algorithms based on the best solution, average solution, and convergence rate.

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Generalized optimal placement of PMUs considering power system observability, communication infrastructure, and quality of service requirements - 01/0

Said Fouad Mohamed Mekhemar

M. M. H. Elroby; M. A. Moustafa Hassan

01/06/2020

This paper presents a generalized optimal placement of Phasor Measurement Units (PMUs) considering power system observability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover, the economic study for additional new data transmission paths is considered as well as the availability of predefined locations of some PMUs and the preexisting communication devices (CDs) in some buses. Two cases for the location of the Control Center Base Station (CCBS) are considered; predefined case and free selected case. The PMUs placement and their required communication network topology and channel capacity are co-optimized simultaneously. In this study, two different approaches are applied to optimize the objective function; the first approach is combined from Binary Particle Swarm Optimization-Gravitational Search Algorithm (BPSOGSA) and the Minimum Spanning Tree (MST) algorithm, while the second approach is based only on BPSOGSA. The feasibility of the proposed approaches are examined by applying it to IEEE 14-bus and IEEE 118-bus systems.

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Generation expansion planning with high shares of variable renewable energies - 01/0

Said Fouad Mohamed Mekhemar

Abdelzaher, M.M., Abdelaziz, A.Y., Mahmoud, H.M., Ali, S.G., Alhelou, H.H.

01/03/2020

Worldwide, the utilization of Renewable Energies (REs) for electricity generation is growing rapidly driven by the increasing fears of fossil fuels depletion, the price volatility of these fuels and the necessity of reducing the Green House Gas (GHG) emissions to preserve the environment. On the other hand, REs especially the Variable Renewable Energies (VREs) like wind and solar power suffer from intermittency in its output generation. This intermittency can introduce severe technical and economic problems for the power systems with high penetration from these energies. This intermittency should be mitigated not only during the system operation phase but also during power system planning phase. For this purpose, the classical power system planning methodologies and models should be upgraded to account for this intermittency in a way to find the optimum solutions to mitigate it. In this regard, this paper will focus on developing a new Generation Expansion Planning (GEP) model to find the optimum mix of dispatchable generation technologies that can allow the integration of VREs into the power system while mitigating the technical and economic impacts of its intermittency. In addition, a number of new concepts related to generation mix flexibility, VREs capacity credit and role of system operating reserve in integrating VREs will be revisited. Then, the developed GEP model will be applied to a case study handling the future expansion scenarios of VREs in the Egyptian grid. Results obtained show that, increasing the share of VREs in the grid will shift the mix of new generation capacities from the least cost and low flexibility options into more expensive and flexible generation options.

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Analyzing Wind Power Ramps for High Penetration of Variable Renewable Generation - 01/1

Said Fouad Mohamed Mekhemar

M Saber Eltohamy, M Said Abdel Moteleb, S Fouad Mekhemer

01/12/2019

One of the greatest issues connected with incorporating high penetration levels of variable renewable generation into the power system is the capability to handle the unlimited ramps in the renewable power production. It is essential for power system operators to have statistical information on the power ramping features of renewables generation. This information can be utilized in power system operations to mitigate ramping events for the sake of power system flexibility, reliability and economic considerations. Grid operators had successfully balanced the variability of collective power output at low penetration of variable renewable generation, but as the installations of renewable energy continue to grow, the ability to manage these fluctuations has become a difficult task. At high renewable penetration, more power ramps with short durations occurred as the number of ramping events increased with increasing penetration level [1]. In this paper the output power of wind generation will be analyzed to get information about the wind power ramping behavior by analyzing the historical data of power-time curve in two directions, vertical and horizontal. While the forecast of wind power has been improved, the forecast errors are still relatively high. As a result, with the increase in the participation rate of variable generation, these errors will significantly affect the balance of generating capacity and consumption. Consequently, from the perspective of grid operators, it will be necessary to gain a deeper understanding of the aggregate ramping scale and the periods that collective ramp events are most likely to occur. The analyzing method will be demonstrated by analyzing the output power of aggregated Belgium's wind farms, 3.16 GW, in the year of 2018.

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Optimal Power Flow of Power Systems Using Hybrid Firefly and Particle Swarm Optimization Technique - 01/1

Said Fouad Mohamed Mekhemar

H. M. Hasanien

01/12/2019

This paper presents a new endeavor of using the Hybrid Firefly and Particle Swarm Optimization (HFPSO) technique in tackling the optimal power flow (OPF) problem for electric power networks. The fuel cost optimization represents the main target considering the system constraints. The decision variable of the OPF problem is chosen to be the generators output real power. The HFPSO technique is chosen to optimize the objective function and to determine the optimal solutions of the problem. Many IEEE test systems are included in this study to assure the soundness of the introduced technique such as the IEEE 14-bus, 30-bus, and 57-bus grids. To acquire a sensible outcome, actual load curves are taken into account during the examination. Simulation results are examined then investigated. They show the appropriateness and privilege of the presented HFPSO -based OPF problem over the genetic algorithm (GA) and the particle swarm optimization (PSO).

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Overview of Power System Flexibility Options with Increasing Variable Renewable Generations - 01/1

Said Fouad Mohamed Mekhemar

aber Eltohamy, M Said Abdel Moteleb

01/11/2019

Many energy systems around the world tend to generate electricity from renewable energy sources as an alternative to the use of high-carbon fossil fuels. Increasing the rate of inclusion of renewable power plants in power systems at the expense of conventional power plants will result in new challenges in dealing with the unexpected generation capacity of these plants. This research discusses the various flexibility options for power systems in dealing with this variable and uncertain generating capacity at different time intervals to achieve the desired balance between generating capacity and load needs.

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Technical Investigation for Power System Flexibility - 01/1

Said Fouad Mohamed Mekhemar

M Saber Eltohamy, M Said Abdel Moteleb, S Fouad Mekhemer

01/11/2019

Power systems face growing flexibility requirements for managing the increased penetrations from variable renewable generation (VRG) like solar and wind power generation. In general, instant balance of temporal inequalities between supply and demand can be reached by many flexibility options. However, an accurate quantification of the flexibility needed and available in a power system is a complex task. Accordingly, this paper introduces a review of various power system flexibility metrics that used to quantify the flexibility. The use of these metrics varied, some of which were used to measure the flexibility available from each conventional generator and others were used to measure the flexibility available and needed by the power system at both the planning and operational stages, but up till now there is no flexibility metric that can be taken as a standard.

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Optimal placement of phasor measurement units considering islanding contingency, communication infrastructure, and quality of service - 01/0

Said Fouad Mohamed Mekhemar

Elroby, M.M.H., Hassan, M.A.M.

01/09/2019

In this study, the PMUs are placed to operate in normal and islanded cases taking into account power systemobservability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover,the economic study for additional new data transmission paths is considered as well as the preexistingCommunication Devices (CDs) and the availability of predefined locations of some PMUs in some buses. ThePMUs placement and their communication network topology and link channel capacity are co-optimized simul-taneously. Two different approaches are applied to optimize the objective function; the first approach is combinedfrom Binary Teaching Learning Based Optimization Algorithm (BTLBOA) and the Minimum Spanning Tree (MST)algorithm, while the second approach is based on BTLBOA. The proposed approaches are examined using IEEE118-bus systems

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Solution of distributed generation allocation problem using a novel method - 01/0

Said Fouad Mohamed Mekhemar

Abdelaziz, A.Y., Shehata, R.H.

01/08/2019

In this paper, A novel optimization technique called whale optimization algorithm (WOA) is modified, used and implemented to find the best possible solution to the problem of optimal locating and sizing of Distributed Generation (DG) resources such as photovoltaic cells, fuel cells and kVAR compensators in radial distribution feeders. The modified technique is used for the first time to solve this kind of optimization problem which includes optimal sizing and location of DG units in radial distribution feeder. The proposed method is applied to two different test distribution feeders (15 bus and 33 bus test systems) using different DG types and the acquired results are analyzed and compared to other modern optimization methods to confirm that they give the best results, lowest system real power losses and highest voltage profile improvement among the other modern methods implemented on the same test systems.

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Optimal Power Flow of Power Systems Including Distributed Generation Units Using Sunflower Optimization Algorithm - 01/0

Said Fouad Mohamed Mekhemar

H. M. Hasanien

01/08/2019

This article introduces a new attempt of utilizing the sunflower optimization (SFO) algorithm in solving the problem of optimal power flow (OPF) in the field of power systems. The principle target is to optimize the generating units' fuel cost under the system constraints. At initial stage, the objective function is solved to find the optimal siting of Distributed Generation (DG) units within the system under study. Then, different scenarios are performed to solve the OPF problem including and excluding DG units. The generators' real output power defines the exploration field for the OPF problem. The SFO algorithm is used to minimize the fitness function and yields the best solutions of the problem. More than one electric grid is tested to check the validity of the proposed algorithm such as the IEEE 14-bus, and 30-bus networks. Simulations included different scenarios are implemented in these two networks. To obtain a realistic result, real daily load curve is considered in this study. The results of simulations are investigated and analyzed. Results confirm the flexibility, validation, and applicability of the introduced SFO-based OPF methodology when compared with the genetic algorithm.

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Solution of distributed generation allocation problem using a novel method - 01/0

Said Fouad Mohamed Mekhemar

Shehata, R.H. Abdelaziz, A.Y.

01/08/2019

In this paper, A novel optimization technique called whale optimization algorithm (WOA) is modified, used and implemented to find the best possible solution to the problem of optimal locating and sizing of Distributed Generation (DG) resources such as photovoltaic cells, fuel cells and kVAR compensators in radial distribution feeders. The modified technique is used for the first time to solve this kind of optimization problem which includes optimal sizing and location of DG units in radial distribution feeder. The proposed method is applied to two different test distribution feeders (15 bus and 33 bus test systems) using different DG types and the acquired results are analyzed and compared to other modern optimization methods to confirm that they give the best results, lowest system real power losses and highest voltage profile improvement among the other modern methods implemented on the same test systems.

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Maximum power point tracking under partial shading condition using particle swarm optimization with DC-DC boost converter - 01/1

Said Fouad Mohamed Mekhemar

Ahmed Hossam EL-Din ; Hadi M. EL-Helw

01/12/2018

This paper introduces a new algorithm based on the particle swarm optimization for maximum power point tracking MPPT of photovoltaic systems under partial shading conditions. In this paper, the PV module is interfaced to the load using DC-DC boost converter. The MATLAB/SIMULINK is utilized to obtain this study. The simulation results show the high tracking efficiency of the proposed technique under different irradiance patterns. The suggested algorithm success to hunt the global operating point of maximum power by controlling the DC/DC converter.

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Considerations on optimal design of hybrid power generation systems using whale and sine cosine optimization algorithms - 01/1

Said Fouad Mohamed Mekhemar

Mostafa A.Algabalawy,Almoataz Y.Abdelaziz, Shady H.E.Abdel Aleem

01/12/2018

Nowadays, the continuous increase of power demand leads to various challenges for distribution system operators (DSOs) such as power quality, system stability and reliability. Microgrids (MGs) and hybrid power generation systems (HPGSs) can play a significant role in solving these issues while improving the performance of electrical power systems. In this paper, an optimal multi-criteria design of a grid-connected HPGS is introduced, taking into consideration involvement of a natural gas distribution network (NGDN) in the proposed configuration, where the NGDN supplies natural gas to a gas turbine. The HPGS system consists of wind turbines (WT), photovoltaic (PV) arrays, battery banks (BBs), gas turbines (GTs), in addition to a utility grid (UG). Two different meta-heuristic optimization algorithms, namely whale, and sine cosine, are employed to find the optimal design of the system for minimizing the total annual cost and system emissions. A detailed comparative study of the results with results of the cuckoo search and firefly optimization algorithms is presented to show the robustness of the used techniques.

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Reactive Power and Voltage Control of Offshore Wind Parks Based PI Controller tuning for STATCOM via Genetic Algorithm - 01/1

Said Fouad Mohamed Mekhemar

Ahmed Z. Hussein, Naggar Hassan Saad

01/12/2018

Nowadays Offshore wind parks have more attention compared with other renewable energy resources. On the other hand, transmitting the generated power from offshore to the onshore grid through high voltage alternating current (HVAC) submarine cables generates a large amount of reactive power; this problem made the transmitting of power is not complying with the grid code requirements. This paper introduces a perfect solution for solving this problem. Static synchronous compensator (STATCOM) was developed to solve these issues. To investigate the influence of STATCOM on the system, a simulation model of the system is created by MATLAB Simulink software, and the results were obtained with and without consideration of STATCOM effect. The simulation results show the operation of the system without compensation, the beneficial performance of STATCOM compensation in the system, the optimum operation of STATCOM with tuning PI controllers using genetic algorithm (GA), and the dynamic performance of STATCOM under fault. The results show the effectiveness of STATCOM on the system.

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Solution of the capacitor allocation problem using an improved whale optimization algorithm - 01/1

Said Fouad Mohamed Mekhemar

R.H. Shehata, A.Y. Abdelaziz

01/10/2018

A superior optimization technique called whale optimization algorithm introduced in 2016 which belongs to swarm intelligence family is used and implemented in this paper with some improvements to solve the problem of capacitor allocation in radial distribution feeders. In order to show the effectiveness of the proposed technique, three test distribution feeders are used (15 bus, 34 bus and 69 bus test systems). The obtained results are compared with other optimization techniques prove that the proposed method gives the optimal results; most reduction in system power losses, voltage profile enhancement and lower annual cost among the other techniques applied to the same distribution feeders.

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Application of Different Optimization Techniques to Load Frequency Control with WECS in A Multi-Area System - 01/1

Said Fouad Mohamed Mekhemar

Mohamed Mostafa Elsaied, Mahmoud Abdallah Attia, Mahmoud Abdelhamed Mostafa

01/10/2018

This article presents a load frequency control in a two-area interconnected system under wave energy disturbance. At steady state, the system frequency is maintained at the nominal value so there is no frequency deviation. Also, there is no deviation in the tie line power from the value at steady state. But increasing and decreasing of load in any of the two areas may affect the system frequency. Renewable energy variation also can affect the frequency deviation. In this article, first two controllers are used to enhance the system stability during the load change. These controllers are proportional-integral-derivative (PID) and proportional-integral-derivative and acceleration (PIDA). Three optimization techniques are presented in this article to tune the controllers’ parameters. The optimization techniques are teaching-learning-based-optimization (TLBO), harmony search algorithm (HS) and sine-cosine algorithm (SCA). PIDA and TLBO have been proved the best performance during the transient period. The system is then subjected to a disturbance in the form of wave energy conversion system (WECS) when it is equipped with PIDA and using TLBO technique.

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Impact of generation mix flexibility on the integration of variable renewable energies - 01/0

Said Fouad Mohamed Mekhemar

  M.M. Abdelzaher, H.M. Mahmoud, A.Y. Abdelaziz, S.F. Mekhamer, M.A.L. Badr

01/08/2018

Worldwide, renewable energies are witnessing a huge expansion especially for power generation driven by different factors including the increased demand on fossil fuels and the depletion of its resources, the increase in its cost and the need to preserve the environment. Variable Renewable Energies (VRE) especially depending on wind and solar resources are intermittent by nature and this intermittency can have severe impacts on the operation of the power systems. Power systems are thus required to have a sufficient degree of flexibility to deal with this intermittency especially in the generation side. This paper introduces a hybrid Flexibility Enhanced Priority List-Mixed Integer Linear Programming (FEPL-MILP) method to solve the Unit Commitment (UC) problem and study the impact of the generation mix flexibility on the integration of renewable energies. Results show that, increasing the flexibility of the thermal energy mix used for power generation will have positive technical and economic impacts on the integration of renewable energies into the power system.

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Design of Hybrid Power Generation Systems Connected to Utility Grid and Natural Gas Distribution Network: A New Contribution - 01/0

Said Fouad Mohamed Mekhemar

Almoataz Abdelaziz – Mostafa Algabalawy

01/04/2018

Hybrid power generation system (HPGS) is an active research area, which is in need of a continuous improvement. It represents the best solution for the most complex problems facing the world in the last decades. These problems are known as the shortage of energy, or lack of electricity, which logically are the results of the continuous increasing demand. Therefore, the researchers do their best to overcome all expected roadblocks facing the development, where the most applicable solutions to solve these problems are introduced. In this paper, the HPGS includes; wind turbine (WT), photovoltaic (PV), storage battery (SB), gas turbine (GT), and utility grid (UG). The GT of this system is fueled directly from the natural gas distribution network considering all operational conditions of it, which may be affected by fueling the natural gas for the GT. So, the natural gas distribution network is becoming an important component of the HPGS, and it is included in the HPGS for the first time. Multi metaheuristic optimization techniques are applied to obtain the components sizing of this system, where cuckoo search algorithm (CSA), firefly algorithm (FA), and flower pollination algorithm (FPA) have been applied. Therefore, this paper introduces a new contribution not only to the new configuration of the HPGS, but also in applying the new optimization techniques as solving tools. The output results are compared to show the effectiveness and the superiority of the applied techniques as well as extract a recommendation for the best solving technique.

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Design of an adaptive overcurrent protection scheme for microgrids - 01/0

Said Fouad Mohamed Mekhemar

Mohamed Awaad , Almoataz Y. Abdelaziz

01/01/2018

Microgrid is a new phenomenon regarded to Distributed Generation (DG) penetration in the existing distribution systems. In this paper adaptive over current (OC) protection technique for a distribution system with DG penetration is proposed. This scheme takes into account general protection requirements, impacts of DG on protection system and protection coordination. A part of IEEE 13 nodes radial distribution test feeder is taken as a study case to test the effectiveness of the proposed scheme using ETAP software.

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Design of Hybrid Power Generation Systems Connected to Utility Grid and Natural Gas Distribution Network: A New Contribution - 01/0

Said Fouad Mohamed Mekhemar

A. Y. Abdelaziz, Mostafa Algabalawy

01/01/2018

Hybrid power generation system (HPGS) is an active research area, which is in need of a continuous improvement. It represents the best solution for the most complex problems facing the world in the last decades. These problems are known as the shortage of energy, or lack of electricity, which logically are the results of the continuous increasing demand. Therefore, the researchers do their best to overcome all expected roadblocks facing the development, where the most applicable solutions to solve these problems are introduced. In this paper, the HPGS includes; wind turbine (WT), photovoltaic (PV), storage battery (SB), gas turbine (GT), and utility grid (UG). The GT of this system is fueled directly from the natural gas distribution network considering all operational conditions of it, which may be affected by fueling the natural gas for the GT. So, the natural gas distribution network is becoming an important component of the HPGS, and it is included in the HPGS for the first time. Multi metaheuristic optimization techniques are applied to obtain the components sizing of this system, where cuckoo search algorithm (CSA), firefly algorithm (FA), and flower pollination algorithm (FPA) have been applied. Therefore, this paper introduces a new contribution not only to the new configuration of the HPGS, but also in applying the new optimization techniques as solving tools. The output results are compared to show the effectiveness and the superiority of the applied techniques as well as extract a recommendation for the best solving technique.

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A Power System Adaptive Scheme Depending on a Data Mining Model - 01/1

Said Fouad Mohamed Mekhemar

W. M. Gamal

01/12/2017

The conditions of any power system always keep on changing over time due to the continuous load variation nature of the system. The conventional relays that had been always used for power system protection face difficulties to comply and offer the required protection because of their fixed settings parameters. Many adaptive solutions have been introduced. They depend on evaluating the system conditions in order to help taking the proper actions, regarding changing the relay settings or protection schemes to suit the new system conditions. Among these solutions, data mining-based solutions are distinctive. The most frequently used data mining algorithm for the evaluation process is the decision trees. This paper introduces a new evaluating data mining model using support vector machines (SVM), as another superior tool. The SVM model proves to have higher correct rate in evaluating and predicting the system conditions than the decision trees model.

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Optimal Battery Sizing in Wind System Using Firefly and Harmony Search Techniques - 01/1

Said Fouad Mohamed Mekhemar

Ibrahim M. Ibrahim

01/12/2017

This paper investigates the use of the battery storage to solve the power fluctuations problem of a grid connected wind energy system. The main objective of the study is to obtain the optimal size of the battery which reduces the wind power fluctuations to be within acceptable limits and maximizes the profit gained from selling the energy to the grid. The formulated optimization problem is solved using two optimization techniques; the Firefly Algorithm and the Harmony Search Algorithm which have not been used in the previous studies related to the wind power fluctuations problem presented in this paper. The problem codes are implemented using MATLAB program.

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Optimal Design of a New Configuration of the Distributed Generation Units using Grey Wolf and Dragonfly Optimizers - 01/0

Said Fouad Mohamed Mekhemar

M. A. Algabalawy, A. Y. Abdelaziz

01/01/2017

Distributed generation units are used to share the loads with the conventional power plants or may be used to supply the power to the loads individually. Wind turbine (WT), photovoltaic (PV), storage battery (SB), fuel cell (FC), gas turbine (GT), and micro-turbine (MT) are considered the most distinctive distributed generation units, which are used in this type of applications. There are much combinations or configurations of these power sources, where the WT may be combined only with the PV. This combination might be combined with the SB. Or WT, PV, and SB are connected with the FC to form another HPGS. This paper introduces a new configuration of these distributed generation units, where WT, PV, SB, and GT are combined to form a new power generation system, known as hybrid power generation system (HPGS). This configuration is classified as a stand-alone HPGS. On the other hand, if this configuration is connected to the utility, it is called as a utility connected HPGS. In this paper, for the first time, the natural gas distribution network is used to deliver the required fuel for the GT of the HPGS, where all operational conditions of this network are considered. New meta-heuristic optimization techniques are also presented for the first time for the HPGS designing. The applied techniques are; the grey wolf optimizer (GWO) and the dragonfly optimizer (DO).

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A probabilistic approach for the optimal placement of PMUs with limited number of channels - 01/1

Said Fouad Mohamed Mekhemar

Ahmed Hamdy Ghazy Ibrahim

01/12/2016

This paper presents a two-stage method for the placement of Phasor Measurement Units (PMUs) to achieve a fully observable power system while considering the PMUs channel limitation. The first stage uses the Binary Integer Linear Programming (BILP) to find the initial optimum locations of PMUs which ensure full system observability under normal conditions. The second stage uses state enumeration based on probabilistic failure of different components to ensure full system observability under single and double outages. The proposed method is validated using the IEEE 14-Bus system, IEEE 30-Bus system and IEEE 57-Bus system. The simulation results show that the method is efficient in providing detailed information about the observability of the power system under different operating conditions.

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Optimal multi-criteria design of a new hybrid power generation system using ant lion and grey wolf optimizers - 01/1

Said Fouad Mohamed Mekhemar

M. A. Algabalawy ; A.Y. Abdelaziz

01/12/2016

The importance of the hybrid power generation systems (HPGS) increased especially in the last few years. HPGS are used to distribute the load between many different energy sources (e.g. utility grid (UG), wind turbine (WT), photovoltaic (PV), fuel cell (FC), and storage battery (SB)). These power sources are combined together in different configurations to form the HPGS. There are two common operation modes for these hybrid power systems; the first one is called as a standalone mode, in which the distributed power sources are combined together to supply the power without any supporting from the utility grid. The other mode is known as the utility grid connect mode, where the combination of these power sources is paralleled connected to the utility grid. This paper introduces a new contributions on the design of the HPGS, where the proposed hybrid system includes for the first time another energy utility such as the natural gas piping network. All operations conditions of this network are considered through the design of the HPGS. Applying modern meta-heuristic optimization techniques for the first time in the sizing of the HPGS. The applied techniques are; the ant lion optimizer (ALO) and grey wolf optimizers (GWO). MATLAB software has been used to execute the optimization process using ALO and GWO, and a detailed comparison is occurred between the results of applying the above mentioned techniques and another two modern optimizations techniques; Cuckoo search algorithm (CSA) and flower pollination algorithm (FPA) to show the effectiveness of applying both of ALO and GWO.

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Power System Observability of Phasor Measurement Units: A Binary Integer Programming Approach - 01/1

Said Fouad Mohamed Mekhemar

Ahmed Hamdy Ghazy Ibrahim

01/11/2015

In this paper, the allocation problem of Phasor measurement units (PMU) is solved using a binary integer programming (BIP) method. The proposed approach aims to minimize the total number of PMUs that can achieve full system observability. Defining N as the number of system buses, the full system observability is ensured both in normal operating conditions and in case of N-1 contingencies such as the outage of a PMU or a transmission line. Moreover, the approach is utilized to allocate the PMUs in case of limited number of PMU channels. The problem formulation considers the Zero Injection Buses (ZIBs) and uses a set of rules that can improve the redundancy of the PMUs by choosing better locations without increasing their number. The proposed approach is applied to the IEEE standard systems 14, 30 and 57 test systems. The simulations results are compared with other approaches used in the literature to validate the effective performance of the proposed approach.

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Enhancing the Power System Observability with the Aid of Phasor Measurement Units - 01/0

Said Fouad Mohamed Mekhemar

Ahmed Hamdy Ghazy Ibrahim

01/09/2015

This paper presents an approach for optimally allocating the Phasor Measurement Units (PMUs) in a power system. The proposed approach is based on Binary Integer Programming (BIP) to minimize the total number of PMUs that can achieve full system observability. The full system observability is ensured both in normal operating conditions and in case ofN-1 contingencies such as the outage of a PMU or a transmission line. Moreover, the approach is utilized to allocate the PMUs in case of limited number of PMU channels. The problem formulation considers the Zero Injection Buses (ZIBs) and uses a set of rules that can improve the redundancy of the PMUs by choosing better locations without increasing their number. The proposed approach is applied on the IEEE standard systems 14, 30 and 57 test systems. The simulations results are compared with other approaches used in the literature to validate the performance of the proposed approach.

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The Firefly Meta-Heuristic Algorithms: Developments and Applications - 01/0

Said Fouad Mohamed Mekhemar

A. Y. Abdelaziz, M. A. Algabalawy

01/09/2015

—The global solution becomes the dream of the researchers, who are interested in optimization techniques. They believe that, the global solution will provide the optimum conditions for the operation. Operations research is the main umbrella for the optimization techniques that study the shortest and critical path to achieve the activities of a project. Thus, the researchers concern the optimization techniques development; especially the meta-heuristic techniques. Researchers aim to obtain the techniques that provide the global solution with minimum time of operation. Firefly algorithm (FA) has been considered one of the meta-heuristic techniques developed to solve the optimization problems using the simulation of the behavior of the fireflies. Much searches prove the high accuracy and quality of the results of the optimization techniques solved by the FA. This paper analyses and summarizes most of these developments and applications. This paper gives a literature survey for different combinations of HPGS that consist of different combinations of PV, WT, SB MT, diesel generator, and Fuel Cell.

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Analysis of Subsynchronous Resonance Using Neural Networks - 01/0

Said Fouad Mohamed Mekhemar

T M K Amer; Hassan Mohamed Mahmoud; Almoataz Y. Abdelaziz; M M Mansour

01/04/2009

Artificial Neural Networks (ANNs) are being advantageously applied for power system problems. They possess the ability to establish complicated input-output mappings through a learning process, without any explicit programming. In this paper, two ANNs for Subsynchronous Resonance (SSR) analysis are presented. The designed ANNs measure the possibility of SSR occurrence. The effectiveness of this approach is tested by experimenting it on the first bench mark model proposed by IEEE Task Force on SSR. I. INTRODUCTION Series capacitor compensation is employed in electric power systems to raise the power transmission limit of long EHV lines. This, however, may lead to the phenomenon of subsynchronous resonance (SSR) [1-2]. SSR occurs when a natural frequency of a series compensated transmission system aligns with the complement of one of the torsional modes of turbine-generator [3-5]. This happens at sub-synchronous frequencies. Under such circumstances, the turbine-generator oscillates at a frequency corresponding to the torsional mode frequency, and unless corrective action is taken, the torsional oscillations can continue for a long time and may result in the failure of the turbine-generator shaft [6-8]. There are several countermeasures proposed in the literature to avoid such a condition like torsional motion relay, armature current relay, static block filter and generator circuit series reactance [9-12]. Eigenvalue analysis is computationally intensive and the modeling complexity required for this method of analysis is quite high. Hence, it is necessary to design effective technique for eigenvalue analysis for the study of SSR which could avoid the conventional computation of eigenvalues and alleviate the modeling complexity as well. Note that there are two modes of oscillations corresponding to the electrical network one in subsynchronous range and the other in supersynchronous range; we only interested with the subsynchronous range. In this paper, two multi-layer feed forward ANN's are presented and used to detect and analyse the SSR conditions .

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ANN for Subsynchronous Resonance Detection - 01/0

Said Fouad Mohamed Mekhemar

T. M. K. Amer, H. M. Mahmoud; . Y. Abdelaziz; M. M. Mansour

01/01/2009

Artificial Neural Networks (ANNs) are being advantageously applied for power system problems. They possess the ability to establish complicated input-output mappings through a learning process, without any explicit programming. In this paper, two ANNs for Subsynchronous Resonance (SSR) analysis are presented. The designed ANNs measure the possibility of SSR occurrence. The effectiveness of this approach is tested by experimenting it on the first bench mark model proposed by IEEE Task Force on SSR.

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