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In this document, the topic of discussion is the combination of two existing algorithms to generate a new hybrid technique. The two algorithms that are subjected to said amalgamation are Genetic Algorithms (GA) and Stain Bowerbird Optimization algorithms (SBO). These two methodologies have profound utility themselves and are used in a multitude of scenarios. The easy application and the constructive outcomes manifested by these two algorithms birthed the idea of their combined usage. Following up on this, the hybrid GASBO was created. GASBO was an optimization approach used to detect and categorize the allotted renewable energy assets in a specific energy generation complex. This was done to regulate the energy dispensing systems otherwise known as ‘distributing’ systems. These renewable resources are reflected by environmental factors and the energy they create is also dependent on their surroundings. Factors like sunlight, rain, waves, and tides etcetera play major roles in determining the outcome of the created energy. Contrary to what it may appear like, the position of the DG sources in the structure affects the outcome a lot. These sources contain fuel cells and photovoltaic cells: in short, devices that can harness energy from a seemingly infinite supply like sunlight. As mentioned before, the GASBO assisted in providing the best location for the system and it also categorized the sources according to their abilities. The potential and position of the sources in the grid are of vast importance. The main purpose of GASBO is to optimize the overall system by improving its efficiency and reducing collateral harm. This shows that GASBO is quite a fundamental tool. It has also been tested on several systems like IEEE 33-bus. The facts in this paper are based on published projects.
Ashraf Mohamed Hemeida; Omaima M. Bakry; Al-Attar A. Mohamed; Eman A. Mahmoud. Genetic Algorithms and Satin Bowerbird Optimization for optimal allocation of distributed generators in radial system. Applied Soft Computing 2021, 111, 107727 .
AMA StyleAshraf Mohamed Hemeida, Omaima M. Bakry, Al-Attar A. Mohamed, Eman A. Mahmoud. Genetic Algorithms and Satin Bowerbird Optimization for optimal allocation of distributed generators in radial system. Applied Soft Computing. 2021; 111 ():107727.
Chicago/Turabian StyleAshraf Mohamed Hemeida; Omaima M. Bakry; Al-Attar A. Mohamed; Eman A. Mahmoud. 2021. "Genetic Algorithms and Satin Bowerbird Optimization for optimal allocation of distributed generators in radial system." Applied Soft Computing 111, no. : 107727.
Electric vehicle charging station have become an urgent need in many communities around the world, due to the increase of using electric vehicles over conventional vehicles. In addition, establishment of charging stations, and the grid impact of household photovoltaic power generation would reduce the feed-in tariff. These two factors are considered to propose setting up charging stations at convenience stores, which would enable the electric energy to be shared between locations. Charging stations could collect excess photovoltaic energy from homes and market it to electric vehicles. This article examines vehicle travel time, basic household energy demand, and the electricity consumption status of Okinawa city as a whole to model the operation of an electric vehicle charging station for a year. The entire program is optimized using MATLAB mixed integer linear programming (MILP) toolbox. The findings demonstrate that a profit could be achieved under the principle of ensuring the charging station’s stable service. Household photovoltaic power generation and electric vehicles are highly dependent on energy sharing between regions. The convenience store charging station service strategy suggested gives a solution to the future issues.
Yongyi Huang; Atsushi Yona; Hiroshi Takahashi; Ashraf Hemeida; Paras Mandal; Alexey Mikhaylov; Tomonobu Senjyu; Mohammed Lotfy. Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation. Sustainability 2021, 13, 6163 .
AMA StyleYongyi Huang, Atsushi Yona, Hiroshi Takahashi, Ashraf Hemeida, Paras Mandal, Alexey Mikhaylov, Tomonobu Senjyu, Mohammed Lotfy. Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation. Sustainability. 2021; 13 (11):6163.
Chicago/Turabian StyleYongyi Huang; Atsushi Yona; Hiroshi Takahashi; Ashraf Hemeida; Paras Mandal; Alexey Mikhaylov; Tomonobu Senjyu; Mohammed Lotfy. 2021. "Energy Management System Optimization of Drug Store Electric Vehicles Charging Station Operation." Sustainability 13, no. 11: 6163.
This article proposes a plan to replace real-time power with constant power from the grid to reduce costs and reduce the impact of the micro-grid on the main grid at the same time. Most of the peak electricity consumption periods of universities or some enterprise institutions are during the daytime. If solar energy can be used reasonably at this time, it can provide a good guarantee of peak power. In this study, a grid-linked solar-plus-storage micro-grid was used to supply power to a university located in Okinawa, Japan. The non-dominated sorting genetic algorithm II (NSGA-II) was used to optimize the model size, and the loss of power supply probability (LPSP), life cycle cost (LCC), and waste of energy (WE) were taken as the optimization indicators. For this study, three scenarios were considered where the first scheme (Case 1) was a comparison scheme, which used a PV battery and real-time power from the infinity bus. Both the second and third cases used constant power. While Case 2 used constant power throughout the year, Case 3 used daily constant power. The optimal solutions for the power supply units were grouped into three cases where Case 1 was found to be the most expensive one. It was found that the costs of Cases 2 and 3 were 62.8% and 63.3% less than Case 1. As a result, the waste of energy was found to be more significant than Case 1: 70 times and 60 times, respectively. On the contrary, Case 1 had 15.2% and 16.7% less carbon emissions than Case 2 and Case 3, respectively. This article put forward the idea of constant power supply growth at the financial markets, which breaks the traditional way in which the power supply side follows the user’s consumption. While reducing costs, it reduces the impact on large-scale power grids and can also ensure the reliability of campus microgrids.
Yongyi Huang; Hasan Masrur; Ryuto Shigenobu; Ashraf Hemeida; Alexey Mikhaylov; Tomonobu Senjyu. A Comparative Design of a Campus Microgrid Considering a Multi-Scenario and Multi-Objective Approach. Energies 2021, 14, 2853 .
AMA StyleYongyi Huang, Hasan Masrur, Ryuto Shigenobu, Ashraf Hemeida, Alexey Mikhaylov, Tomonobu Senjyu. A Comparative Design of a Campus Microgrid Considering a Multi-Scenario and Multi-Objective Approach. Energies. 2021; 14 (11):2853.
Chicago/Turabian StyleYongyi Huang; Hasan Masrur; Ryuto Shigenobu; Ashraf Hemeida; Alexey Mikhaylov; Tomonobu Senjyu. 2021. "A Comparative Design of a Campus Microgrid Considering a Multi-Scenario and Multi-Objective Approach." Energies 14, no. 11: 2853.
Penetration of equipment such as photovoltaic power generations (PV), heat pump water heaters (HP), and electric vehicles (EV) introduces voltage unbalance issues in distribution systems. Controlling PV and energy storage system (ESS) outputs or coordinated EV charging are investigated for voltage unbalance compensation. However, some issues exist, such as dependency on installed capacity and fairness among consumers. Therefore, the ideal way to mitigate unbalanced voltages is to use grid-side equipment mainly. This paper proposes a voltage unbalance compensation based on optimal tap operation scheduling of three-phase individual controlled step voltage regulators (3ϕSVR) and load ratio control transformer (LRT). In the formulation of the optimization problem, multiple voltage unbalance metrics are comprehensively included. In addition, voltage deviations, network losses, and coordinated tap operations, which are typical issues in distribution systems, are considered. In order to investigate the mutual influence among voltage unbalance and other typical issues, various optimization problems are formulated, and then they are compared by numerical simulations. The results show that the proper operation of 3ϕSVRs and LRT effectively mitigates voltage unbalance. Furthermore, the results also show that voltage unbalances and other typical issues can be improved simultaneously with appropriate formulations.
Akito Nakadomari; Ryuto Shigenobu; Takeyoshi Kato; Narayanan Krishnan; Ashraf Hemeida; Hiroshi Takahashi; Tomonobu Senjyu. Unbalanced Voltage Compensation with Optimal Voltage Controlled Regulators and Load Ratio Control Transformer. Energies 2021, 14, 2997 .
AMA StyleAkito Nakadomari, Ryuto Shigenobu, Takeyoshi Kato, Narayanan Krishnan, Ashraf Hemeida, Hiroshi Takahashi, Tomonobu Senjyu. Unbalanced Voltage Compensation with Optimal Voltage Controlled Regulators and Load Ratio Control Transformer. Energies. 2021; 14 (11):2997.
Chicago/Turabian StyleAkito Nakadomari; Ryuto Shigenobu; Takeyoshi Kato; Narayanan Krishnan; Ashraf Hemeida; Hiroshi Takahashi; Tomonobu Senjyu. 2021. "Unbalanced Voltage Compensation with Optimal Voltage Controlled Regulators and Load Ratio Control Transformer." Energies 14, no. 11: 2997.
This paper proposes a new and surge-less solid-state direct current (DC) circuit breaker in a high-voltage direct current (HVDC) transmission system to clear the short-circuit fault. The main purpose is the fast interruption and surge-voltage and over-current suppression capability analysis of the breaker during the fault. The breaker is equipped with series insulated-gate bipolar transistor (IGBT) switches to mitigate the stress of high voltage on the switches. Instead of conventional metal oxide varistor (MOV), the resistance–capacitance freewheeling diodes branch is used to bypass the high fault current and repress the over-voltage across the circuit breaker. The topology and different operation modes of the proposed breaker are discussed. In addition, to verify the effectiveness of the proposed circuit breaker, it is compared with two other types of surge-less solid-state DC circuit breakers in terms of surge-voltage and over-current suppression. For this purpose, MATLAB Simulink simulation software is used. The system is designed for the transmission of 20 MW power over a 120 km distance where the voltage of the transmission line is 220 kV. The results show that the fault current is interrupted in a very short time and the surge-voltage and over-current across the proposed breaker are considerably reduced compared to other topologies.
Gul Ludin; Mohammad Amin; Hidehito Matayoshi; Shriram Rangarajan; Ashraf Hemeida; Hiroshi Takahashi; Tomonobu Senjyu. Solid-State DC Circuit Breakers and Their Comparison in Modular Multilevel Converter Based-HVDC Transmission System. Electronics 2021, 10, 1204 .
AMA StyleGul Ludin, Mohammad Amin, Hidehito Matayoshi, Shriram Rangarajan, Ashraf Hemeida, Hiroshi Takahashi, Tomonobu Senjyu. Solid-State DC Circuit Breakers and Their Comparison in Modular Multilevel Converter Based-HVDC Transmission System. Electronics. 2021; 10 (10):1204.
Chicago/Turabian StyleGul Ludin; Mohammad Amin; Hidehito Matayoshi; Shriram Rangarajan; Ashraf Hemeida; Hiroshi Takahashi; Tomonobu Senjyu. 2021. "Solid-State DC Circuit Breakers and Their Comparison in Modular Multilevel Converter Based-HVDC Transmission System." Electronics 10, no. 10: 1204.
This work introduces multi-objective water cycle algorithm (MOWCA) to find the accurate location and size of distributed energy resource (DERs) considering different load models for two seasons (winter, and summer). The impact of uncertainties produced from load and renewable energy resource (RES) such as wind turbine (WT) and photovoltaic (PV) on the performance of the radial distribution system (RDS) are covered as this is closer to the real operation condition. The point estimate method (PEM) is applied for modeling the RES uncertainties. An optimization technique is implemented to find the multi-objective optimal allocation of RESs in RDSs considering uncertainty effect. The main objectives of the work are to maximize the technical, economic and environmental benefits by minimizing different objective functions such as the dissipated power, the voltage deviation, DG cost and total emissions. The proposed multi-objective model is solved by using multi-objective water cycle algorithm (MOWCA), considering the Pareto criterion with nonlinear sorting based on fuzzy mechanism. The proposed algorithm is carried out on different IEEE power systems with various cases.
Ayat Ali Saleh; Tomonobu Senjyu; Salem Alkhalaf; Majed A. Alotaibi; Ashraf M. Hemeida. Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models. Energies 2020, 13, 5800 .
AMA StyleAyat Ali Saleh, Tomonobu Senjyu, Salem Alkhalaf, Majed A. Alotaibi, Ashraf M. Hemeida. Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models. Energies. 2020; 13 (21):5800.
Chicago/Turabian StyleAyat Ali Saleh; Tomonobu Senjyu; Salem Alkhalaf; Majed A. Alotaibi; Ashraf M. Hemeida. 2020. "Water Cycle Algorithm for Probabilistic Planning of Renewable Energy Resource, Considering Different Load Models." Energies 13, no. 21: 5800.
This work introduces a new population-based stochastic search technique, named multi-variant differential evolution (MVDE) algorithm for solving fifteen well-known real world problems from UCI repository and compared to four popular optimization methods. The MVDE proposes a new self-adaptive scaling factor based on cosine and logistic distributions as an almost factor-free optimization technique. For more updated chances, this factor is binary-mapped by incorporating an adaptive crossover operator. During the evolution, both greedy and less-greedy variants are managed by adjusting and incorporating the binary scaling factor and elite identification mechanism into a new multi-mutation crossover process through a number of sequentially evolutionary phases. Feature selection decreases the number of features by eliminating irrelevant or misleading, noisy and redundant data which can accelerate the process of classification. In this paper, a new feature selection algorithm based on the MVDE method and artificial neural network is presented which enabled MVDE to get a combination features’ set, accelerate the accuracy of the classification, and optimize both the structure and weights of Artificial Neural Network (ANN) simultaneously. The experimental results show the encouraging behavior of the proposed algorithm in terms of the classification accuracies and optimal number of feature selection.
Somaia Hassan; Ashraf M. Hemeida; Salem Alkhalaf; Al-Attar Mohamed; Tomonobu Senjyu. Multi-variant differential evolution algorithm for feature selection. Scientific Reports 2020, 10, 1 -16.
AMA StyleSomaia Hassan, Ashraf M. Hemeida, Salem Alkhalaf, Al-Attar Mohamed, Tomonobu Senjyu. Multi-variant differential evolution algorithm for feature selection. Scientific Reports. 2020; 10 (1):1-16.
Chicago/Turabian StyleSomaia Hassan; Ashraf M. Hemeida; Salem Alkhalaf; Al-Attar Mohamed; Tomonobu Senjyu. 2020. "Multi-variant differential evolution algorithm for feature selection." Scientific Reports 10, no. 1: 1-16.
High-voltage direct current (DC) transmission systems and multi-terminal direct current transmission systems are attracting attention for expanding the grid to promote introduction of renewable energy. Fault clearing in DC systems is difficult because there is no zero point of current. Hybrid circuit breakers are suitable for fault clearing in DC systems. Conventional hybrid circuit breakers have a hard-switching path that damages the switch. Hard switching damages the device and produces emissions due to harmonic noise. A novel resonant hybrid DC circuit breaker is proposed in this paper. The proposed circuit breaker reduces the damage to the switching device using soft switching due to the current zero point. The proposed circuit breaker is compared with conventional hybrid circuit breakers using numerical simulations. Interruption times and switching types of circuit breakers were compared. The simulation results of the fault clearing characteristics of the proposed breakers show that the proposed breakers have sufficient performance and are capable of stable reconnections in multi-terminal direct current transmission systems.
Ryo Miyara; Akito Nakadomari; Hidehito Matayoshi; Hiroshi Takahashi; Ashraf M. Hemeida; Tomonobu Senjyu. A Resonant Hybrid DC Circuit Breaker for Multi-Terminal HVDC Systems. Sustainability 2020, 12, 7771 .
AMA StyleRyo Miyara, Akito Nakadomari, Hidehito Matayoshi, Hiroshi Takahashi, Ashraf M. Hemeida, Tomonobu Senjyu. A Resonant Hybrid DC Circuit Breaker for Multi-Terminal HVDC Systems. Sustainability. 2020; 12 (18):7771.
Chicago/Turabian StyleRyo Miyara; Akito Nakadomari; Hidehito Matayoshi; Hiroshi Takahashi; Ashraf M. Hemeida; Tomonobu Senjyu. 2020. "A Resonant Hybrid DC Circuit Breaker for Multi-Terminal HVDC Systems." Sustainability 12, no. 18: 7771.
Optimal sizing of power systems has a tremendous effective role in reducing the total system cost by preventing unneeded investment in installing unnecessary generating units. This paper presents an optimal sizing and planning strategy for a completely hybrid renewable energy power system in a remote Japanese island, which is composed of photovoltaic (PV), wind generators (WG), battery energy storage system (BESS), fuel cell (FC), seawater electrolysis plant, and hydrogen tank. Demand response programs are applied to overcome the performance variance of renewable energy systems (RESs) as they offer an efficient solution for many problems such as generation cost, high demand peak to average ratios, and assist grid reliability during peak load periods. Real-Time Pricing (RTP), which is deployed in this work, is one of the main price-based demand response groups used to regulate electricity consumption of consumers. Four case studies are considered to confirm the robustness and effectiveness of the proposed schemes. Mixed-Integer Linear Programming (MILP) is utilized to optimize the size of the system’s components to decrease the total system cost and maximize the profits at the same time.
Mahmoud M. Gamil; Makoto Sugimura; Akito Nakadomari; Tomonobu Senjyu; Harun Or Rashid Howlader; Hiroshi Takahashi; Ashraf M. Hemeida. Optimal Sizing of a Real Remote Japanese Microgrid with Sea Water Electrolysis Plant Under Time-Based Demand Response Programs. Energies 2020, 13, 3666 .
AMA StyleMahmoud M. Gamil, Makoto Sugimura, Akito Nakadomari, Tomonobu Senjyu, Harun Or Rashid Howlader, Hiroshi Takahashi, Ashraf M. Hemeida. Optimal Sizing of a Real Remote Japanese Microgrid with Sea Water Electrolysis Plant Under Time-Based Demand Response Programs. Energies. 2020; 13 (14):3666.
Chicago/Turabian StyleMahmoud M. Gamil; Makoto Sugimura; Akito Nakadomari; Tomonobu Senjyu; Harun Or Rashid Howlader; Hiroshi Takahashi; Ashraf M. Hemeida. 2020. "Optimal Sizing of a Real Remote Japanese Microgrid with Sea Water Electrolysis Plant Under Time-Based Demand Response Programs." Energies 13, no. 14: 3666.
Due to changes in wind, the torque obtained from the wind turbine always fluctuates. Here, the wind turbine and the rotor of the generator are connected by a shaft that is one elastic body, and each rotating body has different inertia. The difference in inertia between the wind turbine and the generator causes a torsion between the wind generator and the generator; metal fatigue and torsion can damage the shaft. Therefore, it is necessary to consider the axial torsional vibration suppression of a geared wind power generator using a permanent magnet synchronous generator (PMSG). In addition, errors in axis system parameters occur due to long-term operation of the generator, and it is important to estimate for accurate control. In this paper, we propose torque estimation using H ∞ observer and axial torsional vibration suppression control in a three inertia system. The H ∞ controller is introduced into the armature current control system (q-axis current control system) of the wind power generator. Even if parameter errors and high-frequency disturbances are included, the shaft torsional torque is estimated by the H ∞ observer that can perform robust estimation. Moreover, by eliminating the resonance point of the shaft system, vibration suppression of the shaft torsional torque is achieved. The results by the proposed method can suppress axial torsional vibration and show the effect better than the results using Proportional-Integral (PI) control.
Kosuke Takahashi; Nyam Jargalsaikhan; Shriram Rangarajan; Ashraf Mohamed Hemeida; Hiroshi Takahashi; Tomonobu Senjyu. Output Control of Three-Axis PMSG Wind Turbine Considering Torsional Vibration Using H Infinity Control. Energies 2020, 13, 3474 .
AMA StyleKosuke Takahashi, Nyam Jargalsaikhan, Shriram Rangarajan, Ashraf Mohamed Hemeida, Hiroshi Takahashi, Tomonobu Senjyu. Output Control of Three-Axis PMSG Wind Turbine Considering Torsional Vibration Using H Infinity Control. Energies. 2020; 13 (13):3474.
Chicago/Turabian StyleKosuke Takahashi; Nyam Jargalsaikhan; Shriram Rangarajan; Ashraf Mohamed Hemeida; Hiroshi Takahashi; Tomonobu Senjyu. 2020. "Output Control of Three-Axis PMSG Wind Turbine Considering Torsional Vibration Using H Infinity Control." Energies 13, no. 13: 3474.
Recently, an explosive growth in the potential use of natural metaphors in modelling and solving large-scale non-linear optimization problems. Artificial neural network (ANN) is a potent gadget broadly utilized in many data classification tasks. Fundamentally, nature-inspired algorithms have demonstrated their effectiveness and ability over traditional algorithms for generating the optimal ANN parameters, rules and topology that provide the best classification performance with regarding to the quality of the solution, computational cost and avoiding local minima. The literature is vast and growing. This study provides a review on the basic theories and main recent algorithms for optimizing the ANN. Different types of nature-inspired meta-heuristic algorithms are presented; outlining the concepts and components that are used in order to give a summary and ease of the state-of-the-arts to find suitable methods in real world applications for the readers. Additionally, this survey covers the most used type of neural networks, feed-forward neural network (FFNN) in several optimized applications. The performances of FFNNs designed by nature-inspired algorithms have been explored in single and multi-dimensional optimization space; highlighting their models, features, objectives, constraints, etc. to analyse their differences and similarities. A comprehensive survey of the earliest works and recent modified in the last decade in addition to expect approaches has been investigated in details.
Ashraf Mohamed Hemeida; Somaia Awad Hassan; Al-Attar Ali Mohamed; Salem Alkhalaf; Mountasser Mohamed Mahmoud; Tomonobu Senjyu; Ayman Bahaa El-Din. Nature-inspired algorithms for feed-forward neural network classifiers: A survey of one decade of research. Ain Shams Engineering Journal 2020, 11, 1 .
AMA StyleAshraf Mohamed Hemeida, Somaia Awad Hassan, Al-Attar Ali Mohamed, Salem Alkhalaf, Mountasser Mohamed Mahmoud, Tomonobu Senjyu, Ayman Bahaa El-Din. Nature-inspired algorithms for feed-forward neural network classifiers: A survey of one decade of research. Ain Shams Engineering Journal. 2020; 11 (3):1.
Chicago/Turabian StyleAshraf Mohamed Hemeida; Somaia Awad Hassan; Al-Attar Ali Mohamed; Salem Alkhalaf; Mountasser Mohamed Mahmoud; Tomonobu Senjyu; Ayman Bahaa El-Din. 2020. "Nature-inspired algorithms for feed-forward neural network classifiers: A survey of one decade of research." Ain Shams Engineering Journal 11, no. 3: 1.
Energy storage systems (ESSs) are essential to ensure continuity of energy supply and maintain the reliability of modern power systems. Intermittency and uncertainty of renewable generations due to fluctuating weather conditions as well as uncertain behavior of load demand make ESSs an integral part of power system flexibility management. Typically, the load demand profile can be categorized into peak and off-peak periods, and adding power from renewable generations makes the load-generation dynamics more complicated. Therefore, the thermal generation (TG) units need to be turned on and off more frequently to meet the system load demand. In view of this, several research efforts have been directed towards analyzing the benefits of ESSs in solving optimal unit commitment (UC) problems, minimizing operating costs, and maximizing profits while ensuring supply reliability. In this paper, some recent research works and relevant UC models incorporating ESSs towards solving the abovementioned power system operational issues are reviewed and summarized to give prospective researchers a clear concept and tip-off on finding efficient solutions for future power system flexibility management. Conclusively, an example problem is simulated for the visualization of the formulation of UC problems with ESSs and solutions.
Harun Or Rashid Howlader; Oludamilare Bode Adewuyi; Ying-Yi Hong; Paras Mandal; Ashraf Mohamed Hemeida; Tomonobu Senjyu. Energy Storage System Analysis Review for Optimal Unit Commitment. Energies 2019, 13, 158 .
AMA StyleHarun Or Rashid Howlader, Oludamilare Bode Adewuyi, Ying-Yi Hong, Paras Mandal, Ashraf Mohamed Hemeida, Tomonobu Senjyu. Energy Storage System Analysis Review for Optimal Unit Commitment. Energies. 2019; 13 (1):158.
Chicago/Turabian StyleHarun Or Rashid Howlader; Oludamilare Bode Adewuyi; Ying-Yi Hong; Paras Mandal; Ashraf Mohamed Hemeida; Tomonobu Senjyu. 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment." Energies 13, no. 1: 158.
In Japan, residents of apartments are generally contracted to receive low voltage electricity from electric utilities. In recent years, there has been an increasing number of high voltage batch power receiving contracts for condominiums. In this research, a high voltage batch receiving contractor introduces a demand–response in a low voltage power receiving contract, which maximizes the profit of a high voltage batch receiving contractor and minimizes the electricity charge of residents by utilizing battery storage, electric vehicles (EV), and heat pumps. A multi-objective optimization algorithm calculates a Pareto solution for the relationship between two objective trade-offs in the MATLAB ® environment.
Yuta Susowake; Hasan Masrur; Tetsuya Yabiku; Tomonobu Senjyu; Abdul Motin Howlader; Mamdouh Abdel-Akher; Ashraf M. Hemeida. A Multi-Objective Optimization Approach towards a Proposed Smart Apartment with Demand-Response in Japan. Energies 2019, 13, 127 .
AMA StyleYuta Susowake, Hasan Masrur, Tetsuya Yabiku, Tomonobu Senjyu, Abdul Motin Howlader, Mamdouh Abdel-Akher, Ashraf M. Hemeida. A Multi-Objective Optimization Approach towards a Proposed Smart Apartment with Demand-Response in Japan. Energies. 2019; 13 (1):127.
Chicago/Turabian StyleYuta Susowake; Hasan Masrur; Tetsuya Yabiku; Tomonobu Senjyu; Abdul Motin Howlader; Mamdouh Abdel-Akher; Ashraf M. Hemeida. 2019. "A Multi-Objective Optimization Approach towards a Proposed Smart Apartment with Demand-Response in Japan." Energies 13, no. 1: 127.
The power system voltage controls are developed by generator excitation control, and power system components such as loads and transformers that generally absorb reactive power. This paper presents implementation of thyristor control series capacitor (TCSC) and auxiliary control that can be deployed in the network to improve the voltage profile of a system-based reactive control. Also, TCSCs can be used as controllable devices in power flow and voltage control devices. Since voltage magnitudes in a system are closely related to the ability of various components to absorb or supply reactive power, TCSC with auxiliary controls are used for transients corresponding to rotor relative motion. Two-area system is used to examine the feasibility of the proposed TCSC, with auxiliary control to improve the grid voltage profile, and network performance. The simulation results prove the effectiveness of the proposed method for voltage profile improvement and network performance.
Ashraf Mohamed Hemeida; Mohamed M. Hamada; Youssef A. Mobarak; A. El-Bahnasawy; Mohamed G. Ashmawy; Tomonobu Senjyu. TCSC with auxiliary controls based voltage and reactive power controls on grid power system. Ain Shams Engineering Journal 2019, 11, 587 -609.
AMA StyleAshraf Mohamed Hemeida, Mohamed M. Hamada, Youssef A. Mobarak, A. El-Bahnasawy, Mohamed G. Ashmawy, Tomonobu Senjyu. TCSC with auxiliary controls based voltage and reactive power controls on grid power system. Ain Shams Engineering Journal. 2019; 11 (3):587-609.
Chicago/Turabian StyleAshraf Mohamed Hemeida; Mohamed M. Hamada; Youssef A. Mobarak; A. El-Bahnasawy; Mohamed G. Ashmawy; Tomonobu Senjyu. 2019. "TCSC with auxiliary controls based voltage and reactive power controls on grid power system." Ain Shams Engineering Journal 11, no. 3: 587-609.
This article offers a multi-objective framework for an optimal mix of different types of distributed energy resources (DERs) under different load models. Many renewable and non-renewable energy resources like photovoltaic system (PV), micro-turbine (MT), fuel cell (FC), and wind turbine system (WT) are incorporated in a grid-connected hybrid power system to supply energy demand. The main aim of this article is to maximize environmental, technical, and economic benefits by minimizing various objective functions such as the annual cost, power loss and greenhouse gas emission subject to different power system constraints and uncertainty of renewable energy sources. For each load model, optimum DER size and its corresponding location are calculated. To test the feasibility and validation of the multi-objective water cycle algorithm (MOWCA) is conducted on the IEEE-33 bus and IEEE-69 bus network. The concept of Pareto-optimality is applied to generate trilateral surface of non-dominant Pareto-optimal set followed by a fuzzy decision-making mechanism to obtain the final compromise solution. Multi-objective non-dominated sorting genetic (NSGA-III) algorithm is also implemented and the simulation results between two algorithms are compared with each other. The achieved simulation results evidence the better performance of MOWCA comparing with the NSGA-III algorithm and at different load models, the determined DER locations and size are always righteous for enhancement of the distribution power system performance parameters.
Al-Attar Ali Mohamed; Shimaa Ali; Salem Alkhalaf; Tomonobu Senjyu; Ashraf M. Hemeida. Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm. Sustainability 2019, 11, 6550 .
AMA StyleAl-Attar Ali Mohamed, Shimaa Ali, Salem Alkhalaf, Tomonobu Senjyu, Ashraf M. Hemeida. Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm. Sustainability. 2019; 11 (23):6550.
Chicago/Turabian StyleAl-Attar Ali Mohamed; Shimaa Ali; Salem Alkhalaf; Tomonobu Senjyu; Ashraf M. Hemeida. 2019. "Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm." Sustainability 11, no. 23: 6550.
Data mining optimization received much attention in the last decades due to introducing new optimization techniques, which were applied successfully to solve such stochastic mining problems. This paper addresses implementation of evolutionary optimization algorithms (EOAs) for mining two famous data sets in machine learning by implementing four different optimization techniques. The selected data sets used for evaluating the proposed optimization algorithms are Iris dataset and Breast Cancer dataset. In the classification problem of this paper, the neural network (NN) is used with four optimization techniques, which are whale optimization algorithm (WOA), dragonfly algorithm (DA), multiverse optimization (MVA), and grey wolf optimization (GWO). Different control parameters were considered for accurate judgments of the suggested optimization techniques. The comparitive study proves that, the GWO, and MVO provide accurate results over both WO, and DA in terms of convergence, runtime, classification rate, and MSE.
Mohamed Eid; Salem Alkhalaf; A. Mady; E.A. Mahmoud; M.E. Hussein; Ayman M. Baha Eldin. Implementation of nature-inspired optimization algorithms in some data mining tasks. Ain Shams Engineering Journal 2019, 11, 309 -318.
AMA StyleMohamed Eid, Salem Alkhalaf, A. Mady, E.A. Mahmoud, M.E. Hussein, Ayman M. Baha Eldin. Implementation of nature-inspired optimization algorithms in some data mining tasks. Ain Shams Engineering Journal. 2019; 11 (2):309-318.
Chicago/Turabian StyleMohamed Eid; Salem Alkhalaf; A. Mady; E.A. Mahmoud; M.E. Hussein; Ayman M. Baha Eldin. 2019. "Implementation of nature-inspired optimization algorithms in some data mining tasks." Ain Shams Engineering Journal 11, no. 2: 309-318.
Maximizing the classification accuracy and minimizing the number of selected features are the two main incompatible objectives for using feature selection to overcome the curse of dimensionality. “Classification accuracy highly dependents on the nature of the features in a dataset which may contain irrelevant or redundant data. The main aim of feature selection is to eliminate these types of features to enhance the classification accuracy.” This work presents a new meta-heuristic optimization approach, called Parasitism-Predation Algorithm (PPA), which mimics the interaction between the predator (cats), the parasite (cuckoos) and the host (crows) in the crow–cuckoo–cat system model to overcome the problems of low convergence and the curse of dimensionality of large data. The proposed hybrid framework combines the relative advantages of cat swarm optimization (CSO), cuckoo search (CS) and crow search algorithm (CSA) to attain a combinatorial set of features to boost up the classification accuracy. Nesting, parasitism, and predation phases are supposed to help exploration ability and balance in the context of solving classification problems. In addition, Levy flight distribution is applied to help better diversity of conventional CSA and improve ability of exploration. Meanwhile, an effective fitness function is utilized to enable the proposed PPA-based feature selector using K-Nearest Neighbors algorithm (KNN) to attain a combinatorial set of features. The proposed PPA and four standard heuristic search algorithms are looked at to gauge how efficient the proposed option is. Additionally, eighteen classification datasets are deployed to gauges its efficacy. The results highlight that the algorithm proposed is both effective and competitive in terms of performance of classification and dimensionality reduction as opposed to other heuristic options.
Al-Attar A. Mohamed; S.A. Hassan; A.M. Hemeida; Salem Alkhalaf; M.M.M. Mahmoud; Ayman M. Baha Eldin. Parasitism – Predation algorithm (PPA): A novel approach for feature selection. Ain Shams Engineering Journal 2019, 11, 293 -308.
AMA StyleAl-Attar A. Mohamed, S.A. Hassan, A.M. Hemeida, Salem Alkhalaf, M.M.M. Mahmoud, Ayman M. Baha Eldin. Parasitism – Predation algorithm (PPA): A novel approach for feature selection. Ain Shams Engineering Journal. 2019; 11 (2):293-308.
Chicago/Turabian StyleAl-Attar A. Mohamed; S.A. Hassan; A.M. Hemeida; Salem Alkhalaf; M.M.M. Mahmoud; Ayman M. Baha Eldin. 2019. "Parasitism – Predation algorithm (PPA): A novel approach for feature selection." Ain Shams Engineering Journal 11, no. 2: 293-308.
This work outlines a novel technique for optimization, which stems from the composition of two random distributions: Maxwell and Gaussian, so-called Maxwell Gaussian Algorithm (MGA). The proposed algorithm tends to find the optimum elements of traditional PI controllers for the PMSG-based WECS, in a manner whereby the optimal dynamic performance of PMSG through another grid fault and operation could be achieved easily. In order to realize an optimum search, Maxwell-Gaussian distribution is employed to control the standard deviation of Gaussian normal in addition to a new selection of the mating solutions with adaptive manner control. Furthermore, four different updating equations were created for the purpose of generating the given solution to increase the exploration over research space. MGA-based coordinate control strategy is implemented in the machine side converter (MSC) and grid side converter (GSC). The MGA is compared with the different optimization techniques such as the Ant Lion Optimizer (ALO) and Satin bowerbird optimizer (SBO). In order to ensure the robustness of the proposed algorithm, four case studies namely; step change of wind speed, variables of wind speed, Random wind speed variation and three phase symmetrical faults. The simulation results indicate the superiority of the proposed algorithm over other used optimization techniques.
Al-Attar Mohamed; A.L. Haridy; T. Senjyu; Hany M. Hasanien; Salem Alkhalaf; A.M. Hemeida. WITHDRAWN: PMSG driven by wind energy controller based Maxwell-Gaussian optimization technique. Ain Shams Engineering Journal 2019, 1 .
AMA StyleAl-Attar Mohamed, A.L. Haridy, T. Senjyu, Hany M. Hasanien, Salem Alkhalaf, A.M. Hemeida. WITHDRAWN: PMSG driven by wind energy controller based Maxwell-Gaussian optimization technique. Ain Shams Engineering Journal. 2019; ():1.
Chicago/Turabian StyleAl-Attar Mohamed; A.L. Haridy; T. Senjyu; Hany M. Hasanien; Salem Alkhalaf; A.M. Hemeida. 2019. "WITHDRAWN: PMSG driven by wind energy controller based Maxwell-Gaussian optimization technique." Ain Shams Engineering Journal , no. : 1.
In this paper, the performance of different optimization techniques namely, multi-objective dragonfly algorithm (MODA) and multi-objective differential evolution (MODE) are presented and compared. The uncertainty effect of a wind turbine (WT) on the performance of the distribution system is taken into account. The point estimate method (PEM) is used to model the uncertainty in wind power. Optimization methods are applied to determine the multi-objective optimal allocation of distributed generation (DG) in radial distribution systems at a different load level (light, normal, heavy load level). The multi-objective function is expressed to minimize the total power loss, total operating cost, and improve the voltage stability index of the radial distribution system (RDS). Multi-objective proposed algorithms are used to generate the Pareto optimal solutions; and a fuzzy decision-making function is used to produce a hybrid function for obtaining the best compromise solution. The proposed algorithms are carried out on 33-bus and IEEE-69-bus power systems. The simulation results show the effectiveness of installing the proper size of DG at the suitable location based on different techniques.
Salem Alkhalaf; Tomonobu Senjyu; Ayat Ali Saleh; Ashraf M. Hemeida; Al-Attar Ali Mohamed. A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels. Sustainability 2019, 11, 5323 .
AMA StyleSalem Alkhalaf, Tomonobu Senjyu, Ayat Ali Saleh, Ashraf M. Hemeida, Al-Attar Ali Mohamed. A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels. Sustainability. 2019; 11 (19):5323.
Chicago/Turabian StyleSalem Alkhalaf; Tomonobu Senjyu; Ayat Ali Saleh; Ashraf M. Hemeida; Al-Attar Ali Mohamed. 2019. "A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels." Sustainability 11, no. 19: 5323.
The current paper introduces a realistic solution for energy demand in Makadi Bay, Red-Sea, Hurgada, Egypt using energy system crossbred of Renewable Wind Energy System (WES) and Photovoltaic System (PVS) in the presence of Battery Energy Storage (BES). A real measurement for wind speed was recorded through a year of 2017. Also, the sun irradiance and temperature were recorded through the same period, to be considered for the output power calculations from the proposed crossbred renewable energy system. The demand load data for the city was recoded as well as through the same period for evaluating the feasibility of the system if it can cover the city loads. Linear TORSCHE optimization technique has utilized to reach an optimum solution of the proposed crossbred renewable energy system. Individual configuration of PVS & WES in presence of BES have been studied and compared with the hybrid PV/WT. Furthermore, economic analysis has presented to prove the best economical system. The obtained results show that installing such hybrid system consists of WES, PVS and BES is cheaper than installing each one individually.
A.M. Hemeida; M.H. El-Ahmar; A.M. El-Sayed; Hany M. Hasanien; Salem Alkhalaf; M.F.C. Esmail; T. Senjyu. Optimum design of hybrid wind/PV energy system for remote area. Ain Shams Engineering Journal 2019, 11, 11 -23.
AMA StyleA.M. Hemeida, M.H. El-Ahmar, A.M. El-Sayed, Hany M. Hasanien, Salem Alkhalaf, M.F.C. Esmail, T. Senjyu. Optimum design of hybrid wind/PV energy system for remote area. Ain Shams Engineering Journal. 2019; 11 (1):11-23.
Chicago/Turabian StyleA.M. Hemeida; M.H. El-Ahmar; A.M. El-Sayed; Hany M. Hasanien; Salem Alkhalaf; M.F.C. Esmail; T. Senjyu. 2019. "Optimum design of hybrid wind/PV energy system for remote area." Ain Shams Engineering Journal 11, no. 1: 11-23.