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检索条件"主题词=Whale Optimization Algorithms"

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Super Twisting SMC Based 5L-NPC for Medium Voltage Grid Connected PV-Battery System

Super Twisting SMC Based 5L-NPC for Medium Voltage Grid Conn...

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Smart Power & Internet Energy Systems (SPIES), International Conference on

作者： Kalpana Beura Omar Al Zaabi Mohamed Alkhatib Electrical & Communication Engg. COE UAE University Al Ain Abu Dhabi UAE APEC Electrical Engg. Dept. Khalifa University Abu Dhabi UAE

ISBN: (数字)9798350368864

ISBN: (纸本)9798350368871

Medium voltage drives, particularly those for induction motors, are regularly using in various industrial tasks. The efficient management of induction motors is crucial in nuclear power plants. Induction motors are often controlled using direct torque control (DTC) to achieve smoother speed torque characteristics in comparison to other available control methods. Nevertheless, traditional DTC encounters numerous challenges due to the need to uphold a consistent reference flux across all speed ranges. Therefore, this paper presents the implementation of two innovative super twisting sliding mode (STSM) controllers in a novel DTC system. The induction motor is driven by a 5L-NPC: five level neutral point clamped inverter operating in three phases. The connection to the dc-link is made via a 36-pulse converter. Additionally, a photovoltaic (PV) system is added with a battery bank to ensure uninterrupted power supply in off-grid situations. A constant dc-link voltage is maintained through the use of a dc bidirectional circuit that links the dc-bus with the battery. The suggested regulation of the dc bidirectional converter has the potential to minimize the oscillations and ripples in the dc-link caused by the 36 pulse converter when the grid voltages are unbalanced. In order to identify best vector location, whale optimization methodology has been implemented. This paper presents practical responses by implementing hardware-in-the-loop (HIL) using OPAL-RT circuits. The results obtained from HIL are examined across multiple case studies.

关键词： Induction motor drives Space vector pulse width modulation Torque Torque control Medium voltage whale optimization algorithms Vectors Regulation Batteries Voltage control

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Noise reduction method based on WOA-VMD-FE for fault arc acoustic signals in distribution networks

Noise reduction method based on WOA-VMD-FE for fault arc aco...

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Intelligent Power and Systems (ICIPS), International Conference on

作者： Ying Yang Wenmin Wang Zhengyun Liu Jiahao Wang Cheng Zeng Qi Feng Haojie Wei Kai Chen State Grid Hubei Power Transmission and Transformation Engineering Co. State Grid Corporation of China Wu Han China College of Electrical Engineering and New Energy China Three Gorges University Yi Chang China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

Arc acoustic signals are an effective means of characterizing faults in distribution networks, but their acquisition is often hindered by environmental limitations and various types of noise interference. To address the issue of misjudgment in fault detection due to noise and the challenge of selecting parameters for the Variational Mode Decomposition (VMD) algorithm, this paper proposes a denoising method based on the whale optimization Algorithm (WOA) for arcing acoustic signals in distribution network faults. Firstly, the whale optimization Algorithm is used to optimize the penalty factor α and the decomposition modulus K of VMD, thereby determining the optimal decomposition parameters. Secondly, fuzzy entropy is employed to evaluate each Intrinsic Mode Function (IMF) signal decomposed by VMD, enabling the distinction between the noisy components and the effective signal parts. The Sparrow Search Algorithm, Particle Swarm optimization, Genetic Algorithm, and the whale optimization-based VMD parameter searching method are compared. The results demonstrate that the proposed method significantly improves the accuracy and speed of VMD parameter optimization compared to the Sparrow, Particle Swarm, and Genetic algorithms. Effectively filtering out ambient noise while preserving the original characteristics of the signal to a great extent.

关键词： Heuristic algorithms Noise Noise reduction Distribution networks Acoustics whale optimization algorithms Entropy Particle swarm optimization optimization Genetic algorithms

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Internet Abnormal Traffic Detection Based on WOA-BiLSTM-Attention

Internet Abnormal Traffic Detection Based on WOA-BiLSTM-Atte...

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Control, Electronics and Computer Technology (ICCECT), IEEE International Conference on

作者： Lin Mei Department of Basic Education Shandong University of Engineering and Vocational Technology Jinan China

ISBN: (数字)9798350380958

ISBN: (纸本)9798350380965

With the rise of the Internet, network application coverage is becoming more and more extensive, and a large amount of data has brought security issues to the network environment. In order to detect abnormal network traffic, this research builds a model based on the WOA using BiLSTM-Attention, and conducts empirical research using certain network traffic data as an example. The research results show that the root mean square error (RMSE) of WOA-BiLSTM-Attention is 79.1746, which is better than the traditional prediction model and is more suitable for predicting Internet traffic. Its prediction results can provide certain reference significance for abnormal traffic detection and abnormal data detection in other fields in the future.

关键词： Deep learning Neural networks Telecommunication traffic Predictive models whale optimization algorithms Data models Internet

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Investigations of PAPR reduction methods in FBMC System

Investigations of PAPR reduction methods in FBMC System

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Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), International Conference

作者： Rashmi Rani Samantaray Siddappaji Department of Electronics and Communication VTU HKBK College Of Engineering Bengaluru India Department of Electronics and Communication BMS College of Engineering Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

The primary concern of the 5G radio network has sparked interest in the development of new waveforms beyond 4G (5th generation networks). Filter Bank Multicarrier (FBMC) waveforms have recently been suggested as the desired one for 5G networks. It has both advantages and disadvantages. One of the biggest drawback of the FBMC broadcast signal is its high Peak to Average Power Ratio (PAPR). It has been widely used in wireless communication to achieve high speed and data rates. A high PAPR system results in substantial distortion of the signal because of the nonlinear power amplifier. Therefore, methods that effectively reduce PAPR are necessary for the realization of the FBMC system. The FBMC system uses the some common techniques as the OFDM system. Comparative analysis of various approaches such as PTS, SLM, Companding, etc are performed by considering their simulation outcomes when it comes to effective spectrum utilization, improved PAPR, along with minimum complexity.

关键词： Wireless communication 5G mobile communication Nonlinear distortion Metaheuristics Power amplifiers Peak to average power ratio whale optimization algorithms Complexity theory Radio networks Particle swarm optimization

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Design and Analysis of an Adaptive QoS Aware Approach for Supporting Multiple Services using Meta Heuristic Enhanced whale optimization Algorithm over Hybrid Cloud Environment (EWOC)

Design and Analysis of an Adaptive QoS Aware Approach for Su...

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Automation, Computing and Renewable Systems (ICACRS), International Conference on

作者： Premnadh Katkam P. Anbalagan V.V.S.S.S. Balaram Department of Computer Science and Engineering Annamalai University Annamalainagar Dept. of Computer Science and Engineering Annamalai University Annamalainagar Sreenidhi Institute of Science and Technology Yamnampet Ghatkesar Hyderabad

ISBN: (纸本)9781665460859

Though numerous research works have discussed about approaches towards providing QoS over cloud environment for variable services, research community suggest that the need for an adaptive QoS approach with quantifiable resources is a challenge. Hybrid cloud is currently adopted by industry with need for consistent QoS and variable security features. Variable number of users connected over cloud demand consistent resources such as network link capacity, distributed storage and dynamic processing capabilities for execution of service based on variable cloud. This paper focuses on identification and provisioning of demandable resources over a session for a specific task. The proposed EWOC approach works on an enhanced whale optimization algorithm for QoS supportive sessions in use. This paper models an adaptive resource assignment over PSO, SA scheduling algorithms and their QoS aspects.

关键词： Adaptation models Scheduling algorithms Heuristic algorithms Quality of service Throughput whale optimization algorithms Delays

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Chaotic-Opposition whale optimization algorithm based load flow analysis of small-scale, median and broad critical power systems

Chaotic-Opposition Whale optimization algorithm based load f...

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Power and Renewable Energy Conference (IPRECON), IEEE International

作者： Suvabrata Mukherjee Provas Kumar Roy Dept. of Electrical Engineering Kalyani Government Engineering College West Bengal India

In power system phraseology load flow study deals with attainment of steady state explication of the power network and determined for steady state powers for various buses along with the bus voltages. For adhering to the load flow problem, a modified version of whale optimization Algorithm has been suggested by the authors in this paper. The algorithm is a trustworthy meta-heuristic optimization algorithm derived from nature and motivated by the humpback whale bubble-net hunting hypothesis. The accuracy and reliability has been enhanced by the introduction of chaos theory and opposition-based learning (OBL) to WOA so as to effectively cover the entire search region and thereby enhance the convergence of single or multi-objective metaheuristic algorithms. The new algorithm termed as Chaotic-Opposition based whale optimization (COWOA) uses the chaos theory for primary tuning of parameters of WOA by which the exploitation and exploration processes are adjusted and OBL is used to look for the solutions in reverse direction of indicated values in order to test if selects in reverse direction can provide even better solutions. Numerical and simulation results demonstrate that in discerning scenario when traditional load flow approaches flounder, COWOA is able to provide effective solutions.

关键词： Simulation Metaheuristics whales Power system stability Reliability theory whale optimization algorithms Robustness

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Single neuron adaptive control and parameter optimization of lower limb rehabilitation exoskeleton

Single neuron adaptive control and parameter optimization of...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Zhirui Li Wenjie Chen Xiantao Sun Weihai Chen Zaojun Fang Guilin Yang School of Electrical Engineering and Automation Anhui University Hefei China School of Automation Science and Electrical Engineering Beihang University Beijing China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

ISBN: (纸本)9781665409858

For the bottom position control of the lower limb exoskeleton robot driven by DC motor, a single neuron adaptive control method with parameters selected by the improved whale optimization algorithm is proposed. Since the parameter tuning process existing in traditional control is cumbersome and it is difficult to achieve optimal control accuracy, we present a single neuron adaptive controller to improve the control accuracy. In addition, in order to complete the optimal selection of controller parameters, the whale optimization algorithm is used to select parameters, this algorithm is improved, and the optimization simulation results are displayed. Finally, an adaptive underlying controller is designed, and the simulation results are compared with the traditional PID control. The results show that, compared with the traditional method, the single neuron adaptive control with the optimized parameters of the improved whale optimization algorithm has better control effect.

关键词： PI control Simulation Neurons Exoskeletons Sociology whale optimization algorithms PD control

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Optimal DG Allocation Based on Pay-back Period by a Proposed Modification for Coronavirus Herd Immunity optimization

Optimal DG Allocation Based on Pay-back Period by a Proposed...

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International Middle-East Power System Conference, MEPCON

作者： Tarek A. Boghdady Elsayed Tag Eldin Howaida M. Ragab Ahdab Elmorshedy Electric Power Engineering Dept. Cairo University Giza Egypt Faculty of Engineering and Technology Future University in Egypt New Cairo Egypt Electric Power Engineering Dept. Ahram Canadian University Giza Egypt

ISBN: (纸本)9781665463645

Distribued Generations (DG) have economic, financial, and environmental benefits. DG reduces power losses in the distribution system but has a negative impact on the protection devices. In this article, the IEEE 33 bus system will be used and tested by adding up to three DG units using MATLAB/SIMULINK software. the optimization techniques that will be used are Grey Wolf Optimizer, whale optimization Algorithm, Genetic Algorithm, and Coronavirus Herd Immunity or COVID-19 optimization techniques to select the optimal site and size of the DG units based on the lowest pay-back period considering the voltage limits and power losses. The paper proposes a modified mutation operator for COVID-19 based on Gaussian and Cauchy mutations to have better performance and lower variance. The proposed algorithm is compared with the other optimization techniques. The proposed algorithm achieved better results, which proved to have competitive performance with state-of-the-art evolutionary algorithms.

关键词： COVID-19 Costs Software algorithms Voltage Linear programming whale optimization algorithms Software

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Using Modified whale optimization Algorithm for Solving Traveling Salesman Problem

Using Modified Whale Optimization Algorithm for Solving Trav...

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Artificial Intelligence of Things (ICAIoT), International Conference on

作者： Ali Abdullah Saleh Mesut Çevik Electrical and Computer Engineering Altinbas University Istanbul Turkey

The main problem of the network is that the wrong designs and incorrect connection lead to major problems such as cost impact problems and network efficiency, the most famous being Fiber Optical network problems that still considered a problem for various types of networking. Travel Salesmen’s Problem (TSP) is one of the most traditional methods for solving this type of problem, depending today on optimization. Modified algorithms may be regarded as one of the most resourceful and effective ways to solve animal-based TSP problems. whale optimization Algorithm (WOA) and Genetic Algorithm (GA) focuses this paper on TSPLIB-type issues. This work showed a greatly promising performance with whale optimization Algorithm and was better than the genetic algorithm.

关键词： Costs Optical fiber networks Traveling salesman problems whale optimization algorithms Internet of Things Artificial intelligence optimization

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optimization of Contactless Distribution in the Post-COVID Era

Optimization of Contactless Distribution in the Post-COVID E...

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IEEE International Conference on Intelligent Transportation Engineering (ICITE)

作者： Yang Zhang Jiacheng Li Lei Li Graduate School of Science and Engineering Hosei University Tokyo Japan Department of Electrical Electronics and Information Engineering Kanagawa University Yokohama Japan

During an emergency, timely and effective distribution of emergency supplies is critical in rescue. In the context of Covid-19, given the difficulties in distributing supplies to communities due to super infectious viruses, unmanned vehicle distribution is studied by taking into account the priority and satisfaction of communities to improve distribution safety and effectiveness of supplies. Furthermore, the influence of distribution time on the overall efficiency is also taken into account, thus ultimately establishing an unmanned distribution model with the shortest distribution time while meeting community satisfaction. The improved whale algorithm is used to solve the dual-objective model and compared with the basic whale optimization algorithm. The results show that the improved whale algorithm demonstrates better convergence, searchability, and stability. The constructed model can scientifically distribute daily necessities to communities while considering their priority and satisfaction.

关键词： COVID-19 whales Transportation Stability analysis whale optimization algorithms Safety Planning

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