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检索条件"主题词=Whale optimization algorithms"

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Frequency Regulation of a Distributed Power System via Modified whale optimization Algorithm

Frequency Regulation of a Distributed Power System via Modif...

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Innovations in Power and Advanced Computing Technologies (i-PACT)

作者： Rajendra Ku. Khadanga Sasmita Padhy Preeti Ranjan Sahu Sidhartha Panda Centurion University of Technology and Management Jatani Bhubaneswar Odisha INDIA National Institute of Science & Technology Berhampur Odisha INDIA Veer Surendra Sai University of Technology Burla Odisha INDIA

ISBN: (纸本)9781665426923

This paper proposes the modified methodology for the whale optimization Algorithm (WOA) which improves the first procedure known as Modified WOA algorithm. The modification is established by introducing some correction factors as CF l , CF2 to the original WOA algorithm. In the subsequent stage, the real application of the proposed approach in this field is finished by structuring an AFPID controller for frequency regulation of a Distributed energy power generation system DEPS. The DEPS incorporates renewable sources like photovoltaic, wind and storage gadgets. It is seen that MWOA based AFPID controller is increasingly compelling for the frequency control.

关键词： Photovoltaic systems Technological innovation Renewable energy sources Regulators Philosophical considerations whale optimization algorithms Power systems

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Big Data Clustering using Ghost Opposition Learning based Crayfish optimization Algorithm

Big Data Clustering using Ghost Opposition Learning based Cr...

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Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： Yifeng Wang Yuxia Du Shandong Institute of Commerce and Technology Jinan China

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

Traditional clustering methods often struggle with the sheer scale and complexity of big data. Clustering algorithm of big data models by efficiently handling large datasets, making them more scalable and capable of processing diverse data types. In this big data Clustering technique-based Swarm intelligence optimization various of model are created but still the optimization algorithms are trapping in local optima and its takes huge time for finding the global solution. Addressing these issues and overcome in this paper, proposed the Crayfish optimization Algorithm by using Ghost Opposition-based Learning (GOL-COA) Strategy and environment update technique for enhancing exploitation phase and increasing Exploration convergence speed of optimization, and avoiding local optima problem. The model is evaluated with the accuracy and F1-score metrices and experiment did on various types of datasets. The numerical validation results showing accuracy of 97.56% in LD dataset, and F1 score of 98.10% in LD dataset. This model compares to the other recent year optimization algorithms such as Particle Swarm optimization (PSO), whale optimization (WOA), Ant Colony optimization (ACO), Sand Cat Swam optimization (SCSO), and Werewolf optimization algorithms (WOA).

关键词： Accuracy Clustering algorithms Big Data Data models whale optimization algorithms Numerical models Particle swarm optimization Computer security optimization Convergence

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Improved Energy Balancing based Data Forwarding incorporating whale optimization Technique in Underwater Acoustic Sensor Network

Improved Energy Balancing based Data Forwarding incorporatin...

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Electrical, Electronics, Information and Communication Technologies (ICEEICT), International Conference on

作者： R. Bhairavi M. Thiruveni Anita Christaline J N. Ashokkumar I. Chandra P. Nagarajan Department of ECE SRM Institute of Science and Technology Chennai India Department of ECE PSNA College of Engineering and Technology Dindigul India School of Computer Science and Engineering VIT Chennai India Department of Electronics and Communication Engineering Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College) Tirupati Andhra Pradesh India Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai India

ISBN: (数字)9798350369083

ISBN: (纸本)9798350369090

UWASN has various challenges such as minimal bandwidth availability, long propagation delay, increased energy exhaustion, increased deployment cost and security. The routing protocols should facilitate an enhanced data forwarding towards sink nodes. In this paper, an Improved Energy Balancing based Data Forwarding incorporating whale optimization Technique (IEBDF-WO) is proposed to effectively elect optimal forwarders to participate in the routing process. The whale optimization algorithm has three phases namely, scouring phase, encompassing phase and final bubble net raiding phase for facilitating enhanced data transmission towards sink node. The proposed technique determines a fitness function by using the weighted depth difference W D , Potential Relay Count (PRC), Residual energy of each potential relay node. The performance of the proposed IEBDF-WO technique is analyzed and is collated with the existing Energy-Efficient Probabilistic Depth-Based Routing (EEPDBR) technique. It is seen that, for a network comprising of 200 nodes, the proposed scheme has improved Packet Delivery Ratio of 96.04% while minimizing the end to end delay, energy tax and average number of hops.

关键词： Electric potential Routing Probabilistic logic whale optimization algorithms Routing protocols Security Relays Underwater acoustics optimization Propagation delay

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An Overview of optimization Challenges in Electric Mobility Charging Stations and Driver Behavior in Congested Cities

An Overview of Optimization Challenges in Electric Mobility ...

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International Smart Grid Workshop and Certificate Program (ISGWCP)

作者： Juliana Bermúdez Juan Esteban González David Celeita School of Engineering Science and Technology Universidad del Rosario Bogotá Colombia Faculty of Engineering Universidad de la Sabana Chía Colombia

ISBN: (数字)9798350361612

ISBN: (纸本)9798350361629

As the electric transportation industry expands, is imperative to face the implications of this new infrastructure. In fact, this paper intends to generate a comprehensive overview of the challenges associated with the implementation of an electric vehicle charging system in Colombia’s capital city Bogotá. Given the complexity of the problematic, it is divided into five main components: optimal location for charging stations, electric vehicles’ routing algorithms, scheduling and queue management, driver’s behavior and modeling of dynamical systems. This division, enables the analysis of methodologies such as swarm optimization algorithms, genetic-based algorithms, whale optimization algorithms, spherical fuzzy sets, Voronoi diagrams, dynamic weighted graphs, Lyapunov functions, generalized linear models, convolutional networks, Markov chains and some others in terms of how appropriate they are for providing a solution. Finally, a preliminary model to represent this dynamic is introduced along as further work taking as a starting point the representation of the system.

关键词： Heuristic algorithms Transportation industry Urban areas Charging stations Routing whale optimization algorithms Smart grids

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TDOA Indoor Positioning Based on an Improved whale optimization Algorithm

TDOA Indoor Positioning Based on an Improved Whale Optimizat...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Shen Han Liangbo Xie Yanbang Chen School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China International College Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9798350351019

ISBN: (纸本)9798350351026

In the domain of indoor wireless positioning technology, non-line-of-sight conditions significantly impact signal ranging accuracy, thereby diminishing the positioning accuracy of conventional least squares and CHAN algorithms. To address this issue, we propose an improved whale optimization algorithm (IWOA). Firstly, the target position equation is established based on the time difference of arrival (TDOA) positioning model. Subsequently, we use IWOA to solve the target position equation. Experimental results demonstrate that IWOA enhances positioning accuracy, affirming the algorithm’s effectiveness.

关键词： Location awareness Wireless communication Accuracy Time difference of arrival Simulation Antennas and propagation Mathematical models whale optimization algorithms Distance measurement

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An Optimal Planning of Energy Storage System in Radial Distribution Network Using Aquila optimization Algorithm

An Optimal Planning of Energy Storage System in Radial Distr...

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Data Science and Information System (ICDSIS), IEEE International Conference on

作者： Myasar Mundher Adnan A.V.V. Sudhakar S. Arun Kumar G K Madhura S. Kaliappan Department of computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Electrical and Electronics Engineering SR University Warangal Telangana India Department of Electrical and Electronics Engineering Sona College of Technology Salem India Department of Artificial intelligence and Machine learning Nitte Meenakshi Institute of Technology Bengaluru India Department of Mechanical Engineering Amity University Dubai United Arab Emirates

ISBN: (数字)9798350381665

ISBN: (纸本)9798350381672

Nowadays smart grids are emerging rapidly for their efficiency in operating modern distribution systems. Energy storage systems (ESSs) play a key role in achieving the objectives of smart grids, facilitating the combination of renewable sources and enhancing system reliability. Aquila optimization Algorithm (AOA) is proposed for optimal placement and sizing of ESS within the IEEE Radial Distribution System (RDS) to minimize power losses while maintaining voltage magnitude. This method is used to achieve improvements in loss reduction and voltage profile compared to conventional Analytical Index method and whale optimization Algorithm (WOA). The experimental results indicate that if ESS are sized and installed correctly, the overall losses in the radial system are decreased. The suggested AOA achieved a loss reduction rate of 62.58% and a voltage profile of 79.87 kW in enhancing the performance of distribution systems within smart grid frameworks.

关键词： Renewable energy sources Network topology whale optimization algorithms Smart grids Topology Planning Reliability

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High-performance quarter car active suspension system using PID controller tuned by the dingo optimization algorithm

High-performance quarter car active suspension system using ...

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Power Electronics and Control (SEPOC), Seminar on

作者： Thiago Carvalho Bittencourt Joab Tavares Fagundes Paulo Jefferson Dias de Oliveira Evald Sul-Riograndense Federal Institute Pelotas Brazil Intelligent Systems and Control Group Federal University of Pelotas Pelotas Brazil

ISBN: (数字)9798350379419

ISBN: (纸本)9798350379426

This paper presents a novel approach for tuning a proportional-integral-derivative (PID) controller applied to the active suspension system of an electric vehicle using the dingo optimization algorithm (DOA). The DOA is utilized as the core of a sophisticated controller tuning method and follows systematic rules to provide optimal gains to the PID, enhancing vehicle stability. As an outcome, the security and the comfort of the driver and passengers are increased, once the optimized controller can minimize the vehicle balance on irregular land. The active suspension model is based on a quarter-car representation. Three scenarios were considered in the simulation, including a flat road, a speed bump, and a road with a hole. The results demonstrate that the DOA-tuned PID controller effectively minimizes tracking errors, ensuring stable and precise control of the suspension system without excessive control effort. Another meta-heuristic approach was used for comparison, the whale optimizer algorithm (WOA). The proposed controller presented superior performance, not developing the oscillatory behavior of the WOA-tuned algorithm. Moreover, the settling time using the proposed control approach is null. In this sense, the developed control system enhances the comfort and security of the driver and passengers.

关键词： Suspensions (mechanical systems) Roads Metaheuristics Electric vehicles whale optimization algorithms Stability analysis Security Transient analysis Tuning Vehicles

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Bi-Level Planning for Distributed Power Supply Using the Improved whale optimization Algorithm

Bi-Level Planning for Distributed Power Supply Using the Imp...

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China International Electrical and Energy Conference (CIEEC)

作者： Jinfeng Wang Mengxue Xu School of Electrical and Information Engineering Zhengzhou University Zhengzhou China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Optimizing distributed power supply planning is essential to enhancing the impact of distributed power supply on the secure and cost-effective operation of the distribution network. This study establishes a two-layer programming model and selects wind power, solar, and micro-gas turbines as distributed power sources to be scheduled. This study aims to improve the whale algorithm by utilizing tent mapping, inertial weight, and nonlinear shrinkage factor to address issues like slow convergence and delayed jumping out of local solutions. This study solves the proposed model on the IEEE-33 node system using the enhanced whale algorithm and compares the outcome with other techniques. The enhanced whale algorithm offers the most noticeable improvement in node voltage and the lowest annual comprehensive cost, according to the data.

关键词： Costs Power supplies whales Distribution networks Wind power generation whale optimization algorithms Stability analysis

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Optimal Placement of Distributed Generators and Electric Vehicles Using whale optimization Algorithm (WOA)

Optimal Placement of Distributed Generators and Electric Veh...

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Innovative Sustainable Technologies for Energy, Mechatronics, and Smart Systems (ISTEMS), International Conference on

作者： Rinchen Zangmo Suresh Kumar Sudabattula Sachin Mishra Nagaraju Dharavat School of Electronics and Electrical Engineering Lovely Professional University Punjab India

ISBN: (数字)9798350384246

ISBN: (纸本)9798350384253

Integrating Distributed Generation (DG) sources and Electric Vehicles (EVs) into radial distribution systems (RDS) is a promising approach to enhancing power system efficiency and reliability. This trend is driven by the deregulation of the electric power sector and technical constraints in extending distribution and transmission networks to some areas. By carefully selecting the optimal location and sizing for DG sources and electric vehicles (EVs), it is possible to minimize system losses, improve voltage profiles, and enhance overall reliability. This study suggests the integration of multiple DGs and EV s into the system and how the PLoss get affected along with voltage profiles. However, the PLoss increase if the number of DGs exceeds their optimal level. This study integrates 3 DGs and 3 EVs into the RDS separately. The location of the DGs and EVs are obtained with the help of the voltage stability index, and sizes were obtained using the whale optimization Algorithm (WOA). It is implemented into the IEEE 33 test system to verify its robustness and effectiveness. The results show a loss reduction of 41.96%, 57.52%, and 64.73% for the IEEE bus system with the integration of one, two and three DGs, respectively and a slight increase in power loss concerning EV integration as the system load increases. In addition, the voltage stability index is improved significantly for DGs but was affected in the case of EVs.

关键词： Vehicle-to-grid Electric potential System performance Stability criteria Voltage Power system stability whale optimization algorithms

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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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