Optimal economic analysis of electric vehicle charging stations, renewable energy technologies, and capacitor banks in distribution networks

IET Generation Transmission & Distribution, Journal Year: 2025, Volume and Issue: 19(1)

Published: Jan. 1, 2025

Abstract The study optimizes the placement of electric vehicle charging stations (EVCSs), photovoltaic power plants (PVPPs), wind turbine (WTPPs), battery energy storage system (BESS), and capacitor bank (CB), considering AC DC chargers for EVCSs by using wave search algorithm (WSA), particle swarm optimization (PSO) algorithm, artificial bee colony (ABC) salp (SSA). objective is to minimize sum cost supplied grid total costs from added components a 15‐year project, including investment cost, operation, maintenance (O&M) cost. Finally, WSA can reach smaller than others. hybrid with all 21.83% less base project life cycle. revenue O&M are about $15.3 million $11.3 million. So, profit $4 million, equivalent 35.38%. Furthermore, smallest voltage increased 0.91 0.96 pu, highest branch current reduced 387 329 A, meeting 45.54% consumption in system. Thus, integration EVCSs, PVPPs, WTPPs, BESS, CB into distribution networks bring very high profit.

Language: Английский

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Probabilistic luminance estimation and optimized gamma correction for Wireless capsule endoscopy

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 104, P. 107558 - 107558

Published: Feb. 6, 2025

Language: Английский

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Trajectory Planning and Multi-Agent Reinforcement Learning Vibration Control of T-Shape Movable Three-Coupled Flexible Beam

Journal of Vibration Engineering & Technologies, Journal Year: 2025, Volume and Issue: 13(4)

Published: March 12, 2025

Language: Английский

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Multilabel Vulnerability Classification in Decentralized Blockchain–Based Reputation System

Journal of Software Evolution and Process, Journal Year: 2025, Volume and Issue: 37(4)

Published: April 1, 2025

ABSTRACT Smart contracts serve as decentralized applications essential for extensive utilization of blockchain technology across various contexts that have transitioned from the blockchain, characterized primarily by digital currency systems emphasize financial systems. Blockchain operates a distributed ledger securely records transactions using cryptographic techniques to establish unique, chain‐like data structure managed collectively miners within network. However, current methods analyzing smart often demand substantial processing time and face challenges in accurately detecting vulnerabilities complex contracts. To address these limitations, this research introduces Updated Wave search Graph Bidirectional Convolutional Neural Network (UWGBCNN), novel approach designed enhance contract security. UWGBCNN integrates multilabel vulnerability classification mechanism, utilizing Search Algorithm (UWSA) efficiently analyze identify patterns adapting network parameters detect with speed precision. Additionally, feature extraction is enhanced through Encoder Representations Transformer (BERT) language model, incorporating supplementary word embedding features. The proposed technique achieves superior performance, reaching precision 98.5%, recall 98.6%, an F1‐score 99.6%, surpassing methods. This contributes significantly security minimizing risks associated applications.

Language: Английский

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Modified crayfish optimization algorithm with adaptive spiral elite greedy opposition-based learning and search-hide strategy for global optimization

Journal of Computational Design and Engineering, Journal Year: 2024, Volume and Issue: 11(4), P. 249 - 305

Published: July 3, 2024

Abstract Crayfish optimization algorithm (COA) is a novel bionic metaheuristic with high convergence speed and solution accuracy. However, in some complex problems real application scenarios, the performance of COA not satisfactory. In order to overcome challenges encountered by COA, such as being stuck local optimal insufficient search range, this paper proposes four improvement strategies: search-hide, adaptive spiral elite greedy opposition-based learning, competition-elimination, chaos mutation. To evaluate accuracy, speed, robustness modified crayfish (MCOA), simulation comparison experiments 10 algorithms are conducted. Experimental results show that MCOA achieved minor Friedman test value 23 functions, CEC2014 CEC2020, average superiority rates 80.97%, 72.59%, 71.11% WT, respectively. addition, shows applicability progressiveness five engineering actual industrial field. Moreover, 80% 100% rate against on CEC2020 fixed-dimension function benchmark functions. Finally, owns better population diversity.

Language: Английский

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EPKO: Enhanced pied kingfisher optimizer for numerical optimization and engineering problems

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127416 - 127416

Published: March 1, 2025

Language: Английский

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Black eagle optimizer: a metaheuristic optimization method for solving engineering optimization problems

Cluster Computing, Journal Year: 2024, Volume and Issue: unknown

Published: June 13, 2024

Language: Английский

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