Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system performance enhancement and protection adaptation

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 22, 2025

Language: Английский

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Comprehensive Adaptive Enterprise Optimization Algorithm and Its Engineering Applications

Biomimetics, Journal Year: 2025, Volume and Issue: 10(5), P. 302 - 302

Published: May 9, 2025

In this study, a brand-new algorithm called the Comprehensive Adaptive Enterprise Development Optimizer (CAED) is proposed to overcome drawbacks of (ED) in complex optimization tasks. particular, it aims tackle problems slow convergence and low precision. To enhance algorithm’s ability break free from local optima, lens imaging reverse learning approach incorporated. This creates solutions by utilizing concepts optical imaging. As result, expands search range boosts probability finding superior beyond optima. Moreover, an environmental sensitivity-driven adaptive inertial weight developed. dynamically modifies equilibrium between global exploration, which enables for new promising areas solution space, development, centered on refining close currently best-found areas. evaluate efficacy CAED, 23 benchmark functions CEC2005 are chosen testing. The performance CAED contrasted with that nine other algorithms, such as Particle Swarm Optimization (PSO), Gray Wolf (GWO), Antlion (AOA). Experimental findings show unimodal functions, standard deviation almost 0, reflects its high accuracy stability. case multimodal optimal value obtained notably better than those further emphasizing outstanding performance. also applied engineering challenges, like design cantilever beams three-bar trusses. For beam problem, achieved 13.3925, merely 0.0098. truss 259.805047, extremely small 1.11 × 10−7. These results much traditional ED comparative algorithms. Overall, through coordinated implementation multiple strategies, exhibits precision, strong robustness, rapid when searching spaces. such, offers efficient solving various problems.

Language: Английский

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Multi-Objective Planting Structure Optimisation in an Irrigation Area Using a Grey Wolf Optimisation Algorithm

Water, Journal Year: 2024, Volume and Issue: 16(16), P. 2297 - 2297

Published: Aug. 14, 2024

To improve agricultural production efficiency, increase farmers’ income, and promote sustainable development, we established a multi-objective optimisation model for crop planting structure in an irrigation area using the grey wolf (GWO) algorithm to comprehensively consider resource, economic, social objectives associated with agriculture. This was subsequently applied obtain optimal southern bank of Xiaolangdi Reservoir Henan Province, China. The areas wheat, corn, autumn miscellaneous, economic crops are 30,417; 25,050; 7157; 1789 hm2, respectively. water is 8292.66 × 104 m3, output value 105,721.37 CNY, yield 34,280.31 kg. Different solutions used solve evaluate results, order degree entropy method compare results multiple solutions. scheme obtained this consistent evaluation cooperative game scheme, relative 0.136, which better than that other schemes. Thus, via GWO considers consumption, benefits, yield, ensures coordinated development systems conducive promoting benign whole system.

Language: Английский

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Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design

Advances in Mechanical Engineering, Journal Year: 2024, Volume and Issue: 16(10)

Published: Oct. 1, 2024

This paper presents a comprehensive study on the design optimization of robotic gripper, focusing both gripper modeling and its parallel mechanism structure. integrates Black-winged Kite Algorithm (BKA), Finite Element Analysis (FEA), Backpropagation Neural Network (BPNN), response surface techniques. The Good Point Set (GPS), nonlinear convergence factor, adaptive t-distribution method improve BKA, which enhances exploration exploitation performance, speed, solution quality. Subsequently, structure is designed to minimize total mass, deformation, maximum equivalent stress. central composite (CCD) was used FEA experiment establish BKA-BPNN regression prediction model. RMSE this model’s training set test are 0.001615 0.0029328. A model constructed determine best solution. optimized achieves 33.12% reduction in stress, 1.47% decrease 0.16% deformation. provides valuable insights into process for grippers, showcasing effectiveness proposed methodologies enhancing performance while reducing mass improving structural integrity.

Language: Английский

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Performance enhancement of a hybrid energy storage systems using meta-heuristic optimization algorithms: Genetic algorithms, ant colony optimization, and grey wolf optimization

Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 103, P. 114451 - 114451

Published: Nov. 7, 2024

Language: Английский

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