scholarly journals Optimal Setting Method of Inverse Time Overcurrent Protection for the Distribution Networks Based on the Improved Grey Wolf Optimization

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Bo Yang ◽  
Jun Tang ◽  
Changsen Feng ◽  
Chen Yang ◽  
Xiaofeng Dong
Keyword(s):  
Large Scale ◽  
Engineering Application ◽  
Distribution Networks ◽  
Parameter Determination ◽  
Grey Wolf ◽  
Reverse Time ◽  
Two Phase ◽  
Overcurrent Protection ◽  
Mutation Strategy ◽  
Grey Wolf Algorithm

The setting of protection parameters is vital to the large-scale application of reverse time overcurrent protection in the distribution networks. A fixed value optimization method of inverse time overcurrent protection for the distribution networks with distributed generation based on the improved Grey Wolf algorithm is proposed, which takes the protection action equation and the sensitivity, speed, and selectivity into consideration. Subsequently, four strategies, including good point set initialization, convergence factor exponential decay strategy, mutation strategy, and heuristic parameter determination strategy, are introduced to improve the Grey Wolf algorithm on the premise of retaining fewer adjustable parameters. Simulation results verify the feasibility and superiority of the proposed model in case of the two-phase and three-phase faults and discuss the influence of time differential on parameters setting and the research direction of algorithm optimization and engineering application.

Optimal Siting and Sizing of DGs on Distribution Networks Using Grey Wolf Algorithm

2021 ◽  
Vol 9 (3) ◽  
pp. 113
Author(s):  
Nancy Gamaleldin Azazy ◽  
Walid E. Helmy ◽  
Hany Mohamed Hasanien
Keyword(s):  
Distribution Networks ◽  
Grey Wolf ◽  
Grey Wolf Algorithm

scholarly journals Hybrid Genetic Grey Wolf Algorithm for Large-Scale Global Optimization

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Qinghua Gu ◽  
Xuexian Li ◽  
Song Jiang
Keyword(s):  
Global Optimization ◽  
Large Scale ◽  
Learning Strategy ◽  
Optimization Problems ◽  
Grey Wolf Optimizer ◽  
Local Optimum ◽  
Grey Wolf ◽  
Genetic Operators ◽  
Opposition Based Learning ◽  
Grey Wolf Algorithm

Most real-world optimization problems tackle a large number of decision variables, known as Large-Scale Global Optimization (LSGO) problems. In general, the metaheuristic algorithms for solving such problems often suffer from the “curse of dimensionality.” In order to improve the disadvantage of Grey Wolf Optimizer when solving the LSGO problems, three genetic operators are embedded into the standard GWO and a Hybrid Genetic Grey Wolf Algorithm (HGGWA) is proposed. Firstly, the whole population using Opposition-Based Learning strategy is initialized. Secondly, the selection operation is performed by combining elite reservation strategy. Then, the whole population is divided into several subpopulations for cross-operation based on dimensionality reduction and population partition in order to increase the diversity of the population. Finally, the elite individuals in the population are mutated to prevent the algorithm from falling into local optimum. The performance of HGGWA is verified by ten benchmark functions, and the optimization results are compared with WOA, SSA, and ALO. On CEC’2008 LSGO problems, the performance of HGGWA is compared against several state-of-the-art algorithms, CCPSO2, DEwSAcc, MLCC, and EPUS-PSO. Simulation results show that the HGGWA has been greatly improved in convergence accuracy, which proves the effectiveness of HGGWA in solving LSGO problems.

scholarly journals Thermoelectric Properties of Thin Films from Sorted Single-Walled Carbon Nanotubes

Materials ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 3808 ◽  
Author(s):  
Blazej Podlesny ◽  
Bogumila Kumanek ◽  
Angana Borah ◽  
Ryohei Yamaguchi ◽  
Tomohiro Shiraki ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Thermoelectric Properties ◽  
Large Scale ◽  
Single Walled Carbon Nanotubes ◽  
Parent Material ◽  
Free Standing ◽  
Two Phase ◽  
Single Walled Carbon ◽  
Walled Carbon Nanotubes ◽  
Aqueous Two Phase Extraction

Single-walled carbon nanotubes (SWCNTs) remain one of the most promising materials of our times. One of the goals is to implement semiconducting and metallic SWCNTs in photonics and microelectronics, respectively. In this work, we demonstrated how such materials could be obtained from the parent material by using the aqueous two-phase extraction method (ATPE) at a large scale. We also developed a dedicated process on how to harvest the SWCNTs from the polymer matrices used to form the biphasic system. The technique is beneficial as it isolates SWCNTs with high purity while simultaneously maintaining their surface intact. To validate the utility of the metallic and semiconducting SWCNTs obtained this way, we transformed them into thin free-standing films and characterized their thermoelectric properties.

scholarly journals Time-resolved PIV measurements of a deflected submerged jet interacting with liquid-gas and liquid-liquid interfaces

2021 ◽  
Author(s):  
Stefan Puttinger ◽  
Mahdi Saeedipour
Keyword(s):  
Liquid Layer ◽  
Large Scale ◽  
Free Surface Flow ◽  
Industrial Applications ◽  
Liquid Pool ◽  
Surface Flow ◽  
Two Phase ◽  
Time Resolved ◽  
Submerged Jet ◽  
Major Interest

AbstractThis paper presents an experimental investigation on the interactions of a deflected submerged jet into a liquid pool with its above interface in the absence and presence of an additional lighter liquid. Whereas the former is a free surface flow, the latter mimics a situation of two stratified liquids where the liquid-liquid interface is disturbed by large-scale motions in the liquid pool. Such configurations are encountered in various industrial applications and, in most cases, it is of major interest to avoid the entrainment of droplets from the lighter liquid into the main flow. Therefore, it is important to understand the fluid dynamics in such configurations and to analyze the differences between the cases with and without the additional liquid layer. To study this problem, we applied time-resolved particle image velocimetry experiments with high spatial resolution. A detailed data analysis of a small layer beneath the interface shows that although the presence of an additional liquid layer stabilizes the oscillations of the submerged jet significantly, the amount of kinetic energy, enstrophy, and velocity fluctuations concentrated in the proximity of the interface is higher when the oil layer is present. In addition, we analyze the energy distribution across the eigenmodes of a proper orthogonal distribution and the distribution of strain and vortex dominated regions. As the main objective of this study, these high-resolution time-resolved experimental data provide a validation platform for the development of new models in the context of the volume of fluid-based large eddy simulation of turbulent two-phase flows.

The effect of bubbles on the rheology of basaltic lava flows: Insights from large-scale two-phase experiments

2020 ◽  
Vol 548 ◽  
pp. 116504
Author(s):  
A. Soldati ◽  
J.A. Farrell ◽  
C. Sant ◽  
R. Wysocki ◽  
J.A. Karson
Keyword(s):  
Large Scale ◽  
Lava Flows ◽  
Basaltic Lava ◽  
Two Phase

scholarly journals A hybridized model based on neural network and swarm intelligence-grey wolf algorithm for spatial prediction of urban flood-inundation

2021 ◽  
pp. 126854
Author(s):  
Hamid Darabi ◽  
Ali Torabi Haghighi ◽  
Omid Rahmati ◽  
Abolfazl Jalali Shahrood ◽  
Sajad Rouzbeh ◽  
...  
Keyword(s):  
Neural Network ◽  
Swarm Intelligence ◽  
Spatial Prediction ◽  
Flood Inundation ◽  
Grey Wolf ◽  
Urban Flood ◽  
Model Based ◽  
Grey Wolf Algorithm
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