Multi-objective genetic algorithm (MOGA) based optimization of high-pressure coolant assisted hard turning of 42CrMo4 steel

Saha, Shanta; Zaman, Prianka B.; Tusar, Md. Imran Hasan; Dhar, Nikhil Ranjan

doi:10.1007/s12008-022-00848-7

Cited by 7 publications

(1 citation statement)

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“…It can be applied in manufacturing, service section, energy industry, queuing theory, design optimization, multitask supply chain optimization problems, scheduling and sequencing problem, etc. (Azam et al, 2020;Saha et al, 2022). The proposed model in this study contains some integer variables and non-linear functions, thus MINLP model is being used.…”

Section: Introductionmentioning

confidence: 99%

Location and turbine parameter selection for offshore wind power maximization

Tusar

Sarker

2023

Wind Engineering

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Offshore wind turbines can capture more wind than onshore because of their larger structure and location. This higher yield even fails to reduce the high installation and maintenance cost of an offshore wind farm (OWF). Appropriate turbine parameters and installation site selection may maximize the power generation which is a way to trade off these costs. Knowing the wind thrust force, air density, and power coefficient beforehand can help select an appropriate site for turbine location. Once the site is selected, the optimal value of turbine variables such as height and radius can contribute to higher power yield. In this paper, a MINLP (Mixed Integer Non-Linear Programing) model is formulated with these important variables and the optimal values of these variables are determined to maximize the annual power production ([Formula: see text]) from offshore wind farm. The estimated power production, [Formula: see text], is calculated using two methods, mathematical programing method and simulation method. Computational result indicates that mathematical programing method is time consuming but more accurate whereas the accuracy of simulation method is proportional to the number of iterations. Although the result of a simulation can be improved to some extent, it cannot be as accurate as mathematical modeling for this study. These study results have great impact on the managerial decision and long range strategic and technical planning for maximizing power generation from an offshore wind farm.

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Section: Introductionmentioning

confidence: 99%