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Journal ArticleDOI

Wind characterization analysis incorporating genetic algorithm: A case study in Taiwan Strait

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TLDR
In this article, the authors applied the GA to compute the Weibull parameters for wind characterization analysis, in which an objective function required in GA for searching optimization solution has been first defined as well.
About
This article is published in Energy.The article was published on 2011-05-01. It has received 32 citations till now. The article focuses on the topics: Wind power & Wind profile power law.

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Citations
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Journal ArticleDOI

Mixture probability distribution functions to model wind speed distributions

TL;DR: In this article, the quality of wind speed assessment depends on the capability of chosen probability density function (PDF) to describe the measured wind speed frequency distribution, which is critical for harnessing wind power effectively.
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Wind energy potential assessment for the site of Inner Mongolia in China

TL;DR: In this article, three probability density functions, i.e., two-parameter Weibull, Logistic and Lognormal, are employed to wind speed distribution modeling using data measured at a typical site in Inner Mongolia, China, over the latest three year period from 2009 to 2011.
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Analysis of wind speed data and wind energy potential in Faya-Largeau, Chad, using Weibull distribution

TL;DR: In this paper, the authors aimed at analyzing the wind speed of Faya-Largeau and making decisions of the cost effective wind turbine for the Saharan zone of Chad, where three commercial wind turbine models were used.
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Analysis of Wind Energy Conversion System Using Weibull Distribution

TL;DR: In this paper, the wind speed data has been statistically analyzed using Weibull distribution to find out wind energy conversion characteristics of Hatiya Island in Bangladesh, and the authors found that more than 58% of the total hours in a year have wind speed above 6.0 m/s.
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Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions

TL;DR: In this article, three comparison metaheuristic optimization algorithms (MOAs), including bat algorithm (BA), cuckoo search algorithm (CS), and particle swarm optimization (PSO) are employed as comparison methods to tune the optimal parameters.
References
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Book

Adaptation in natural and artificial systems

TL;DR: Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Journal ArticleDOI

Modern estimation of the parameters of the Weibull wind speed distribution for wind energy analysis

TL;DR: In this article, three methods for calculating the parameters of the Weibull wind speed distribution for wind energy analysis are presented: the maximum likelihood method, the proposed modified maximum likelihood (MML) method, and the commonly used graphical method.
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Implementation of genetic algorithm for distribution systems loss minimum re-configuration

TL;DR: In this paper, the loss minimum reconfiguration problem in the open loop radial distribution system is formulated as a mixed integer programming problem and a detailed solution methodology by the use of genetic algorithm is outlined.
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A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands

TL;DR: In this paper, a review of the use of the probability density function (PDF) of wind speed is carried out for a wide collection of models, and the methods that have been used to estimate the parameters on which these models depend are reviewed and the degree of complexity of the estimation is analyzed in function of the model selected.
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An overview of wind energy-status 2002

TL;DR: In this article, the authors provide an overview of the historical development of wind energy technology and discuss the current world-wide status of grid-connected as well as stand-alone wind power generation.
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