Published August 1, 2016 | Version v1
Journal article

Statistical analysis of wind speed using two-parameter Weibull distribution in Alaçatı region

Description

Highlights: • Wind speed & direction data from September 2008 to March 2014 has been analyzed. • Mean wind speed for the whole data set has been found to be 8.11 m/s. • Highest wind speed is observed in July with a monthly mean value of 9.10 m/s. • Wind speed with the most energy has been calculated as 12.77 m/s. • Observed data has been fit to a Weibull distribution and k &c parameters have been calculated as 2.05 and 9.16. - Abstract: Weibull Statistical Distribution is a common method for analyzing wind speed measurements and determining wind energy potential. Weibull probability density function can be used to forecast wind speed, wind density and wind energy potential. In this study a two-parameter Weibull statistical distribution is used to analyze the wind characteristics of Alaçatı region, located in Çeşme, İzmir. The data used in the density function are acquired from a wind measurement station in Alaçatı. Measurements were gathered on three different heights respectively 70, 50 and 30 m between 10 min intervals for five and half years. As a result of this study; wind speed frequency distribution, wind direction trends, mean wind speed, and the shape and the scale (k&c) Weibull parameters have been calculated for the region. Mean wind speed for the entirety of the data set is found to be 8.11 m/s. k&c parameters are found as 2.05 and 9.16 in relative order. Wind direction analysis along with a wind rose graph for the region is also provided with the study. Analysis suggests that higher wind speeds which range from 6–12 m/s are prevalent between the sectors 340–360°. Lower wind speeds, from 3 to 6 m/s occur between sectors 10–29°. Results of this study contribute to the general knowledge about the regions wind energy potential and can be used as a source for investors and academics.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2016.05.026

Additional details

Identifiers

DOI
10.1016/j.enconman.2016.05.026;
PII
S0196-8904(16)30396-X;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
121
Journal Page Range
p. 49-54
ISSN
0196-8904
CODEN
ECMADL

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
48003466
Subject category
S17: WIND ENERGY;
Descriptors DEI
COST; DENSITY; DIAGRAMS; ECONOMICS; GRAPH THEORY; PROBABILITY DENSITY FUNCTIONS; VELOCITY; WIND; WIND POWER
Descriptors DEC
ENERGY SOURCES; FUNCTIONS; INFORMATION; MATHEMATICS; PHYSICAL PROPERTIES; POWER; RENEWABLE ENERGY SOURCES

Optional Information

Copyright
Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.