full2013_e - page 604

TABLE III
M
ONTHLY WIND SPEED MEAN AND
ME
VALUES
(
M
/
S
)
E
ACH
P
ERCENTAGE IS
M
E WITH
R
ESPECT TO MEAN
Mean
P1
ARIMA
dARIMA
SARIMA
ME %
ME %
ME %
ME %
Jan.
8.2
2.0 24
2.0
24
2.2
27
1.9
23
Feb.
6.0
2.2
37
1.9
32
2.1
35
1.9
32
Mar.
6.2
3.0
48
2.1
34
2.0
32
2.0
32
Apr.
6.0
2.4
40
2.0
33
1.9
32
1.9
32
May
5.8
1.9
33
1.9
33
1.9
33
1.8
31
Jun.
6.9
2.2
32
1.7
25
1.7
25
1.7
25
Jul.
8.2
2.0
24
2.2
27
2.8
34
2.0
24
Aug.
8.5
2.2
26
2.5
29
2.5
29
2.3
27
Sep.
5.0
2.6
52
1.9
38
2.0
40
1.9
38
Oct.
8.0
2.1
26
2.1
26
2.3
29
2.1
26
Nov.
9.8
2.6
27
2.6
27
2.8
29
2.3
23
Dec.
7.4
2.0
27
1.8
24
2.2
30
1.8
24
Fig. 6. ME over forecast hours, based on all forecast episodes.
Fig. 7. ME values by different models over entire evaluation period at
different wind speed intervals. Each parenthesized percentage represents
the ratio of no. of hours in a particular interval to all hours.
A
CKNOWLEDGEMENTS
The wind dataset was kindly provided by Electricity
Generating Authority of Thailand (EGAT). We thank the
JGSEE Computational Laboratory (Bang Khun Thien
Campus) for general assistance. The study is technically
supported by the National Science and Technology
Development Agency (NSTDA) and the Electricity
Generating Authority of Thailand (under joint grant No.
P-12-00858), the Thailand Research Fund (under grant
RDG5050016), and the Asahi Glass Foundation.
R
EFERENCES
[1]
Manomaiphiboon K., Prabamroong A., Chanaprasert W.,
Rajpreeja N., Phan T.T.;
Dual database system of wind
resource for Thailand. Wind Resource Assessment Using
Advanced Atmospheric Modeling and GIS Analysis
. Final
report, Joint Graduate School of Energy and Environment
(King Mongkut’s University of Technology Thonburi),
supported by Thailand Research Fund. 2010.
/
[2]
Manwell J.F., McGowan J.G., Rogers A.L.;
Wind Energy
Explained: Theory, Design and Application
. Wiley, 2002.
[3]
Torres J.L., Garcia A., De Blas M., De Francisco A.;
Forecast of hourly average wind speed with ARMA
models in Navarre (Spain)
. Solar Energy, Vol. 79, 2005
pp. 65-77.
[4]
Lei M., Shiyan L., Hongling L., Yan Z.;
A review of the
forecasting of wind speed and generated power
.
Renewable and Sustainable Energy Reviews, Vol. 13,
2009 pp. 915-920.
[5]
Shumway R. H., Stoffer D.S.;
Time-series Analysis and
Its Applications
. 3
rd
ed., Springer, 2011.
[6]
Electricity Generating Authority of Thailand;
Annual
Report
. 2011.
/
index.html (accessed on 3 February, 2013)
[7]
Thai Meteorological Department;
Climate of Thailand
.
Ministry
of
Information
and
Communication
Technology.
2010.
(accessed on 19 August, 2012)
[8]
Hyndman R.J., Khandakar Y.;
Automatic time-series
forecasting: The forecast package for R.
Journal of
Statistical Software, Vol. 27, No. 3, 2008, pp. 1-22.
[9]
R Development Core Team;
The R Project for Statistical
Computing
. 2012. Version 2.15.2.
project.org
[10]
Kaigwara W., Manomaiphiboon K.;
Wind Speed
Forecasting at a Coastal Industrialized Site in Thailand
using Time-Series Modeling
. Proc. 2nd International
Conference on Environmental Science & Engineering and
Management, Khon Kaen (Thailand), March 27-29, 2013,
pp. 47-48.
2013 International Conference on Alternative Energy in Developing Countries and Emerging Economies
- 601 -
1...,594,595,596,597,598,599,600,601,602,603 605,606,607,608,609,610,611,612,613,614,...907
Powered by FlippingBook