The global quest for energy sustainability has motivated the development of efficiently transforming various renewable natural resources, such as wind, into energy. This transformation requires long-term planning, and we are interested in how to make systematic decisions when the dependency on the existing power plant decreases, toward eventual microgrid systems. The present study investigates the upgrading of an existing power system into one with a wind-integrated microgrid. The standard approach applies wind resource assessment to determine suitable wind farm locations with high energy potential and then develops specific dispatch strategies to meet the power demand for the wind-integrated system with low cost, high reliability, and low impact on the environment. However, the uncertainties in wind resource result in fluctuating power generation. The installation of additional energy storage devices is thus needed in the dispatch strategy to ensure a stable power supply. The present work proposes a design procedure for obtaining the optimal rated power of the wind farm and the size of storage devices considering wind resource assessment and dispatch strategy under uncertainty. Two wind models are developed from real-world wind data and apply in the proposed optimization framework. Based on comparisons of system reliability between the optimal results and real operating states, an appropriate wind model can be chosen to represent the wind characteristics of a particular region. Results show that the wind model in the optimization framework should consider the uncertainties of wind resource to maintain high system reliability. The proposed method provides a gradual planning of a power system and leads the existing power system toward energy sustainability.

References

References
1.
Chadwick
,
J. E.
,
2013
, “
How a Smarter Grid Could Have Prevented the 2003 U.S. Cascading Blackout
,”
2013 IEEE Power and Energy Conference at Illinois
(
PECI
), Champaign, IL, Feb. 22–23, pp.
65
71
.10.1109/PECI.2013.6506036
2.
Spencer
,
M. D.
,
Stol
,
K. A.
,
Unsworth
,
C. P.
,
Cater
,
J. E.
, and
Norris
,
S. E.
,
2013
, “
Model Predictive Control of a Wind Turbine Using Short-Term Wind Field Predictions
,”
Wind Energy
,
16
(
3
), pp.
417
434
.10.1002/we.1501
3.
Whitefoot
,
J. W.
,
Mechtenberg
,
A. R.
,
Peters
,
D. L.
, and
Papalambros
,
P. Y.
,
2011
, “
Optimal Component Sizing and Forward-Looking Dispatch of an Electrical Microgrid for Energy Storage Planning
,”
ASME
Paper No. DETC2011-48513.10.1115/DETC2011-48513
4.
Rogers
,
A. L.
,
Rogers
,
J. W.
, and
Manwell
,
J. F.
,
2005
, “
Comparison of the Performance of Four Measure-Correlate-Predict Algorithms
,”
J. Wind Eng. Ind. Aerodyn.
,
93
(
3
), pp.
243
264
.10.1016/j.jweia.2004.12.002
5.
Rogers
,
A. L.
,
Rogers
,
J. W.
, and
Manwell
,
J. F.
,
2006
, “
Uncertainties in Results of Measure-Correlate-Predict Analyses
,”
European Wind Energy Conference and Exhibition 2006
,
EWEC 2006
,
Vol. 3, Athens, Greece
, pp.
2211
2220
.
6.
Lackner
,
M. A.
,
Rogers
,
A. L.
, and
Manwell
,
J. F.
,
2008
, “
Uncertainty Analysis in MCP-Based Wind Resource Assessment and Energy Production Estimation
,”
ASME J. Sol. Energy Eng.
,
130
(
3
), p.
031006
.10.1115/1.2931499
7.
Beltrán
,
J.
,
Cosculluela
,
L.
,
Pueyo
,
C.
, and
Melero
,
J. J.
,
2010
, “
Comparison of Measure-Correlate-Predict Methods in Wind Resource Assessments
,”
European Wind Energy Conference and Exhibition 2010
, EWEC 2010, Warsaw, Poland, pp.
3280
3286
.
8.
Skittides
,
C.
,
2012
, “
Wind Resource Assessment Using Principal Component Analysis
,”
European Wind Energy Conference and Exhibition 2012
, EWEC 2012, Copenhagen, Denmark, pp.
1858
1867
.
9.
Al Buflasa
,
H.
,
Infield
,
D.
,
Watson
,
S.
, and
Thomson
,
M.
,
2008
, “
Wind Resource Assessment for the Kingdom of Bahrain
,”
Wind Eng.
,
32
(
5
), pp.
439
448
.10.1260/030952408786411976
10.
Hynynen
,
K. M.
,
Baygildina
,
E.
, and
Pyrhonen
,
O.
,
2012
, “Wind Resource Assessment in Southeast Finland,” 2012
IEEE
Power Electronics and Machines in Wind Applications
, Denver, CO, July 16–18, pp.
1
5
.10.1109/PEMWA.2012.6316376
11.
Roy
,
A.
,
Kedare
,
S. B.
, and
Bandyopadhyay
,
S.
,
2009
, “
Application of Design Space Methodology for Optimum Sizing of Wind-Battery Systems
,”
Appl. Energy
,
86
(
12
), pp.
2690
2703
.10.1016/j.apenergy.2009.04.032
12.
Roy
,
A.
,
Kedare
,
S. B.
, and
Bandyopadhyay
,
S.
,
2010
, “
Optimum Sizing of Wind-Battery Systems Incorporating Resource Uncertainty
,”
Appl. Energy
,
87
(
8
), pp.
2712
2727
.10.1016/j.apenergy.2010.03.027
13.
Gao
,
Z. Y.
,
Wang
,
P.
,
Bertling
,
L.
, and
Wang
,
J. H.
,
2011
, “
Sizing of Energy Storage for Power Systems With Wind Farms Based on Reliability Cost and Wroth Analysis
,”
IEEE
Power and Energy Society General Meeting
, Detroit, MI.10.1109/PES.2011.6039468
14.
Bao
,
W.
,
He
,
G.
,
Shi
,
W.
,
Feng
,
K.
, and
Zhao
,
W.
,
2012
, “Distributed Wind Generation Siting and Sizing Considering Fluctuate Wind Resources,”
2012 IEEE Innovative Smart Grid Technologies—Asia
,
ISGT
Asia 2012, Tianjin, China, May 21–24, pp.
1
7
.10.1109/ISGT-Asia.2012.6303362
15.
Dutta
,
S.
, and
Sharma
,
R.
,
2012
, “Optimal Storage Sizing for Integrating Wind and Load Forecast Uncertainties,”
2012 IEEE PES Innovative Smart Grid Technologies
,
ISGT
2012, Washington, DC, Jan. 16–20, pp.
1
7
.10.1109/ISGT.2012.6175721
16.
Chen
,
W. Z.
,
Li
,
Q. B.
,
Shi
,
L.
,
Luo
,
Y.
,
Zhan
,
D. D.
,
Shi
,
N.
, and
Liu
,
K.
,
2012
, “
Energy Storage Sizing for Dispatchability of Wind Farm
,”
2012 11th International Conference on Environment and Electrical Engineering
, Venice, May 18–25, pp.
382
387
.10.1109/EEEIC.2012.6221407
17.
Ren
,
H.
,
Zhou
,
W.
,
Nakagami
,
K.
,
Gao
,
W.
, and
Wu
,
Q.
,
2010
, “
Multi-Objective Optimization for the Operation of Distributed Energy Systems Considering Economic and Environmental Aspects
,”
Appl. Energy
,
87
(
12
), pp.
3642
3651
.10.1016/j.apenergy.2010.06.013
18.
Sanseverino
,
E. R.
,
Di Silvestre
,
M. L.
,
Ippolito
,
M. G.
,
De Paola
,
A.
, and
Lo Re
,
G.
,
2011
, “
An Execution, Monitoring and Replanning Approach for Optimal Energy Management in Microgrids
,”
Energy
,
36
(
5
), pp.
3429
3436
.10.1016/j.energy.2011.03.047
19.
Sortomme
,
E.
,
Al-Awami
,
A. T.
, and
El-Sharkawi
,
M. A.
,
2010
, “
Multi-Objective Optimization for Wind Energy Integration
,” 2010
IEEE
Transmission and Distribution Conference and Exposition
, New Orleans, LA, Apr. 11–22, pp. 1–6.10.1109/TDC.2010.5484224
20.
Söder
,
L.
,
1993
, “
Reserve Margin Planning in a Wind-Hydro-Thermal Power System Introduction Problem Statement
,”
IEEE Trans. Power Syst.
,
8
(
2
), pp.
564
571
.10.1109/59.260826
21.
Contaxis
,
G.
, and
Vlachos
,
A.
,
2000
, “
Optimal Power Flow Considering Operation of Wind Parks and Pump Storage Hydro Units Under Large Scale Integration of Renewable Energy Sources
,”
Power Engineering Society Winter Meeting
, Jan. 23–27, pp.
1745
1750
.10.1109/PESW.2000.847616
22.
Tsai
,
S.-R.
,
2009
, “
Multi-Objective Optimal Power Flow Including Wind Generation With Uncertainties
,” Master’s thesis, National Yunlin University of Science and Technology, Douliu, Taiwan.
23.
Al-Awami
,
A. T.
, and
El-Sharkawi
,
M. A.
,
2010
, “
Stochastic Dispatch of Power Grids With High Penetration of Wind Power Using Pareto Optimization
,”
Wind Power Systems
,
Springer
,
Berlin, Germany
, pp.
125
149
.
24.
Lu
,
S.
,
Schroeder
,
N. B.
,
Kim
,
H. M.
, and
Shanbhag
,
U.
V
,
2010
, “
Hybrid Power/Energy Generation Through Multidisciplinary and Multilevel Design Optimization With Complementarity Constraints
,”
ASME J. Mech. Des.
,
132
(
10
), p.
101007
.10.1115/1.4002292
25.
Kusiak
,
A.
, and
Song
,
Z.
,
2010
, “
Design of Wind Farm Layout for Maximum Wind Energy Capture
,”
Renewable Energy
,
35
(
3
), pp.
685
694
.10.1016/j.renene.2009.08.019
26.
Chowdhury
,
S.
,
Zhang
,
J.
,
Messac
,
A.
, and
Castillo
,
L.
,
2013
, “
Optimizing the Arrangement and the Selection of Turbines for Wind Farms Subject to Varying Wind Conditions
,”
Renewable Energy
,
52
, pp.
273
282
.10.1016/j.renene.2012.10.017
27.
Department of Statistics, Ministry of the Interior,
2012
, http://www.moi.gov.tw/
28.
Taiwan Power Company,
2012
, http://www.taipower.com.tw/
29.
Anping District Household Registration Office, Tainan City,
2012
, http://www.tnapcg.gov.tw/
30.
Mathworks,
2013
, matlab.
31.
Enercon Product Overview,
2013
, http://www.enercon.de/
You do not currently have access to this content.