In this study, economical options to meet the load demand of Hormoz Island as a green Island in future years, located in Iran, are investigated. For this purpose, construction of a new undersea transmission line (UTL) and design of a grid-connected hybrid renewable energy system (RES) are selected as two possible options. Therefore, the optimization problem is modeled as a minimization of cost function including the investment, replacement, operation, and maintenance costs of components, carbon tax, and cost of purchased power from the upstream network as well as the cost of loss of load. It is notable that the grid-connected hybrid RES consists of photovoltaic (PV) and wind energy systems with consideration of redox flow battery storage. The optimization problem is simulated for a 20 year planning horizon subject to technical and geographical constraints of RES. To simulate the problem, the annual hour-based data of wind, solar radiation, and load demand of Hormoz Island are used. Also, wind energy potential of the region is used for the selection of the best turbine for this island. Moreover, an imperialist competitive algorithm and an improved particle swarm optimization algorithm are applied to find the best size and design of the hybrid RES and also the best time to use the RES and the new UTL. Three different scenarios for optimum hybrid RES designing are determined to consider the effects of using the hybrid system to postpone the grid expansion investments. Two of these scenarios have 20 year planning horizon, and one of them optimizes the system for a special year with a specific predicted load demand. The obtained results revealed that the wind/PV/vanadium redox flow battery hybrid system is the best configuration, where the new UTL will be constructed in 2020 with zero load energy shortage.
References
1.
M.
Liserre
, T.
Sauter
, and J. Y.
Hung
, “Future energy systems: Integrating renewable energy sources into the smart power grid through industrial electronics
,” IEEE Ind. Electron. Mag.
4
(1
), 18
–37
(2010
).2.
See http://www.saba.org.ir/fa/energyinfo/tashilat/taraz for
Energy Balance
of Iran; accessed 21 May 2012 (2011
).3.
Iran Energy Efficiency Organization (IEEO) (SABA)
, http://www.saba.org.ir for technical and economic data of HES components; accessed 05 September 2013.4.
A.
Kashefi Kaviani
, H. R.
Baghaee
, and G. H.
Riahy
, “Design and optimal sizing of a photovoltaic/wind-generator system using particle swarm optimization
,” in 22nd Power System Conference (PSC)
, Tehran, Iran (2007
).5.
Y.
Hongxing
, Z.
Wei
, and L.
Chengzhi
, “Optimal design and techno-economic analysis of a hybrid solar-wind power generation system
,” Appl. Energy
86
, 163
–169
(2009
).6.
M.
Ikhsan
, A.
Purwadi
, N.
Hariyanto
, N.
Heryana
, and Y.
Haroen
, “Study of renewable energy sources capacity and loading using data logger for sizing of solar-wind hybrid power system
,” Procedia Technol.
11
, 1048
–1053
(2013
).7.
S.
Rehman
and L. M.
Al-Hadhrami
, “Study of a solar PV/diesel battery hybrid power system for a remotely located population near Rafha, Saudi Arabia
,” Energy
35
(12
), 4986
–4995
(2010
).8.
D.
Nelson
, M.
Nehrir
, and C.
Wang
, “Unit sizing and cost analysis of stand-alone hybrid wind/PV/fuel cell power generation systems
,” Renewable Energy
31
, 1641
–1656
(2006
).9.
R. K.
Rajkumar
, V. K.
Ramachandaramurthy
, B. L.
Yong
, and D. B.
Chia
, “Techno-economical optimization of hybrid pv/wind/battery system using Neuro-Fuzzy
,” Energy
36
, 5148–5153
(2011
).10.
A.
Kaabeche
and R.
Ibtiouen
, “Techno-economic optimization of hybrid photovoltaic/wind/diesel/battery generation in a stand-alone power system
,” Sol. Energy
103
, 171
–182
(2014
).11.
Y. Y.
Hong
and C. R.
Lian
, “Optimal sizing of hybrid wind/PV/diesel generation in a stand-alone power system using Markov-based genetic algorithm
,” IEEE Trans. Power Delivery
27
(2
), 640
–647
(2012
).12.
A.
Maleki
and F.
Pourfayaz
, “Sizing of stand-alone photovoltaic/wind/diesel system with battery and fuel cell storage devices by harmony search algorithm
,” J. Energy Storage
2
, 30
–42
(2015
).13.
A.
Khalilnejad
and G. H.
Riahy
, “A hybrid wind-PV system performance investigation for the purpose of maximum hydrogen production and storage using advanced alkaline electrolyzer
,” Energy Convers. Manage.
80
, 398
–406
(2014
).14.
S.
Roy
, “Optimal planning of wind energy conversion systems over an energy scenario
,” IEEE Trans. Energy Convers.
12
(3
), 248
–254
(1997
).15.
S. G.
Malla
, P. K.
Dadi
, and J.
Dadi
, “Wind and photovoltaic based hybrid stand-alone power generation system
,” in International Conference on Energy, Communication, Data Analytics and Soft Computing
(ICECDS-2017), India (2017).16.
B.
Zhao
, X.
Zhang
, P.
Li
, K.
Wang
, M.
Xue
, and C.
Wang
, “Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan, Island
,” Appl. Energy
113
, 1656
–1666
(2014
).17.
A.
Kashefi Kaviani
, G. H.
Riahy
, and S. H. M.
Kouhsari
, “Optimal design of a reliable hydrogen-based stand-alone wind/PV generating system, considering component outages
,” Renewable Energy
34
, 2380
–2390
(2009
).18.
R.
Dufo-López
, J. L.
Bernal-Agustín
, J. M.
Yusta-Loyo
, J. A.
Domínguez-Navarro
, I. J.
Ramírez-Rosado
, J.
Lujano
, and I.
Aso
, “Multi-objective optimization minimizing cost and life cycle emissions of stand-alone PV/wind/diesel systems with batteries storage
,” Appl. Energy
88
, 4033
–4041
(2011
).19.
J. H.
Lim
, “Optimal combination and sizing of a new and renewable hybrid generation system
,” Int. J. Future Gener. Commun. Networking
5
(2
), 43
–60
(2012
).20.
S.
Diaf
, D.
Diaf
, M.
Belhamel
, M.
Haddadi
, and A.
Louche
, “A methodology for optimal sizing of autonomous hybrid PV/wind system
,” Energy Policy
35
(11
), 5708
–5718
(2007
).21.
S. A.
Ahmadi
, “Human behavior-based optimization: A novel metaheuristic approach to solve complex optimization problems
,” Neural Comput. Appl.
28
, 233
–244
(2017
).22.
A.
Kaabeche
, M.
Belhamel
, and R.
Ibtiouen
, “Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system
,” Energy
36
, 1214
–1222
(2011
).23.
R.
Luna-Rubio
, M.
Trejo-Perea
, D.
Vargas-Vazquez
, and G. J.
Rios-Moreno
, “Optimal sizing of renewable hybrids energy systems: A review of methodologies
,” Sol. Energy
86
, 1077
–1088
(2012
).24.
W.
Zhou
, C.
Lou
, Z.
Li
, L.
Lu
, and H.
Yang
, “Current status of research on optimum sizing of stand-alone hybrid solar/wind power generation systems
,” Appl. Energy
87
, 380
–389
(2010
).25.
G.
Merei
, C.
Berger
, and D. U.
Sauer
, “Optimization of an offgrid hybrid PV/wind/diesel system with different battery technologies using genetic algorithm
,” Sol. Energy
97
, 460
–473
(2013
).26.
F. Z.
Kadda
, S.
Zouggar
, M.
El Hafyani
, and A.
Rabhi
, “Contribution to the optimization of the electrical energy production from hybrid renewable energy system
,” in 5th International Renewable Energy Congress (IREC)
, Hammamet
, Tunisia
, 25–27 March 2014
.27.
H.
Chen
, T. N.
Cong
et al., “Progress in electrical energy storage system: A critical review
,” Prog. Nat. Sci.
19
, 291
–312
(2009
).28.
A.
Chauhan
and R. P.
Saini
, “A review on integrated renewable energy system based power generation for stand-alone applications: Configurations, storage options, sizing methodologies and control
,” Renewable Sustainable Energy Rev.
38
, 99
–120
(2014
).29.
S.
Li
, F.
Sun
, H.
He
, and Y.
Chen
, “Optimization for a grid-connected hybrid PV-wind-retired HEV battery microgrid system
,” Energy Procedia
105
, 1634
–1643
(2017
).30.
A. Á.
Bayod-Rújula
, M. E.
Haro-Larrode
, and A.
Martínez-Gracia
, “Sizing criteria of hybrid photovoltaic–wind systems with battery storage and self-consumption considering interaction with the grid
,” Sol. Energy
98
, 582
–591
(2013
).31.
S. K.
Nandi
and H. R.
Ghosh
, “Prospect of wind/PV/battery hybrid power system as an alternative to grid extension in Bangladesh
,” Energy
35
, 3040
–3047
(2010
).32.
F. J.
Ardakani
, G. H.
Riahy
, and M.
Abedi
, “Optimal sizing of a stand-alone hybrid wind/PV/battery system considering reliability indices accompanied by eror propagation assessment
,” Int. Rev. Electr. Eng.
5
(2
), 748
–757
(2010
).33.
V.
Marano
, G.
Rizzo
, and F. A.
Tiano
, “Application of dynamic programming to the optimal management of a hybrid power plant with wind turbines, photovoltaic panels and compressed air energy storage
,” Appl. Energy
97
, 849
–859
(2012
).34.
M.
Dahbi
, A.
Benatiallahb
, and M.
Sellam
, “The analysis of wind power potential in sahara site of algeria-an estimation using the ‘weibull’ density function
,” Energy Procedia
36
, 179
–188
(2013
).35.
D.
Weisser
, “A wind energy analysis of Grenada: An estimation using the “Weibull” density function
,” Renewable Energy
28
, 1803
–1812
(2003
).36.
T. H.
Yeh
and L.
Wang
, “A study on generator capacity for wind turbines under various tower heights and rated wind speeds using weibull distribution
,” IEEE Trans. Energy Convers.
23
(2
), 592
–602
(2008
).37.
A. S.
Ahmed
, “Wind energy as a potential generation source at Ras Benas, Egypt
,” Renewable Sustainable Energy Rev.
14
(8
), 2167
–2173
(2010
).38.
I.
Fyrippis
, P. J.
Axaopoulos
, and G.
Panayiotou
, “Wind energy potential assessment in Naxos Island, Greece
,” Appl. Energy
87
(2
), 577
–586
(2010
).39.
Wind Energy Resource Atlas of Iran
, http://www.suna.org.ir/en/home for wind speed data of Hormoz Island; accessed 25 November 2015
.40.
Winpro Software
, http://www.emd.dk/windpro/ for calculation of Weibull parameters; accessed 05 February 2016
.41.
Catalogue of European Urban Turbine Manufacturers
, http://www.urbanwind.net/pdf/CATALOGUE_V2.pdf for specifications of candidate WTGs; accessed 14 March 2016
.42.
E.
Koutroulis
, D.
Kolokotsa
, A.
Potirakis
, and K.
Kalaitzakis
, “Methodology for optimal sizing of stand-alone photovoltaic/wind-generator systems using genetic algorithms
,” Sol. Energy
80
, 1072
–1088
(2006
).43.
W.
Zhou
, H. X.
Yang
, and Z. H.
Fang
, “A novel model forphotovoltaic array performance prediction
,” Appl. Energy
84
(12
), 1187
–1198
(2007
).44.
K.
Skeiker
, “Optimum tilt angle and orientation for solar collectors in Syria
,” Energy Convers. Manage.
50
, 2439
–2448
(2009
).45.
F.
D-Gonzáleza
, A.
Sumper
, O.
Gomis-Bellmunta
, and R.
Villafafila-Robles
, “A review of energy storage technologies for wind power applications
,” Renewable Sustainable Energy Rev.
16
, 2154
–2171
(2012
).46.
M. J.
Khan
and M. T.
Iqbal
, “Pre-feasibility study of stand-alone hybrid energy systems for applications in Newfoundland
,” Renewable Energy
30
, 835
–854
(2005
).47.
H.
Yang
, W.
Zhou
, L.
Lu
, and Z.
Fang
, “Optimal sizing method for stand-alone hybrid solar–wind system with LPSP technology by using genetic algorithm
,” Sol. Energy
82
, 354
–367
(2008
).48.
A. H.
Shahirinia
, S. M. M.
Tafreshi
, A.
Hajizadeh Gastaj
, and A. R.
Moghaddomjoo
, “Optimal sizing of hybrid power system using genetic algorithm
,” 2005 International Conference on Future Power Systems
(2005
).49.
H.
Belmili
, M.
Haddadi
, S.
Bacha
, M. F.
Almi
, and B.
Bendib
, “Sizing stand-alone photovoltaic/wind hybrid system: Techno-economic analysis and optimization
,” Renewable Sustainable Energy Rev.
30
, 821
–832
(2014
).50.
R. S.
Garcia
and D.
Weisser
, “A wind/diesel system with hydrogen storage joint optimisation of design and dispatch
,” Renewable Energy
31
, 2296
–2320
(2006
).51.
K. E.
Parasopoulos
and M. N.
Vrahatis
, “On the computation of all global minimizers through particle swarm optimization
,” IEEE Trans. Evol. Comput.
8
(3
), 211
–224
(2004
).52.
Y.
Zhang
, Y.
Wang
, and C.
Peng
, “Improved imperialist competitive algorithm for constrained optimization
,” Comput. Sci.- Technol. Appl.
1
(12
), 204
–207
(2009
).© 2018 Author(s).
2018
Author(s)
You do not currently have access to this content.
