A global evaluation model applied to wind power plant site selection

被引:23
作者
Asadi, Meysam [1 ]
Ramezanzade, Mohsen [2 ]
Pourhossein, Kazem [1 ]
机构
[1] Islamic Azad Univ, Dept Elect Engn, Tabriz Branch, Tabriz, Iran
[2] Noshirvani Univ Technol, Dept Elect & Comp Engn, Babol, Iran
关键词
Wind energy; Site selection; GIS; Full Factorial Design (FFD); AHP; Model design; DECISION-MAKING MCDM; ANALYTIC HIERARCHY PROCESS; ELECTRICITY PRODUCTION; INFORMATION-SYSTEM; FARM LOCATIONS; ENERGY; GIS; SOLAR; DESIGN; OPTIMIZATION;
D O I
10.1016/j.apenergy.2023.120840
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Site selection is one of the most critical steps in designing wind farms due to the heterogeneous distribution of wind energy on the Earth's surface. Additionally, the wind power site selection problem is a complex process since it must be evaluated from multiple perspectives, including techno-economic, social, and environmental factors. In this regard, the current study proposes a new approach which combines Full Factorial Design and Analytic Hierarchy Process. The output of this combination creates a global model for the site selection of wind power plants. Using this model, the decision-making space is transformed into the scoring space which makes the scores related to candidate sites more meaningful and understandable. Therefore, Iran is selected to find suitable wind sites to reveal the proposed model's capability. The results indicate that approximately 1300, 5109, and 16000 km2 of the study area are considered outstanding, excellent, and good for the utilization of wind energy. Furthermore, a functional analysis was conducted to ensure that the proposed model was robust, and accord-ingly, the accuracy of siting some existing wind farm sites was also studied. Based on the calculated scores, some real sites, e.g., Khaf and Manjil, are suitable for wind power development. Some sites could be more carefully selected, like the Binaloud wind site; others have not been appropriately selected, such as the Soffeh, Shiraz, and Sarab sites. Finally, the model can be employed worldwide as a standard index for assessing wind farm site quality.
引用
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页数:24
相关论文
共 104 条
[1]  
Abd El Aziz Y, 2022, RENEWABLES 2022 GLOB
[2]   A new hybrid multi-criteria decision-making approach for location selection of sustainable offshore wind energy stations: A case study [J].
Abdel-Basset, Mohamed ;
Gamal, Abduallah ;
Chakrabortty, Ripon K. ;
Ryan, Michael .
JOURNAL OF CLEANER PRODUCTION, 2021, 280
[3]   Exploring the environmental and economic impacts of wind energy: a cost-benefit perspective [J].
Adeyeye, Kehinde ;
Ijumba, Nelson ;
Colton, Jonathan .
INTERNATIONAL JOURNAL OF SUSTAINABLE DEVELOPMENT AND WORLD ECOLOGY, 2020, 27 (08) :718-731
[4]   Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia [J].
Al Garni, Hassan Z. ;
Awasthi, Anjali .
APPLIED ENERGY, 2017, 206 :1225-1240
[5]   Assessment of wind energy in Iran: A review [J].
Alamdari, P. ;
Nematollahi, O. ;
Mirhosseini, M. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2012, 16 (01) :836-860
[6]   Prioritizing the existing power generation technologies in Bangladesh ?s clean energy scheme using a hybrid multi -criteria decision making model [J].
Ali, Tausif ;
Chiu, Yie-Ru ;
Aghaloo, Kamaleddin ;
Nahian, Ahmed Jaudat ;
Ma, Hongzhong .
JOURNAL OF CLEANER PRODUCTION, 2020, 267
[7]   Determining the appropriate location for renewable hydrogen development using multi-criteria decision-making approaches [J].
Almutairi, Khalid .
INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2022, 46 (05) :5876-5895
[8]  
Alookandeh AE, 2019, 2019 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2019 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)
[9]   An ANP-based approach for the selection of photovoltaic solar power plant investment projects [J].
Aragones-Beltran, P. ;
Chaparro-Gonzalez, F. ;
Pastor-Ferrando, J. P. ;
Rodriguez-Pozo, F. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2010, 14 (01) :249-264
[10]  
Asadi M, 2021, ROBUST SITE SELECTIO, P1, DOI [10.1109/IWEC52400.2021.9466963, DOI 10.1109/IWEC52400.2021.9466963]