[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Browse::
Journal Info::
Guide for Authors::
Submit Manuscript::
Articles archive::
For Reviewers::
Contact us::
Site Facilities::
Reviewers::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 14, Issue 2 (12-2024) ::
JGST 2024, 14(2): 71-87 Back to browse issues page
Developing a fuzzy analytic network process (ANP) and fuzzy analytic hierarchy process (AHP) model to evaluate small hydropower plant potential
Hossei Joulaei * , Ali Moridi , Mohammad Saeed Heidari , Alireza Vafaeinajad
Abstract:   (241 Views)
Despite the fact that the energy sector has contributed to the destruction of the environment through its emissions of greenhouse gases, human societies have paid more attention to renewable energy sources such as small hydropower plants in response to this issue. For the purpose of determining zoning, 12 layers of environmental, technical, and geographical criteria have been used. In order to achieve the results of this study, we combined multi-criteria decision-making (MCDM) with fuzzy algorithms. Basically, the fuzzy-AHP method of weighting is used as a method for evaluating the technical and environmental criteria that do not have an internal relationship with one another. Using the fuzzy-ANP method, we are able to weight geographical criteria that are related to one another and are evaluated in terms of their relative importance. In order to identify the zoning map, layers have been overlaid by using the gamma operator 0.9 in order to identify the zoning map. In order to produce the final zoning map, the zoning and the physiographic maps are combined using the Sum operator. Therefore, 13 suitable sites were selected for the construction of power plants, resulting in 22084.69 megawatts of energy being generated per year and 5.8 tons of greenhouse gases being prevented from being released into the atmosphere. During the course of this study, a watershed located in Iran, known as the Karoun watershed, was studied. Furthermore, the methods applied in this research could be performed in other watersheds and evaluated the potential of other power plants such as solar and wind power plants.

 
Article number: 5
Keywords: SHP (Small Hydropower Plants), AHP, ANP, GHG emissions
Full-Text [PDF 2737 kb]   (150 Downloads)    
Type of Study: Research | Subject: GIS
Received: 2024/04/18
References
1. S. M. Hosseini, A. Aslani, and A. Kasaeian, "Energy, water, and environmental impacts assessment of electricity generation in Iran," Sustainable Energy Technologies and Assessments, vol. 52, p. 102193, 2022. [DOI:10.1016/j.seta.2022.102193]
2. G. E. Review, "Assessing the effects of economic recoveries on global energy demand and CO2 emissions in 2021," 2021.
3. N. O. a. A. Administration, "Carbon dioxide now more than 50% higher than pre-industrial levels," ed, June 3, 2022
4. "Tripling renewable power and doubling energy efficiency by 2030: Crucial steps towards 1.5°C, International Renewable Energy Agency, Abu Dhabi.," in IRENA, ed, 2023.
5. R. Marks-Bielska, S. Bielski, K. Pik, and K. Kurowska, "The importance of renewable energy sources in Poland's energy mix," Energies, vol. 13, no. 18, p. 4624, 2020. [DOI:10.3390/en13184624]
6. X. Xu, J. E. González, S. Shen, S. Miao, and J. Dou, "Impacts of urbanization and air pollution on building energy demands-Beijing case study," Applied Energy, vol. 225, pp. 98-109, 2018. [DOI:10.1016/j.apenergy.2018.04.120]
7. IEA, "World Energy Outlook 2021," in IEA, ed. paris, (2021).
8. R. Brini, "Renewable and non-renewable electricity consumption, economic growth and climate change: Evidence from a panel of selected African countries," Energy, vol. 223, p. 120064, 2021. [DOI:10.1016/j.energy.2021.120064]
9. V. Khare, C. Khare, S. Nema, and P. Baredar, "Chapter 1 - Introduction to Energy Sources," in Tidal Energy Systems, V. Khare, C. Khare, S. Nema, and P. Baredar Eds.: Elsevier, 2019, pp. 1-39. [DOI:10.1016/B978-0-12-814881-5.00001-6]
10. E. F. Moran, M. C. Lopez, N. Moore, N. Müller, and D. W. Hyndman, "Sustainable hydropower in the 21st century," Proceedings of the National Academy of Sciences, vol. 115, no. 47, pp. 11891-11898, 2018, doi: doi:10.1073/pnas.1809426115. [DOI:10.1073/pnas.1809426115]
11. A. S. Assessment, "Hydropower Development in India."
12. X. Zhang et al., "Impacts of climate change, policy and Water-Energy-Food nexus on hydropower development," Renewable Energy, vol. 116, pp. 827-834, 2018. [DOI:10.1016/j.renene.2017.10.030]
13. J. Zhang, C.-Y. Luo, Z. Curtis, S.-h. Deng, Y. Wu, and Y.-w. Li, "Carbon dioxide emission accounting for small hydropower plants-A case study in southwest China," Renewable and Sustainable Energy Reviews, vol. 47, pp. 755-761, 2015. [DOI:10.1016/j.rser.2015.03.027]
14. P. Tomczyk and M. Wiatkowski, "Challenges in the development of hydropower in selected European countries," Water, vol. 12, no. 12, p. 3542, 2020. [DOI:10.3390/w12123542]
15. Y. Bayazıt, R. Bakış, and C. Koç, "An investigation of small scale hydropower plants using the geographic information system," Renewable and Sustainable Energy Reviews, vol. 67, pp. 289-294, 2017. [DOI:10.1016/j.rser.2016.09.062]
16. D. Connolly, H. Lund, B. V. Mathiesen, and M. Leahy, "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied energy, vol. 87, no. 4, pp. 1059-1082, 2010. [DOI:10.1016/j.apenergy.2009.09.026]
17. P. Aragonés-Beltrán, F. Chaparro-González, J.-P. Pastor-Ferrando, and A. Pla-Rubio, "An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects," Energy, vol. 66, pp. 222-238, 2014. [DOI:10.1016/j.energy.2013.12.016]
18. A. A. Othman et al., "GIS-based modeling for selection of dam sites in the Kurdistan Region, Iraq," ISPRS International Journal of Geo-Information, vol. 9, no. 4, p. 244, 2020. [DOI:10.3390/ijgi9040244]
19. X. Dai, "Dam site selection using an integrated method of AHP and GIS for decision making support in Bortala, Northwest China," University of Twente, 2016.
20. T. F. Ajibade et al., "Potential dam sites selection using integrated techniques of remote sensing and GIS in Imo State, Southeastern, Nigeria," Sustainable Water Resources Management, vol. 6, pp. 1-16, 2020. [DOI:10.1007/s40899-020-00416-5]
21. O. Caleb, M. Adepoju, I. Idris, A. Oluwatola, N. Ihenacho, and A. Olaide, "Small hydropower dam site suitability modelling in upper Benue river watershed, Nigeria," Applied Water Science, vol. 11, no. 8, 2021. [DOI:10.1007/s13201-021-01466-6]
22. D. G. Palomino Cuya, L. Brandimarte, I. Popescu, J. Alterach, and M. Peviani, "A GIS-based assessment of maximum potential hydropower production in La Plata basin under global changes," Renewable Energy, vol. 50, pp. 103-114, 2013/02/01/ 2013, doi: https://doi.org/10.1016/j.renene.2012.06.019 [DOI:10.1016/j.renene.2012.06.019.]
23. S. Kucukali, O. Al Bayatı, and H. H. Maraş, "Finding the most suitable existing irrigation dams for small hydropower development in Turkey: A GIS-Fuzzy logic tool," Renewable Energy, vol. 172, pp. 633-650, 2021/07/01/ 2021, doi: https://doi.org/10.1016/j.renene.2021.03.049 [DOI:10.1016/j.renene.2021.03.049.]
24. O. A. Fasipe, O. C. Izinyon, and J. O. Ehiorobo, "Hydropower potential assessment using spatial technology and hydrological modelling in Nigeria river basin," Renewable Energy, vol. 178, pp. 960-976, 2021/11/01/ 2021, doi: https://doi.org/10.1016/j.renene.2021.06.133 [DOI:10.1016/j.renene.2021.06.133.]
25. Y. Noorollahi, A. G. Senani, A. Fadaei, M. Simaee, and R. Moltames, "A framework for GIS-based site selection and technical potential evaluation of PV solar farm using Fuzzy-Boolean logic and AHP multi-criteria decision-making approach," Renewable Energy, vol. 186, pp. 89-104, 2022. [DOI:10.1016/j.renene.2021.12.124]
26. Z. Ullah, M. Elkadeem, K. M. Kotb, I. B. Taha, and S. Wang, "Multi-criteria decision-making model for optimal planning of on/off grid hybrid solar, wind, hydro, biomass clean electricity supply," Renewable Energy, vol. 179, pp. 885-910, 2021. [DOI:10.1016/j.renene.2021.07.063]
27. T. L. Saaty, "TheAnalyticHierarchyProcess," McGrawhill, Juc. New York, 1980.
28. T. L. Saaty, Fundamentals of decision making and priority theory with the analytic hierarchy process. RWS publications, 1994.
29. T. L. Saaty, Decision making with dependence and feedback: The analytic network process (no. 2). RWS publications Pittsburgh, 1996.
30. T. L. Saaty, Theory and applications of the analytic network process: decision making with benefits, opportunities, costs, and risks. RWS publications, 2005.
31. C.-L. Yang, S.-P. Chuang, and R.-H. Huang, "Manufacturing evaluation system based on AHP/ANP approach for wafer fabricating industry," Expert Systems with Applications, vol. 36, no. 8, pp. 11369-11377, 2009/10/01/ 2009, doi: https://doi.org/10.1016/j.eswa.2009.03.023 [DOI:10.1016/j.eswa.2009.03.023.]
32. C. Gencer and D. Gürpinar, "Analytic network process in supplier selection: A case study in an electronic firm," Applied Mathematical Modelling, vol. 31, no. 11, pp. 2475-2486, 2007/11/01/ 2007, doi: https://doi.org/10.1016/j.apm.2006.10.002 [DOI:10.1016/j.apm.2006.10.002.]
33. R. Yu and G.-H. Tzeng, "A soft computing method for multi-criteria decision making with dependence and feedback," Applied Mathematics and Computation, vol. 180, no. 1, pp. 63-75, 2006/09/01/ 2006, doi: https://doi.org/10.1016/j.amc.2005.11.163 [DOI:10.1016/j.amc.2005.11.163.]
34. M. Dağdeviren and İ. Yüksel, "A fuzzy analytic network process (ANP) model for measurement of the sectoral competititon level (SCL)," Expert Systems with Applications, vol. 37, no. 2, pp. 1005-1014, 2010/03/01/ 2010, doi: https://doi.org/10.1016/j.eswa.2009.05.074 [DOI:10.1016/j.eswa.2009.05.074.]
35. D. L. Tennant, "Instream Flow Regimens for Fish, Wildlife, Recreation and Related Environmental Resources," Fisheries, vol. 1, no. 4, pp. 6-10, 1976, doi: https://doi.org/10.1577/1548-8446(1976)001<0006:IFRFFW>2.0.CO;2. https://doi.org/10.1577/1548-8446(1976)001<0006:IFRFFW>2.0.CO;2 [DOI:10.1577/1548-8446(1976)0012.0.CO;2.]
36. A. Hatamkhani, A. Moridi, and J. Yazdi, "A simulation - Optimization models for multi-reservoir hydropower systems design at watershed scale," Renewable Energy, vol. 149, pp. 253-263, 2020/04/01/ 2020, doi: https://doi.org/10.1016/j.renene.2019.12.055 [DOI:10.1016/j.renene.2019.12.055.]
37. A. Hatamkhani and A. Moridi, "Multi-Objective Optimization of Hydropower and Agricultural Development at River Basin Scale," Water Resources Management, vol. 33, 10/01 2019, doi: 10.1007/s11269-019-02365-x. [DOI:10.1007/s11269-019-02365-x]
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA



XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Joulaei H, Moridi A, Heidari M S, Vafaeinajad A. Developing a fuzzy analytic network process (ANP) and fuzzy analytic hierarchy process (AHP) model to evaluate small hydropower plant potential. JGST 2024; 14 (2) : 5
URL: http://jgst.issgeac.ir/article-1-1183-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 14, Issue 2 (12-2024) Back to browse issues page
نشریه علمی علوم و فنون نقشه برداری Journal of Geomatics Science and Technology