A decision-making framework for scheme selection for sustainable hydropower development

References

• Aksoy, A. 2019. Integrated model for renewable energy planning in Turkey. International Journal of Green Energy 16 (1):34–48. doi:10.1080/15435075.2018.1531872.
   Web of Science ®Google Scholar
• Alipour, M. H. 2015. Risk-informed decision making framework for operating a multi-purpose hydropower reservoir during flooding and high inflow events, case study: cheakamus river system. Water Resources Management 29 (3):801–15. doi:10.1007/s11269-014-0844-3.
   Web of Science ®Google Scholar
• Begić, F., and N. H. Afgan. 2007. Sustainability assessment tool for the decision making in selection of energy system-Bosnian case. Energy 32 (10):1979–85. doi:10.1016/j.energy.2007.02.006.
   Web of Science ®Google Scholar
• Bian, Y., M. Hu, Y. Wang, and H. Xu. 2016. Energy efficiency analysis of the economic system in China during 1986–2012: A parallel slacks-based measure approach. Renewable and Sustainable Energy Reviews 55:990–98. doi:10.1016/j.rser.2015.11.008.
   Web of Science ®Google Scholar
• Branker, K., M. J. M. Pathak, and J. M. Pearce. 2011. A review of solar photovoltaic levelized cost of electricity. Renewable and Sustainable Energy Reviews 15 (9):4470–82. doi:10.1016/j.rser.2011.07.104.
   Web of Science ®Google Scholar
• Brown, P. H., D. Tullos, B. Tilt, D. Magee, and A. T. Wolf. 2009. Modeling the costs and benefits of dam construction from a multidisciplinary perspective. Journal of Environmental Management 90:S303–S311. doi:10.1016/j.jenvman.2008.07.025.
   PubMed Web of Science ®Google Scholar
• Buckland, J., and M. O’Gorman. 2017. The Keeyask hydro dam plan in northern Canada: A model for inclusive indigenous development? Canadian Journal of Development Studies 38 (1):72–90. doi:10.1080/02255189.2016.1224969.
   Web of Science ®Google Scholar
• Cayir Ervural, B., S. Zaim, O. F. Demirel, Z. Aydin, and D. Delen. 2018. An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renewable and Sustainable Energy Reviews 82:1538–50. doi:10.1016/j.rser.2017.06.095.
   Web of Science ®Google Scholar
• Chatterjee, K., D. Pamucar, and E. K. Zavadskas. 2018. Evaluating the performance of suppliers based on using the R’AMATEL-MAIRCA method for green supply chain implementation in electronics industry. Journal of Cleaner Production 184:101–29. doi:10.1016/j.jclepro.2018.02.186.
   Web of Science ®Google Scholar
• Chatzimouratidis, A. I., and P. A. Pilavachi. 2009. Technological, economic and sustainability evaluation of power plants using the analytic hierarchy process. Energy Policy 37 (3):778–87. doi:10.1016/j.enpol.2008.10.009.
   Web of Science ®Google Scholar
• Chen, W., Y. Fan, and Y. Lv. 2011. On ecological flow influence of hydroelectric cascade development and compensating measures. In 2011 Second International Conference on Mechanic Automation and Control Engineering, 6650–53. Inner Mongolia, China. IEEE. doi:10.1109/MACE.2011.5988570.
   Google Scholar
• de Almeida, A. T., P. S. Moura, A. S. Marques, and J. L. de Almeida. 2005. Multi-impact evaluation of new medium and large hydropower plants in Portugal centre region. Renewable and Sustainable Energy Reviews 9 (2):149–67. doi:10.1016/j.rser.2004.01.015.
   Web of Science ®Google Scholar
• Dincer, H., and S. Yuksel. 2019. Balanced scorecard-based analysis of investment decisions for the renewable energy alternatives: A comparative analysis based on the hybrid fuzzy decision-making approach. Energy 175:1259–70. doi:10.1016/j.energy.2019.03.143.
   Web of Science ®Google Scholar
• Ehteram, M., H. Karami, and S. Farzin. 2018. Reservoir optimization for energy production using a new evolutionary algorithm based on Multi-Criteria Decision-Making models. Water Resources Management 32 (7):2539–60. doi:10.1007/s11269-018-1945-1.
   Web of Science ®Google Scholar
• Evans, A., and V. Strezov. 2010. A sustainability assessment of electricity generation. In 2010 International Conference on Biosciences, 106–11. Cancun, Mexico. IEEE. doi:10.1109/BioSciencesWorld.2010.29.
   Google Scholar
• Fu, Y., Q. Zhang, and C. Wang. 2008. Assessing the sustainability of cascade hydropower development based on complex ecology system. In 2008 2nd International Conference on Bioinformatics and Biomedical Engineering, 4282–85. Shanghai, China . IEEE. doi:10.1109/ICBBE.2008.570.
   Google Scholar
• Genoud, S., and J.-B. Lesourd. 2009. Characterization of sustainable development indicators for various power generation technologies. International Journal of Green Energy 6 (3):257–67. doi:10.1080/15435070902880943.
   Web of Science ®Google Scholar
• Goumas, M., and V. Lygerou. 2000. An extension of the PROMETHEE method for decision making in fuzzy environment: ranking of alternative energy exploitation projects. European Journal of Operational Research 123 (3):606–13. doi:10.1016/S0377-2217(99)00093-4.
   Web of Science ®Google Scholar
• Guan, H., J. He, S. Guan, and A. Zhao. 2019. Neutrosophic soft sets forecasting model for multi-attribute time series. IEEE Access 7:25575–88. doi:10.1109/ACCESS.2019.2897719.
   Web of Science ®Google Scholar
• IHA. 2018a. Hydropower sustainability assessment protocol. in international hydropower association, 56.
   Google Scholar
• IHA. 2018b. Hydropower sustainability environmental, social and governance(ESG) gap analysis tool reference version. In International Hydropower Association.
   Google Scholar
• IHA. 2018c. Hydropower sustainability guidelines on good international industry practice. in international hydropower association.
   Google Scholar
• IHA. 2020. Hydropower Status Report 2020. International Hydropower Association.
   Google Scholar
• Jadoon, T. R., M. K. Ali, S. Hussain, A. Wasim, and M. Jahanzaib. 2020. Sustaining power production in hydropower stations of developing countries. Sustainable Energy Technologies and Assessments 37 (2020):100637. doi:10.1016/j.seta.2020.100637.
   Google Scholar
• Jha, D. K., and R. Shrestha. 2006. Measuring efficiency of hydropower plants in Nepal using data envelopment analysis. IEEE Transactions on Power Systems 21 (4):1502–11. doi:10.1109/TPWRS.2006.881152.
   Web of Science ®Google Scholar
• Ji, Y., G. H. Huang, and W. Sun. 2015. Risk assessment of hydropower stations through an integrated fuzzy entropy-weight multiple criteria decision making method: A case study of the Xiangxi River. Expert Systems with Applications 42 (12):5380–89. doi:10.1016/j.eswa.2014.12.026.
   Web of Science ®Google Scholar
• Kentel, E., and E. Alp. 2013. Hydropower in Turkey: economical, social and environmental aspects and legal challenges. Environmental Science & Policy 31:34–43. doi:10.1016/j.envsci.2013.02.008.
   Web of Science ®Google Scholar
• Kliestik, T., E. Nica, H. Musa, M. Poliak, and E.-A. Mihai. 2020. Networked, smart, and responsive devices in industry 4.0 manufacturing systems. in economics, management, and financial markets. ed.. J. T. Queenan, J. C. Hobbins, and C. Y. Spong. Vol. 15. 3. Oxford, UK: Wiley-Blackwell:23. doi: 10.22381/EMFM15320203.
   Google Scholar
• Kumar, A., B. Sah, A. R. Singh, Y. Deng, X. He, P. Kumar, and R. C. Bansal. 2017. A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews 69 (2017):596–609. doi:10.1016/j.rser.2016.11.191.
   Google Scholar
• Lee, H., and C. Chang. 2018. Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and Sustainable Energy Reviews 92 (2018):883–96. doi:10.1016/j.rser.2018.05.007.
   Google Scholar
• Li, R., Z. Jiang, C. Ji, A. Li, and S. Yu. 2018. An improved risk-benefit collaborative grey target decision model and its application in the decision making of load adjustment schemes. Energy 156:387–400. doi:10.1016/j.energy.2018.05.119.
   Web of Science ®Google Scholar
• Li, X., F. Gui, and Q. Li. 2019. Can hydropower still be considered a clean energy source? compelling evidence from a middle-sized hydropower station in China. Sustainability (Switzerland) 11:16. doi:10.3390/su11164261.
   Web of Science ®Google Scholar
• LIHI. 2018. Low impact hydropower certification handbook. in low impact hydropower institute.
   Google Scholar
• Liu, B., X. Chen, X. Wang, and Y. Chen. 2014. Development potential of Chinese construction industry in the new century based on regional difference and spatial convergence analysis. KSCE Journal of Civil Engineering 18 (1):11–18. doi:10.1007/s12205-014-0099-9.
   Web of Science ®Google Scholar
• Mardoyan, A., and P. Braun. 2015. Analysis of czech subsidies for solid biofuels. International Journal of Green Energy 12 (4):405–08. doi:10.1080/15435075.2013.841163.
   Web of Science ®Google Scholar
• Maroušek, J. 2015. Economic analysis of the pressure shockwave disintegration process. International Journal of Green Energy 12 (12):1232–35. doi:10.1080/15435075.2014.895740.
   Web of Science ®Google Scholar
• Maroušek, J., O. Strunecký, L. Kolář, M. Vochozka, M. Kopecký, A. Maroušková, J. Batt, M. Poliak, M. Šoch, P. Bartoš, et al. 2020. Advances in nutrient management make it possible to accelerate biogas production and thus improve the economy of food waste processing. Energy sources, part A: recovery, utilization, and environmental effects. 1–10 10.1080/15567036.2020.1776796
   Google Scholar
• Matsumoto, K., K. Morita, D. Mavrakis, and P. Konidari. 2017. Evaluating Japanese policy instruments for the promotion of renewable energy sources. International Journal of Green Energy 14 (8):724–36. doi:10.1080/15435075.2017.1326050.
   Web of Science ®Google Scholar
• McCully, P. 1996. Silienced rivers: the ecology and politics of large dams. In Zed books.
   Google Scholar
• McManamay, R. A., E. S. Parish, C. R. DeRolph, A. M. Witt, W. L. Graf, and A. Burtner. 2020. Evidence-based indicator approach to guide preliminary environmental impact assessments of hydropower development. Journal of Environmental Management 265 (2020):110489. doi:10.1016/j.jenvman.2020.110489.
   PubMedGoogle Scholar
• Mulongo, N. Y., and P. Kholopane. 2018. An economic competitiveness analysis of power generation plants. In 2018 5th International Conference on Industrial Engineering and Applications (ICIEA), 543–47. Singapore. IEEE. doi:10.1109/IEA.2018.8387160.
   Google Scholar
• Muradian, R. 2001. Ecological thresholds: A survey. Ecological Economics 38 (1):7–24. doi:10.1016/S0921-8009(01)00146-X.
   Web of Science ®Google Scholar
• Niezen, R. 2003. The origins of indigenism: human rights and the politics of identity. In Burkeley: University of California Press.
   Google Scholar
• Purvis, B., Y. Mao, and D. Robinson. 2019. Three pillars of sustainability: In search of conceptual origins. Sustainability Science 14(3):681–95. Springer Japan. doi:10.1007/s11625-018-0627-5.
   Web of Science ®Google Scholar
• Roozbahani, A., H. Ghased, and M. Hashemy Shahedany. 2020. Inter-basin water transfer planning with grey COPRAS and fuzzy COPRAS techniques: A case study in Iranian Central Plateau. Science of the Total Environment 726:138499. doi:10.1016/j.scitotenv.2020.138499.
   PubMed Web of Science ®Google Scholar
• Roy, B. 1996. Multicriteria methodology for decision aiding. Dordrecht, Netherlands. In Kluwer Academic Publishers.
   Google Scholar
• Roy, K., A. K. Gain, B. Mallick, and J. Vogt. 2017. Social, hydro-ecological and climatic change in the southwest coastal region of Bangladesh. Regional Environmental Change 17 (7):1895–906. doi:10.1007/s10113-017-1158-9.
   Web of Science ®Google Scholar
• Santoyo-Castelazo, E., and A. Azapagic. 2014. Sustainability assessment of energy systems: integrating environmental, economic and social aspects. Journal of Cleaner Production 80 (2014):119–38. doi:10.1016/j.jclepro.2014.05.061.
   Google Scholar
• Sharma, D., R. Vaish, and S. Azad. 2015. Selection of India’s energy resources: A fuzzy decision making approach. Energy Systems 6 (3):439–53. doi:10.1007/s12667-015-0149-5.
   Google Scholar
• Simsek, Y., D. Watts, and R. Escobar. 2018. Sustainability evaluation of concentrated solar power (CSP) projects under clean development mechanism (CDM) by using multi criteria decision method (MCDM). Renewable and Sustainable Energy Reviews 93:421–38. doi:10.1016/j.rser.2018.04.090.
   Web of Science ®Google Scholar
• Singh, R. K., H. R. Murty, S. K. Gupta, and A. K. Dikshit. 2012. An overview of sustainability assessment methodologies. Ecological Indicators 15 (1):281–99. doi:10.1016/j.ecolind.2011.01.007.
   Web of Science ®Google Scholar
• Sitorus, F., and P. R. Brito-Parada. 2020. A multiple criteria decision making method to weight the sustainability criteria of renewable energy technologies under uncertainty. Renewable and Sustainable Energy Reviews 127 (2019):109891. doi:10.1016/j.rser.2020.109891.
   Google Scholar
• Solangi, Y. A., Q. Tan, N. H. Mirjat, G. Das Valasai, M. W. A. Khan, and M. Ikram. 2019. An integrated Delphi-AHP and fuzzy TOPSIS approach toward ranking and selection of renewable energy resources in Pakistan. Processes 7 (2):1–31. doi:10.3390/pr7020118.
   Web of Science ®Google Scholar
• Song, X., J. Xu, C. Shen, F. Peña-Mora, and Z. Zeng. 2017. A decision making system for construction temporary facilities layout planning in large-scale construction projects. International Journal of Civil Engineering 15 (2):333–53. doi:10.1007/s40999-016-0107-1.
   Web of Science ®Google Scholar
• Stein, E. W. 2013. A comprehensive multi-criteria model to rank electric energy production technologies. Renewable and Sustainable Energy Reviews 22:640–54. doi:10.1016/j.rser.2013.02.001.
   Web of Science ®Google Scholar
• Supriyasilp, T., K. Pongput, and T. Boonyasirikul. 2009. Hydropower development priority using MCDM method. Energy Policy 37 (5):1866–75. doi:10.1016/j.enpol.2009.01.023.
   Web of Science ®Google Scholar
• Tan, S. T., W. S. Ho, H. Hashim, and C. T. Lee. 2014. A feasibility study of renewable energy and carbon emission reduction in Iskandar Malaysia.  Pattaya, Chonburi, Thailand. In Proceedings of the 2014 International Conference and utility exhibition on green energy for sustainable development, Vol. 2014, 19–21. ICUE.
   Google Scholar
• Tegou, L.-I., H. Polatidis, and D. A. Haralambopoulos. 2012. A multi-criteria framework for an isolated electricity system design with renewable energy sources in the context of distributed generation: the case study of Lesvos Island, Greece. International Journal of Green Energy 9 (3):256–79. doi:10.1080/15435075.2011.621484.
   Web of Science ®Google Scholar
• Tian, G., H. Zhang, Y. Feng, D. Wang, Y. Peng, and H. Jia. 2018. Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method. Renewable and Sustainable Energy Reviews 81 (2018):682–92. doi:10.1016/j.rser.2017.08.050.
   Google Scholar
• U.S. Energy Information Adiministration. 2020. Levelized cost and levelized avoided cost of new generation resources in the annual energy outlook 2020. In Us Eia Lcoe.
   Google Scholar
• Väisänen, S., M. Mikkilä, J. Havukainen, L. Sokka, M. Luoranen, and M. Horttanainen. 2016. Using a multi-method approach for decision-making about a sustainable local distributed energy system: A case study from Finland. Journal of Cleaner Production 137:1330–38. doi:10.1016/j.jclepro.2016.07.173.
   Web of Science ®Google Scholar
• Wang, B., I. Nistor, T. Murty, and Y. M. Wei. 2014. Efficiency assessment of hydroelectric power plants in Canada: A multi criteria decision making approach. Energy Economics 46:112–21. doi:10.1016/j.eneco.2014.09.001.
   Web of Science ®Google Scholar
• Wang, J., Y. Jing, C. Zhang, and J. Zhao. 2009. Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Reviews 13 (9):2263–78. doi:10.1016/j.rser.2009.06.021.
   Web of Science ®Google Scholar
• WCD. 2000. Dams and development: A new framework for decision-making. In Earthscan Publications Ltd.
   Google Scholar
• Weisser, D. 2007. A guide to life-cycle greenhouse gas (GHG) emissions from electric supply technologies. Energy 32 (9):1543–59. doi:10.1016/j.energy.2007.01.008.
   Web of Science ®Google Scholar
• Xu, Z. 2009. Multi-period multi-attribute group decision-making under linguistic assessments. International Journal of General Systems 38 (8):823–50. doi:10.1080/03081070903257920.
   Web of Science ®Google Scholar
• Yang, Z., K. Yang, L. Su, and H. Hu. 2018. The improved binary-real coded shuffled frog leaping algorithm for solving short-term hydropower generation scheduling problem in large hydropower station. Mathematical Problems in Engineering 2018:1–29. doi:10.1155/2018/3726274.
   Web of Science ®Google Scholar
• Zhao, W., W. Guo, L. Zhao, Q. Li, X. Cao, and X. Tang. 2019. Influence of different types of small hydropower stations on macroinvertebrate communities in the changjiang river basin, China. Water 11 (9):1892. doi:10.3390/w11091892.
   Web of Science ®Google Scholar