Comprehensive Risk Analysis and Decision-Making Model for Hydroelectricity Energy Investments
DOI:
https://doi.org/10.31181/jscda21202421Keywords:
Hydroelectricity energy, Clean energy investment, Decision-making models, Spherical fuzzy setsAbstract
The risks of hydroelectricity energy investments should be managed effectively to increase the performance of these projects. Thus, more significant risks should be identified to take effective measures for risk management without experiencing high costs. Accordingly, the purpose of this study is to define critical risks in hydroelectricity energy investment projects by making a priority analysis. Within this scope, a new decision-making model is created. In the first stage, five different risks are examined by considering Spherical fuzzy Entropy. Moreover, the second stage consists of ranking emerging seven countries with the help of Spherical fuzzy multi-attribute ideal-real comparative assessment (MAIRCA). The main contribution of this study is that more important risks of hydroelectricity energy investments can be identified by the help of the priority analysis. This situation provides an opportunity to implement effective strategies to increase these investments without having high costs. Additionally, considering Spherical fuzzy sets has a positive impact on the appropriateness of the results. Since these numbers use a wider data range, the effectiveness of the analysis results can increase. It is determined that the most important risk is environmental risk with the highest weight value of 0.2478. Financial risks and personnel risks are other significant factors that affect the performance of the hydroelectricity energy investments. Furthermore, as a result of ranking the alternatives, it is seen that China is the most suitable country for hydroelectric energy investments. India and Mexico are other successful countries in this respect. However, Turkey and Indonesia have lower performance for this situation.
References
Onu, U. G., Silva, G. S., de Souza, A. C. Z., Bonatto, B. D., & da Costa, V. B. F. (2022). Integrated design of photovoltaic power generation plant with pumped hydro storage system and irrigation facility at the Uhuelem-Amoncha African community. Renewable Energy, 198, 1021-1031. https://doi.org/10.1016/j.renene.2022.08.059
Alnaqbi, S. A., Alasad, S., Aljaghoub, H., Alami, A. H., Abdelkareem, M. A., & Olabi, A. G. (2022). Applicability of hydropower generation and pumped hydro energy storage in the Middle East and North Africa. Energies, 15(7), 2412. https://doi.org/10.3390/en15072412
Alshammari, M. (2022, July). Hydroelectric Energy: Challenges, Solutions and Future Trends. In 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) (pp. 1-6). IEEE. https://doi.org/10.1109/ICECET55527.2022.9873025
Rahman, A., Farrok, O., & Haque, M. M. (2022). Environmental impact of renewable energy source based electrical power plants: Solar, wind, hydroelectric, biomass, geothermal, tidal, ocean, and osmotic. Renewable and Sustainable Energy Reviews, 161, 112279. https://doi.org/10.1016/j.rser.2022.112279
Özbay, R. D., Athari, S. A., Saliba, C., & Kirikkaleli, D. (2022). Towards environmental sustainability in China: role of globalization and hydroelectricity consumption. Sustainability, 14(7), 4182. https://doi.org/10.3390/su14074182
Bayazıt, Y. (2021). The effect of hydroelectric power plants on the carbon emission: An example of Gokcekaya dam, Turkey. Renewable Energy, 170, 181-187. https://doi.org/10.1016/j.renene.2021.01.130
Okang, Q. A., Bakken, T. H., & Bor, A. (2023). Investigation of the Hydroelectric Development Potential of Nonpowered Dams: A Case Study of the Buyuk Menderes River Basin. Water, 15(4), 717. https://doi.org/10.3390/w15040717
Li, Y., & Liu, Y. (2022). Numerical study on the impacts of layered heterogeneity on the underground process in compressed air energy storage in aquifers. Journal of Energy Storage, 46, 103837. https://doi.org/10.1016/j.est.2021.103837
Guo, L. N., She, C., Kong, D. B., Yan, S. L., Xu, Y. P., Khayatnezhad, M., & Gholinia, F. (2021). Prediction of the effects of climate change on hydroelectric generation, electricity demand, and emissions of greenhouse gases under climatic scenarios and optimized ANN model. Energy Reports, 7, 5431-5445. https://doi.org/10.1016/j.egyr.2021.08.134
Ma, Y., Zhang, T., Qian, W., & Wei, D. (2022). Financial development, demographic changes, and the growth of the non-hydro renewable energy industry—an empirical test based on R&D and financing costs. Renewable Energy, 185, 217-229. https://doi.org/10.1016/j.renene.2021.12.059
Hashemizadeh, A., Ju, Y., Bamakan, S. M. H., & Le, H. P. (2021). Renewable energy investment risk assessment in belt and road initiative countries under uncertainty conditions. Energy, 214, 118923. https://doi.org/10.1016/j.energy.2020.118923
Bai, X. (2021, May). The Analysis of a Model for Assessing Investment Risks of Overseas Clean Energy Projects. In 2021 International Conference on Control Science and Electric Power Systems (CSEPS) (pp. 142-147). IEEE. https://doi.org/10.1109/CSEPS53726.2021.00035
Abba, Z. Y. I., Balta-Ozkan, N., & Hart, P. (2022). A holistic risk management framework for renewable energy investments. Renewable and Sustainable Energy Reviews, 160, 112305. https://doi.org/10.1016/j.rser.2022.112305
Karamoozian, A., Wu, D., Lambert, J. H., & Luo, C. (2022). Risk assessment of renewable energy projects using uncertain information. International Journal of Energy Research, 46(13), 18079-18099. https://doi.org/10.1002/er.8428
Zai, W., He, Y., & Wang, H. (2023). Risk Prediction Method for Renewable Energy Investments Abroad Based on Cloud-DBN. Sustainability, 15(14), 11297. https://doi.org/10.3390/su151411297
Ünlü, U., Yıldırım, F., Kuloğlu, A., Ersoy, E., & Çetenak, E. H. (2022). Nexus between Renewable Energy, Credit Gap Risk, Financial Development and R&D Expenditure: Panel ARDL Approach. Sustainability, 14(23), 16232. https://doi.org/10.3390/su142316232
Mensah, J. H. R., dos Santos, I. F. S., Raimundo, D. R., de Oliveira Botan, M. C. C., Barros, R. M., & Tiago Filho, G. L. (2022). Energy and economic study of using Pumped Hydropower Storage with renewable resources to recover the Furnas reservoir. Renewable Energy, 199, 320-334. https://doi.org/10.1016/j.renene.2022.09.003
Eze, F., Ogola, J., Kivindu, R., Egbo, M., & Obi, C. (2022). Technical and economic feasibility assessment of hybrid renewable energy system at Kenyan institutional building: A case study. Sustainable Energy Technologies and Assessments, 51, 101939. https://doi.org/10.1016/j.seta.2021.101939
Zhang, Y., Yang, X., & Cui, W. (2022). Estimation of the Student Employment in the Aviation Industry Based on Novel Fractional Error Accumulation Grey Model. Journal of Mathematics, 2022. https://doi.org/10.1155/2022/7738447
İpin, S., & Ercan, T. (2021). Financing hydroelectric power plants: a review and evaluation of financing channels. International Journal of Energy Sector Management, 15(1), 58-80. https://doi.org/10.1108/IJESM-04-2020-0001
Gyanwali, K., Karki, S., Adhikari, P., Devkota, S., & Aryal, P. (2023). Techno-economic assessment of green urea production utilizing municipal solid waste and hydropower in Nepal. Journal of Cleaner Production, 419, 138320. https://doi.org/10.1016/j.jclepro.2023.138320
Li, H., Xu, B., Arzaghi, E., Abbassi, R., Chen, D., Aggidis, G. A., ... & Patelli, E. (2020). Transient safety assessment and risk mitigation of a hydroelectric generation system. Energy, 196, 117135. https://doi.org/10.1016/j.energy.2020.117135
Lauro, A., Kitamura, D., Lima, W., Dias, B., & Soares, T. (2023). Considering Forward Electricity Prices for a Hydro Power Plant Risk Analysis in the Brazilian Electricity Market. Energies, 16(3), 1173. https://doi.org/10.3390/en16031173
Martins, A. C., Pereira, M. D. C., & Pasqualino, R. (2023). Renewable Electricity Transition: A Case for Evaluating Infrastructure Investments through Real Options Analysis in Brazil. Sustainability, 15(13), 10495. https://doi.org/10.3390/su151310495
Liu, Y., & Feng, C. (2023). Promoting renewable energy through national energy legislation. Energy Economics, 118, 106504. https://doi.org/10.1016/j.eneco.2023.106504
Lazaro, L. L. B., Soares, R. S., Bermann, C., Collaço, F. M. D. A., Giatti, L. L., & Abram, S. (2022). Energy transition in Brazil: Is there a role for multilevel governance in a centralized energy regime?. Energy Research & Social Science, 85, 102404. https://doi.org/10.1016/j.erss.2021.102404
Sokulski, C. C., Barros, M. V., Salvador, R., Broday, E. E., & de Francisco, A. C. (2022). Trends in renewable electricity generation in the G20 countries: An analysis of the 1990–2020 period. Sustainability, 14(4), 2084. https://doi.org/10.3390/su14042084
Wojewnik-Filipkowska, A., Filipkowski, P., & Frąckowiak, O. (2023). Analysis of Investments in RES Based on the Example of Photovoltaic Panels in Conditions of Uncertainty and Risk—A Case Study. Energies, 16(7), 3006. https://doi.org/10.3390/en16073006
Cheng, L., & Zhou, H. (2023). Investment obstacles of main countries situated along the 21st century Maritime Silk Road–a perspective of risk assessment. Maritime Policy & Management, 1-16. https://doi.org/10.1080/03088839.2023.2224804
Wuni, I. Y., Bao, Z., Yevu, S. K., & Tetteh, M. O. (2023). Theorizing the path dependencies and hierarchical structure of the multidimensional risks in green building projects. Journal of Building Engineering, 106069. https://doi.org/10.1016/j.jobe.2023.106069
Słotwiński, S. (2022). The Significance of the “Power Purchase Agreement” for the Development of Local Energy Markets in the Theoretical Perspective of Polish Legal Conditions. Energies, 15(18), 6691. https://doi.org/10.3390/en15186691
Zoričić, D., Knežević, G., Miletić, M., Dolinar, D., & Sprčić, D. M. (2022). Integrated Risk Analysis of Aggregators: Policy Implications for the Development of the Competitive Aggregator Industry. Energies, 15(14), 5076. https://doi.org/10.3390/en15145076
Ma, Q. X., Zhu, X. M., Bai, K. Y., Zhang, R. T., & Liu, D. W. (2023). A novel failure mode and effect analysis method with spherical fuzzy entropy and spherical fuzzy weight correlation coefficient. Engineering Applications of Artificial Intelligence, 122, 106163. https://doi.org/10.1016/j.engappai.2023.106163
Erdoğan, M. (2022). Assessing farmers' perception to Agriculture 4.0 technologies: A new interval‐valued spherical fuzzy sets based approach. International Journal of Intelligent Systems, 37(2), 1751-1801. https://doi.org/10.1002/int.22756
Adebayo, T. S., Kartal, M. T., & Ullah, S. (2023). Role of hydroelectricity and natural gas consumption on environmental sustainability in the United States: evidence from novel time-frequency approaches. Journal of environmental management, 328, 116987. https://doi.org/10.1016/j.jenvman.2022.116987
Cribari-Neto, F., Scher, V. T., & Bayer, F. M. (2023). Beta autoregressive moving average model selection with application to modeling and forecasting stored hydroelectric energy. International Journal of Forecasting, 39(1), 98-109. https://doi.org/10.1016/j.ijforecast.2021.09.004
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