Uncertainties-Based Potential Time and Cost Overrun Assessment While Planning a Hydropower Project
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 4
Abstract
Uncertainties are predominant in hydropower development that lead to risks of time and cost overruns. The overruns’ assessment requires quantitative data that is difficult to obtain and sometimes partially or completely unavailable. Accordingly, this study proposes an expert fuzzy-based system for assessing the impact of uncertainties on time and cost overrun. A Bayesian network analysis is used wherein the experts’ opinions are incorporated through an analytic hierarchy process for the uncertainty’s likelihood and impact. A fuzzy inference system is used to incorporate the decision maker’s optimistic and pessimistic approaches. The proposed methodology is illustrated through a run-of-river Myntdu Leshka Hydroelectric project in India. The project’s initial likely completion time was five years with a cost of ₹3,630 million at the 1999 price level. The results state that the project’s time and cost overruns lie between 158% and 196% and between 235% and 276%, respectively, under optimistic and pessimistic conditions. Such a methodology has not been applied by past studies for hydropower projects, which is the study’s main contribution. The methodology can be easily applied by construction project developers globally in different fields by varying the uncertainties, their likelihood, and impact scales as per different risk perceptions and regional conditions.
Practical Applications
The methodology shown in the current study can be applied by hydropower and other construction project developers globally. The likelihood and impact scales, fuzzy optimistic and pessimistic rule base, and number and type of uncertainties can be changed easily based on the developers’ perceptions. In the case of hydropower projects, this method should be applied once the detailed project report (DPR) is prepared and prior to its submission to the approval authority.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
The experts’ opinions on the uncertainty likelihood and impact that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors are thankful to the Ministry of Human Resources Development (MHRD), GoI, for providing a scholarship to the second author during his Ph.D. program.
References
Agarwal, S. S. 2021. “Hydropower development under uncertainties and operational performance assessment.” Ph.D. thesis, Water Resources Development and Management, Indian Institute of Technology Roorkee.
Agarwal, S. S., and M. L. Kansal. 2017. “Issues of hydropower development in Uttarakhand region of Indian Himalaya.” Water Energy Int. Water Resour. Sect. 59 (11): 52–64.
Agarwal, S. S., and M. L. Kansal. 2018. “Importance of hydropower for energy sustenance in India.” Water Energy Int. Water Resour. Sect. 61 (2): 61–73.
Agarwal, S. S., and M. L. Kansal. 2020. “Risk based initial cost assessment while planning a hydropower project.” Energy Strategy Rev. 31 (Sep): 100517. https://doi.org/10.1016/j.esr.2020.100517.
Ahmadi, M., K. Behzadian, A. Ardeshir, and Z. Kapelan. 2016. “Comprehensive risk management using fuzzy FMEA and MCDA techniques in highway construction projects.” J. Civ. Eng. Manage. 23 (2): 300–310. https://doi.org/10.3846/13923730.2015.1068847.
Aladağ, H., and Z. Işık. 2019. “Design and construction risks in BOT type mega transportation projects.” Eng. Constr. Archit. Manage. 26 (10): 2223–2242. https://doi.org/10.1108/ECAM-08-2018-0351.
Banaitiene, N., and A. Banaitis. 2012. “Risk management in construction projects.” In Risk management—Current issues and challenges, edited by N. Banaitiene. London: InTech. https://doi.org/10.5772/51460.
Beltrão, L. M. P., and M. T. M. Carvalho. 2019. “Prioritizing construction risks using fuzzy AHP in Brazilian public enterprises.” J. Constr. Eng. Manage. 145 (2): 05018018. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001606.
Bobbio, A., L. Portinale, M. Minichino, and E. Ciancamerla. 2001. “Improving the analysis of dependable systems by mapping fault trees into Bayesian networks.” Reliab. Eng. Syst. Saf. 71 (3): 249–260. https://doi.org/10.1016/S0951-8320(00)00077-6.
CEA (Central Electricity Authority). 2004a. “Best practices in planning and appraisal of hydro electric projects.” In Best practices and bench marks in hydropower generation, 20–58. New Delhi, India: Central Electricity Authority.
CEA (Central Electricity Authority). 2004b. “Best practices on survey and investigations of hydro electric projects.” In Best practices and bench marks in hydropower generation, 5–19. New Delhi, India: Central Electricity Authority.
CEA (Central Electricity Authority). 2015. Guidelines for formulation of detailed project reports for hydro electric schemes, their acceptance and examination for concurrence. New Delhi, India: Central Electricity Authority.
CEA (Central Electricity Authority). 2020. “Executive summary, power sector, December.” Accessed January 18, 2021. https://cea.nic.in/old/reports/monthly/executivesummary/2020/exe_summary-12.pdf.
CEA: HPMD (Central Electricity Authority: Hydro Project Monitoring Division). 2020. “Progress of on-going hydro electric projects, quarterly review no. 100, January–March 2020.”Accessed January 18, 2021.
CEA: HPPID (Central Electricity Authority: Hydro Project Planning and Investigation Division). 2019. “Review of performance of hydro power stations 2018-19.” Accessed January 18, 2021. http://cea.nic.in/reports/annual/hydroreview/hydro_review-2018.pdf.
Ćerić, A. 2003. A framework for process-driven risk management in construction projects. Salford, UK: Univ. of Salford.
Chapman, R. J. 1998. “The effectiveness of working group risk identification and assessment techniques.” Int. J. Project Manage. 16 (6): 333–343. https://doi.org/10.1016/S0263-7863(98)00015-5.
Chen, T.-T., and C.-H. Wang. 2015. “Fall risk assessment of bridge construction using bayesian network transferring from fault tree analysis.” J. Civ. Eng. Manage. 23 (2): 273–282. https://doi.org/10.3846/13923730.2015.1068841.
Chin, K. S., D. W. Tang, J. B. Yang, S. Y. Wong, and H. Wang. 2009. “Assessing new product development project risk by Bayesian network with a systematic probability generation methodology.” Expert Syst. Appl. 36 (6): 9879–9890. https://doi.org/10.1016/j.eswa.2009.02.019.
Dey, P. K. 2010. “Managing project risk using combined analytic hierarchy process and risk map.” Appl. Soft Comput. 10 (4): 990–1000. https://doi.org/10.1016/j.asoc.2010.03.010.
Enshassi, M. S. A., S. Walbridge, J. S. West, and C. T. Haas. 2020. “Dynamic and proactive risk-based methodology for managing excessive geometric variability issues in modular construction projects using Bayesian theory.” J. Constr. Eng. Manage. 146 (2): 04019096. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001747.
Hussain, A., G. K. Sarangi, A. Pandit, S. Ishaq, N. Mamnun, B. Ahmad, and M. K. Jamil. 2019. “Hydropower development in the Hindu Kush Himalayan region: Issues, policies and opportunities.” Renewable Sustainable Energy Rev. 107 (Jun): 446–461. https://doi.org/10.1016/j.rser.2019.03.010.
Idrus, A., M. F. Nuruddin, and M. A. Rohman. 2011. “Development of project cost contingency estimation model using risk analysis and fuzzy expert system.” Expert Syst. Appl. 38 (3): 1501–1508. https://doi.org/10.1016/j.eswa.2010.07.061.
IHA (International Hydropower Association). 2020. Hydropower status report: Sector trends and insights. London: International Hydropower Association.
Kalinina, A., M. Spada, and P. Burgherr. 2018. “Application of a Bayesian hierarchical modeling for risk assessment of accidents at hydropower dams.” Saf. Sci. 110 (Dec): 164–177. https://doi.org/10.1016/j.ssci.2018.08.006.
Kim, S. Y., N. Van Tuan, and S. O. Ogunlana. 2009. “Quantifying schedule risk in construction projects using Bayesian belief networks.” Int. J. Project Manage. 27 (1): 39–50. https://doi.org/10.1016/j.ijproman.2008.03.003.
Kucukali, S. 2011. “Risk assessment of river-type hydropower plants using fuzzy logic approach.” Energy Policy 39 (10): 6683–6688. https://doi.org/10.1016/j.enpol.2011.06.067.
Kumar, D., and S. S. Katoch. 2014. “Sustainability indicators for Run of the River (RoR) hydropower projects in hydro rich regions of India.” Renewable Sustainable Energy Rev. 35 (2014): 101–108. https://doi.org/10.1016/j.rser.2014.03.048.
Lee, S. 2015. “Determination of priority weights under multiattribute decision-making situations: AHP versus fuzzy AHP.” J. Constr. Eng. Manage. 141 (2): 05014015. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000897.
Leu, S.-S., and C.-M. Chang. 2013. “Bayesian-network-based safety risk assessment for steel construction projects.” Accid. Anal. Prev. 54 (May): 122–133. https://doi.org/10.1016/j.aap.2013.02.019.
Mayeda, A. M., and A. D. Boyd. 2020. “Factors influencing public perceptions of hydropower projects: A systematic literature review.” Renewable Sustainable Energy Rev. 121 (Mar): 109713. https://doi.org/10.1016/j.rser.2020.109713.
Mhatre, T. N., J. J. Thakkar, and J. Maiti. 2017. “Modelling critical risk factors for Indian construction project using interpretive ranking process (IRP) and system dynamics (SD).” Int. J. Qual. Reliab. Manage. 34 (9): 1451–1473. https://doi.org/10.1108/IJQRM-09-2015-0140.
Mustafa, M. A., and J. F. Al-Bahar. 1991. “Project risk assessment using the analytic hierarchy process.” IEEE Trans. Eng. Manage. 38 (1): 46–52. https://doi.org/10.1109/17.65759.
Namazian, A., and S. Haji Yakhchali. 2018. “Modified Bayesian network–based risk analysis of construction projects: Case study of South Pars gas field development projects.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 4 (4): 05018003. https://doi.org/10.1061/AJRUA6.0000997.
Narayanan, S., A. Madhav Kure, and S. Palaniappan. 2019. “Study on time and cost overruns in mega infrastructure projects in India.” J. Inst. Eng. (India): Ser. A 100 (1): 139–145. https://doi.org/10.1007/s40030-018-0328-1.
Panthi, K., S. M. Ahmed, and S. O. Ogunlana. 2009. “Contingency estimation for construction projects through risk analysis.” Int. J. Constr. Educ. Res. 5 (2): 79–94. https://doi.org/10.1080/15578770902952181.
Plummer Braeckman, J., T. Disselhoff, and J. Kirchherr. 2020. “Cost and schedule overruns in large hydropower dams: An assessment of projects completed since 2000.” Int. J. Water Resour. Dev. 36 (5): 839–854. https://doi.org/10.1080/07900627.2019.1568232.
PMI (Project Management Institute). 2000. A guide to the project management body of knowledge (PMBOK guide). Newtown Square, PA: PMI.
Qazi, A., and I. Dikmen. 2019. “From risk matrices to risk networks in construction projects.” IEEE Trans. Eng. Manage. 68 (5): 1449–1460. https://doi.org/10.1109/TEM.2019.2907787.
Qazi, A., J. Quigley, A. Dickson, and K. Kirytopoulos. 2016. “Project complexity and risk management (ProCRiM): Towards modelling project complexity driven risk paths in construction projects.” Int. J. Project Manage. 34 (7): 1183–1198. https://doi.org/10.1016/j.ijproman.2016.05.008.
Razi, P. Z., M. I. Ali, and N. I. Ramli. 2019. “Overview of analytical hierarchy process decision making method for construction risk management.” IOP Conf. Ser. Earth Environ. Sci. 244 (Mar): 012034. https://doi.org/10.1088/1755-1315/244/1/012034.
Ribas, J. R., M. Elena Arce, F. Augusto Sohler, and A. Suárez-García. 2019. “Multi-criteria risk assessment: Case study of a large hydroelectric project.” J. Cleaner Prod. 227 (Aug): 237–247. https://doi.org/10.1016/j.jclepro.2019.04.043.
Saaty, R. W. 1987. “The analytic hierarchy process—What it is and how it is used.” Math. Modell. 9 (3–5): 161–176. https://doi.org/10.1016/0270-0255(87)90473-8.
Shih, H.-S., H.-J. Shyur, and E. Stanley Lee. 2007. “An extension of TOPSIS for group decision making.” Math. Comput. Modell. 45 (7–8): 801–813. https://doi.org/10.1016/j.mcm.2006.03.023.
Sivakumar, N., D. Das, N. P. Padhy, A. S. Kumar, and N. Bisoyi. 2013. “Status of pumped hydro-storage schemes and its future in India.” Renewable Sustainable Energy Rev. 19 (Mar): 208–213. https://doi.org/10.1016/j.rser.2012.11.001.
Sousa, R. L., and H. H. Einstein. 2012. “Risk analysis during tunnel construction using Bayesian networks: Porto metro case study.” Tunnell. Underground Space Technol. 27 (1): 86–100. https://doi.org/10.1016/j.tust.2011.07.003.
Sovacool, B. K., A. Gilbert, and D. Nugent. 2014. “An international comparative assessment of construction cost overruns for electricity infrastructure.” Energy Res. Social Sci. 3 (Sep): 152–160. https://doi.org/10.1016/j.erss.2014.07.016.
Tabish, S. Z. S., and K. Neeraj Jha. 2012. “Success traits for a construction project.” J. Constr. Eng. Manage. 138 (10): 1131–1138. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000538.
Tah, J. H. M., and V. Carr. 2000. “A proposal for construction project risk assessment using fuzzy logic.” Construct. Manage. Econ. 18 (4): 491–500. https://doi.org/10.1080/01446190050024905.
Taylan, O., A. O. Bafail, R. M. S. Abdulaal, and M. R. Kabli. 2014. “Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies.” Appl. Soft Comput. 17 (Apr): 105–116. https://doi.org/10.1016/j.asoc.2014.01.003.
WRDM (Water Resources Development and Management). 2015. “Cost verification of Myntdu Leshka H. E. Project (3X42 MW) (Meghalaya Energy Corporation Limited).” Accessed January 18, 2021. http://meecl.nic.in/tariffs/MePGCL/MePGCL_Petitions/LESHKAPETTION2.12.2016/FINALREPORTIITMePGCL22Jan2015-IITRoorkee.pdf.
Yu, Y., A. Darko, A. P. C. Chan, C. Chen, and F. Bao. 2018. “Evaluation and ranking of risk factors in transnational public–private partnerships projects: Case study based on the intuitionistic fuzzy analytic hierarchy process.” J. Infrastruct. Syst. 24 (4): 04018028. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000448.
Zayed, T., M. Amer, and J. Pan. 2008. “Assessing risk and uncertainty inherent in Chinese highway projects using AHP.” Int. J. Project Manage. 26 (4): 408–419. https://doi.org/10.1016/j.ijproman.2007.05.012.
Zeng, J., M. An, and N. J. Smith. 2007. “Application of a fuzzy based decision making methodology to construction project risk assessment.” Int. J. Project Manage. 25 (6): 589–600. https://doi.org/10.1016/j.ijproman.2007.02.006.
Zhang, S., B. Sun, L. Yan, and C. Wang. 2013. “Risk identification on hydropower project using the IAHP and extension of TOPSIS methods under interval-valued fuzzy environment.” Nat. Hazards 65 (1): 359–373. https://doi.org/10.1007/s11069-012-0367-2.
Zyoud, S. H., and D. Fuchs-Hanusch. 2017. “A bibliometric-based survey on AHP and TOPSIS techniques.” Expert Syst. Appl. 78 (Jul): 158–181. https://doi.org/10.1016/j.eswa.2017.02.016.
Information & Authors
Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8 • Issue 4 • December 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Jul 15, 2021
Accepted: Jun 11, 2022
Published online: Aug 12, 2022
Published in print: Dec 1, 2022
Discussion open until: Jan 12, 2023
ASCE Technical Topics:
- Analysis (by type)
- Artificial intelligence and machine learning
- Bayesian analysis
- Business management
- Computer programming
- Computing in civil engineering
- Construction costs
- Construction engineering
- Construction management
- Continuum mechanics
- Decision making
- Disaster risk management
- Dynamics (solid mechanics)
- Energy engineering
- Energy sources (by type)
- Engineering fundamentals
- Engineering mechanics
- Fuzzy logic
- Hydro power
- Motion (dynamics)
- Practice and Profession
- Project management
- Renewable energy
- Risk management
- Solid mechanics
- Statistical analysis (by type)
- Uncertainty principles
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Hema Vijay Sekar Bellapu, Rabindra Kumar Sinha, Sripad Ramchandra Naik, Estimation of Modulus of Deformation Using Rock Mass Rating—A Review and Validation Using 3D Numerical Modelling, Sustainability, 10.3390/su15075721, 15, 7, (5721), (2023).