Technical Papers
Jul 9, 2014

Evaluation of Stakeholder Utility Risk Caused by the Objective Functions in Multipurpose Multireservoir Systems

Publication: Journal of Irrigation and Drainage Engineering
Volume 141, Issue 2

Abstract

Optimal operation of reservoir systems is a challenging task in water resource management, involving stakeholders with different utilities. These utilities are conflicting, especially in a multireservoir system when the number of stakeholders increases compared to a single-reservoir system. A reservoir system with hydropower energy generation and supplying downstream demands is an example of these challenges. An appropriate objective framework can improve mitigation of stakeholder conflicts. This paper considers a 1-year optimal operation of a multireservoir system, with two parallel upstream reservoirs and a downstream reservoir in series. System objectives are hydropower energy generation as well as supplying downstream demands. Existing conflicts of this system are determined in single-objective reservoir operation models. The mathematical form of objective functions can limit utility risk in multiobjective problems. To overcome impacts of existing conflicts, a simulation model has been coupled with the weighting method and Nash equilibrium in multiobjective models. Results show that although the calculated objectives using the Nash equilibrium are less (worse) than the maximum (best) values of the objective function with the largest weight for the first (highest) objective priority using the weighting method, in two parallel reservoirs the values of the objective function are larger (better), about 70.83 and 54.17%, respectively, for hydropower energy generation and supplying downstream demands objectives. Moreover, these objectives calculated by the Nash equilibrium are 58.33 and 50% better, respectively, than same values by the weighting method in series reservoirs. Thus, utilities were significantly balanced and increased from the worst (minimum) utility values by the Nash equilibrium. The Nash equilibrium increases considerably the reliability value for all stakeholders at the same time.

Get full access to this article

View all available purchase options and get full access to this article.

References

Afshar, A., Shafii, M., and Bozorg Haddad, O. (2010). “Optimizing multi-reservoir operation rules: An improved HBMO approach.” J. Hydroinf., 13(1), 121–139.
Ahmadi, M., Bozorg Haddad, O., Mariño, M. A. (2014). “Extraction of flexible multi-objective real-time reservoir operation rules.” Water Resour. Manage., 28(1), 131–147.
Beygi, S., Bozorg Haddad, O., Fallah-Mehdipour, E., Mariño, M. A. (2014). “Bargaining models for optimal design of water distribution networks.” J. Water Resour. Plann. Manage., 92–99.
Bolouri-Yazdeli, Y., Bozorg Haddad, O., Fallah-Mehdipour, E., Mariño, M. A. (2014). “Evaluation of real-time operation rules in reservoir systems operation.” Water Resour. Manage., 28(3), 715–729.
Bozorg Haddad, O., Adams, B. J., and Mariño, M. A. (2008a). “Optimum rehabilitation strategy of water distribution systems using the HBMO algorithm.” J. Water Supply: Res. Technol.—AQUA, 57(5), 337–350.
Bozorg Haddad, O., Afshar, A., and Mariño, M. A. (2008b). “Design-operation of multi-hydropower reservoirs: HBMO approach.” Water Resour. Manage., 22(12), 1709–1722.
Bozorg Haddad, O., Afshar, A., and Mariño, M. A. (2008c). “Honey-bee mating optimization (HBMO) algorithm in deriving optimal operation rules for reservoirs.” J. Hydroinf., 10(3), 257–264.
Bozorg Haddad, O., Afshar, A., and Mariño, M. A. (2009). “Optimization of nonconvex water resource problems by honey-bee mating optimization (HBMO) algorithm.” Eng. Comput., 26(3), 267–280.
Bozorg Haddad, O., Afshar, A., and Mariño, M. A. (2011a). “Multireservoir optimisation in discrete and continuous domains.” Proc., Inst. Civ. Eng. Water Manage., 164(2), 57–72.
Bozorg Haddad, O., and Mariño, M. A. (2007). “Dynamic penalty function as a strategy in solving water resources combinatorial optimization problems with honey-bee optimization (HBMO) algorithm.” J. Hydroinf., 9(3), 233–250.
Bozorg Haddad, O., and Mariño, M. A. (2011). “Optimum operation of wells in coastal aquifers.” Proc., Inst. Civ. Eng. Water Manage., 164(3), 135–146.
Bozorg Haddad, O., Moradi-Jalal, M., and Mariño, M. A. (2011b). “Design-operation optimisation of run-of-river power plants.” Proc., Inst. Civ. Eng. Water Manage., 164(9), 463–475.
Cai, X., Lasdon, L., and Michelsen, A. L. (2004). “Group decision making in water resources planning using multiple objective analysis.” J. Water Resour. Plann. Manage., 4–14.
Fallah-Mehdipour, E., Bozorg Haddad, O., Beygi, S., Mariño, M. A. (2011a). “Effect of utility function curvature of Young’s bargaining method on the design of WDNs.” Water Resour. Manage., 25(9), 2197–2218.
Fallah-Mehdipour, E., Bozorg Haddad, O., Mariño, M. A. (2011b). “MOPSO algorithm and its application in multipurpose multireservoir operations.” J. Hydroinf., 13(4), 794–811.
Fallah-Mehdipour, E., Bozorg Haddad, O., Mariño, M. A. (2012). “Real-time operation of reservoir system by genetic programming.” Water Resour. Manage., 26(14), 4091–4103.
Ganji, A., Karamouz, M., and Khalili, D. (2007a). “Development of stochastic dynamic Nash game model for reservoir operation. II. The value of players’ information availability and cooperative behavior.” Adv. Water Resour., 30(1), 157–168.
Ganji, A., Khalili, D., and Karamouz, M. (2007b). “Development of stochastic dynamic Nash game model for reservoir operation. I. The symmetric stochastic model with perfect information.” Adv. Water Resour., 30(3), 528–542.
Ghajarnia, N., Bozorg Haddad, O., Mariño, M. A. (2011). “Performance of a novel hybrid algorithm in the design of water networks.” Proc., Inst. Civ. Eng. Water Manage., 164(4), 173–191.
Hakimi-Asiaber, M., Ghodypour, S. H., and Kerachian, R. (2009). “Deriving operating policies for multi-objective reservoir systems: Application of self-learning genetic algorithm.” Appl. Soft Comput., 10(5), 1151–1163.
Harsanyi, J. C. (1959). “A bargaining model for the cooperative n-person game.” Contribution to the theory of games, no 4, Princeton University Press, Princeton, NJ, 324–356.
Harsanyi, J. C. (1963). “A simplified bargaining model for the n-person game.” Int. Econ. Rev., 4(2), 194–220.
Hashimoto, T., Stedinger, J. R., and Loucks, D. P. (1982). “Reliability, resiliency, and vulnerability criteria for water resources performance evaluation.” Water Resour. Res., 18(1), 14–20.
Karamouz, M., Ahmadi, A., and Moridi, A. (2009). “Probabilistic reservoir operation using Bayesian stochastic model and support vector machine.” Adv. Water Resour., 32(11), 1588–1600.
Karimi-Hosseini, A., Bozorg Haddad, O., Mariño, M. A. (2011). “Site selection of rain gauges using entropy methodologies.” Proc., Inst. Civ. Eng. Water Manage., 164(7), 321–333.
Labadie, J. W. (2004). “Optimal operation of multireservoir systems: State-of-the-art review.” J. Water Resour. Plann. Manage., 93–111.
LINDO Systems. (2010). LINDO API 6.0 user manual, 〈http://www.lindo.com〉 (Jan. 30, 2012).
Li, Z., Xu, Q., Li, N., and Ma, Y. (2010). “Mathematical model and solving method based on software for the shortest time limited transportation problem.” Ninth Int. Symp. on Operations Research and Its Applications (ISORA’10), Chengdu-Jiuzhaigou, China, 1–8.
Madani-Larijani, K. (2009). “Climate change effects on high-elevation hydropower systems in California.” Ph.D. Dissertation, Univ. of California, Davis, CA.
Mohajery, M., and Khoshalhan, F. (2008). “Application of differential evolution for a single-item resource-constrained aggregate production planning problem.” Proc., Int. Multi Conf. of Engineers and Computer Scientists, Hong Kong.
Moradi-Jalal, M., Bozorg Haddad, O., Karney, B. W., Mariño, M. A. (2007). “Reservoir operation in assigning optimal multi-crop irrigation areas.” Agric. Water Manage., 90(1–2), 149–159.
Nash, J. F. (1953). “Two person cooperative games.” Economia, 18(2), 155–162.
Noory, H., Liaghat, A. M., Parsinejad, M., and Bozorg Haddad, O. (2012). “Optimizing irrigation water allocation and multicrop planning using discrete PSO algorithm.” J. Irrig. Drain. Eng., 437–444.
Oliveira, R., and Loucks, D. P. (1997). “Operating rules for multireservoir systems.” Water Resour. Res., 33(4), 839–852.
Rasoulzadeh-Gharibdousti, S., Bozorg Haddad, O., Mariño, M. A. (2011). “Optimal design and operation of pumping stations using NLP-GA.” Proc., Inst. Civ. Eng. Water Manage., 164(4), 163–171.
Reddy, M. J., and Kumar, D. N. (2007). “Multi-objective particle swarm optimization for generating optimal trade-offs in reservoir operation.” Hydrol. Process., 21(21), 2897–2909.
Sabbaghpour, S., Naghashzadehgan, M., Javaherdeh, K., and Bozorg Haddad, O. (2012). “HBMO algorithm for calibrating water distribution network of Langarud city.” Water Sci. Technol., 65(9), 1564–1569.
Seifollahi-Aghmiuni, S., Bozorg Haddad, O., Omid, M. H., Mariño, M. A. (2011). “Long-term efficiency of water networks with demand uncertainty.” Proc., Inst. Civ. Eng. Water Manage., 164(3), 147–159.
Shirangi, E., Kerachian, R., and Bajestan, M. S. (2008). “A simplified model for reservoir operation considering the water quality issues: Application of the Young conflict resolution theory.” Environ. Assess. Monit., 146(1–4), 77–89.
Soltanjalili, M., Bozorg Haddad, O., Mariño, M. A. (2011). “Effect of breakage level one in design of water distribution networks.” Water Resour. Manage., 25(1), 311–337.
Wardlaw, R., and Sharif, M. (1999). “Evaluation of genetic algorithms for optimal reservoir system operation.” J. Water Resour. Plann. Manage., 25–33.
Yeh, W. (1985). “Reservoir management and operations models: A state-of-the-art review.” Water Resour. Res., 21(12), 1797–1818.
Young, H. P., Okada, N., and Hashimoto, T. (1982). “Cost allocation in water resources development.” Water Resour. Res., 18(3), 463–475.

Information & Authors

Information

Published In

Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 141Issue 2February 2015

History

Received: Nov 3, 2013
Accepted: May 28, 2014
Published online: Jul 9, 2014
Discussion open until: Dec 9, 2014
Published in print: Feb 1, 2015

Permissions

Request permissions for this article.

Authors

Affiliations

Elahe Fallah-Mehdipour, Ph.D. [email protected]
Dept. of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, Univ. of Tehran, Karaj, Tehran, Iran. E-mail: [email protected]
Omid Bozorg Haddad [email protected]
Associate Professor, Dept. of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural Resources, Univ. of Tehran, Karaj, Tehran, Iran (corresponding author). E-mail: [email protected]; [email protected]
Miguel A. Mariño, Dist.M.ASCE [email protected]
Distinguished Professor Emeritus, Dept. of Land, Air and Water Resources, Dept. of Civil and Environmental Engineering; and Dept. of Biological and Agricultural Engineering, Univ. of California, 139 Veihmeyer Hall, Davis, CA 95616-8628. E-mail: [email protected]

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

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share