Technical Papers
Jun 13, 2016

Simultaneous Optimization of Operating Rules and Rule Curves for Multireservoir Systems Using a Self-Adaptive Simulation-GA Model

This article has a reply.
VIEW THE REPLY
This article has a reply.
VIEW THE REPLY
Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 10

Abstract

This study introduces a simulation-optimization model for deriving an operating policy for multireservoir systems. Two adjustable monthly rule curves are introduced to each reservoir in the system. The applied rule curves divide the reservoir volume into three zones in each within-year period. For each zone, a release coefficient is specified to indicate releases from the reservoir as a function of the available storage and time of the year. To obtain optimum rule curves and release rules, a self-adaptive genetic algorithm (GA) is developed to maximize the system’s hydropower production, subject to the system’s physical constraints as well as a desirable reliability to satisfy water demands. To evaluate the objective function and constraints, a simulation model based on the network flow technique and linear programming is developed and coupled to the GA. The model is applied to a real three-reservoir system in Iran and the results are discussed and compared to the standard operation policy (SOP).

Get full access to this article

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

References

Aboutalebi, M., Bozorg Haddad, O., and Loáiciga, H. (2015). “Optimal monthly reservoir operation rules for hydropower generation derived with SVR-NSGAII.” J. Water Resour. Plann. Manage., 04015029.
Ahmadi, M., Bozorg Hadad, O., and Mariño, M. A. (2014). “Extraction of flexible multi-objective real-time reservoir operation rules.” Water Resour. Manage., 28(1), 131–147.
Ahmadianfar, I., Adib, A., and Salarijazi, M. (2015). “Optimizing multireservoir operation: Hybrid of bat algorithm and differential evolution.” J. Water Resour. Plann. Manage., 05015010.
Allen, R. B., and Bridgeman, S. G. (1986). “Dynamic programming in hydropower scheduling.” J. Water Resour. Plann. Manage., 339–353.
Ashofteh, P., Haddad, O., and Loáiciga, H. (2015). “Evaluation of climatic-change impacts on multiobjective reservoir operation with multiobjective genetic programming.” J. Water Resour. Plann. Manage., 04015030.
Bayazit, M., and Unal, N. E. (1990). “Effects of hedging on reservoir performance.” Water Resour. Res., 26(4), 713–719.
Bower, B. T., Hufschmidt, M. M., and Reedy, W. W. (1966). “Operating procedures: Their role in the design of water-resource systems by simulation analyses.” Design of water-resource systems, A. Maass, et al., eds., Harvard University Press, Cambridge, MA, 443–458.
Bozorg-Haddad, O., Karimirad, I., Seifollahi-Aghmiuni, S., and Loáiciga, H. (2014). “Development and application of the bat algorithm for optimizing the operation of reservoir systems.” J. Water Resour. Plann. Manage., 04014097.
Chang, J. X., Bai, T., Huang, Q., and Yang, D. W. (2013). “Optimization of water resources utilization by PSO-GA.” Water Resour. Manage., 27(10), 3525–3540.
Chen, L. (2003). “Real coded genetic algorithm optimization of long term reservoir operation.” J. Am. Water Resour. Assoc., 39(5), 1157–1165.
Chen, L., Mcphee, J., and Yeh, G. W. W. (2007). “A diversified multiobjective GA for optimizing reservoir rule curves.” Adv. Water Resour., 30(5), 1082–1093.
Chung, I., and Helweg, O. (1985). “Modeling the California State water project.” J. Water Resour. Plann. Manage., 82–97.
Clark, E. J. (1950). “New York control curves.” J. Am. Water Works Assoc., 42(9), 823–827.
Clark, E. J. (1956). “Impounding reservoirs.” J. Am. Water Works Assoc., 48(4), 349–354.
Dahe, P. D., and Srivastava, D. K. (2002). “Multi reservoir multi yield model with allowable deficit in annual yield.” Water Resour. Plann. Manage., 406–414.
Dariane, A. B., and Karami, F. (2014). “Deriving Hedging rules of multi-reservoir system by online evolving neural networks.” Water Resour. Manage., 28(11), 3651–3665.
Dariane, A. B., and Momtahen, Sh. (2009). “Optimization of multi-reservoir systems operation using modified direct search genetic algorithm.” Water Resour. Plann. Manage., 141–148.
Davidsen, C., Pereira-Cardenal, S., Liu, S., Mo, X., Rosbjerg, D., and Bauer-Gottwein, P. (2015). “Using stochastic dynamic programming to support water resources management in the Ziya River Basin, China.” J. Water Resour. Plann. Manage., 04014086.
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002). “A fast and elitist multi-objective genetic algorithm: NSGA-II.” IEEE Trans. Evol. Comput., 6(2), 182–197.
Draper, A. J., and Lund, J. R (2004). “Optimal hedging and carry over storage value.” Water Resour. Plann. Manage., 83–87.
Eshelman, L. J., and Shaffer, D. J. (1993). “Real-coded genetic algorithms and interval schemata.” Foundations of genetic algorithms 2, D. L. Whitley, ed., Morgan Kaufman, San Mateo, CA, 187–202.
Eum, H., Kim, Y., and Palmer, R. (2011). “Optimal drought management using sampling stochastic dynamic programming with a hedging rule.” J. Water Resour. Plann. Manage., 113–122.
Fallah-Mehdipour, E., Bozorg Haddad, O., and Mariño, M. A. (2011). “MOPSO algorithm and its application in multipurpose multireservoir operations.” J. Hydroinf., 13(4), 794–811.
Finardi, E. C.da Silva, E. L., and Sagastizabal, C. (2005). “Solving the unit commitment problem of hydropower plants via Lagrangian relaxation and sequential quadratic programming.” Comput. Appl. Math., 24(3), 317–342.
Guo, X., Hu, T., Wu, C., Zhang, T., and Lv, Y. (2013). “Multi-objective optimization of the proposed multi-reservoir operating policy using improved NSPSO.” Water Resour. Manage., 27(7), 2137–2153.
Guo, X., Hu, T., Zeng, X., and Li, X. (2012). “Extension of parametric rule with the hedging rule for managing multireservoir system during droughts.” J. Water Resour. Plann. Manage., 139–148.
Hidalgo, I., et al. (2015). “Hybrid model for short-term scheduling of hydropower systems.” J. Water Resour. Plann. Manage., 04014062.
Hincal, O., Altan-sakarya, A. B., and Metin Ger, A. (2011). “Optimization of multireservoir systems by genetic algorithm.” Water Resour. Manage., 25(5), 1465–1487.
Hu, M., et al. (2014). “Multi-objective ecological reservoir operation based on water quality response models and improved genetic algorithm: A case study in Three Gorges Reservoir, China.” Eng. Appl. Artif. Intell., 36, 332–346.
Ilich, N. (2009). “Limitations of network flow algorithms in river basin modeling.” J. Water Resour. Plann. Manage., 48–55.
Jalali, M. R., Afshar, A., and Mariño, M. A. (2007). “Multi-colony ant algorithm for continuous multi-reservoir operation optimization problem.” Water Resour. Manage., 21(9), 1429–1447.
Ji, C., Jiang, Z., Sun, P., Zhang, Y., and Wang, L. (2015). “Research and application of multidimensional dynamic programming in cascade reservoirs based on multilayer nested structure.” J. Water Resour. Plann. Manage., 04014090.
Johnson, S. A., Stedinger, J. R., and Staschus, K. (1991). “Heuristic operating policies for reservoir system simulation.” Water Resour. Res., 27(5), 673–685.
Jothiprakash, V., Shanthi, G., and Arunkumar, R. (2011). “Development of operational policy for a multi-reservoir system in India using genetic algorithm.” Water Resour. Manage., 25(10), 2405–2423.
Karamouz, M., and Houck, M. H. (1987). “Comparison of stochastic and deterministic dynamic programming for reservoir operating rule generation.” Water Resour. Bull., 23(1), 1–9.
Kjeldsen, T. R., and Rosbjerg, D. (2004). “Choice of reliability, resilience and vulnerability estimators for risk assessments of water resources systems.” J. Hydrol. Sci., 49(5), 755–767.
Kumar, D., and Reddy, J. (2006). “Ant colony optimization for multi-purpose reservoir operation.” J. Water Resour. Manage., 20(6), 879–898.
Kumar, D., and Reddy, J. (2007). “Multiple reservoir operation using particle swarm optimization.” J. Water Resour. Plann. Manage., 192–201.
López-Ibáñez, M., Prasad, T. D., and Paechter, B. (2008). “Ant colony optimisation for the optimal control of pumps in water distribution networks.” J. Water Resour. Plann. Manage., 337–346.
Louati, M. H., Benabdallah, S., Lebdi, F., and Milutin, D. (2011). “Application of a genetic algorithm for the optimization of a complex reservoir system in Tunisia.” Water Resour. Manage., 25(10), 2387–2404.
Loucks, D. P., Stedinger, J. R., and Haith, D. A. (1981). Water resource systems planning and analysis, Prentice-Hall, Englewood Cliffs, NJ.
Lund, J. R., and Reed, R. U. (1995). “Drought water rationing and transferable rations.” Water Resour. Plann. Manage., 429–437.
Maass, A., Hufschmidt, M. M., Dorfman, R., Thomas, H. A., Jr., Marglin, S. A., and Fair, G. M. (1962). Design of water-resource systems, Harvard University Press, Cambridge, MA.
Madadgar, S., and Afshar, A. (2009). “An improved continuous ant algorithm for optimization of water resources problems.” Water Resour. Manage., 23(10), 2119–2139.
Martin, Q. W. (1987). “Optimal daily operation of surface-water system.” J. Water Resour. Plann. Manage., 453–470.
Momtahen, S., and Dariane, A. (2007). “Direct search approaches using genetic algorithms for optimization of water reservoir operating policies.” J. Water Resour. Plann. Manage., 202–209.
Oliveira, R., and Loucks, D. (1997). “Operating rules for multireservoir systems.” Water Resour. Res., 33(4), 839–852.
Ostadrahimi, L., Mariño, M. A., and Afshar, A. (2012). “Multi-reservoir operation rules: Multi-swarm PSO-based optimization approach.” Water Resour. Manage., 26(2), 407–427.
Palmer, R. N., and Holmes, K. J. (1988). “Operational guidance during droughts: Expert system approach.” J. Water Resour. Plann. Manage., 647–666.
Pereira-Cardenal, S., Mo, B., Riegels, N., Arnbjerg-Nielsen, K., and Bauer-Gottwein, P. (2014). “Optimization of multipurpose reservoir systems using power market models.” J. Water Resour. Plann. Manage., 04014100.
Randall, D., Houck, M. H., and Wright, J. R. (1990). “Drought management of existing water supply system.” J. Water Resour. Plann. Manage., 1–20.
Reis, L. F. R., Walter, G. A., Savic, D., and Chaudry, F. H. (2005). “Multi-reservoir operation planning using hybrid genetic algorithm and linear programming (GA-LP): An alternative stochastic approach.” Water Resour. Manage., 19(6), 831–848.
Rosenthal, R. E. (1981). “A nonlinear network algorithm for maximization of benefits in a hydroelectric power system.” Oper. Res., 29(4), 763–786.
Sand, G. M. (1984). “An analytical investigation of operating policies for water-supply reservoirs in parallel.” Ph.D. dissertation, Cornell Univ., Ithaca, NY.
Schardong, A., and Simonovic, S. (2015). “Coupled self-adaptive multiobjective differential evolution and network flow algorithm approach for optimal reservoir operation.” J. Water Resour. Plann. Manage., 04015015.
Shourian, M., Mousavi, S. J., and Tahershamsi, A. (2008). “Basin-wide water resources planning by integrating PSO algorithm and MODSIM.” Water Resour. Manage., 22(10), 1347–1366.
Sigvaldason, O. T. (1976). “A simulation model for operating a multipurpose multireservoir system.” Water. Resour. Res., 12(2), 263–278.
Simonovic, S. P., and Marino, M. A. (1980). “Reliability programming in reservoir management. 1: Single multiple reservoir.” Water Resour. Res., 16(5), 844–848.
Stedinger, R. J., Sule, B. F., and Loucks, D. P. (1984). “Stochastic dynamic programming models for reservoir operation optimization.” Water Resour. Res., 20(11), 1499–1505.
Taghian, M., Rosbjerg, D., Haghighi, A., and Madsen, H. (2014). “Optimization of conventional rule curves coupled with hedging rules for reservoir operation.” J. Water Resour. Plann. Manage., 693–698.
Wu, R.-S. (1988). “Derivation of balancing curves for multiple reservoir operation.” M.S. thesis, Dept. of Civil and Environmental Engineering, Cornell Univ., Ithaca, NY.
Xu, W., Zhao, J., Zhao, T., and Wang, Z. (2014). “Adaptive reservoir operation model incorporating nonstationary inflow prediction.” J. Water Resour. Plann. Manage., 04014099.
Zeng, Y., Xinyu, W., Cheng, C., and Wang, Y. (2014). “Chance-constrained optimal hedging rules for cascaded hydropower reservoirs.” J. Water Resour. Plann. Manage., 04014010.
Zhao, T., Cai, X., Lei, X., and Wang, H. (2012). “Improved dynamic programming for reservoir operation optimization with a concave objective function.” J. Water Resour. Plann. Manage., 590–596.

Information & Authors

Information

Published In

Go to Journal of Water Resources Planning and Management
Journal of Water Resources Planning and Management
Volume 142Issue 10October 2016

History

Received: Jul 22, 2014
Accepted: Apr 6, 2016
Published online: Jun 13, 2016
Published in print: Oct 1, 2016
Discussion open until: Nov 13, 2016

Permissions

Request permissions for this article.

Authors

Affiliations

Ali Ahmadi Najl [email protected]
Ph.D. Candidate, Dept. of Civil Engineering, Engineering Faculty, Shahid Chamran Univ. of Ahvaz, 61357831351 Ahvaz, Iran. E-mail: [email protected]
Ali Haghighi [email protected]
Associate Professor, Dept. of Civil Engineering, Engineering Faculty, Shahid Chamran Univ. of Ahvaz, 61357831351 Ahvaz, Iran (corresponding author). E-mail: [email protected]; [email protected]
Hossein Mohammad Vali Samani [email protected]
Professor, Dept. of Civil Engineering, Engineering Faculty, Shahid Chamran Univ. of Ahvaz, 61357831351 Ahvaz, Iran. 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