Modelling and Simulation of Coupled Systems-Water and Energy - Case Study of the Water Reservoir System of the Rimac River Catchments

  • Gloria Robleto
  • Manfred Schütze
  • Edy Godoy
Part of the Studies in Computational Intelligence book series (SCI, volume 391)


Approx 80 % of the fresh water consumption of the megacity of Lima (Peru) is covered by the reservoir system of the Rimac river catchments. A further task is the production of electrical energy by hydropower plants. Lima, with its 8 million inhabitants, is situated on the very dry pacific coast of Peru. Continuous water supply is a challenging task. Water supply and energy production lead to operational conflicts regarding the water releases of the reservoir system. Currently, the decision about the water releases is based on a general discharge Plan, precipitation forecast and a simplified reservoir model. This contribution presents the first working steps for the optimisation of the operation of the reservoir system based on a more detailed modelling approach. The model of the reservoir system has been simulated for two different hydrological periods (dry and humid) including the water discharge plan of the operating company.


Energy Modelling Operation Reservoir systems Water supply 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Becker, L., Yeh, W.: Optimisation of Real Time Operation of a Multiple Reservoir System. Water Resources Research 10, 1107–1112 (1974)CrossRefGoogle Scholar
  2. Brass, C.: Betriebsoptimierung von Talsperrensystemen mittels Stochastisch Dynamischer Programmierung (SDP) unter Berücksichtigung veränderlicher Ziele und Randbedingungen. Dissertation, Ruhr-Universität Bochum (2006)Google Scholar
  3. Chu, W., Yeh, W.: A Nonlinear programming algorithm for real time hourly reservoir operations. Water Resources Bulletin, American Water Resources Association 14, 1048–1073 (1978)CrossRefGoogle Scholar
  4. Draper, A., Lund, J.: Optimal Hedging and Carryover Storage Value. Journal of Water Resources Planning and Management 130, 83–87 (2004)CrossRefGoogle Scholar
  5. Esat, V., Hall, M.: Water resources system optimisation using genetic algorithms: Hydroinformatics ’94. In: Esat, V., Hall, M. (eds.) Proceedings of the First International Conference of Hydroinformatics, Balkema, Roterdam, The Netherlands, pp. 225–231 (1994)Google Scholar
  6. Godoy, E.: Modelling and control of the control reservoir system of the Rimca river catchment, Final Report (2011)Google Scholar
  7. Hashemi, M., Barani, G., Ebrahimi, H.: Optimisation of Reservoir Operation by Genetic Algorithm considering inflow probabilities (Case Study: The Jiroft Dam Reservoir). Journal of Applied Sciences 8, 2173–2177 (2008)CrossRefGoogle Scholar
  8. IEC 61131-3, Programmable controllers - Part 3: Programming languages, 2nd Edn., International Electrotechnical Commission, Genf (2002)Google Scholar
  9. ifak, SIMBA6 – Simulation of Wastewater systems, Reference and Tutorial, ifak – Institut für Automation und Kommunikation e. V. Magdeburg, Germany (2009)Google Scholar
  10. Karamouz, M., Houck, M., Delleur, J.: Optimisation and Simulation of Multiple Reservoir Systems. Journal of Water Resources Planning and Management 118, 71–81 (1992)CrossRefGoogle Scholar
  11. Labadie, J.: Optimal operation of Multireservoir Systems: State-of-the-Art-Review. Journal of Water Resources Planning and Management 130(2), 93–111 (2004), doi:10.1061/(ASCE)0733-9496CrossRefGoogle Scholar
  12. Lund, J., Guzman, J.: Some Derived Operating Rules for Reservoirs in Series or in Parallel. Journal of Water Resources Planning and Management 125, 143–153 (1999)CrossRefGoogle Scholar
  13. Murray, D., Yakowitz, S.: Constrained Differential Dynamic Programming and its Application to Multireservoir Control. Water Resources Research 15, 1017–1027 (1979)CrossRefGoogle Scholar
  14. Ogurek, M., Alex, J., Schütze, M.: Simulation als Basis für Entwicklung, Test und fehlerarme Inbetriebnahme von Automatisierungssystemen komplexer Prozesse, EKA 2008, Magdeburg (2008)Google Scholar
  15. Schütze, G., Robleto, G., León, C., Rodriguez, I.: Modelling and scenario building of urban water and wastewater systems – Addressing water shortage in Lima. In: IWA/IAHR International Conference on Urban Drainage, Porto Alegre (September 2011)Google Scholar
  16. Trott, W., Yeh, W.: Optimisation of Multiple Reservoir Systems. Journal of Hydraulics Divisions 99, 1865–1884 (1973)Google Scholar
  17. Tu, M., Hsu, N., Yeh, W.: Optimisation of Reservoir Management and Operation with Hedging Rules. Journal of Water Resources Planning and Management 129(2), 86–97 (2003), doi:10.1061/(ASCE)0733-9496CrossRefGoogle Scholar
  18. Wardlaw, R., Sharif, M.: Evaluation of genetic algorithm for optimal reservoir system operation. Journal of Water Resources Planning and Management 125, 25–33 (1999)CrossRefGoogle Scholar
  19. Yeh, W.: Reservoir Management and operation models: A State of the Art Review. Water Resources Research 21, 1797–1818 (1985)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Ifak, Institut für Automation und Kommunikation e.V. MagdeburgMagdeburgGermany
  2. 2.EDEGEL S.A.ALimaPerú

Personalised recommendations