Skip Navigation Links
Journal of Environmental Accounting and Management
António Mendes Lopes (editor), Jiazhong Zhang(editor)
António Mendes Lopes (editor)

University of Porto, Portugal

Email: aml@fe.up.pt

Jiazhong Zhang (editor)

School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China

Fax: +86 29 82668723 Email: jzzhang@mail.xjtu.edu.cn


Optimal Control of Reservoir Operation Policy under Different Inflow Probabilities: A Case Study of Mohamed V Dam, Morocco

Journal of Environmental Accounting and Management 8(2) (2020) 201--214 | DOI:10.5890/JEAM.2020.06.007

Wafae El Harraki$^{1}$, Driss Ouazar$^{1}$, Imad El Harraki$^{2}$, Ahmed Bouziane$^{1}$

$^{1}$ Mohammed V University, Mohammadia School of Engineers, Rabat, Morocco

$^{2}$ Rabat Superior National School of Mines, Morocco

Download Full Text PDF

 

Abstract

This paper examines reservoir operation optimization considering probabilistic inflows. Optimal control of this model is obtained using Pontryagin’s Minimum Principle. The formulated problem includes non-linear equations on the state variables related to evaporation, stochastic inflows derived from historical time series and target ending storage constraint. Mohamed V dam is used as a case study to derive optimal operating rules through numerical simulation. The effect of inflows variability is demonstrated and a risk assessment of initial storage’s variation is discussed. A benchmark based on Genetic Algorithms showed the developed model’s performance. 9% of improvement for the low inflows scenario, are achieved.

References

  1. [1]  Ahmed, J.A. and Sarma, A.K. (2005), Genetic algorithm for optimal operating policy of a multipurpose reservoir, Water Resources Management, 19(2), 145-161.
  2. [2]  Ahmad, A.A., El-Shafie, A., Razali, S.F.M., and Mohamad, Z.S.(2014), Reservoir optimization in water resources: a review, Water resources Management, 28(11), 3391-3405.
  3. [3]  Aunkumar, R. and Jothiprakah, V. (2012), Optimal Reservoir operation for hydropower generation using non-linear programming model, Journal of The Institution of Engineers(India): Series A, 93(2), 111-120.
  4. [4]  Crandall, M.G. and Lions, P.L. (1983), Viscosity solutions of Hamilton-Jacobi equations, Transactions of The American Mathematical Society, 277(1), 1-42.
  5. [5]  Fayaed, S.S., El-Shafie, A., and Jaafar, O. (2013), Reservoir-system simulation and optimization techniques, Stochastic Environmental Research and Risk Assessment, 27(7), 1751–1772.
  6. [6]  Friesz, T.L. (2010), Nonlinear Programming and Discrete-Time Optimal Control, Dynamic Optimization and Differential Games, 33-78.
  7. [7]  Grygier, J.C. and Stedinger, J. (1985),Algorithms for optimizing hydropower system operation,Water Resources Research, 21(1), 1-10.
  8. [8]  Hinçal, O., Altan-Sakarya, A.B., and Ger, A.M. (2011), Optimization of multireservoir systems by genetic algorithm, Water Resources Management, 25(5), 1465–1487.
  9. [9]  Jothiprakash, V., Shanthi, G., and Arunkumar, R. (2011), Development of operational policy for a multireservoir system in India using genetic algorithm, Water Resources Management, 25(10), 2405-2423.
  10. [10]  Labadie, J.W. (2004), Optimal operation of multireservoir systems: State-of-the-art review, Journal of Water Resources Planning and Management, 130(2), 93-111.
  11. [11]  Lenhart, S. and Workman, J. (2007), Optimal Control Applied to Biological Models, New York: Chapman and Hall/CRC, https://doi.org/10.1201/9781420011418.
  12. [12]  Mizyed, N.R., Lotfis, J.C., and Fontane, D.G. (1992), Operation of Large multireservoir systems using optimal control theory, Journal of Water Resources Planning and Management, 118(4), 371-387.
  13. [13]  Mousavi, H. and Ramamurthy, A.S. (2000), Optimal design of multi-reservoir systems for water supply, Advances in Water Resources, 23(6),613-624.
  14. [14]  Oliveira, R. and Loucks, D.P. (1997), Operating rules for multireservoir systems, Water Resources Research, 33(4), 839- 852.
  15. [15]  Ouarda, T.B.M.J. and Labadie, J.W. (2001), Chance-constrained optimal control for multireservoir system optimization and risk analysis, Stochastic Environmental Research and Risk Assessment, 15(3),185-204.
  16. [16]  Pontryagin, L., Boltyanskii, V., Gamkrelidze, R., and Mishchenko, E. (1962), The mathematical theory of optimal process.
  17. [17]  Rani, D. and Moreira, M. (2010), Simulation-optimization modeling: a survey and potential application in reservoir systems operation, Water Resources Management, 24(6), -1138.
  18. [18]  Sharif, M. and Wardlaw, R. (2000), Multireservoir systems optimization using genetic algorithms: case study, Journal of Computing in Civil Engineering, 14(4), 255-263.
  19. [19]  Suiadee, W. and Tingsanchali, T. (2007), A combined simulation-genetic algorithm optimization model for optimal rule curves of a reservoir: a case study of the Nam Oon Irrigation Project.Thailand, Hydrological Processes, 21(23), 3211- 3225.
  20. [20]  Yeh,W.W.G. (1985), ReservoirManagement and OperationsModels a State-of-the-Art Review,Water Resources Research textbf21, 1797-1818.