Reliability-based Optimal Design and Operation of Cascade Hydraulically-Coupled Hydropower Reservoir Systems

Document Type : Original Article

Authors

1 Former MSc. Student of Water Engineering, Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran.

2 Professor, Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran

Abstract

Optimal design and operation of a cascade hydropower reservoir system accounting for the reliability level of the system’s firm energy is a complex, difficult-to-solve problem in terms of both the problem formulation and its solution approach. This study deals with the reliability-based optimal design and operation of cascade hydropower reservoirs considering hydraulic coupling between the tail-race of the upstream powerplant and the water elevation at downstream reservoir. The formulation of the resulting optimization model is a nonlinear, nonconvex program (NLP) that becomes a mixed integer NLP (MINLP) to account for the reliability level of energy production and the hydraulic coupling. The resulted MINLP, which is an NP-hard (nonpolynomial deterministic-hard) problem, was solved by both classical and evolutionary optimization algorithms, and their performances were tested in Karoon2-Karoon3 cascade hydropower system as a real case study. Since the number of binary variables is large and the nonlinear part of the MINLP is nonconvex, classical gradient-based algorithms were not able to solve the problem. However, particle swarm optimization (PSO) algorithm, a metaheuristic optimization algorithm, was able to find near optimal good solutions to the problem. This was made possible by the help of generating feasible solutions incrementally, which satisfy the equality constraints of balance equations, and the system operation characteristics during low-flow periods.

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References

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Iran-Water Resources Research
Volume 12, Issue 4 - Serial Number 38
Special Issue on the 6th National Conference on Water Resources Management
February 2017
Pages 70-83

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History

  • Receive Date: 24 October 2016
  • Revise Date: 04 January 2017
  • Accept Date: 04 January 2017

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