Operating Sittaung's Reservoirs

Operating Sittaung's Reservoirs: A two-stage model predictive control method for managing a multi-reservoir system for hydropower, irrigation and flood mitigation.

Lugt, Dorien (TU Delft Civil Engineering and Geosciences; TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Water Management)

Rutten, Martine (mentor)
Abraham, Edo (mentor)
Heemink, Arnold (mentor)
van der Woude, Jacob (mentor)

Delft University of Technology

2018-02-15

There is an increasing amount of attention for the application of model predictive control (MPC) for the optimal control of multi-purpose multi-reservoir systems (Tian et al. (2015), Raso (2013)). A major advantage of MPC is that multi-variate system dynamics and constraints of the control problem can be explicitly incorporated in the method. Challenges for application to reservoir systems include nonlinearities in the system dynamics and objectives and the large-scale optimization problem that arise when dealing with large systems (Lin and Rutten, 2016).

In this research a two-stage MPC method is presented for the optimal operation of a system of 21 reservoirs for hydropower, irrigation and flood management. The two-stage approach divides the problem into subproblems using the structure of the dynamical system (parallel connection of the reservoirs to the river) and periodicity of the external disturbances to the system (wet season and dry season). This approach reduces computational time for solution of the problem by using a decentralized approach (Christofides et al., 2013) for periods without flood risk, allowing parallel optimization of the reservoirs. In periods with flood risk, a coordinated MPC approach (Rawlings and Stewart, 2007) reduces the size of the problem while optimizing for the system-wide objective to mitigate flood. Spillway dynamics were defined by a complementarity constraint and included in the objective function using the penalty method (Pecci et al., 2017). Results showed appropriate behavior of the flows through the spillways. The main challenges for solving the nonlinear optimization problem were the scaling of the problem, the normalization of terms in the objective function, determination of appropriate penalties for the spillway constraint and the increasing size of the problem for longer optimization horizons.

The method was applied to a system in the Sittaung river basin, which suffers from frequent floodings (Rest, 2015). Results showed that trade-offs between irrigation, hydropower and flood mitigation for this basin are limited. The main limitation for flood mitigation by the reservoir system are the conduit capacities and optimization horizon of the MPC system. Results for the case study were promising and indicate clear directions for future research and necessary steps to be taken for practical implementation of a MPC system in the Sittaung river basin.

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Student theses

master thesis

© 2018 Dorien Lugt