This work presents the application of optimal control strategies to pumped storage power plants
(PSPPs). Four main aspects are considered here: optimal stationary operation optimal power
control optimal plant shutdown and optimal electricity market operation. A detailed and
computationally efficient plant model is developed in the first step as the basis for these
tasks. The developed models are used to study the optimal stationary operation of PSPPs. A
special focus is given to heterogeneous plants containing combinations of fixed- and
variable-speed generators. The power control is achieved by means of a nonlinear model
predictive control-based strategy. This control strategy consists of a stationary optimizer for
optimal quasi-stationary operation a model predictive controller (MPC) for optimal closed-loop
performance and an extended Kalman filter (EKF) to estimate non-measurable states and
parameters. Simulation studies show that the control strategy allows for fast following of
set-point changes while allowing for safe plant operation by systematically considering all
system constraints within the MPC. The dynamic performance in a plant shutdown is also studied
by developing optimal (nonlinear) guide vane closing laws. Finally the optimal market
operation of PSPPs in different electricity markets is studied. A reduced-order model which
contains all necessary effects is developed in the first step. This model is used to study the
performance of PSPPs in the Day-Ahead and Ancillary services markets. A moving horizon
optimization for the Intraday market is developed subsequently. Finally a robust
optimization-based bidding curve generation strategy to generate offer and demand curves in the
Day-Ahead market is developed in the last step.
