Predictive control for balancing wind generation variability using run-of-river power plants

In many countries, hydro power plays an important role in the electric power generation. While its fast ramping capabilities make it a perfect source to overcome the variability and intermittency of electric energy sources such as wind and solar power, constraints imposed to reduce the environmental impacts of hydro power plants also reduce its operational flexibility. In this paper, Model Predictive Control (MPC) is employed to optimally schedule the available hydro power from cascaded river power plants while complying with the imposed constraints. A model of the river dynamics derived from the Saint Venant equations is used to predict the influence of the changes in turbine discharge on water levels and discharges along the river. The objective is to reduce the variability of wind generation and at the same time also to minimize the environmental impact of river power plants by minimizing water level and discharge variations.