Efficient River Management using Stochastic MPC and Ensemble Forecast of Uncertain In-flows

Efficient river management is essential in improving water resource utilisation. However, river flows and water-levels are affected by unregulated in- and out-flows. Therefore, it is important to consider the forecasts of these unregulated flows and the uncertainties in the forecasts. The presentation will describe control and modelling tools from the literature that suit the river management problem. Specifically, a scenario-based Stochastic Model Predictive Control (MPC) strategy, that makes use of ensemble forecast of unregulated flows, is proposed, where the ensemble forecast contains multiple flow scenarios to characterise future flows and their uncertainties.


Bio: Hasan A. Nasir received his bachelors degree in electrical engineering from NUST, Islamabad, in 2009, his masters degree in computer engineering from the LUMS, Lahore, in 2011, and a Ph.D. degree from The University of Melbourne, Melbourne, Australia, in 2016. He is currently working as an Assistant Professor at the School of Electrical Engineering and Computer Science (SEECS), NUST, Pakistan. His research interests include system identification and optimisation-based control, with water and power systems as the application areas.