Dynamic Modeling with Empirical Data for Hydropower Decision Support

Long-term decision making strategic investment planning under the condition of great uncertainty is of great importance to power utilities such as Manitoba Hydro. A review of standard and existing planning methodologies will be the basis for identifying and testing new formal methods to support the definition of robust investment programme planning. This project will address the long-term decision making problem typically facing power utilities like Manitoba Hydro; using dynamic modeling, model filtering techniques, and practical data fusion. This project is expected to result in a novel proof-of-concept framework and system that would be broadly applicable to dynamically exploit real data for decision making, execute in-time model intervention simulation, and visualize data in appropriate formats to support decision makers in assessing options.

Faculty Supervisor:

Nate Osgood

Student:

Weicheng Qian

Partner:

Manitoba Hydro

Discipline:

Computer science

Sector:

Energy

University:

University of Saskatchewan