Comparison of two Approximate Stochastic Dynamic Programming Schemes for Mid-term Hydropower System Management

The Energy potential of water has been successfully harnessed to produce electricity since the late 19th century. In 2018, hydropower production accounts for approximately 61 % of the total electricity produced in Canada. To exploit this source of energy, water is stored in dams and is strategically used based on hydrological cycles. Over the years, researchers around the globed have devised sophisticated mathematical tools to efficiently manage hydropower systems thanks to advancement in both Mathematics and Computer Science. However, more research is still needed as hydropower management problems are known to be difficult, due to uncertain factors such as natural inflows, and demand for electricity, among others. This research project aims to test a novel mathematical approach on the Rio Tinto hydropower system located in Saguenay, in the province of Québec.

Intern: 
Acheampong Solomon
Faculty Supervisor: 
Luckny Zephyr;Bernard Lamond
Province: 
Ontario
Partner: 
Sector: 
Partner University: 
Program: