About
Most participants watch the videos at 1.5x speed. Prerequisites: All courses of the "Data Science for Energy" category. Duration: 3 hours, 11 minutes Course Description: This is an advanced research course specifically for PhD candidates or researchers (PhD). The course teaches how an electricity grid can be reinforced by deploying conventional technologies and / or smart grid technologies. Regarding conventional technologies, we consider the upgrade of the capacity of existing power lines. Regarding smart grid technologies, we consider Dynamic Line Rating (DLR) and Energy Storage. We also consider two sources of uncertainty. First, the electricity demand is expected to increase over the coming years in an uncertain way. Secondly, the electricity grid includes a wind farm, whose installed capacity is expected to increase also in an uncertain way. The course also provides an introduction to stochastic optimization, Benders decomposition, and the option value of investing in smart grid technologies.