Wednesday, April 19, 2023 - 4:00pm to 4:30pm
Event Calendar Category
LIDS & Stats Tea
Speaker Name
Sylvie Koziel
Affiliation
LIDS
Building and Room Number
LIDS Lounge
Abstract
Taking decisions requires information and data. The more data the better the decisions. From machine learning to artificial intelligence and internet-of-things, data, and especially big data, plays a central part in today's applications and research activities. However, data is neither cheap nor readily available, and can be a sensitive social and ethical topic. In the area of power systems, collecting and processing data has an economic and environmental cost, not to mention the technical difficulties associated with sensor failures, cyber threats and processing of huge amounts of data. How much data is really needed to keep the grid reliable, considering the deployment of electric vehicles and distributed generation? This is the central question of the talk. First, the reasons why more data in power systems might be needed will be clarified, as well as the drawbacks associated with more data generation. During the talk, we will also present the work done so far to assess the level of data granularity needed for power grids to be smarter, reliable and efficient.
Biography
Sylvie Koziel has a diversified education and experience working in the fields of agronomy, energy and climate economics, electrical engineering and computer science. She received her MSc in agronomy from AgroParisTech, and specialized in Energy and Environmental economics at the Center of Atomic Energy and IFP School. She worked with different organizations in France and Switzerland: she advised private companies, as well as public authorities on topics related to oil and gas company strategies, energy consumption modeling and implementation of climate mitigation measures. She then decided to dedicate to research and is currently enrolled as a PhD student at the Royal Institute of Technology (KTH, Stockholm, Sweden), with a focus on smart grids. In particular, she is looking into the use of data to improve grid reliability in a profitable way, in the context of the integration of renewable distributed generation and electric vehicles into distribution grids.