About the event
On Thursday, October 29, at 12:00 PM, the Institute for Science, Society and Policy hosted Prof. Melike Erol-Kantarci, Faculty Affiliate, ISSP and Associate Professor, School of Electrical Engineering and Computer Science, uOttawa.
Renewable energy resources are underutilized worldwide, regardless of geography or economy. This is partly due to the challenge of integrating a large number of small-scale, distributed renewable energy generators to the utility power grid; and partly due to the intermittency and cost of such resources. The current practice for installing small generators is to invest for capacity that only meets the average demand of the consumers with rigid contracts, simply because in general, there is no stake in surplus energy from prosumers.
In this talk, we introduce novel AI-based tools that will allow a peer-to-peer energy trading platform consisting of microgrids to become a part of the future transactive energy systems. Energy trading among microgrid communities promises to make use of the renewable energy more efficiently and strengthen the resilience of the power grid during disasters and attacks. In this talk, we present our Bayesian learning and correlated deep q-learning based techniques that address uncertainty and improve energy trading decisions in transactive energy systems