By 2050, the costs of an average PV and wind plant are expected to fall by 71% and 58%, respectively. Meanwhile, batteries will further depress market prices, which in turn enable the deeper penetration of renewable energies like PV, wind, and electric vehicles (EVs). However, the transition on primary energy resources can be a double-edged sword. Problems such as protective relay is landing and fault detection, protective relay coordination under environmental uncertainty, topology recovery of secondary distribution networks, and EV charging station planning are critical to the security and resilience of the electric systems. This presentation describes several timely solutions to enable more secure and efficient grid operations by analyzing voluminous power system operation data. The aforementioned solutions include the multifunction intelligent relays, an environment-driven adaptive protection scheme, a transformer connectivity inferencing tool, and an EV charging station planning method. Several types of machine learning algorithms are developed in power systems to support renewable energy integration for sustainability.
Qiushi Cui earned his M.Sc. degree from Illinois Institute of Technology, and the Ph.D. degree from McGill University, both in ElectricEngineering. Currently, he is Associate Director of Machine LearningLaboratory for Power Systems in the Ira A. Fulton School of Engineering at Arizona State University (ASU). Prior to joining ASU, he was a ResearchEngineer at OPAL-RT Technologies Inc. from Nov. 2015 to Nov. 2017. His research interests are in the areas of machine learning and big data applications in power systems, power system protection, smart cities, microgrid, EV integration, renewable energies, and real-time simulations power engineering. Dr. Cui won the Best Paper Award at the 13th IETInternational Conference in Developments in Power System Protection in Edinburgh, UK, in 2016. He was the winner of the Chunhui Cup Innovation and EntrepreneurshipCompetition for Overseas Chinese Scholars in the Energy Sector in 2018. Dr. Cui received thePostdoctoral Research Scholarship from Québec Research Fund - Nature and Technology (FRQNT) and held the MITACS Accelerate Research Program Fellowship from Canada.