Abstract: Nowadays the electric power system isundergoing a fundamental transition to being more sustainable and intelligent,commonly known as the smart grid. To enable a seamless transition, varioustechnologies have been developed, including demand response, renewable energygeneration, energy storage, and decentralized operation paradigms. These newtechnologies bring both opportunities and challenges to the short-termoperation and long-term planning of power systems. I will present my researchon the development of frameworks and algorithms to integrate new devices andtechnologies into power systems. I will first discuss a cooperative frameworkfor the optimal planning and operation of autonomous microgrids, which enablesproactive interactions of microgrids toward a socially optimal solution. I willthen talk about a recent project that leverages machine learning techniques toimprove the economic viability of energy storage and takes a key step towardsthe integration of energy storage systems. I will also briefly introduce someother projects that address the problems of integrating distributed resources.I will conclude with some thoughts on future research opportunities in the areaof smart energy systems.
Bio： Hao Wang is a Washington Research FoundationInnovation Fellow at Department of Electrical Engineering and Clean EnergyInstitute, University of Washington. He received his Ph.D. from The ChineseUniversity of Hong Kong. His research interests are in control and optimizationof power and energy systems. His recent projects include machine learning fordemand response and energy storage, planning and operation of distributedenergy resources including renewable energy and electric vehicles. He serves aTPC member for conferences including SmartGridComm, Globecom, and ICC. He is arecipient of WRF Fellowship, Best Paper Award at IEEE PECON 2016, andOutstanding Tutor Award.
