报告题目：Advanced Modeling and Optimization Techniques for Power System Operation under Uncertain Environment
报告人：吴磊副教授（美国克拉克森大学）
时间：2017年6月26日（周一）10:30
地点：校本部乐乎新楼一楼上善厅

报告摘要：
The electric power grid, as a whole networked system, has been recognized as an essential element of the nation’s energy infrastructure.  In emerging power systems, smart grid technology has been playing an increasingly important role for enhancing energy reliability, sustainability, resiliency, and economics.  Specifically, as the electric power industry is a major contributor to carbon dioxide, renewable energy such as wind and solar has become more competitive for its environmentally friendly nature.  However, highly variable and uncertain renewable energy demands for supporting technologies to firm it up and achieve a deeper penetration.  Under this environment, demand response (DR) programs provide system operators the flexibility to manage uncertainty and maintain reliability.  Nevertheless, DR also brings new challenges to power system operation since it introduces price-related demand variations and makes the system load profile stochastic and price-sensitive.
Furthermore, the electricity distribution sector is envisioned to include a deeper penetration of distributed energy resources (DERs), plug-in electric vehicles, plug-and-play energy storage devices, and microgrids, which present significant benefits for reducing real power losses, promoting energy sustainability, enhancing resiliency, and deferring generation/transmission upgrades.  However, with an increased penetration of DERs and microgrids, electric distribution systems are transforming from traditionally passive radial networks to more sophisticated active networked topologies, and in turn are facing with new operational challenges such as bidirectional power flows and voltage issues.  Indeed, as the generation side gets more distributed and the demand side becomes more active, it is of critical importance to evaluate the impacts of individual assets on the reliable and economic operation of power systems.
This talk will highlight several key issues in the reliable and economic operation of power systems with a significant penetration of renewable energy and DR assets, and discuss advanced modeling and optimization techniques, robust optimization based security-constrained unit commitment (SCUC) models in particular, for enhancing the reliability and economics of power system operation under uncertain environment.  Various applications of the robust SCUC approach, including short-term power system operation, mid-term multiple energy resource scheduling, and long-term multi-stage multiple time-scale power system planning, will be also discussed.  In addition, we will also talk about key characteristics, new challenges, and potential solutions for the operation of future distribution systems and microgrids.  A practical community resilience microgrid that is underway for serving Potsdam, NY will also be discussed.
报告人简介:  Dr. Lei Wu is an Associate Professor in the Department of Electrical and Computer Engineering at Clarkson University, Potsdam, NY.  He received Ph.D. degree in electrical engineering from Illinois Institute of Technology, Chicago, in 2008.  His primary research and teaching areas are focused on power and energy system optimization and control, with specific interests in the modeling of large-scale power systems with a high penetration of demand response and renewable energy.  His educational and research activities are supported by NSF, DOE, NYSERDA, other federal/state/local agencies, and private industry.  He has extensive experiences working with power industry such as GE Energy, NYISO, MISO, and National Grid.  He is the co-author of over 70 journal papers and the recipient of several Transactions Prize Paper Awards from the IEEE Power and Energy Society.  He is the receipt of NSF CAREER Award in 2013, IBM Smarter Planet Faculty Innovation Award in 2011, and John Graham Faculty Award at Clarkson in 2015.  He serves as Editor or member of editorial boards of several internationally recognized journals.