Microgrids represent an emerging paradigm of future electric power systems that integrate both distributed and centralized generation. Two recent trends in microgrids are the integration of local renewable energy sources (such as wind farms) and the use of co-generation (i.e., to supply both electricity and heat). However, these trends also bring unprecedented challenges to the design of intelligent control strategies for the microgrids. Traditional generation scheduling paradigms assuming perfect prediction of future electricity supply and demand are no longer applicable to microgrids with unpredictable renewable energy supply and co-generation (that depends on both electricity and heat demand). In this work, we study online algorithms for the microgrid generation scheduling problem with intermittent renewable energy sources and co-generation, in order to maximize the cost savings without the need to predict future demand and supply. Based on insights from the structure of the offline optimal solution, we propose a class of competitive online algorithms, called CHASE (Competitive Heuristic Algorithm for Scheduling Energy-generation), that track the offline optimal in an online fashion. Under typical settings, we show that CHASE achieves the best competitive ratio of all deterministic online algorithms and the ratio is no larger than 3. We also extend our algorithms to intelligently leverage on limited prediction of the future, such as near-term demand or wind forecast. By extensive empirical evaluation using real-world traces, we show that our proposed algorithms can achieve near-offline-optimal performance. In a representative scenario, CHASE leads to around 20% cost savings with no future look-ahead at all, and the cost-savings further increase with limited future look-ahead.
Minghua Chen received his B.Eng. and M.S. degrees from the Department of Electronic Engineering at Tsinghua University in 1999 and 2001, respectively. He received his Ph.D. degree from the Department of Electrical Engineering and Computer Sciences at University of California at Berkeley in 2006. He spent one year visiting Microsoft Research Redmond as a Postdoc Researcher. He joined the Department of Information Engineering, the Chinese University of Hong Kong, in 2007, where he is now an Associate Professor. He is also currently an Adjunct Associate Professor in Tsinghua University, Institute of Interdisciplinary Information Sciences. He received the Eli Jury award from UC Berkeley in 2007 (presented to a graduate student or recent alumnus for outstanding achievement in the area of Systems, Communications, Control, or Signal Processing) and The Chinese University of Hong Kong Young Researcher Award in 2013. He also received several best paper awards, including the IEEE ICME Best Paper Award in 2009, the IEEE Transactions on Multimedia Prize Paper Award in 2009, and the ACM Multimedia Best Paper Award in 2012. He is currently an Associate Editor of the IEEE/ACM Transactions on Networking. His recent research interests include energy systems (e.g., microgrids and energy-efficient data centers), distributed optimization, multimedia networking, wireless networking, network coding, and delay-constrained network communications.