Skip to content

Optimization in Microgrids

Liu_GuodongDr. Guodong Liu
Research and Development Staff, ORNL
October 23, 2015, 1:00-2:00pm
410 John D. Tickle Building

Dr. Guodong Liu received his B.S. and M.S. degrees, both in electric power engineering, from Shandong University (China) in 2007 and Huazhong University of Science and Technology (China) in 2009, respectively. He started his Ph.D. study at The University of Tennessee, Knoxville, in August 2009. During his Ph. D. study, he has been involved in several projects about power system scheduling considering demand response, large scale integration of wind energy and microgrid energy management system development funded by both NSF and DOE. After getting his Ph. D. degree in January 2014, he has been working as a Post-doctorate Research Associate, later as a Research and Development Staff in the Power and Energy Systems (PES) group of Oak Ridge National Laboratory (ORNL) until now. He currently leads projects on Microgrid operation and planning, renewable energy integration and active distribution network management. He is the major developer of CSEISMIC microgrid controller, DECC microgrid and RTDS-based microgrid testbed. He is the PI of Microgrid Assisted Design for Remote Areas (MADRA) sponsored by the DOE Office of Electricity Delivery and Energy (DOE-OE). He is a member of IEEE and a reviewer of IEEE Transaction on Power Systems/Smart Grid/ Sustainable Energy. His current interests include power system operation and planning, power system reliability and security assessment, distributed energy resource and microgrids as well as new optimization methods and its application in power systems.

Abstract: The increasing installation of distributed renewable and/or nonrenewable energy resources, energy storage, rapid growth of plug-in hybrid electric vehicles (PHEV), and the maturing demand response in the distribution systems bring unprecedented opportunities and challenges to utilities, end users, manufacturers, and other participants in distribution system operations. A microgrid can be defined as a low voltage distribution network comprising various DGs, storage devices, and responsive loads that can be operated in both grid-connected and islanded modes. A microgrid is connected to the main distribution network at the Point of Common Coupling (PCC). Power may be imported from, or exported to the main distribution network under different market tariffs and microgrid operational conditions. Microgrid improves local reliability of energy supply, reduces emissions and contributes to lower cost of energy supply by taking advantage of distributed energy resources (DERs), storage devices and responsive loads. Furthermore, a microgrid can improve power quality by supporting voltage and reducing voltage dips. In order to achieve these benefits and supply energy in a reliable and economic way, multiple DERs, storage devices and responsive loads within the microgrid must be operated in a coordinated and coherent fashion. To that end, a microgrid energy management system (EMS) is developed. It has two stages: day-ahead bidding/scheduling and real-time dispatch. For the day-ahead bidding/scheduling, a Hybrid Stochastic/Robust optimization model is proposed to minimize the expected net cost, i.e., expected total cost of operation minus total benefit of demand considering the stochasticity of renewable energy and market prices. For the real-time dispatch, a multiobjective optimization model is proposed to dispatch the real and reactive power simultaneously considering the distribution network. Both optimization models are formulated as MILP and solved by CPLEX. Numerical simulations verify the soundness and efficiency of the proposed models.

The flagship campus of the University of Tennessee System and partner in the Tennessee Transfer Pathway.