Microgrid Clusters with Adaptive Decentralized Energy Management Towards Resilient Power Systems
Microgrids, as individual controllable units of power generation, storage, and consumption, have emerged as a promising solution to improving reliability and resilience to disturbance. When networked together in a self-adaptive manner, a cluster of microgrids can significantly enhance the reliability of power supply in a cooperative manner. With this insight, we explore the self-adaptive and decentralized energy management of a microgrid cluster considering the variations in wind and solar resources, as well as disturbances.
As a case study, a microgrid energy management scheme is proposed, by taking into account distributed energy storage responsive to the nodal prices throughout the cluster. The presented method comprises the ex-ante optimal dispatch to minimize the anticipated operation cost, followed by a near real-time dispatch to manage the violation of security constraints regarding any branch limit and voltage limit in the microgrid cluster. The second dispatch, as recourse to the ex-ante dispatch, aims to minimize the operation cost and the deviation from the ex-ante dispatch decisions, while any possible binding constraint occurred in the ex-ante dispatch is mitigated. Simulation results on a test microgrid system demonstrate that the presented scheme can effectively ensure secure and economic operations of the microgrid cluster as well as the risk reduction of the ex-ante decisions.
Sajjad Abedi, Ph.D.
Postdoctoral Research Fellow, School of Mechanical Engineering
Sajjad Abedi is currently a Postdoctoral Research Fellow with School of Mechanical Engineering, Purdue University, IN, USA. He received his B.Sc. and M.Sc. degrees in Electrical Engineering from Isfahan University of Technology, Isfahan, Iran and Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran, in 2008 and 2011, respectively. He received his Ph.D. degree in Electrical Engineering from Texas Tech University, TX, USA, in 2017. Notably, he is a recipient of the National Science Foundation I-Corps Award and the GLEAMM SPARK Award for recognition of his contributions to power system steady-state modeling and operations.
His areas of expertise lie within power system operations with a significant integration of renewable resources using optimization under uncertainty and predictive data analytics. Such research efforts have culminated in several book chapters, journal papers in top publication venues and articles in peer-reviewed conference proceedings. He is a recipient of the Outstanding Doctoral Student of the Year Award from IEEE South Plains section in and the Texas Tech University Doctoral Dissertation Completion Fellowship Award.