报告题目:Technologies and Control Mechanisms for DC Microgrids Clusters
摘要:
Microgrids (MGs) are drawing growing attention due to their advantages in the distribution systems such as lower losses, high reliability, and efficiency, and coordinated incorporation of the distributed energy resources (DERs) in the power scheme. MGs which heavily reliant on renewable energy source (RES) are prone to severe disturbances arising due to drastic changes in load or generation. Such a disturbance can overstress other units which can result in system failure. Since it is not always feasible and economically viable to add storage or additional generation, different MGs near to each other may be joined to form a MG cluster. Coordination of clustered MGs needs to be achieved in a seamless manner to tackle supply-demand mismatch among MGs. A hierarchical control strategy including local and global layers has been used in the literature to coordinate DC MGs in a cluster based on a consensus algorithm. However, this control strategy may not be able to resist large load disturbances and unexpected generated powers due to the intermittent nature of RESs such as wind and solar. These issues are inevitable due to both layers (local and global) are highly dependent on classical PI-controllers that cannot fully overcome the above-mentioned obstacles. Therefore, modified consensus algorithm based on optimized PI-control utilizing the grey wolf optimiser (GWO) and hybrid particle swam optimisation (PSO) and GWO are proposed to enhance the performance of the global layer. For this study, the four interconnected DC MGs will be simulated in MATLAB Simulink to validate the proposed techniques.
报告人简介:
Professor Tek Tjing LIE received his Bachelor degree in Electrical Engineering from Oklahoma State University, USA in 1986. He also received his Master of Science and Ph. D. degrees in Electrical Engineering from Michigan State University, USA in 1988 and 1992 respectively.
Professor Lie is the Deputy Head of School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, New Zealand. His research interests include power system control and operation, AI applications in power systems, deregulated power systems, smart grids, microgrids, renewable energy systems and energy management systems. He has authored/co-authored more than 250 journal and international conference papers.
报告时间: 2021年11月17日10:00 – 14:00(北京时间)
报告链接:https://aut.zoom.us/j/91595858372
Zoom会议ID: 915 9585 8372