5G Scheduling for Distributed Control in Microgrids
dc.contributor.author | Iyer, Rahul Rajan | en |
dc.contributor.committeechair | Mehrizi-Sani, Ali | en |
dc.contributor.committeemember | Shah, Vijay K. | en |
dc.contributor.committeemember | Liu, Chen-Ching | en |
dc.contributor.department | Electrical Engineering | en |
dc.date.accessioned | 2021-11-13T09:00:34Z | en |
dc.date.available | 2021-11-13T09:00:34Z | en |
dc.date.issued | 2021-11-12 | en |
dc.description.abstract | There is an increasing integration of distributed energy resources (DER), controllable loads, and other technologies that are making the grid more robust, reliable, and decentralized. Communication is a major aspect that enables this decentralization and can improve control of important system parameters by allowing different grid components to communicate their states with each other. This information exchange requires a reliable and fast communication infrastructure. Different communication techniques can be used towards this objective, but with recent technological advancements, 5G communication is proving to be a very viable option. 5G is being widely deployed throughout the world due to its high data rates combined with increased reliability compared with its predecessor technologies. This thesis focuses on application and performance analysis of a 5G network for different power system test cases. These test cases are microgrids, and consist of DERs that use distributed control for efficient operation. Under distributed control, the DERs communicate with each other to achieve fast and improved dynamic response. This work develops a co-simulation platform to analyze the impact that a 5G network has in this distributed control objective. This offers key insights on 5G's capability to support critical functions. Different scenarios including set point changes and transients are evaluated. Since distributed control is a time-critical application and DERs rely on the availability of up-to-date information, the scheduling aspect of 5G becomes very important and is given more focus. Information freshness measured using age of information (AoI) is used in this work. Information freshness is a measure of how recent and updated the information communicated by DERs is. This thesis compares the performance of AoI-based schedulers against standard schedulers. These different schedulers are then used on test systems employing distributed control. | en |
dc.description.abstractgeneral | Communication has become an important aspect of modern power systems due to increased integration of distributed energy resources (DER), controllable loads and other components that have communication capabilities for improved grid performance. Of the various communication techniques available for power systems, 5G is very promising due to its advantages over its predecessors and other wired communication methods. This work develops a cosimulation framework to implement a 5G network for different microgrid test cases that employ distributed control. Under distributed control, the DERs communicate with each other to achieve fast and improved dynamic response. Due to the time-critical nature of distributed control, DERs rely on the availability of up-to-date information. Hence the scheduling aspect of 5G becomes very important and is given more focus in this work. 5G schedulers that account for the availability of up-to-date information, also referred to as information freshness, are compared with standard 5G schedulers and their performance in distributed control test systems is analyzed. | en |
dc.description.degree | Master of Science | en |
dc.format.medium | ETD | en |
dc.identifier.other | vt_gsexam:33029 | en |
dc.identifier.uri | http://hdl.handle.net/10919/106645 | en |
dc.language.iso | en | en |
dc.publisher | Virginia Tech | en |
dc.rights | In Copyright | en |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
dc.subject | Age of information | en |
dc.subject | distributed control | en |
dc.subject | distributed energy resources | en |
dc.subject | microgrids | en |
dc.subject | scheduling | en |
dc.subject | 5G | en |
dc.title | 5G Scheduling for Distributed Control in Microgrids | en |
dc.type | Thesis | en |
thesis.degree.discipline | Electrical Engineering | en |
thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
thesis.degree.level | masters | en |
thesis.degree.name | Master of Science | en |
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