Graduation Year
2020
Document Type
Thesis
Degree
M.S.E.E.
Degree Name
MS in Electrical Engineering (M.S.E.E.)
Degree Granting Department
Electrical Engineering
Major Professor
Mahshid Rahnamay Naeini, Ph.D.
Committee Member
Nasir Ghani, Ph.D.
Committee Member
Ismail Uysal, Ph.D.
Keywords
Edge architecture, Edge computing, Edge layer design, Reliability
Abstract
The emergence of modern monitoring, communication, computation, and controlequipment into power systems has made them evolve into smart grids that can be thought of as the electric grid of things. This evolution has enhanced the efficiency of the power systems through the availability of a large volume of system data that can help with system functions, nevertheless, it has intensified the communication and computation burden on these systems. While many of such computations were traditionally deployed in central servers, new technologies such as edge computing can provide unique opportunities to address some of the computational challenges and improve the responsiveness of the power system by processing data locally. In this thesis, first the application of edge computing technology in smart grids’ applications are reviewed and discussed. These applications are ranging from functions in Advanced Metering Infrastructure to monitoring and control of transmission grids. Next, an edge enabled smart grid architecture, particularly for the support of transmission grid functions is presented. The edge layer for the smart grid is designed through optimization formulations to identify the placement of edge servers and their connectivity structure to the Phasor Measurement Units in the system. Various factors affecting the design, such as the geographical and resource constraints as well as the communication technology considerations have been incorporated in the formulations and evaluated using a power system test case, the IEEE 118 bus system. Finally, the future direction of research and challenges for the emerging field of edge-enabled smart grids are discussed.
Scholar Commons Citation
Adeniran, Adetola B., "Architecture design and optimization of Edge-enabled Smart Grids" (2020). USF Tampa Graduate Theses and Dissertations.
https://digitalcommons.usf.edu/etd/8506