Rapid Grid State Estimation using Singular Value Decomposition Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/rf55z990q

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  • Synchrophasor technology has gained great momentum with the widely adopted concept of smart grids in power systems at transmission and generation level. This has led to an improved state estimation of a power system with the advent of Phasor Measurement Units (PMU). PMUs contribute in providing real-time information about the grid state at a higher frequency than that has been historically available. This research aims to extend power system state estimation to a distribution level using the Oregon State University campus. Two state estimation techniques utilizing Singular Value Decomposition have been investigated in this research to estimate the state of the OSU power system with measurements from the sparsely deployed PMUs on the campus. The main objective is to build a state estimation technique for a system with incomplete observability based on static set of data compiled by valid power flow solutions and limited number of PMU measurements. Within this research both methods of estimating the state of the grid are demonstrated on three different sized power grids comprising of 3 buses, 14 buses and 286 buses, respectively. The two methods - Similarity Matching and Filtering - have been discussed as potential methods to determine the state of a partially observable system at real-time or near real-time. Both the methods have been evaluated on the basis of computational speed and complexity as well as accuracy. The results obtained from both techniques of SVD are shown to have promising applications to rapid grid estimation at the distribution level of a system in which speed and sparseness are key.
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