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  • Power Network Parameter Correction via Sparse Unsupervised Regression

    Creator:
    Senaratne, Galpottage Dilan S.
    Abstract:
    Accurate information of power network parameters is essential for performing various power system monitoring and control tasks including state estimation, economic dispatch, and contingency analysis. In this paper, we present a novel approach of power network parameter correction wherein we exploit the sparse nature of parameter errors. Parameter error correction...
    Resource Type:
    Masters Thesis
    Full Text:
    , which rely on local sensitivity analysis for parameter error detec- tion and identification (wherein

  • Secure Data Analytics under Data Integrity Attacks

    Creator:
    De Silva, Shashini A.
    Abstract:
    There has been tremendous growth in using data analytic and machine learning algorithms to make critical decisions, such as in the national power grid, healthcare operations, and autonomous vehicles. Employing data analytic for decision-making allows cyber attackers to manipulate the decisions of these algorithms through data falsification. Hence, the trustworthiness...
    Resource Type:
    Dissertation
    Full Text:
    for the degree of Doctor of Philosophy in Electrical and Computer Engineering presented on November

  • Identifiability-Aware Joint Sparse Error Correction For Robust State Estimation

    Creator:
    Kibria, Sharmin
    Abstract:
    We study joint nonlinear state estimation with multi-period measurement vectors that are potentially corrupted by sparse gross errors. The identifiability-aware approach is proposed to leverage common characteristics of fundamentally identifiable gross errors to enhance error correction performance. First, we derive a necessary rank condition that the sparsity pattern of any...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . 55 C Mathematical Proofs Ffor Convergence Analysis . . . . . . . . . . . . . . . 58 LIST OF