Measurement Differences, Faults and Instabilities in Intelligent Energy Systems – Part 2: Fault and Instability Prediction in Overhead High-Voltage Broadband over Power Lines Networks by Applying Fault and Instability Identification Methodology (FIIM)

Abstract

This companion paper of [1] focuses on the prediction of various faults and instabilities that may occur during the operation of the transmission power grid when overhead high-voltage broadband over power lines (OV HV BPL) networks are deployed across it. Having already been identified the theoretical OV HV BPL transfer function for a given OV HV BPL network [1], the faults and instabilities of the transmission power grid are first differentiated from the measurement differences, which can occur during the determination of an OV HV BPL transfer function, and, then, are identified by applying the best L1 Piecewise Monotonic data Approximation (best L1PMA) to the measured OV HV BPL transfer function. When faults and instabilities are detected, a warning is issued. The contribution of this paper is triple. First, the Topology Identification Methodology (TIM) of [1] is here extended to the proposed Fault and Instability Identification Methodology (FIIM) so that faults and instabilities across the transmission power grid can be identified. Also, the curve similarity performance percentage metric (CSPpM) that acts as the accompanying performance metric of FIIM is introduced. Second, the impact of various fault and instability conditions on the OV HV BPL transfer functions is demonstrated. Third, the fault and instability prediction procedure by applying the FIIM is first reported. Citation: Lazaropoulos, A. G. (2016). Measurement Differences, Faults and Instabilities in Intelligent Energy Systems – Part 2: Fault and Instability Prediction in Overhead High-Voltage Broadband over Power Lines Networks by Applying Fault and Instability Identification Methodology (FIIM). Trends in Renewable Energy, 2(3), 113-142. DOI: 10.17737/tre.2016.2.3.0027