Business Analytics and IT in Smart Grid – Part 3: New Application Aspect and the Quantitative Mitigation Analysis of Piecewise Monotonic Data Approximations on the iSHM Class Map Footprints of Overhead Low-Voltage Broadband over Power Lines Topologies Contaminated by Measurement Differences

Abstract

Βig data that overwhelm smart grid (SG) are susceptible to errors that can further affect business analytics and related human decisions. In [1], the impact of measurement differences that follow various distributions has been examined via initial Statistical Hybrid Model (iSHM) footprints while the mitigation impact of piecewise monotonic data approximations has been qualitatively assessed via corresponding iSHM footprints in [2]. In this companion paper, the potential of applying piecewise monotonic data approximations in the intrinsic procedure of iSHM rather than its inputs and the quantitative mitigation analysis of piecewise monotonic data approximations against measurement differences via iSHM footprints are proposed for the overhead low-voltage broadband over power lines (OV LV BPL) topologies.Citation: Lazaropoulos, A. G. (2020). Business Analytics and IT in Smart Grid – Part 3: New Application Aspect and the Quantitative Mitigation Analysis of Piecewise Monotonic Data Approximations on the iSHM Class Map Footprints of Overhead Low-Voltage Broadband over Power Lines Topologies Contaminated by Measurement Differences. Trends in Renewable Energy, 6, 214-233. DOI: 10.17737/tre.2020.6.2.0011