Analysis Techniques for Pulse Sequences in Medium and High Voltage DC and Battery Energy Storage Systems

There are significant concerns regarding corona discharge, partial discharge, arcing, and minor arcing in mediumand high-voltage DC systems, as well as in battery energy storage systems (BESS). These issues may arise from various factors, including micro-voids in insulation, metal powder, loose connections in medium- and high-voltage buses, and internal short circuits in lithium-ion batteries. Detecting signals below 50 MHz presents challenges due to a low signal-to-noise ratio, making it crucial to differentiate between corona signals, partial discharges, arcing signals, and external noise. To address this challenge, the authors propose a novel signal differentiation analysis technique aimed at classifying signals and reducing unwanted noise. This analysis emphasizes four key parameters: repetition rate, signal frequency, signal duration, and magnitude. The authors apply high-voltage DC and overlapping harmonic voltage to a sample of epoxy insulation. To simulate the micro arc in a BESS, a positive electrode made of braided strand wire is paired with a flat metal piece as the negative electrode inside a transparent fiberglass tube. A new method classifies various signals and examines their behaviors using the aforementioned parameters. The process involves three steps. When the signal exceeds the alarm threshold, the device assesses whether to trigger an alarm by analyzing the signal's behavior over several minutes, utilizing magnitude, time, and frequency (MTF) analysis. This paper presents the results of the experiment related to the classification of different discharges.