Year: 2024
Type: dissertation
Abstract: This thesis explores DC Instrument Transformers. The research addresses the gap between the rising use of DC power sources and the limited advancements in instrumentation for DC signal measurement. A comprehensive classification of DC instrument transformers has been developed based on voltage levels, electrical parameters, and technological frameworks. \nThe analysis covers 8 types of DC ITs, including Fiber Optic Current Sensors (FOCS), Hall Effect Current Transformers (open and closed loop, as well as coreless), Pockels Optical Voltage Sensors, closed-loop Hall Voltage Sensors, shunt resistor current transformers, and resistive voltage divider transformers. Each transformer’s operational principles and circuit representations are examined, leading to the identification of 15 key performance parameters such as electromagnetic compatibility, linearity, accuracy, sensitivity, size, and reliability. A comparative analysis using a 15x8 matrix highlights that the FOCS outperforms others by meeting 11 of the 15 parameters, with closed-loop Hall sensors and resistive voltage dividers also showing strong performance. \nIn addition, the thesis investigates the market dynamics for instrument transformers, focusing on regional trends and forecasts in Asia Pacific (APAC), North America, Latin America, Europe, and the Middle East and Africa (MEA). The APAC region emerges as the leading market due to rising electricity demand and renewable energy integration, while North America offers significant investment opportunities. In Europe, a consolidation trend suggests a shift towards market dominance by fewer firms. Overall, global market growth for instrument transformers is expected to maintain a compound annual growth rate (CAGR) below 10%. The findings enhance the understanding of DC instrument transformers, their performance, and market dynamics, thereby supporting informed decision-making in the power industry and promoting the adoption of efficient measurement solutions.
Author: Mwinisin, Peter
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7035708847