Development of a Single - Phase Power Quality Monitoring System

Abstract

Electricity is crucial for the social, cultural, and overall well-being of Uganda. However, the absence of real-time monitoring and reporting on single-phase electricity networks exacerbates downtime and power instability, resulting in reduced productivity, equipment damage, and revenue loss. The existing call center structure, which depends on social media feedback and phone calls to the Supervisory control and data acquisition (SCADA), is susceptible to human error, process delays, and is labor-intensive in managing reference numbers. This study aimed to develop a prototype of an automated voltage quality reporting system with location updates. The conceptual framework was employed to visually represent the relationships between various concepts and variables. A comprehensive literature review of related studies and system development life cycle (SDLC) models was conducted to inform and guide the research. Methods were developed to address the research questions and to guide activities to fulfill the objectives' requirements. Data were gathered using measurement instruments from a sample area of single-phase households, with a focus on shops for ease of accessibility. The findings were subsequently employed to benchmark the study's test setup. The data collected from the sample area closely aligned with the test bench results, exhibiting only minor deviations, which indicated that the trends observed in the test bench were consistent with those in the sample area. The hardware and software were assembled and calibrated, resulting in a functional singlephase power quality monitoring system, with reports and alerts accessible online and on mobile devices. The developed prototype exhibited hardware and software configurations analogous to those documented in comparable studies. The study recommended integrating the system with an existing powermeter for regular power supply to prevent misreporting of power failures when customer units are depleted. Further research recommends embedding of algorithms and AI tools for designing power distribution topologies, promoting continuous improvement within the energy sector.